A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.

Use time-splits for Materials Project entries for generative modeling benchmarking.

[npj Computational Materials] The implementation for the paper "Physics-informed graph neural network representation learning for crystal property prediction"

AI-native materials discovery workspace with graph-grounded evidence and agentic candidate screening

Interactive phase diagram generator for up to 4 components (solid phases) using the Materials Project API and pymatgen.

Automatic Generation of Quantum ESPRESSO Input Files

Modern React UI library based on mp-react-components, for materials science applications, with full TypeScript support and reusable scientific UI components.

Some programs I use in my research

Scientific data enrichment tool for Open WebUI - Chemistry and materials science integration with PubChem, ChEMBL, Materials Project, and RDKit

Predicting lithium cathode properties (voltage, capacity, formation energy, stability) from crystal structure using CGCNN, M3GNet, TensorNet, Random Forest, and XGBoost on data from Materials Project, OQMD, AFLOW, and JARVIS

Transfer learning using a high order message passing foundational model to F-Li-B cells.

Criticality-aware sodium-ion cathode prioritization using Materials Project records, text-mined evidence, and leakage-audited ML.

Multimodal Deep Learning pipeline for crystalline bandgap prediction. Combines 1D X-Ray Diffraction (XRD) patterns with engineered tabular features (Magpie & CrystalNN) using a dual-branch PyTorch ResNet architecture. Features high-throughput data extraction via Materials Project API and automated structural featurization.

Does crystal symmetry predict oxide stability? Four-part analysis on Materials Project data: exception detection, composite scoring, polymorph case studies, and solar band gap screening.

ML pipeline that screens the Materials Project for overlooked solar absorbers — surfaced a validated 1.3 eV candidate with zero PV literature

Heuristic, phase-specific screening for 2D MX2 semiconductor candidates, published with its full critical-review trail. Independent chemist audit verdict: "not scientifically reliable in its current form". A high-school exploratory project, not experimentally validated - do not use to guide synthesis, safety, investment, or engineering decisions.

I want to download data from Materials Project through API but I have an import error. Could anyone tell me how to solve it?

Graph-based material intelligence platform for battery material screening, criticality analysis, similarity search, and recommendation-driven decision support.