Parameter sets#
How to describe parameter claims: a parameter set is a batch of claims about a target, each naming a curated parameter, a quantity, and a provenance class.
A batch of claims about a target: each names a curated parameter, a quantity or curve, and a provenance class (literature, measured, fitted, assumed).
Claims are records so sources can disagree; consumers select among them.
Define one#
A claim batch from the literature#
from battinfo.api import create_parameter_set
record = create_parameter_set(
uid="fm9p-sqkk-tbx3-rr66",
name="Graphite density claims, Smith 2026",
material_kind="graphite",
claims=[
{
"parameter": "density",
"quantity": {"value": 2.26, "unit": "g/cm3"},
"provenance_class": "literature",
}
],
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/fm9p-sqkk-tbx3-rr66",
"short_id": "fm9psq",
"name": "Graphite density claims, Smith 2026",
"material_kind": "graphite",
"scope": "material",
"claims": [
{
"parameter": "density",
"quantity": {
"value": 2.26,
"unit": "g/cm3"
},
"provenance_class": "literature"
}
]
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1750000000,
"battinfo_version": "0.7.0"
}
}
Emitted by record_to_jsonld, hosted-context mode.
{
"@context": "https://w3id.org/battinfo/context/records/v1.json",
"@id": "https://w3id.org/battinfo/spec/fm9p-sqkk-tbx3-rr66",
"@type": "schema:Dataset",
"schema:name": "Graphite density claims, Smith 2026",
"schema:about": {
"@type": "Graphite",
"@id": "https://w3id.org/emmo/domain/chemical-substance#substance_d53259a7_0d9c_48b9_a6c1_4418169df303",
"schema:name": "Graphite"
},
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "scope",
"schema:value": "material"
},
"hasProperty": {
"@type": [
"Density",
"ConventionalProperty"
],
"skos:prefLabel": "Density",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 2.26
},
"hasMeasurementUnit": "https://w3id.org/emmo#GramPerCubicCentiMetre",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "literature"
}
}
}
What to notice:
The claim batch emits as one
schema:Datasetnode: scalar claims as EMMO-typed quantities, the target onschema:about.A BPX file imports the same way:
from_bpx_parameters(...).to_records(materials=...)turns its physics blocks into claim records, header lineage included (see the design notes).
Common examples#
A selection of real, validated records from the packaged examples corpus — each one click away, included from its single source under examples/. The full, living library is the registry: browse it there.
Chen 2020 - graphite (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-8qqs-rh43-wt8d-172n.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/8qqs-rh43-wt8d-172n",
"short_id": "8qqsrh",
"name": "Chen 2020 - graphite",
"material_kind": "graphite",
"scope": "material",
"claims": [
{
"parameter": "particle_radius",
"quantity": {
"value": 5.86e-06,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "max_concentration",
"quantity": {
"value": 33133.0,
"unit": "mol/m3"
},
"provenance_class": "fitted"
},
{
"parameter": "reaction_rate_constant",
"quantity": {
"value": 6.716e-06,
"unit": "mol.m-2.s-1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_min",
"quantity": {
"value": 0.0279,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_max",
"quantity": {
"value": 0.9014,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "ocp",
"curve": {
"x_quantity": "stoichiometry",
"x": [
0.0,
0.05,
0.1,
0.2,
0.4,
0.6,
0.8,
1.0
],
"y": [
1.2,
0.35,
0.22,
0.16,
0.13,
0.12,
0.1,
0.05
],
"y_unit": "V",
"interpolation": "linear",
"branch": "average"
},
"provenance_class": "measured",
"method": "GITT",
"comment": "Coarsened illustrative curve; the source provides the full-resolution table."
}
],
"model_context": {
"tool": "BPX",
"name": "Chen2020",
"model": "DFN"
},
"description": "Subset of the Chen et al. 2020 LG M50 parameterization for the graphite negative electrode material, as a worked example of parameter claims."
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1786968980,
"citation_doi": "10.1149/1945-7111/ab9050",
"battinfo_version": "0.7.0",
"citation": "https://doi.org/10.1149/1945-7111/ab9050"
},
"notes": [
"Worked example generated by scripts in the parameter-claims change; values from the cited source."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
"@context": "https://w3id.org/battinfo/context/records/v1.json",
"@id": "https://w3id.org/battinfo/spec/8qqs-rh43-wt8d-172n",
"@type": "schema:Dataset",
"schema:name": "Chen 2020 - graphite",
"schema:description": "Subset of the Chen et al. 2020 LG M50 parameterization for the graphite negative electrode material, as a worked example of parameter claims.",
"schema:about": {
"@type": "Graphite",
"@id": "https://w3id.org/emmo/domain/chemical-substance#substance_d53259a7_0d9c_48b9_a6c1_4418169df303",
"schema:name": "Graphite"
},
"schema:additionalProperty": [
{
"@type": "schema:PropertyValue",
"schema:name": "scope",
"schema:value": "material"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_model",
"schema:value": "DFN"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_name",
"schema:value": "Chen2020"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_tool",
"schema:value": "BPX"
}
],
"hasProperty": [
{
"@type": [
"ParticleRadius",
"ConventionalProperty"
],
"skos:prefLabel": "ParticleRadius",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 5.86e-06
},
"hasMeasurementUnit": "https://w3id.org/emmo#Metre",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"MaximumConcentration",
"ConventionalProperty"
],
"skos:prefLabel": "MaximumConcentration",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 33133.0
},
"schema:unitText": "mol/m3",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"ReactionRateConstant",
"ConventionalProperty"
],
"skos:prefLabel": "ReactionRateConstant",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 6.716e-06
},
"schema:unitText": "mol.m-2.s-1",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"MinimumStoichiometricCoefficient",
"ConventionalProperty"
],
"skos:prefLabel": "MinimumStoichiometricCoefficient",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 0.0279
},
"hasMeasurementUnit": "https://w3id.org/emmo#EMMO_5ebd5e01_0ed3_49a2_a30d_cd05cbe72978",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"MaximumStoichiometricCoefficient",
"ConventionalProperty"
],
"skos:prefLabel": "MaximumStoichiometricCoefficient",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 0.9014
},
"hasMeasurementUnit": "https://w3id.org/emmo#EMMO_5ebd5e01_0ed3_49a2_a30d_cd05cbe72978",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
}
],
"schema:variableMeasured": {
"@type": "schema:PropertyValue",
"schema:name": "ocp",
"schema:description": "tabulated curve vs stoichiometry, 8 points, average branch",
"schema:unitText": "V",
"schema:measurementTechnique": "GITT",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "measured"
}
},
"schema:citation": {
"@id": "https://doi.org/10.1149/1945-7111/ab9050",
"@type": "schema:CreativeWork",
"bibo:doi": "10.1149/1945-7111/ab9050"
},
"schema:comment": "Worked example generated by scripts in the parameter-claims change; values from the cited source."
}
BPX LFP 18650 (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-1e31-69dh-s500-h9j4.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/1e31-69dh-s500-h9j4",
"short_id": "1e3169",
"name": "BPX LFP 18650",
"cell_spec_id": "https://w3id.org/battinfo/spec/b10q-6qh6-3v2x-4sp7",
"scope": "cell",
"members": {
"negative_material": "https://w3id.org/battinfo/spec/2563-gee9-ppq0-8p2r",
"negative_electrode": "https://w3id.org/battinfo/spec/a979-b0s3-rzzt-4m57",
"positive_material": "https://w3id.org/battinfo/spec/956b-frrf-hfg6-m4d9",
"positive_electrode": "https://w3id.org/battinfo/spec/sa76-qhyc-pesq-jvge",
"separator": "https://w3id.org/battinfo/spec/4gvn-f7sq-cchp-36rm",
"electrolyte": "https://w3id.org/battinfo/spec/ayt4-483v-13dj-hqgc"
},
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an LFP|graphite 2 Ah cylindrical 18650 cell.",
"model": "DFN",
"version": "0.1.0"
},
"description": "LFP|graphite 2 Ah cylindrical 18650 cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Gerver and Meyers 2011 (doi:10.1149/1.3591799). Other thermal properties are estimated."
