Wang-Group / Machine-learning-for-Cu-CO2RRLinks
This is the Python code and original data of "Machine-Learning Guided Discovery and Optimization of Additives in Preparing Cu Catalyst for Selective Electrochemical CO2 Reduction" from XMU Wang-group.
☆8Updated 2 years ago
Alternatives and similar repositories for Machine-learning-for-Cu-CO2RR
Users that are interested in Machine-learning-for-Cu-CO2RR are comparing it to the libraries listed below
Sorting:
- ☆60Updated 4 years ago
- Ionic liquid force field parameters (OPLS-2009IL and OPLS-VSIL)☆65Updated 11 months ago
- Universal Transfer Learning in Porous Materials, including MOFs.☆106Updated last year
- Python library for the construction of porous materials using topology and building blocks.☆70Updated 2 months ago
- Crystal Edge Graph Attention Neural Network☆22Updated last year
- A system for rapid identification and analysis of metal-organic frameworks☆59Updated 8 months ago
- ☆48Updated 3 years ago
- molSimplify code☆194Updated last week
- AI-enhanced computational chemistry☆100Updated last month
- We developed a novel method, MOF-CGCNN, to efficiently and accurately predict the methane the volumetric uptakes at 65 bar for MOFs. Two …☆19Updated 3 years ago
- Heat capacity predictor for porous materials☆12Updated last year
- BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simu…☆115Updated 3 months ago
- The QMOF Database: A database of quantum-mechanical properties for metal-organic frameworks.☆146Updated 2 months ago
- A Large Language Model of the CIF format for Crystal Structure Generation☆116Updated 6 months ago
- A collection of Nerual Network Models for chemistry☆154Updated last month
- Gromacs to Lammps simulation converter☆82Updated last year
- Force field for ionic liquids☆65Updated 2 months ago
- A package for Covalent Organic Frameworks structure assembly based on specific building block, topology and functional groups based on th…☆55Updated last week
- A collection of tools and databases for atomistic machine learning☆48Updated 4 years ago
- AlphaCrytal: Contact map based deep learning algorithm for crystal structure prediction☆10Updated last year
- Supporting material for the paper "Data driven collective variables for enhanced sampling"☆19Updated last year
- Interpolation of molecular geometries through geodesics in redundant internal coordinate hyperspace for complex transformations☆59Updated 5 months ago
- EDBO+. Bayesian reaction optimization as a tool for chemical synthesis.☆77Updated last month
- ☆17Updated 3 years ago
- Example scripts using the CSD Python API☆75Updated 2 weeks ago
- SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT, SLICES-PLUS☆114Updated 4 months ago
- Clean, Uniform and Refined with Automatic Tracking from Experimental Database (CURATED) COFs☆38Updated last year
- AI for crystal materials☆74Updated last week
- ☆29Updated last year
- PoreBlazer (v4.0) source code, examples, and geometric properties of porous materials calculated for the subset of 12,000 structures from…☆54Updated last year