Open Chemistry: Quantum Chemical Data with Jupyter and REST APIs

The Open Chemistry project provides an open source framework for producing, sharing, and visualizing quantum chemical data interactively on the web. It integrates tools like Jupyter notebooks, 3D accelerated visualization, computational chemistry codes including NWChem and Psi4, and machine learning tools such as ChemML and ANI. The framework was developed by Marcus D. Hanwell at Brookhaven National Laboratory.

Use Cases

• Visualizing molecular structures and quantum chemical results based on the integrated 3D accelerated visualization tools.
• Developing interactive computational chemistry workflows based on the integration with Jupyter notebooks.
• Applying machine learning to quantum chemistry problems based on the inclusion of tools like ChemML and ANI.
• Comparing computational and experimental data based on the described flexible data import/export and comparison approaches.

Strengths

• Framework integrates several established open-source community projects, including Jupyter.
• Supports state-of-the-art computational chemistry codes such as NWChem and Psi4.
• Includes emerging machine learning and data mining tools like ChemML and ANI.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

Brookhaven National Laboratory

Collection Method

Developed as an open source framework for quantum chemistry.