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/lfp_18650_cell_BPX.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
"@context": "https://w3id.org/battinfo/context/records/v1.json",
"@id": "https://w3id.org/battinfo/spec/1e31-69dh-s500-h9j4",
"@type": "schema:Dataset",
"schema:name": "BPX LFP 18650",
"schema:description": "LFP|graphite 2 Ah cylindrical 18650 cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Gerver and Meyers 2011 (doi:10.1149/1.3591799). Other thermal properties are estimated.",
"schema:about": {
"@id": "https://w3id.org/battinfo/spec/b10q-6qh6-3v2x-4sp7"
},
"schema:additionalProperty": [
{
"@type": "schema:PropertyValue",
"schema:name": "scope",
"schema:value": "cell"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_model",
"schema:value": "DFN"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_name",
"schema:value": "Parameterisation example of an LFP|graphite 2 Ah cylindrical 18650 cell."
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_tool",
"schema:value": "BPX"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_version",
"schema:value": "0.1.0"
}
],
"dcterms:hasPart": [
{
"@id": "https://w3id.org/battinfo/spec/ayt4-483v-13dj-hqgc"
},
{
"@id": "https://w3id.org/battinfo/spec/a979-b0s3-rzzt-4m57"
},
{
"@id": "https://w3id.org/battinfo/spec/2563-gee9-ppq0-8p2r"
},
{
"@id": "https://w3id.org/battinfo/spec/sa76-qhyc-pesq-jvge"
},
{
"@id": "https://w3id.org/battinfo/spec/956b-frrf-hfg6-m4d9"
},
{
"@id": "https://w3id.org/battinfo/spec/4gvn-f7sq-cchp-36rm"
}
],
"schema:citation": {
"@id": "https://github.com/FaradayInstitution/BPX",
"@type": "schema:CreativeWork"
},
"schema:comment": "Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford).",
"dcterms:license": {
"@id": "https://spdx.org/licenses/MIT.html"
}
}
BPX LFP 18650 - electrolyte (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-ayt4-483v-13dj-hqgc.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/ayt4-483v-13dj-hqgc",
"short_id": "ayt448",
"name": "BPX LFP 18650 - electrolyte",
"cell_spec_id": "https://w3id.org/battinfo/spec/b10q-6qh6-3v2x-4sp7",
"scope": "electrolyte",
"claims": [
{
"parameter": "diffusivity_activation_energy",
"quantity": {
"value": 17100.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
},
{
"parameter": "initial_concentration",
"quantity": {
"value": 1000.0,
"unit": "mol/m3"
},
"provenance_class": "fitted"
},
{
"parameter": "transference_number",
"quantity": {
"value": 0.259,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "ionic_conductivity",
"expression": {
"text": "0.1297 * (x / 1000) ** 3 - 2.51 * (x / 1000) ** 1.5 + 3.329 * (x / 1000)",
"language": "bpx",
"argument": "x"
},
"provenance_class": "fitted"
},
{
"parameter": "electrolyte_diffusivity",
"expression": {
"text": "8.794e-11 * (x / 1000) ** 2 - 3.972e-10 * (x / 1000) + 4.862e-10",
"language": "bpx",
"argument": "x"
},
"provenance_class": "fitted"
},
{
"parameter": "conductivity_activation_energy",
"quantity": {
"value": 17100.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
}
],
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an LFP|graphite 2 Ah cylindrical 18650 cell.",
"model": "DFN",
"version": "0.1.0"
},
"description": "LFP|graphite 2 Ah cylindrical 18650 cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Gerver and Meyers 2011 (doi:10.1149/1.3591799). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/1e31-69dh-s500-h9j4"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/lfp_18650_cell_BPX.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
"@context": "https://w3id.org/battinfo/context/records/v1.json",
"@id": "https://w3id.org/battinfo/spec/ayt4-483v-13dj-hqgc",
"@type": "schema:Dataset",
"schema:name": "BPX LFP 18650 - electrolyte",
"schema:description": "LFP|graphite 2 Ah cylindrical 18650 cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Gerver and Meyers 2011 (doi:10.1149/1.3591799). Other thermal properties are estimated.",
"schema:about": {
"@id": "https://w3id.org/battinfo/spec/b10q-6qh6-3v2x-4sp7"
},
"schema:additionalProperty": [
{
"@type": "schema:PropertyValue",
"schema:name": "scope",
"schema:value": "electrolyte"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_model",
"schema:value": "DFN"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_name",
"schema:value": "Parameterisation example of an LFP|graphite 2 Ah cylindrical 18650 cell."
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_tool",
"schema:value": "BPX"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_version",
"schema:value": "0.1.0"
}
],
"hasProperty": [
{
"@type": [
"ActivationEnergy",
"ConventionalProperty"
],
"skos:prefLabel": "ActivationEnergy",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 17100.0
},
"schema:unitText": "J/mol",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"battinfo:initialConcentration",
"ConventionalProperty"
],
"skos:prefLabel": "initialConcentration",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 1000.0
},
"schema:unitText": "mol/m3",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"ChargeCarrierTransportNumber",
"ConventionalProperty"
],
"skos:prefLabel": "ChargeCarrierTransportNumber",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 0.259
},
"hasMeasurementUnit": "https://w3id.org/emmo#EMMO_5ebd5e01_0ed3_49a2_a30d_cd05cbe72978",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"ActivationEnergyOfElectrolyteConductivity",
"ConventionalProperty"
],
"skos:prefLabel": "ActivationEnergyOfElectrolyteConductivity",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 17100.0
},
"schema:unitText": "J/mol",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
}
],
"schema:variableMeasured": [
{
"@type": "schema:PropertyValue",
"schema:name": "ionic_conductivity",
"schema:value": "0.1297 * (x / 1000) ** 3 - 2.51 * (x / 1000) ** 1.5 + 3.329 * (x / 1000)",
"schema:description": "expression (bpx)",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": "schema:PropertyValue",
"schema:name": "electrolyte_diffusivity",
"schema:value": "8.794e-11 * (x / 1000) ** 2 - 3.972e-10 * (x / 1000) + 4.862e-10",
"schema:description": "expression (bpx)",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
}
],
"schema:isPartOf": {
"@id": "https://w3id.org/battinfo/spec/1e31-69dh-s500-h9j4"
},
"schema:citation": {
"@id": "https://github.com/FaradayInstitution/BPX",
"@type": "schema:CreativeWork"
},
"schema:comment": "Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford).",
"dcterms:license": {
"@id": "https://spdx.org/licenses/MIT.html"
}
}
BPX LFP 18650 - negative electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-a979-b0s3-rzzt-4m57.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/a979-b0s3-rzzt-4m57",
"short_id": "a979b0",
"name": "BPX LFP 18650 - negative electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/b10q-6qh6-3v2x-4sp7",
"scope": "electrode",
"claims": [
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],
"electrode_polarity": "negative",
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}
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BPX LFP 18650 - negative electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-2563-gee9-ppq0-8p2r.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/2563-gee9-ppq0-8p2r",
"short_id": "2563ge",
"name": "BPX LFP 18650 - negative electrode material",
"material_kind": "graphite",
"scope": "material",
"claims": [
{
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"quantity": {
"value": 4.8e-06,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "solid_diffusivity",
"quantity": {
"value": 9.6e-15,
"unit": "m2/s"
},
"provenance_class": "fitted"
},
{
"parameter": "ocp",
"expression": {
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"language": "bpx",
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},
"provenance_class": "fitted"
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"value": 30000.0,
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"description": "LFP|graphite 2 Ah cylindrical 18650 cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Gerver and Meyers 2011 (doi:10.1149/1.3591799). Other thermal properties are estimated.",
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"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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}
BPX LFP 18650 - positive electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-sa76-qhyc-pesq-jvge.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/sa76-qhyc-pesq-jvge",
"short_id": "sa76qh",
"name": "BPX LFP 18650 - positive electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/b10q-6qh6-3v2x-4sp7",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 6.43e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "electronic_conductivity",
"quantity": {
"value": 0.8,
"unit": "S/m"
},
"provenance_class": "fitted"
},
{
"parameter": "surface_area_per_volume",
"quantity": {
"value": 4418460.0,
"unit": "1/m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.20359,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
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},
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}
],
"electrode_polarity": "positive",
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"model": "DFN",
"version": "0.1.0"
},
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"set_id": "https://w3id.org/battinfo/spec/1e31-69dh-s500-h9j4"
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"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
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"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
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}
}
BPX LFP 18650 - positive electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-956b-frrf-hfg6-m4d9.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/956b-frrf-hfg6-m4d9",
"short_id": "956bfr",
"name": "BPX LFP 18650 - positive electrode material",
"material_kind": "lfp",
"scope": "material",
"claims": [
{
"parameter": "particle_radius",
"quantity": {
"value": 5e-07,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "solid_diffusivity",
"quantity": {
"value": 6.873e-17,
"unit": "m2/s"
},
"provenance_class": "fitted"
},
{
"parameter": "ocp",
"expression": {
"text": "3.41285712e+00 - 1.49721852e-02 * x + 3.54866018e+14 * exp(-3.95729493e+02 * x) - 1.45998465e+00 * exp(-1.10108622e+02 * (1 - x))",
"language": "bpx",
"argument": "x"
},
"provenance_class": "fitted"
},
{
"parameter": "entropic_coefficient",
"curve": {
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0.0,
0.05,
0.1,
0.15,
0.2,
0.25,
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0.8,
0.85,
0.9,
0.95,
1.0
],
"y": [
0.0001,
4.7145e-05,
3.7666e-05,
2.0299e-05,
5.9833e-06,
-4.6859e-06,
-1.3966e-05,
-2.3528e-05,
-3.3593e-05,
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-6.0211e-05,
-6.8006e-05,
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-9.913e-05,
-0.00010855,
-0.00011266,
-0.00011238,
-0.00010921,
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],
"y_unit": "V/K"
},
"provenance_class": "fitted"
},
{
"parameter": "reaction_rate_constant",
"quantity": {
"value": 9.736e-07,
"unit": "mol.m-2.s-1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_min",
"quantity": {
"value": 0.0875,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_max",
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"value": 0.95038,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "max_concentration",
"quantity": {
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"unit": "mol/m3"
},
"provenance_class": "fitted"
},
{
"parameter": "diffusivity_activation_energy",
"quantity": {
"value": 80000.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
},
{
"parameter": "reaction_rate_activation_energy",
"quantity": {
"value": 35000.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
}
],
"model_context": {
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"name": "Parameterisation example of an LFP|graphite 2 Ah cylindrical 18650 cell.",
"model": "DFN",
"version": "0.1.0"
},
"description": "LFP|graphite 2 Ah cylindrical 18650 cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Gerver and Meyers 2011 (doi:10.1149/1.3591799). Other thermal properties are estimated.",
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"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
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]
}
Emitted by record_to_jsonld, hosted-context mode.
