chiang-yuan

mace

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

mlip-arena

Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics

CADReality

3D realtime design drawing, modification and presentation using augmented reality technology on the Unity platform.

csh4lmp

The computational modeling tool for custom atomistic model of calcium-silicate-hydrates (C-S-H)

culsm

CUDA C++ code implementing GPU-accelerated Lattice Spring Model (CuLSM) simulations.

llamp

A web app and Python API for multi-modal RAG framework to ground LLMs on high-fidelity materials informatics. An agentic materials scientist powered by @materialsproject, @langchain-ai, and @openai

matbench-discovery

An evaluation framework for machine learning models simulating high-throughput materials discovery.

atomate2

atomate2 is a library of computational materials science workflows

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

chiang-yuan/llamp

A web app and Python API for multi-modal RAG framework to ground LLMs on high-fidelity materials informatics. An agentic materials scientist powered by @materialsproject, @langchain-ai, and @openai

chiang-yuan/csh4lmp

The computational modeling tool for custom atomistic model of calcium-silicate-hydrates (C-S-H)

chiang-yuan/CADReality

3D realtime design drawing, modification and presentation using augmented reality technology on the Unity platform.

chiang-yuan/culsm

CUDA C++ code implementing GPU-accelerated Lattice Spring Model (CuLSM) simulations.

chiang-yuan/ProDAR

PyTorch implementation of Protein Dynamically Activated Residues (ProDAR) for dyamics-informed protein function prediction/annotation

chiang-yuan/muse

A python package for fast building amorphous solids and liquid mixtures from @materialsproject computed structures and machine learning interatomic potentials

chiang-yuan/OFF2Particle

Fill solid with FCC particles

chiang-yuan/Img2Particle

chiang-yuan/atomate2

atomate2 is a library of computational materials science workflows

chiang-yuan/chiang-yuan.github.io

A beautiful, simple, clean, and responsive Jekyll theme for academics

chiang-yuan/culsm-cpu

chiang-yuan/lammps

Public development project of the LAMMPS MD software package

chiang-yuan/cyclone

chiang-yuan/devops_tutorial_2023

A tutorial repository for LLNL's 2023 Data Science Summer Institute.

chiang-yuan/fairchem

FAIR Chemistry's library of machine learning methods for chemistry

chiang-yuan/jax-md

Differentiable, Hardware Accelerated, Molecular Dynamics

chiang-yuan/jobflow

jobflow is a library for writing computational workflows.

chiang-yuan/langchain

⚡ Building applications with LLMs through composability ⚡

chiang-yuan/mace

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

chiang-yuan/matbench-discovery

An evaluation framework for machine learning models simulating high-throughput materials discovery.

chiang-yuan/matcalc

A python library for calculating materials properties

chiang-yuan/mgmol

MGmol is a scalable O(N) First-Principles Molecular Dynamics code that is capable of performing large-scale electronics structure calculations and molecular dynamics simulations of atomistic systems.

chiang-yuan/notes

chiang-yuan/plumed2

Development version of plumed 2

chiang-yuan/pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

chiang-yuan/quacc

quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.

chiang-yuan/vasp-interactive