Genarris¶
A scalable, MPI-parallel Crystal Structure Prediction workflow for organic molecular crystals.
🏛️ Developed by the Noa Marom Group at Carnegie Mellon University.
📦 Installation
Set up Genarris with pip in minutes.
🚀 Quick Start
Run your first CSP workflow step by step.
📖 API Reference
Learn about gnrs API.
💎 Case Studies
CSP results and applications.
Key Features¶
Random crystal generation across all 230 space groups.
Improve efficiency of close-packed molecular crystal generation.
Evaluate energies with state-of-the-art MLIPs including UMA, MACE-OFF, and AIMNet2 with GPU acceleration.
AP / K-Means clustering with ACSF descriptors and flexible selection strategies.
Scales to hundreds of cores with GPU worker/feeder pattern.
Configurable CSP workflows with extensible base classes.
Supported Energy Calculators¶
🔧 Calculator |
🏷️ Type |
🖥️ GPU |
📝 Description |
|---|---|---|---|
MLIP |
✅ |
Universal Model for Atoms from Meta FAIR Chemistry Team. |
|
MLIP |
✅ |
Transferable Organic Force Fields |
|
MLIP |
✅ |
Flexible long-range interactions |
|
Semi-Empirical |
— |
Density Functional Tight Binding |
|
DFT |
— |
All-electron DFT code |
|
DFT |
— |
Plane-wave DFT code |
Citation¶
Please cite
Yang, Y., Tom, R., Wui, J. A., Moussa, J. E., & Marom, N. Genarris 3.0: Generating Close-Packed Molecular Crystal Structures with Rigid Press. Journal of Chemical Theory and Computation, 21, 11318–11332 (2025).
See the full Citation page for all related papers.