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}
BPX LFP 18650 - separator (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-4gvn-f7sq-cchp-36rm.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/4gvn-f7sq-cchp-36rm",
"short_id": "4gvnf7",
"name": "BPX LFP 18650 - separator",
"cell_spec_id": "https://w3id.org/battinfo/spec/b10q-6qh6-3v2x-4sp7",
"scope": "separator",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 2e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.47,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
"quantity": {
"value": 0.3222,
"unit": "1"
},
"provenance_class": "fitted"
}
],
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an LFP|graphite 2 Ah cylindrical 18650 cell.",
"model": "DFN",
"version": "0.1.0"
},
"description": "LFP|graphite 2 Ah cylindrical 18650 cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Gerver and Meyers 2011 (doi:10.1149/1.3591799). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/1e31-69dh-s500-h9j4"
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"provenance": {
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"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
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}
BPX NMC111 pouch (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-ma31-1g1r-m2x1-h7d2.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/ma31-1g1r-m2x1-h7d2",
"short_id": "ma311g",
"name": "BPX NMC111 pouch",
"cell_spec_id": "https://w3id.org/battinfo/spec/h9a9-pzge-8bvf-gss4",
"scope": "cell",
"members": {
"negative_material": "https://w3id.org/battinfo/spec/nzk2-dv72-c12e-497h",
"negative_electrode": "https://w3id.org/battinfo/spec/ftg3-krew-9dq5-mntm",
"positive_material": "https://w3id.org/battinfo/spec/vdek-3ryx-83cq-0fcc",
"positive_electrode": "https://w3id.org/battinfo/spec/wdd4-4r9a-zcc8-wnj1",
"separator": "https://w3id.org/battinfo/spec/2wm3-4t64-h09k-ackh",
"electrolyte": "https://w3id.org/battinfo/spec/2p6b-xrjf-jtcr-57hx"
},
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an NMC111|graphite 12.5 Ah pouch cell",
"model": "DFN",
"version": "0.1.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated."
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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"@id": "https://w3id.org/battinfo/spec/wdd4-4r9a-zcc8-wnj1"
},
{
"@id": "https://w3id.org/battinfo/spec/vdek-3ryx-83cq-0fcc"
},
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"@id": "https://w3id.org/battinfo/spec/2wm3-4t64-h09k-ackh"
}
],
"schema:citation": {
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"schema:comment": "Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford).",
"dcterms:license": {
"@id": "https://spdx.org/licenses/MIT.html"
}
}
BPX NMC111 pouch - electrolyte (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-2p6b-xrjf-jtcr-57hx.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/2p6b-xrjf-jtcr-57hx",
"short_id": "2p6bxr",
"name": "BPX NMC111 pouch - electrolyte",
"cell_spec_id": "https://w3id.org/battinfo/spec/h9a9-pzge-8bvf-gss4",
"scope": "electrolyte",
"claims": [
{
"parameter": "diffusivity_activation_energy",
"quantity": {
"value": 17100.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
},
{
"parameter": "initial_concentration",
"quantity": {
"value": 1000.0,
"unit": "mol/m3"
},
"provenance_class": "fitted"
},
{
"parameter": "transference_number",
"quantity": {
"value": 0.2594,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "ionic_conductivity",
"expression": {
"text": "0.1297 * (x / 1000) ** 3 - 2.51 * (x / 1000) ** 1.5 + 3.329 * (x / 1000)",
"language": "bpx",
"argument": "x"
},
"provenance_class": "fitted"
},
{
"parameter": "electrolyte_diffusivity",
"expression": {
"text": "8.794e-11 * (x / 1000) ** 2 - 3.972e-10 * (x / 1000) + 4.862e-10",
"language": "bpx",
"argument": "x"
},
"provenance_class": "fitted"
},
{
"parameter": "conductivity_activation_energy",
"quantity": {
"value": 17100.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
}
],
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an NMC111|graphite 12.5 Ah pouch cell",
"model": "DFN",
"version": "0.1.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/ma31-1g1r-m2x1-h7d2"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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}
}
BPX NMC111 pouch - negative electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-ftg3-krew-9dq5-mntm.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/ftg3-krew-9dq5-mntm",
"short_id": "ftg3kr",
"name": "BPX NMC111 pouch - negative electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/h9a9-pzge-8bvf-gss4",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 5.62e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "electronic_conductivity",
"quantity": {
"value": 0.222,
"unit": "S/m"
},
"provenance_class": "fitted"
},
{
"parameter": "surface_area_per_volume",
"quantity": {
"value": 499522.0,
"unit": "1/m"
},
"provenance_class": "fitted"
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{
"parameter": "porosity",
"quantity": {
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"unit": "1"
},
"provenance_class": "fitted"
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{
"parameter": "transport_efficiency",
"quantity": {
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"unit": "1"
},
"provenance_class": "fitted"
}
],
"electrode_polarity": "negative",
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an NMC111|graphite 12.5 Ah pouch cell",
"model": "DFN",
"version": "0.1.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/ma31-1g1r-m2x1-h7d2"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
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"schema:description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
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}
BPX NMC111 pouch - negative electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-nzk2-dv72-c12e-497h.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/nzk2-dv72-c12e-497h",
"short_id": "nzk2dv",
"name": "BPX NMC111 pouch - negative electrode material",
"material_kind": "graphite",
"scope": "material",
"claims": [
{
"parameter": "particle_radius",
"quantity": {
"value": 4.12e-06,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "solid_diffusivity",
"quantity": {
"value": 2.728e-14,
"unit": "m2/s"
},
"provenance_class": "fitted"
},
{
"parameter": "ocp",
"expression": {
"text": "9.47057878e-01 * exp(-1.59418743e+02 * x) - 3.50928033e+04 + 1.64230269e-01 * tanh(-4.55509094e+01 * (x - 3.24116012e-02 )) + 3.69968491e-02 * tanh(-1.96718868e+01 * (x - 1.68334476e-01)) + 1.91517003e+04 * tanh(3.19648312e+00 * (x - 1.85139824e+00)) + 5.42448511e+04 * tanh(-3.19009848e+00 * (x - 2.01660395e+00))",
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"argument": "x"
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{
"parameter": "entropic_coefficient",
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"argument": "x"
},
"provenance_class": "fitted"
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{
"parameter": "reaction_rate_constant",
"quantity": {
"value": 5.199e-06,
"unit": "mol.m-2.s-1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_min",
"quantity": {
"value": 0.005504,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_max",
"quantity": {
"value": 0.75668,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "max_concentration",
"quantity": {
"value": 29730.0,
"unit": "mol/m3"
},
"provenance_class": "fitted"
},
{
"parameter": "diffusivity_activation_energy",
"quantity": {
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],
"model_context": {
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"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/ma31-1g1r-m2x1-h7d2"
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"provenance": {
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"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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],
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}
}
BPX NMC111 pouch - positive electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-wdd4-4r9a-zcc8-wnj1.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/wdd4-4r9a-zcc8-wnj1",
"short_id": "wdd44r",
"name": "BPX NMC111 pouch - positive electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/h9a9-pzge-8bvf-gss4",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 5.23e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "electronic_conductivity",
"quantity": {
"value": 0.789,
"unit": "S/m"
},
"provenance_class": "fitted"
},
{
"parameter": "surface_area_per_volume",
"quantity": {
"value": 432072.0,
"unit": "1/m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.277493,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
"quantity": {
"value": 0.1462,
"unit": "1"
},
"provenance_class": "fitted"
}
],
"electrode_polarity": "positive",
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an NMC111|graphite 12.5 Ah pouch cell",
"model": "DFN",
"version": "0.1.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/ma31-1g1r-m2x1-h7d2"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
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"@type": "schema:Dataset",
"schema:name": "BPX NMC111 pouch - positive electrode build",
"schema:description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
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"dcterms:license": {
"@id": "https://spdx.org/licenses/MIT.html"
}
}
BPX NMC111 pouch - positive electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-vdek-3ryx-83cq-0fcc.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/vdek-3ryx-83cq-0fcc",
"short_id": "vdek3r",
"name": "BPX NMC111 pouch - positive electrode material",
"material_kind": "nmc111",
"scope": "material",
"claims": [
{
"parameter": "particle_radius",
"quantity": {
"value": 4.6e-06,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "solid_diffusivity",
"quantity": {
"value": 3.2e-14,
"unit": "m2/s"
},
"provenance_class": "fitted"
},
{
"parameter": "ocp",
"expression": {
"text": "-3.04420906 * x + 10.04892207 - 0.65637536 * tanh(-4.02134095 * (x - 0.80063948)) + 4.24678547 * tanh(12.17805062 * (x - 7.57659337)) - 0.3757068 * tanh(59.33067782 * (x - 0.99784492))",
"language": "bpx",
"argument": "x"
},
"provenance_class": "fitted"
},
{
"parameter": "entropic_coefficient",
"quantity": {
"value": -0.0001,
"unit": "V/K"
},
"provenance_class": "fitted"
},
{
"parameter": "reaction_rate_constant",
"quantity": {
"value": 2.305e-05,
"unit": "mol.m-2.s-1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_min",
"quantity": {
"value": 0.42424,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_max",
"quantity": {
"value": 0.9621,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "max_concentration",
"quantity": {
"value": 46200.0,
"unit": "mol/m3"
},
"provenance_class": "fitted"
},
{
"parameter": "diffusivity_activation_energy",
"quantity": {
"value": 15000.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
},
{
"parameter": "reaction_rate_activation_energy",
"quantity": {
"value": 35000.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
}
],
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an NMC111|graphite 12.5 Ah pouch cell",
"model": "DFN",
"version": "0.1.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/ma31-1g1r-m2x1-h7d2"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
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"@id": "https://w3id.org/battinfo/spec/vdek-3ryx-83cq-0fcc",
"@type": "schema:Dataset",
"schema:name": "BPX NMC111 pouch - positive electrode material",
"schema:description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
"schema:about": {
"@type": "LithiumNickelManganeseCobaltOxide111",
"@id": "https://w3id.org/emmo/domain/chemical-substance#substance_a0b57956_8ba1_4021_ade9_44a87d103d90",
"schema:name": "NMC111 (LiNi1/3Mn1/3Co1/3O2)"
},
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},
{
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"dcterms:license": {
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}
}
BPX NMC111 pouch - separator (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-2wm3-4t64-h09k-ackh.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/2wm3-4t64-h09k-ackh",
"short_id": "2wm34t",
"name": "BPX NMC111 pouch - separator",
"cell_spec_id": "https://w3id.org/battinfo/spec/h9a9-pzge-8bvf-gss4",
"scope": "separator",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 2e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.47,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
"quantity": {
"value": 0.3222,
"unit": "1"
},
"provenance_class": "fitted"
}
],
"model_context": {
"tool": "BPX",
"name": "Parameterisation example of an NMC111|graphite 12.5 Ah pouch cell",
"model": "DFN",
"version": "0.1.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Electrolyte properties from Nyman et al. 2008 (doi:10.1016/j.electacta.2008.04.023). Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/ma31-1g1r-m2x1-h7d2"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
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"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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BPX NMC111 pouch SPM (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-zwap-fsws-m4yx-p5pp.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/zwap-fsws-m4yx-p5pp",
"short_id": "zwapfs",
"name": "BPX NMC111 pouch SPM",
"cell_spec_id": "https://w3id.org/battinfo/spec/a91f-kqde-1hrg-fenr",
"scope": "cell",
"members": {
"negative_material": "https://w3id.org/battinfo/spec/z3ac-1me1-hsfd-pa56",
"negative_electrode": "https://w3id.org/battinfo/spec/3n1b-f8n3-zrtc-psjs",
"positive_material": "https://w3id.org/battinfo/spec/f4tg-ahwq-1mgt-xn7x",
"positive_electrode": "https://w3id.org/battinfo/spec/dgjc-w8j1-evf7-e2kb"
},
"model_context": {
"tool": "BPX",
"name": "Test case: Single Particle Model (SPM) parameterisation example based on nmc_pouch_cell_BPX.json from About:Energy open-source release.",
"model": "SPM",
"version": "0.4.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated."
