Materials Project

Official Resources

• Homepage: https://materialsproject.org/
• Documentation: https://docs.materialsproject.org/
• Source Repository: https://github.com/materialsproject
• License: CC BY 4.0 (Data), MIT (Code)

Overview

The Materials Project (MP) is a major initiative to compute the properties of all known inorganic materials and provide the data freely to the public. It provides a searchable database of calculated properties (band structures, elastic constants, piezoelectricity, etc.) generated using high-throughput DFT (VASP). It also provides an API (MAPIDoc) and a Python client (mp_api) for programmatic access.

Scientific domain: Materials database, high-throughput DFT, materials informatics
Target user community: Materials scientists, data scientists, chemists

Capabilities (CRITICAL)

• Data Access: Web interface to search materials by elements, formula, or properties.
• Properties: Structure, formation energy, band gap, density of states, elastic tensor, piezoelectric tensor, dielectric constant, X-ray absorption spectra, phonon dispersion.
• Apps: Phase diagram app, Pourbaix diagram app, Battery explorer, Crystal toolkit.
• API: RESTful API (MPRester) for downloading large datasets.
• Provenance: Full calculation details (inputs/outputs) available.

Sources: Materials Project website, APL Mater. 1, 011002 (2013)

Inputs & Outputs

• Input formats: Queries (JSON, Python criteria)
• Output data types: Structures (CIF/POSCAR), Property values, Plots

Interfaces & Ecosystem

• Pymatgen: The official analysis library and API client.
• FireWorks/Atomate: The workflow stack used to generate the data.
• Crystal Toolkit: Web-based visualization.

Workflow and Usage

1. Web: Go to materialsproject.org, search for "Li-Fe-P", filter by stable materials.
2. Python:

   from mp_api.client import MPRester
   with MPRester("API_KEY") as mpr:
       docs = mpr.summary.search(chemsys="Li-Fe-P", band_gap=(1.0, 3.0))
   

Performance Characteristics

• Massive database (>140,000 materials)
• API rate limits apply
• Pre-computed data (instant retrieval vs waiting for calculation)

Application Areas

• Battery material discovery
• Photovoltaic screening
• Thermoelectric material search
• Machine learning model training

Community and Support

• Developed by LBNL and partners
• Huge user base (>200,000 registered users)
• Active forum (MatSci.org)

Verification & Sources

Primary sources:

1. Homepage: https://materialsproject.org/
2. Documentation: https://docs.materialsproject.org/
3. Publication: A. Jain et al., APL Mater. 1, 011002 (2013)

Confidence: VERIFIED

Verification status: ✅ VERIFIED

• Website: ACTIVE
• Documentation: COMPREHENSIVE
• Source: OPEN (Code), OPEN ACCESS (Data)
• Development: ACTIVE
• Applications: Materials database, API, discovery