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import json
# Transform value in metadata
def transform_value(key, value):
if isinstance(value, dict):
if "Value" in value and "Unit" in value:
value_type = "str" if isinstance(value["Value"], str) else "float"
return {
"key": key,
"type": "dict",
"value": [
{"key": "Value", "type": value_type, "value": value["Value"]},
{"key": "Unit", "type": "str", "value": value["Unit"]},
],
}
else:
return {
"key": key,
"type": "dict",
"value": [transform_value(k, v) for k, v in value.items()],
}
elif isinstance(value, list):
return {
"key": key,
"type": "list",
"value": [transform_value("", item) for item in value],
}
elif isinstance(value, str):
return {"key": key, "type": "str", "value": value}
else:
raise ValueError(f"Unsupported value type: {type(value)}")
def my_json_to_kadi(data):
return [transform_value(key, value) for key, value in data.items()]
# Print the output JSON in a formatted way
# Some example JSON inputs for testing
input_json = {
"Material": {
"Name": "LLTO",
"Composition": "(Li,La)TiO-type",
"Type": "Perovskite-type",
"Properties": {
"Ionic Conductivity": {"Value": "10^-3", "Unit": "S cm^-1"},
"Chemical Stability": "",
"Dendrite Formation Risk": "",
"Operating Voltage": "",
"Flexibility": "",
"Processing": "",
},
},
"Performance": {
"Specific Capacity": {"Value": "", "Unit": ""},
"Energy Density": {"Value": "", "Unit": ""},
"Capacity Retention": "",
"Operating Temperature": {"Value": "Room temperature", "Unit": ""},
},
"Usage": {"Battery Type": "", "Benefits": []},
}
# Another test
input_json = {
"Experiment": {
"Material": "LATP powders",
"SynthesisRoute": "modified sol-gel synthesis route described by (Bucharsky et al., 2015)",
"Precursors": [
{
"Name": "lithium acetate Li(C2H3O2) ⋅2H2O",
"Purity": "purity ≥ 99 %",
"Supplier": "Alfa Aesar GmbH & Co KG",
"Location": "Germany",
},
{
"Name": "aluminum nitrate Al(NO3)3 ⋅9H2O",
"Purity": "purity ≥ 98.5 %",
"Supplier": "Merck KGaA",
"Location": "Germany",
},
{
"Name": "titanium-isopropoxide Ti[OCH(CH3)2]4",
"Purity": "purity ≥ 98 %",
"Supplier": "Merck KGaA",
"Location": "Germany",
},
],
"Procedure": [
{
"Step": "Dissolve lithium acetate and aluminum nitrate in distilled water under constant stirring."
},
{"Step": "Add titanium-isopropoxide dropwise to the solution."},
{"Step": "Add phosphoric acid slowly through a drip funnel to form a gel."},
{"Step": "Dry the gel at room temperature for 24 h."},
],
"HeatTreatment": [
{
"Step": "First, heat treat samples at 400°C for 6 h to achieve precursor formation and eliminate reaction gases."
},
{
"Step": "Second, process samples at 900°C for 8 h to complete the reaction to crystalline LATP."
},
],
"BatchVariations": [
{
"Description": "Prepare one batch with all precursors in stoichiometric quantities (marked as 0.0 wt%)."
},
{
"Description": "Explore different batches with either an excess up to +7.5 wt% or a deficiency up to -15.0 wt% of phosphoric acid compared to the stoichiometric composition."
},
],
"Processing": [
{"Step": "Process the obtained powders in a planetary ball mill."},
{
"Step": "Form pellets by uniaxial pressing and then further densify by cold isostatic pressing at 400 MPa."
},
{
"Step": "All pressed samples have a green density of approximately 62% relative density."
},
],
"Sintering": {
"TemperatureRange": "850 to 1,050°C",
"IsothermalSinteringTime": "30 to 540 min",
"Cooling": "Cool down to room temperature in furnace",
"DensityDetermination": "Determine densities by Archimedes’ method",
},
"IonicConductivityMeasurements": {
"Method": "Impedance analysis",
"Conditions": "At room temperature over the frequency range from 0.1 Hz to 1 MHz with an AC amplitude of 50 mV in the frequency response analyzer (AMTEK GmbH, VersaSTAT 4, Pennsylvania, United States)",
"Reference": "For further details of the experimental part please refer to our previous work (Schiffmann et al., 2021)",
},
}
}
if __name__ == "__main__":
# Transform the input JSON
from kadi_apy.lib.conversion import json_to_kadi
output_json = json_to_kadi(input_json)
# Print the output JSON
print(json.dumps(output_json, indent=2))
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