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_SPM.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
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"schema:name": "BPX NMC111 pouch SPM",
"schema:description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
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}
BPX NMC111 pouch SPM - negative electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-3n1b-f8n3-zrtc-psjs.json")
.read_text(encoding="utf-8")
)
{
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"id": "https://w3id.org/battinfo/spec/3n1b-f8n3-zrtc-psjs",
"short_id": "3n1bf8",
"name": "BPX NMC111 pouch SPM - negative electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/a91f-kqde-1hrg-fenr",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 5.62e-05,
"unit": "m"
},
"provenance_class": "fitted"
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"quantity": {
"value": 499522.0,
"unit": "1/m"
},
"provenance_class": "fitted"
}
],
"electrode_polarity": "negative",
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"tool": "BPX",
"name": "Test case: Single Particle Model (SPM) parameterisation example based on nmc_pouch_cell_BPX.json from About:Energy open-source release.",
"model": "SPM",
"version": "0.4.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
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},
"provenance": {
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"citation": "https://github.com/FaradayInstitution/BPX"
},
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"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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}
BPX NMC111 pouch SPM - negative electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-z3ac-1me1-hsfd-pa56.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/z3ac-1me1-hsfd-pa56",
"short_id": "z3ac1m",
"name": "BPX NMC111 pouch SPM - negative electrode material",
"material_kind": "graphite",
"scope": "material",
"claims": [
{
"parameter": "particle_radius",
"quantity": {
"value": 4.12e-06,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "solid_diffusivity",
"quantity": {
"value": 2.728e-14,
"unit": "m2/s"
},
"provenance_class": "fitted"
},
{
"parameter": "ocp",
"expression": {
"text": "9.47057878e-01 * exp(-1.59418743e+02 * x) - 3.50928033e+04 + 1.64230269e-01 * tanh(-4.55509094e+01 * (x - 3.24116012e-02 )) + 3.69968491e-02 * tanh(-1.96718868e+01 * (x - 1.68334476e-01)) + 1.91517003e+04 * tanh(3.19648312e+00 * (x - 1.85139824e+00)) + 5.42448511e+04 * tanh(-3.19009848e+00 * (x - 2.01660395e+00))",
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{
"parameter": "entropic_coefficient",
"expression": {
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"language": "bpx",
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},
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"quantity": {
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"model_context": {
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"model": "SPM",
"version": "0.4.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
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},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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],
"skos:prefLabel": "ActivationEnergy",
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"schema:name": "provenance_class",
"schema:value": "fitted"
}
}
],
"schema:variableMeasured": [
{
"@type": "schema:PropertyValue",
"schema:name": "ocp",
"schema:value": "9.47057878e-01 * exp(-1.59418743e+02 * x) - 3.50928033e+04 + 1.64230269e-01 * tanh(-4.55509094e+01 * (x - 3.24116012e-02 )) + 3.69968491e-02 * tanh(-1.96718868e+01 * (x - 1.68334476e-01)) + 1.91517003e+04 * tanh(3.19648312e+00 * (x - 1.85139824e+00)) + 5.42448511e+04 * tanh(-3.19009848e+00 * (x - 2.01660395e+00))",
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"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": "schema:PropertyValue",
"schema:name": "entropic_coefficient",
"schema:value": "(-0.1112 * x + 0.02914 + 0.3561 * exp(-((x - 0.08309) ** 2) / 0.004616)) / 1000",
"schema:description": "expression (bpx)",
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],
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"schema:comment": "Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford).",
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}
}
BPX NMC111 pouch SPM - positive electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-dgjc-w8j1-evf7-e2kb.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/dgjc-w8j1-evf7-e2kb",
"short_id": "dgjcw8",
"name": "BPX NMC111 pouch SPM - positive electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/a91f-kqde-1hrg-fenr",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 5.23e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "surface_area_per_volume",
"quantity": {
"value": 432072.0,
"unit": "1/m"
},
"provenance_class": "fitted"
}
],
"electrode_polarity": "positive",
"model_context": {
"tool": "BPX",
"name": "Test case: Single Particle Model (SPM) parameterisation example based on nmc_pouch_cell_BPX.json from About:Energy open-source release.",
"model": "SPM",
"version": "0.4.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
"set_id": "https://w3id.org/battinfo/spec/zwap-fsws-m4yx-p5pp"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_SPM.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
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"@type": "schema:Dataset",
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}
}
BPX NMC111 pouch SPM - positive electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-f4tg-ahwq-1mgt-xn7x.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/f4tg-ahwq-1mgt-xn7x",
"short_id": "f4tgah",
"name": "BPX NMC111 pouch SPM - positive electrode material",
"material_kind": "nmc111",
"scope": "material",
"claims": [
{
"parameter": "particle_radius",
"quantity": {
"value": 4.6e-06,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "solid_diffusivity",
"quantity": {
"value": 3.2e-14,
"unit": "m2/s"
},
"provenance_class": "fitted"
},
{
"parameter": "ocp",
"expression": {
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"language": "bpx",
"argument": "x"
},
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},
{
"parameter": "entropic_coefficient",
"quantity": {
"value": -0.0001,
"unit": "V/K"
},
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{
"parameter": "reaction_rate_constant",
"quantity": {
"value": 2.305e-05,
"unit": "mol.m-2.s-1"
},
"provenance_class": "fitted"
},
{
"parameter": "stoichiometry_min",
"quantity": {
"value": 0.42424,
"unit": "1"
},
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},
{
"parameter": "stoichiometry_max",
"quantity": {
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"unit": "1"
},
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{
"parameter": "max_concentration",
"quantity": {
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"unit": "mol/m3"
},
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},
{
"parameter": "diffusivity_activation_energy",
"quantity": {
"value": 15000.0,
"unit": "J/mol"
},
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{
"parameter": "reaction_rate_activation_energy",
"quantity": {
"value": 35000.0,
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],
"model_context": {
"tool": "BPX",
"name": "Test case: Single Particle Model (SPM) parameterisation example based on nmc_pouch_cell_BPX.json from About:Energy open-source release.",
"model": "SPM",
"version": "0.4.0"
},
"description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
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},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_SPM.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
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"@type": "schema:Dataset",
"schema:name": "BPX NMC111 pouch SPM - positive electrode material",
