Artificial Intelligence for Materials Science group

gcnn_keras

Graph convolutions in Keras with TensorFlow, PyTorch or Jax.

MOF_Synthesis_Prediction

ChemMatData

An overview over chemical datasets and where to find them

3DSC

Repo for the paper publishing the superconductor database with 3D crystal structures.

NNsForMD

Neural network class for molecular dynamics to predict potential energy, forces and non-adiabatic couplings.

graph_attention_student

Minimal implementation of graph attention student model architecture

ML4HEOs

Machine Learning methods for high entropy oxides

ActiveLearningFramework

Bachelor Thesis of Meret Unbehaun, Topic: Active Learning strategies for Machine Learned potentials

MOF_web_interface

perovskite_htm_screening

Code for paper "Accelerating the discovery of materials for integrated/complex device"

ChemEngML

MAChINE

Client-Server Web App to introduce usage of ML in materials science to beginners

microdroplet_segmentation

Segmentation for microdroplet arrays used in screening experiments.

visual_graph_datasets

Datasets for the training of graph neural networks (GNNs) and subsequent visualization of attributional explanations of XAI methods

ActiveLearningFramework-1

Bachelor Thesis of Meret Unbehaun, Topic: Active Learning strategies for Machine Learned potentials

GraphReactionNet

ML4pXRDs

Contains code to train neural networks based on simulated powder XRDs from synthetic crystals.

package-index

Public package index for the AIMat Lab.

smilesDrawer

A small, highly performant JavaScript component for parsing and drawing SMILES strings. Released under the MIT license.

Towards-a-high-quality-public-pXRD-dataset

Draft of a paper presenting and discussing a dataset that is currently being assembled by the AiMat group at KIT. It will be released for public and free use as soon as possible.

AutoMol

AutoML for chemistry/materials

cluster-hyperopt-tutorial

jarvis_leaderboard

This project provides benchmark-performances for materials science applications including Artificial Intelligence (AI), Electronic Structure (ES), Force-field (FF), Quantum Computation (QC) and Experiments (EXP) methods.

llm-data-extraction

Using Large Language Models for Zero-Shot Data Extraction from Scientific Literature

megan_global_explanations

Extracting global concept explanations from the self-explaining MEGAN model

MOF_Literature_Extraction

xrdpattern

Python library for XrdPatterns including file import, file export and postprocessing functionalities