Papers

Active Learning

Scaling Deep Learning for Materials Discovery (Nature, 2023) – Google DeepMind

DOI: https://doi.org/10.1038/s41586-023-06735-9

Accelerated Discovery of Large Electrostrains in BaTiO3‐Based Piezoelectrics Using Active Learning (Advanced Materials, 2018)

DOI: https://doi.org/10.1002/adma.201702884

Accelerated Search for Materials with Targeted Properties by Adaptive Design (Nature Communications, 2016)

DOI: https://doi.org/10.1038/ncomms11241

Bias Free Multiobjective Active Learning for Materials Design and Discovery (Nature Communications, 2021)

DOI: https://doi.org/10.1038/s41467-021-22437-0

Graph Neural Networks

MEGNet: Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals (Chemistry of Materials, 2019)

DOI: https://doi.org/10.1021/acs.chemmater.9b01294

CHGNet as a Pretrained Universal Neural Network Potential for Charge-informed Atomistic Modelling (Nature Machine Intelligence, 2023)

DOI: https://doi.org/10.1038/s42256-023-00716-3

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties (Physical Review Letters, 2018)

DOI: https://doi.org/10.1103/PhysRevLett.120.145301

GemNet: Universal Directional Graph Neural Networks for Molecules (arXiv, 2022)

DOI: https://doi.org/10.48550/arXiv.2106.08903

E(3)-Equivariant Graph Neural Networks for Data-efficient and Accurate Interatomic Potentials (Nature Communication, 2022)

DOI: https://doi.org/10.1038/s41467-022-29939-5 

Natural Language Processing

ChemDataExtractor: A Toolkit for Automated Extraction of Chemical Information from the Scientific Literature (Journal of Chemical Information and Modeling, 2016)

DOI: https://doi.org/10.1021/acs.jcim.6b00207

Quantifying the Advantage of Domain-specific Pre-training on Named Entity Recognition Tasks in Materials Science (Patterns, 2022)

DOI: https://doi.org/10.1016/j.patter.2022.100488

Leveraging Large Language Models for Predictive Chemistry (Nature Machine Intelligence, 2024)

DOI: https://doi.org/10.1038/s42256-023-00788-1

A Multi-modal Pre-training Transformer for Universal Transfer Learning in Metal-organic Frameworks (Nature Machine Intelligence, 2023)

DOI: https://doi.org/10.1038/s42256-023-00628-2

ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis (Journal of the American Chemical Society, 2023)

DOI: https://doi.org/10.1021/jacs.3c05819

Crystal Structure Generation with Autoregressive Large Language Modeling (arXiv, 2023)

DOI: https://doi.org/10.48550/arXiv.2307.04340

CrystalLMM