"schema:description": "NMC111|graphite 12.5 Ah pouch cell. Parameterisation by About:Energy Limited (aboutenergy.io), December 2022, based on cell cycling data, and electrode data gathered after cell teardown. Negative electrode entropic coefficient data are from O'Regan et al. 2022 (doi:10.1016/j.electacta.2022.140700). Positive electrode entropic coefficient data are from Viswanathan et al. 2010 (doi:10.1016/j.jpowsour.2009.11.103). Other thermal properties are estimated.",
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}
}
BPX NMC111 pouch blended (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-pyss-2m8j-y8c1-rmcb.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/pyss-2m8j-y8c1-rmcb",
"short_id": "pyss2m",
"name": "BPX NMC111 pouch blended",
"cell_spec_id": "https://w3id.org/battinfo/spec/vtz0-b7fc-6jdr-8ndn",
"scope": "cell",
"members": {
"negative_material": "https://w3id.org/battinfo/spec/baez-0ppf-14qx-6rt0",
"negative_electrode": "https://w3id.org/battinfo/spec/q3dk-9sq9-7s86-43vw",
"positive_electrode": "https://w3id.org/battinfo/spec/9cwx-f2pf-6sv6-3n9e",
"separator": "https://w3id.org/battinfo/spec/e04y-e56s-wz45-yvk4",
"electrolyte": "https://w3id.org/battinfo/spec/0kaz-t3ef-8ehm-yhhb"
},
"model_context": {
"tool": "BPX",
"name": "Test case: blended electrode definition with two particle sizes but equivalent chemistry. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
}
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_blended_electrode.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
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"@id": "https://w3id.org/battinfo/spec/pyss-2m8j-y8c1-rmcb",
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"schema:name": "BPX NMC111 pouch blended",
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}
}
BPX NMC111 pouch blended - electrolyte (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-0kaz-t3ef-8ehm-yhhb.json")
.read_text(encoding="utf-8")
)
{
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"short_id": "0kazt3",
"name": "BPX NMC111 pouch blended - electrolyte",
"cell_spec_id": "https://w3id.org/battinfo/spec/vtz0-b7fc-6jdr-8ndn",
"scope": "electrolyte",
"claims": [
{
"parameter": "diffusivity_activation_energy",
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{
"parameter": "ionic_conductivity",
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"language": "bpx",
"argument": "x"
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{
"parameter": "electrolyte_diffusivity",
"expression": {
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}
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}
BPX NMC111 pouch blended - negative electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-q3dk-9sq9-7s86-43vw.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/q3dk-9sq9-7s86-43vw",
"short_id": "q3dk9s",
"name": "BPX NMC111 pouch blended - negative electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/vtz0-b7fc-6jdr-8ndn",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 5.62e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "electronic_conductivity",
"quantity": {
"value": 0.222,
"unit": "S/m"
},
"provenance_class": "fitted"
},
{
"parameter": "surface_area_per_volume",
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"value": 499522.0,
"unit": "1/m"
},
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"unit": "1"
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},
{
"parameter": "transport_efficiency",
"quantity": {
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"unit": "1"
},
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}
],
"electrode_polarity": "negative",
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"tool": "BPX",
"name": "Test case: blended electrode definition with two particle sizes but equivalent chemistry. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
},
"set_id": "https://w3id.org/battinfo/spec/pyss-2m8j-y8c1-rmcb"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_blended_electrode.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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}
BPX NMC111 pouch blended - negative electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-baez-0ppf-14qx-6rt0.json")
.read_text(encoding="utf-8")
)
{
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"short_id": "baez0p",
"name": "BPX NMC111 pouch blended - negative electrode material",
"material_kind": "graphite",
"scope": "material",
"claims": [
{
"parameter": "particle_radius",
"quantity": {
"value": 4.12e-06,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "solid_diffusivity",
"quantity": {
"value": 2.728e-14,
"unit": "m2/s"
},
"provenance_class": "fitted"
},
{
"parameter": "ocp",
"expression": {
"text": "9.47057878e-01 * exp(-1.59418743e+02 * x) - 3.50928033e+04 + 1.64230269e-01 * tanh(-4.55509094e+01 * (x - 3.24116012e-02 )) + 3.69968491e-02 * tanh(-1.96718868e+01 * (x - 1.68334476e-01)) + 1.91517003e+04 * tanh(3.19648312e+00 * (x - 1.85139824e+00)) + 5.42448511e+04 * tanh(-3.19009848e+00 * (x - 2.01660395e+00))",
"language": "bpx",
"argument": "x"
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"parameter": "entropic_coefficient",
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"argument": "x"
},
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"unit": "1"
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{
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"value": 29730.0,
"unit": "mol/m3"
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"parameter": "diffusivity_activation_energy",
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"unit": "J/mol"
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],
"model_context": {
"tool": "BPX",
"name": "Test case: blended electrode definition with two particle sizes but equivalent chemistry. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
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"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
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}
}
BPX NMC111 pouch blended - positive electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-9cwx-f2pf-6sv6-3n9e.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/9cwx-f2pf-6sv6-3n9e",
"short_id": "9cwxf2",
"name": "BPX NMC111 pouch blended - positive electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/vtz0-b7fc-6jdr-8ndn",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 5.23e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "electronic_conductivity",
"quantity": {
"value": 0.789,
"unit": "S/m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.277493,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
"quantity": {
"value": 0.1462,
"unit": "1"
},
"provenance_class": "fitted"
}
],
"electrode_polarity": "positive",
"model_context": {
"tool": "BPX",
"name": "Test case: blended electrode definition with two particle sizes but equivalent chemistry. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
},
"set_id": "https://w3id.org/battinfo/spec/pyss-2m8j-y8c1-rmcb"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_blended_electrode.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
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"@type": "schema:Dataset",
"schema:name": "BPX NMC111 pouch blended - positive electrode build",
"schema:about": {
"@id": "https://w3id.org/battinfo/spec/vtz0-b7fc-6jdr-8ndn"
},
"schema:additionalProperty": [
{
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"schema:value": "electrode"
},
{
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"schema:name": "electrode_polarity",
"schema:value": "positive"
},
{
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"schema:value": "DFN"
},
{
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"schema:value": "Test case: blended electrode definition with two particle sizes but equivalent chemistry. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release."
