mat-reaction-network

You can predict thermodynamically favorable solid-state synthesis pathways by enumerating balanced reaction networks and solving for minimum-energy routes from specified precursors to a target material using Materials Project thermodynamics. It identifies the most favorable step sequences and highlights competing sinks.

Thermodynamic modeling calculates minimum-energy routes by building a reaction network for a specified chemical system and temperature, then using a pathway solver to tabulate candidate elementary and combined pathways that approximate the overall net synthesis reaction from precursors.

Yes, you can model open-system synthesis conditions by applying open phases and chemical potential approaches. This supports air-like or reservoir-like conditions using grand potential minimization enumerators alongside standard basic_open enumerators.

Yes, you need Materials Project API access to retrieve thermodynamic data. The pathway prediction requires the mp-api and rxn-network dependencies to generate the reaction network and solve for optimal synthesis routes.

The best way to compare alternative precursor sets is to run pathway predictions for each set of precursor candidates. The solver tabulates candidate pathways, allowing you to identify the most favorable step sequences and compare thermodynamic bottlenecks across different precursors.

Competing sink phases appear because the reaction network enumerates all balanced reactions in the specified chemical system. The pathway solver highlights these competing sinks to show thermodynamic bottlenecks that may prevent efficient synthesis of your target material.