A machine learning environment for atomic-scale modeling in surface science and catalysis.
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Updated
Jun 28, 2024 - Python
A machine learning environment for atomic-scale modeling in surface science and catalysis.
Python tools for automating routine tasks encountered when running quantum chemistry computations.
yadg: yet another datagram
Plug-in for ChimeraX providing features for building and manipulating organic and organometallic molecules as well as displaying output from quantum chemistry computations.
AARON (An Automated Reaction Optimizer for New catalysts) automates DFT optimizations of TS structures for asymmetric catalytic reactions.
[ICML'24] Adsorbate Placement via Conditional Denoising Diffusion
PyCatKin is a class-based Python toolset for catalysis kinetics calculations. It includes modules for energy span analysis and mean-field microkinetic modelling with ideal reactor models.
A program for the electrostatic catalysis of chemical rections. MANULS finds the smallest electric field that removes the reaction barrier.
Lattice Kinetic Monte Carlo (KMC) Simulations for Subnanometer Pdn clusters Dynamics under a pressure of CO.
Repo of GAME-Net-UQ, a graph neural network with uncertainty quantification for predicting the DFT energy of adsorbed intermediates and transition states on monometallic surfaces.
Quantum-inspired Cluster Expansion: formulating chemical space search as QUBOs and Ising models
Kinetics-Constrained Neural Ordinary Differential Equations (KCNODE) that can be trained even with small data
Scripts to use CatChemi to generate figure for thje manuscript "Limits to scaling relations betwen adsorption energies?"
Tools supporting recent DFT electrocatalytic work in the Dr. Mike Janik group
First order Temperature Programmed Desorption analysis package
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