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_tool",
"schema:value": "BPX"
},
{
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"schema:name": "source_version",
"schema:value": "0.4.0"
}
],
"hasProperty": [
{
"@type": [
"Thickness",
"ConventionalProperty"
],
"skos:prefLabel": "Thickness",
"hasNumericalPart": {
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"hasNumberValue": 5.23e-05
},
"hasMeasurementUnit": "https://w3id.org/emmo#Metre",
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},
{
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},
{
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},
{
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],
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"dcterms:license": {
"@id": "https://spdx.org/licenses/MIT.html"
}
}
BPX NMC111 pouch blended - separator (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-e04y-e56s-wz45-yvk4.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/e04y-e56s-wz45-yvk4",
"short_id": "e04ye5",
"name": "BPX NMC111 pouch blended - separator",
"cell_spec_id": "https://w3id.org/battinfo/spec/vtz0-b7fc-6jdr-8ndn",
"scope": "separator",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 2e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.47,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
"quantity": {
"value": 0.3222,
"unit": "1"
},
"provenance_class": "fitted"
}
],
"model_context": {
"tool": "BPX",
"name": "Test case: blended electrode definition with two particle sizes but equivalent chemistry. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
},
"set_id": "https://w3id.org/battinfo/spec/pyss-2m8j-y8c1-rmcb"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_blended_electrode.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
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"@type": "schema:Dataset",
"schema:name": "BPX NMC111 pouch blended - separator",
"schema:about": {
"@id": "https://w3id.org/battinfo/spec/vtz0-b7fc-6jdr-8ndn"
},
"schema:additionalProperty": [
{
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"schema:name": "scope",
"schema:value": "separator"
},
{
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"schema:value": "DFN"
},
{
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"schema:value": "Test case: blended electrode definition with two particle sizes but equivalent chemistry. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release."
},
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},
{
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}
],
"hasProperty": [
{
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],
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},
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},
{
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],
"hasNumericalPart": {
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"hasNumberValue": 0.47
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},
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"@id": "https://spdx.org/licenses/MIT.html"
}
}
BPX NMC111-Si pouch hysteresis (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-5rjm-2a2w-4x8c-5dqy.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/5rjm-2a2w-4x8c-5dqy",
"short_id": "5rjm2a",
"name": "BPX NMC111-Si pouch hysteresis",
"cell_spec_id": "https://w3id.org/battinfo/spec/41wx-hskh-xk9g-z9fh",
"scope": "cell",
"members": {
"negative_material": "https://w3id.org/battinfo/spec/4afn-7wan-67hf-nwys",
"negative_electrode": "https://w3id.org/battinfo/spec/340n-s2eb-qy4g-h2rh",
"positive_material": "https://w3id.org/battinfo/spec/sdw7-cp7b-nsst-tvvy",
"positive_electrode": "https://w3id.org/battinfo/spec/geyv-hp0x-jhrh-c44z",
"separator": "https://w3id.org/battinfo/spec/smjg-7gh6-93vg-geh5",
"electrolyte": "https://w3id.org/battinfo/spec/5znm-m359-cbp5-77hn"
},
"model_context": {
"tool": "BPX",
"name": "Test case: user-defined 0th-order hysteresis for graphite-Si blend in negative electrode. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
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"annex": {
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"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_user-defined_hysteresis.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
"@context": "https://w3id.org/battinfo/context/records/v1.json",
"@id": "https://w3id.org/battinfo/spec/5rjm-2a2w-4x8c-5dqy",
"@type": "schema:Dataset",
"schema:name": "BPX NMC111-Si pouch hysteresis",
"schema:about": {
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},
"schema:additionalProperty": [
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},
{
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"schema:value": "Test case: user-defined 0th-order hysteresis for graphite-Si blend in negative electrode. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release."
},
{
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},
{
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}
],
"dcterms:hasPart": [
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}
BPX NMC111-Si pouch hysteresis - electrolyte (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-5znm-m359-cbp5-77hn.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/5znm-m359-cbp5-77hn",
"short_id": "5znmm3",
"name": "BPX NMC111-Si pouch hysteresis - electrolyte",
"cell_spec_id": "https://w3id.org/battinfo/spec/41wx-hskh-xk9g-z9fh",
"scope": "electrolyte",
"claims": [
{
"parameter": "diffusivity_activation_energy",
"quantity": {
"value": 17100.0,
"unit": "J/mol"
},
"provenance_class": "fitted"
},
{
"parameter": "initial_concentration",
"quantity": {
"value": 1000.0,
"unit": "mol/m3"
},
"provenance_class": "fitted"
},
{
"parameter": "transference_number",
"quantity": {
"value": 0.2594,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "ionic_conductivity",
"expression": {
"text": "0.1297 * (x / 1000) ** 3 - 2.51 * (x / 1000) ** 1.5 + 3.329 * (x / 1000)",
"language": "bpx",
"argument": "x"
},
"provenance_class": "fitted"
},
{
"parameter": "electrolyte_diffusivity",
"expression": {
"text": "8.794e-11 * (x / 1000) ** 2 - 3.972e-10 * (x / 1000) + 4.862e-10",
"language": "bpx",
"argument": "x"
},
"provenance_class": "fitted"
},
{
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"quantity": {
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"unit": "J/mol"
},
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}
],
"model_context": {
"tool": "BPX",
"name": "Test case: user-defined 0th-order hysteresis for graphite-Si blend in negative electrode. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
},
"annex": {
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"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_user-defined_hysteresis.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
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},
{
"@type": "schema:PropertyValue",
"schema:name": "source_model",
"schema:value": "DFN"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_name",
"schema:value": "Test case: user-defined 0th-order hysteresis for graphite-Si blend in negative electrode. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release."
