Data Models

All output data is represented as Pydantic models. You can serialise any model to JSON with .model_dump() and parse from a dict with .model_validate(data).

Core synthesis ontology#

GeneralSynthesisOntology#

class GeneralSynthesisOntology(BaseModel)

Bases: BaseModel

Comprehensive synthesis ontology for structured synthesis procedures.

ProcessStep#

class ProcessStep(BaseModel)

Bases: BaseModel

Material#

class Material(BaseModel)

Bases: BaseModel

Equipment#

class Equipment(BaseModel)

Bases: BaseModel

Conditions#

class Conditions(BaseModel)

Bases: BaseModel

Paper models#

Paper#

class Paper(BaseModel)

Bases: BaseModel

PaperWithSynthesisOntologies#

class PaperWithSynthesisOntologies(Paper)

Bases: Paper

SynthesisEntry#

class SynthesisEntry(BaseModel)

Bases: BaseModel

Performance / plot models#

MaterialPerformanceData#

class MaterialPerformanceData(BaseModel)

Bases: BaseModel

All performance data for a single material, aggregated across plots.

MaterialPlotEntry#

class MaterialPlotEntry(BaseModel)

Bases: BaseModel

One plot series linked to a material, with its coordinate data.

PlotMaterialMapping#

class PlotMaterialMapping(BaseModel)

Bases: BaseModel

All series-to-material mappings for a single plot.

SeriesMapping#

class SeriesMapping(BaseModel)

Bases: BaseModel

A single mapping from a plot series name to a material name.

LinkingStats#

class LinkingStats(BaseModel)

Bases: BaseModel

Statistics about plot linking for summary output.