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_tool",
"schema:value": "BPX"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_version",
"schema:value": "0.4.0"
}
],
"hasProperty": [
{
"@type": [
"ActivationEnergy",
"ConventionalProperty"
],
"skos:prefLabel": "ActivationEnergy",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 17100.0
},
"schema:unitText": "J/mol",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"battinfo:initialConcentration",
"ConventionalProperty"
],
"skos:prefLabel": "initialConcentration",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 1000.0
},
"schema:unitText": "mol/m3",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"ChargeCarrierTransportNumber",
"ConventionalProperty"
],
"skos:prefLabel": "ChargeCarrierTransportNumber",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 0.2594
},
"hasMeasurementUnit": "https://w3id.org/emmo#EMMO_5ebd5e01_0ed3_49a2_a30d_cd05cbe72978",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"ActivationEnergyOfElectrolyteConductivity",
"ConventionalProperty"
],
"skos:prefLabel": "ActivationEnergyOfElectrolyteConductivity",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 17100.0
},
"schema:unitText": "J/mol",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
}
],
"schema:variableMeasured": [
{
"@type": "schema:PropertyValue",
"schema:name": "ionic_conductivity",
"schema:value": "0.1297 * (x / 1000) ** 3 - 2.51 * (x / 1000) ** 1.5 + 3.329 * (x / 1000)",
"schema:description": "expression (bpx)",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": "schema:PropertyValue",
"schema:name": "electrolyte_diffusivity",
"schema:value": "8.794e-11 * (x / 1000) ** 2 - 3.972e-10 * (x / 1000) + 4.862e-10",
"schema:description": "expression (bpx)",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
}
],
"schema:isPartOf": {
"@id": "https://w3id.org/battinfo/spec/5rjm-2a2w-4x8c-5dqy"
},
"schema:citation": {
"@id": "https://github.com/FaradayInstitution/BPX",
"@type": "schema:CreativeWork"
},
"schema:comment": "Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford).",
"dcterms:license": {
"@id": "https://spdx.org/licenses/MIT.html"
}
}
BPX NMC111-Si pouch hysteresis - negative electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-340n-s2eb-qy4g-h2rh.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/340n-s2eb-qy4g-h2rh",
"short_id": "340ns2",
"name": "BPX NMC111-Si pouch hysteresis - negative electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/41wx-hskh-xk9g-z9fh",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 5.62e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "electronic_conductivity",
"quantity": {
"value": 0.222,
"unit": "S/m"
},
"provenance_class": "fitted"
},
{
"parameter": "surface_area_per_volume",
"quantity": {
"value": 499522.0,
"unit": "1/m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.253991,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
"quantity": {
"value": 0.128,
"unit": "1"
},
"provenance_class": "fitted"
}
],
"electrode_polarity": "negative",
"model_context": {
"tool": "BPX",
"name": "Test case: user-defined 0th-order hysteresis for graphite-Si blend in negative electrode. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
},
"annex": {
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BPX NMC111-Si pouch hysteresis - negative electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-4afn-7wan-67hf-nwys.json")
.read_text(encoding="utf-8")
)
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"schema:name": "provenance_class",
"schema:value": "fitted"
}
}
],
"schema:variableMeasured": {
"@type": "schema:PropertyValue",
"schema:name": "entropic_coefficient",
"schema:value": "(-0.1112 * x + 0.02914 + 0.3561 * exp(-((x - 0.08309) ** 2) / 0.004616)) / 1000",
"schema:description": "expression (bpx)",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
"schema:isPartOf": {
"@id": "https://w3id.org/battinfo/spec/5rjm-2a2w-4x8c-5dqy"
},
"schema:citation": {
"@id": "https://github.com/FaradayInstitution/BPX",
"@type": "schema:CreativeWork"
},
"schema:comment": "Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford).",
"dcterms:license": {
"@id": "https://spdx.org/licenses/MIT.html"
}
}
BPX NMC111-Si pouch hysteresis - positive electrode build (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-geyv-hp0x-jhrh-c44z.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/geyv-hp0x-jhrh-c44z",
"short_id": "geyvhp",
"name": "BPX NMC111-Si pouch hysteresis - positive electrode build",
"cell_spec_id": "https://w3id.org/battinfo/spec/41wx-hskh-xk9g-z9fh",
"scope": "electrode",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 5.23e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "electronic_conductivity",
"quantity": {
"value": 0.789,
"unit": "S/m"
},
"provenance_class": "fitted"
},
{
"parameter": "surface_area_per_volume",
"quantity": {
"value": 432072.0,
"unit": "1/m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.277493,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
"quantity": {
"value": 0.1462,
"unit": "1"
},
"provenance_class": "fitted"
}
],
"electrode_polarity": "positive",
"model_context": {
"tool": "BPX",
"name": "Test case: user-defined 0th-order hysteresis for graphite-Si blend in negative electrode. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
},
"annex": {
"Negative electrode delithiation OCP [V]": {
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Emitted by record_to_jsonld, hosted-context mode.
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BPX NMC111-Si pouch hysteresis - positive electrode material (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-sdw7-cp7b-nsst-tvvy.json")
.read_text(encoding="utf-8")
)
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]
}
Emitted by record_to_jsonld, hosted-context mode.
{
"@context": "https://w3id.org/battinfo/context/records/v1.json",
"@id": "https://w3id.org/battinfo/spec/sdw7-cp7b-nsst-tvvy",
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},
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}
BPX NMC111-Si pouch hysteresis - separator (parameter-set)
The record ships in the installed wheel — load it as a starting point:
import json
from importlib import resources
record = json.loads(
resources.files("battinfo")
.joinpath("data/examples/parameter-set/parameter-set-smjg-7gh6-93vg-geh5.json")
.read_text(encoding="utf-8")
)
{
"schema_version": "0.2.0",
"parameter_set": {
"id": "https://w3id.org/battinfo/spec/smjg-7gh6-93vg-geh5",
"short_id": "smjg7g",
"name": "BPX NMC111-Si pouch hysteresis - separator",
"cell_spec_id": "https://w3id.org/battinfo/spec/41wx-hskh-xk9g-z9fh",
"scope": "separator",
"claims": [
{
"parameter": "thickness",
"quantity": {
"value": 2e-05,
"unit": "m"
},
"provenance_class": "fitted"
},
{
"parameter": "porosity",
"quantity": {
"value": 0.47,
"unit": "1"
},
"provenance_class": "fitted"
},
{
"parameter": "transport_efficiency",
"quantity": {
"value": 0.3222,
"unit": "1"
},
"provenance_class": "fitted"
}
],
"model_context": {
"tool": "BPX",
"name": "Test case: user-defined 0th-order hysteresis for graphite-Si blend in negative electrode. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release.",
"model": "DFN",
"version": "0.4.0"
},
"annex": {
"Negative electrode delithiation OCP [V]": {
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1.381,
1.382,
1.383,
1.384,
1.385,
1.386,
1.387,
1.388,
1.389,
1.39,
1.391,
1.392,
1.393,
1.394,
1.395,
1.396,
1.397,
1.398,
1.399,
1.4,
1.401,
1.402,
1.403,
1.404,
1.405,
1.406,
1.407,
1.408,
1.4089999999999998,
1.41,
1.4109999999999998,
1.412,
1.4129999999999998,
1.414,
1.4149999999999998,
1.416,
1.4169999999999998,
1.418,
1.4189999999999998,
1.42,
1.4209999999999998,
1.422,
1.4229999999999998,
1.424,
1.4249999999999998,
1.426,
1.4269999999999998,
1.428,
1.4289999999999998,
1.43,
1.4309999999999998,
1.432,
1.4329999999999998,
1.434,
1.4349999999999998,
1.436,
1.4369999999999998,
1.438,
1.4389999999999998,
1.44,
1.4409999999999998,
1.442,
1.4429999999999998,
1.444,
1.4449999999999998,
1.446,
1.4469999999999998,
1.448,
1.4489999999999998,
1.45,
1.4509999999999998,
1.452,
1.4529999999999998,
1.454,
1.4549999999999998,
1.456,
1.4569999999999999,
1.458,
1.4589999999999999,
1.46,
1.4609999999999999,
1.462,
1.4629999999999999,
1.464,
1.4649999999999999,
1.466,
1.4669999999999999,
1.468,
1.4689999999999999,
1.47,
1.4709999999999999,
1.472,
1.4729999999999999,
1.474,
1.4749999999999999,
1.476,
1.4769999999999999,
1.478,
1.4789999999999999,
1.48,
1.4809999999999999,
1.482,
1.4829999999999999,
1.484,
1.4849999999999999,
1.486,
1.4869999999999999,
1.488,
1.4889999999999999,
1.49,
1.4909999999999999,
1.492,
1.4929999999999999,
1.494,
1.4949999999999999,
1.496,
1.4969999999999999,
1.498,
1.4989999999999999
]
}
},
"set_id": "https://w3id.org/battinfo/spec/5rjm-2a2w-4x8c-5dqy"
},
"provenance": {
"source_type": "literature",
"retrieved_at": 1789900000,
"battinfo_version": "0.7.0",
"source_url": "https://github.com/FaradayInstitution/BPX/blob/main/examples/nmc_pouch_cell_BPX_user-defined_hysteresis.json",
"citation": "https://github.com/FaradayInstitution/BPX"
},
"license": "mit",
"notes": [
"Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford)."
]
}
Emitted by record_to_jsonld, hosted-context mode.
{
"@context": "https://w3id.org/battinfo/context/records/v1.json",
"@id": "https://w3id.org/battinfo/spec/smjg-7gh6-93vg-geh5",
"@type": "schema:Dataset",
"schema:name": "BPX NMC111-Si pouch hysteresis - separator",
"schema:about": {
"@id": "https://w3id.org/battinfo/spec/41wx-hskh-xk9g-z9fh"
},
"schema:additionalProperty": [
{
"@type": "schema:PropertyValue",
"schema:name": "scope",
"schema:value": "separator"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_model",
"schema:value": "DFN"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_name",
"schema:value": "Test case: user-defined 0th-order hysteresis for graphite-Si blend in negative electrode. Compare to nmc_pouch_cell_BPX.json in About:Energy open-source release."
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_tool",
"schema:value": "BPX"
},
{
"@type": "schema:PropertyValue",
"schema:name": "source_version",
"schema:value": "0.4.0"
}
],
"hasProperty": [
{
"@type": [
"Thickness",
"ConventionalProperty"
],
"skos:prefLabel": "Thickness",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 2e-05
},
"hasMeasurementUnit": "https://w3id.org/emmo#Metre",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"Porosity",
"ConventionalProperty"
],
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 0.47
},
"hasMeasurementUnit": "https://w3id.org/emmo#EMMO_5ebd5e01_0ed3_49a2_a30d_cd05cbe72978",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
},
{
"@type": [
"battinfo:transportEfficiency",
"ConventionalProperty"
],
"skos:prefLabel": "transportEfficiency",
"hasNumericalPart": {
"@type": "RealData",
"hasNumberValue": 0.3222
},
"hasMeasurementUnit": "https://w3id.org/emmo#EMMO_5ebd5e01_0ed3_49a2_a30d_cd05cbe72978",
"schema:additionalProperty": {
"@type": "schema:PropertyValue",
"schema:name": "provenance_class",
"schema:value": "fitted"
}
}
],
"schema:isPartOf": {
"@id": "https://w3id.org/battinfo/spec/5rjm-2a2w-4x8c-5dqy"
},
"schema:citation": {
"@id": "https://github.com/FaradayInstitution/BPX",
"@type": "schema:CreativeWork"
},
"schema:comment": "Imported from the FaradayInstitution/BPX examples (MIT licence, (c) 2022 University of Oxford).",
"dcterms:license": {
"@id": "https://spdx.org/licenses/MIT.html"
}
}
Fields#
Generated from the packaged JSON Schemas — the same files battinfo validate and the registry’s publish gate enforce. Every record also carries the shared envelope (schema_version, provenance, and optional notes, funding, contributor, license). Quantities are {value, unit} maps and may also carry value_basis (Measured, Conventional, Rated, or Nominal) and conditions (the parameters under which the value holds, each itself a quantity; a qualitative condition may be value_text alone). In JSON-LD, conditions ride a measurement node the quantity isOutputOf; the voltage_reference key instead becomes a hasMetrologicalReference datum on the quantity, beside its unit. When authoring, an instance references its spec with the spec_id= kwarg; the record stores the self-describing <type>_spec_id key shown in the tables below.
parameter-set fields#
Schema: parameter-set.schema.json · required at top level: schema_version, parameter_set, provenance
Field |
Type |
Required |
Description |
|---|---|---|---|
|
→ SpecIri |
yes |
|
|
→ ShortId |
||
|
string |
yes |
Human-readable label for this batch of claims, conventionally ‘ |
|
string |
Target: a generic material kind key from the curated material_kinds vocabulary (e.g. ‘graphite’, ‘nmc811’). Claims about the generic chemistry collate here; resolution falls back from a product-specific material spec to its kind. |
|
|
→ MaterialSpecIri |
Target: a specific material spec (a vendor product/grade). Use for claims measured on a particular product rather than the generic chemistry. |
|
|
→ SpecIri |
Target: a cell spec. Use for cell-level fitted sets (full-cell parameterizations, ECM fits) and for electrode/separator/electrolyte claims that describe this cell’s build rather than a material. |
|
|
|
Physical scope the claims describe. Defaults (in the builder) to ‘material’ for material targets and ‘cell’ for cell-spec targets. Electrode/separator/electrolyte scopes carry manufactured-build parameters (thickness, porosity, transport) that belong to a cell design, not to a powder. |
|
|
|
For electrode-scope claims on a cell-spec target: which electrode the claims describe. |
|
|
object |
The digital artifact these claims came from, when they were imported from a modelling parameter set (BPX file, PyBaMM parameter set, …). |
|
|
array of → Claim |
||
|
string |
||
|
string |
||
|
object |
Source-file extension entries carried verbatim (e.g. a BPX User-defined block): original key -> raw value. No standard semantics are claimed for these; they exist so a re-export reproduces the source file and nothing is silently lost. |
|
|
object |
Parameterisation-set flavor: the explicit block map of member parameter-set records that constitute one co-fitted, runnable parameterisation. A set record carries members INSTEAD of claims (the strict policy admits the empty claims for this flavor only); side assignment lives here because which material parameterises which electrode is a fact of the set, not of the material. |
|
|
→ SpecIri |
Membership in a parameterisation set (the record listing this one under members). Emitted as schema:isPartOf; the set emits dcterms:hasPart. Members carry the backlink; the set publishes with the members. |
Design notes#
The reasoning behind the model
Why claims, not properties. It is tempting to say a diffusivity of graphite is a property of graphite and file it on a material record. Four facts break that model. Most claims target a kind (graphite as such), and kinds are vocabulary, not records — there is no bearer to carry the property. Sources disagree — five published graphite OCPs, fitted diffusivities an order of magnitude apart — and a record’s properties presuppose one adjudicated value, while the spread is the data. Many parameters are not properties of the material at all but of a model fit — a reaction rate constant fitted under DFN belongs to (material × model × calibration), and asserting it on the material would poison the record with model artifacts. And a calibration is a joint estimate: values fitted together are only valid together, so the set is the unit of self-consistency. Hence one record per source, provenance_class per claim, resolution downstream. The describer’s own declarations (a datasheet density) stay properties of the description; third-party and model-bound assertions are claims about the target — the same epistemics rule as spec vs instance.
BPX interop, both directions. from_bpx_parameters imports a BPX file’s electrode/separator/electrolyte physics as claims — scalars, tables as curves, function strings as expressions — splitting material-intrinsic claims (stoichiometry window, diffusivity, OCP) from build claims (thickness, porosity) that target the cell design instead. Header lineage rides along: Model and BPX version in model_context (a DFN-fitted value is not model-free), Description on the record, References as citation or note; the User-defined block travels verbatim as each record’s annex, and Cell-block fields become spec properties (or verbatim extras) via from_bpx — nothing in the file is dropped silently. The reverse: to_bpx(spec, parameter_sets=...) turns ONE source’s records back into a runnable BPX file — claims at full precision, Header.Model from the source’s own model context, State sections for BPX ≥ 1.1 — and the official bpx parser accepts the result. One source per file, deliberately: a calibration is a joint estimate, so mixing sources across blocks would produce a file no validation supports (a labeled composed mode is a planned refinement).
Complete and part, both. Breaking a BPX file into per-component records serves re-use — the graphite claims can inform any graphite cell — but a simulation needs the whole parameterisation, and “which six records go together” must be a stated fact, not a filename convention. So a parameter set comes in two flavors, the same split the dataset-series pattern established. A per-source member record carries claims about one target. A parameterisation set carries members instead of claims: a block map naming the member records that jointly form one source’s complete cell parameterisation, targeting the cell spec. Members point back via set_id; in JSON-LD the set asserts dcterms:hasPart and each member schema:isPartOf, mirroring series ↔ dataset. The set is where the joint-estimate epistemics live explicitly: it says these particular records were calibrated together and are valid together. from_bpx_parameters mints the set whenever it imports a whole file against a cell spec, load_parameter_set_members() resolves it back to the member records, and to_bpx accepts that map directly, so the complete-file round trip is one load away from the re-usable parts.