--- id: "/science-medicine/materials-chemistry/" title: "materials & chemistry: 24 curated resources" url: "https://skillissue.dev/science-medicine/materials-chemistry/" --- # materials & chemistry: 24 curated resources materials & chemistry [Beginner](/science-medicine/beginner/index.md) [Intermediate](/science-medicine/intermediate/index.md) [Advanced](/science-medicine/advanced/index.md) [Expert](/science-medicine/expert/index.md) 24 resources · page 1 of 1 - ### [BEEP](/frontier/research-feeds/beep/index.md) by [Toyota Research Institute (Accelerated Materials Design & Discovery)](https://github.com/TRI-AMDD) TRI BEEP GitHub repo: tools for battery evaluation and early prediction of cycle life from cycling data. entity repo US en - ### [ChemCrow](/frontier/research-feeds/chemistry/index.md) by [White Laboratory](https://thewhitelab.org/) ChemCrow GitHub repo: LLM agent package using chemistry tools for reasoning-intensive tasks. entity repo US en - ### [CHGNet](/frontier/research-feeds/chgnet/index.md) by [Ceder Group](https://ceder.berkeley.edu/) CHGNet GitHub repo (Ceder Group): pretrained universal neural network potential for charge-informed atomistic modelling. entity repo US en - ### [DeePMD-kit](/frontier/research-feeds/deepmd-kit/index.md) by [DeepModeling](https://deepmodeling.com) DeePMD-kit GitHub repo: deep learning package for many-body potential energy and molecular dynamics. entity repo China; US; international en - ### [DimeNet](/frontier/research-feeds/dimenet/index.md) by [Johannes Gasteiger, né Klicpera](https://github.com/gasteigerjo) DimeNet GitHub repo: DimeNet and DimeNet++ directional message-passing models for molecules. entity repo EU-DE en - ### [FAIR Chemistry](/frontier/research-feeds/fair-chemistry/index.md) by [Meta Research](https://opensource.fb.com) Meta FAIR Chemistry GitHub repo: machine learning methods and models for chemistry and materials. entity repo US en - ### [FAIR Chemistry Documentation](/frontier/research-feeds/fair-chemistry-open-catalyst-omat-omol/index.md) by [Meta Research](https://opensource.fb.com) FAIR Chemistry documentation: open catalysis, materials and molecule datasets such as Open Catalyst, OMat and OMol, plus models. entity dataset US en - ### [GemNet](/frontier/research-feeds/gemnet/index.md) by [Data Analytics and Machine Learning Group](https://www.in.tum.de/daml) TUM-DAML GemNet GitHub repo: TensorFlow implementation of the GemNet directional message-passing model for molecules. entity repo EU-DE en - ### [Lila Sciences](/frontier/research-feeds/lila-sciences/index.md) by [Lila Sciences](https://lila.ai/) Lila Sciences: company building AI systems and automated labs for scientific discovery. entity lab US en - ### [M3GNet](/frontier/research-feeds/m3gnet/index.md) by [Materialyze.AI](https://materialyze.ai) M3GNet GitHub repo: materials graph network with three-body interactions as an interatomic potential. entity repo US en - ### [MACE](/frontier/research-feeds/mace/index.md) by [ACEsuit](https://github.com/ACEsuit) MACE GitHub repo: equivariant machine learning interatomic potentials for atomistic simulation. entity repo West en - ### [materials](/frontier/research-feeds/materials/index.md) by [Google DeepMind](https://www.deepmind.com/) DeepMind materials_discovery GitHub repo: GNoME dataset of predicted stable crystals, models and Colabs. entity repo UK en - ### [MatterGen](/frontier/research-feeds/mattergen/index.md) by [Microsoft](https://opensource.microsoft.com) Microsoft MatterGen GitHub repo: generative model for designing inorganic materials. entity repo US en - ### [NequIP](/frontier/research-feeds/nequip/index.md) by [MIR@Harvard](https://mir.g.harvard.edu/) NequIP GitHub repo: E(3)-equivariant neural network interatomic potentials. entity repo West en - ### [Periodic Labs](/frontier/research-feeds/periodic-labs/index.md) by [Periodic Labs](https://periodic.com/) Periodic Labs: company using AI and autonomous labs for materials science discovery. entity lab US en - ### [TorchANI](/frontier/research-feeds/torchani/index.md) by [AIQM](https://github.com/aiqm) TorchANI GitHub repo: library for training and using ANI neural network potentials for molecules. entity repo US; international en - ### [Uni-Mol](/frontier/research-feeds/uni-mol/index.md) by [DeepModeling](https://deepmodeling.com) Uni-Mol GitHub repo (DP Technology): 3D molecular pretraining models for property prediction and docking. entity model China en - ### [Autonomous chemical research with large language models (Coscientist)](/frontier/research-feeds/coscientist-boiko-et-al-nature-2023/index.md) by [Daniil A. Boiko et al. (Carnegie Mellon University)](https://www.cmu.edu/) Nature paper (2023) on Coscientist, autonomous chemical research with large language models. Advanced learning_resource paper US en - ### [Scaling deep learning for materials discovery (GNoME)](/frontier/research-feeds/gnome-scaling-deep-learning-for-materials-discovery-nature-2023/index.md) by [Amil Merchant et al. (Google)](https://ai.google/) Nature paper (2023) on GNoME, scaling deep learning to discover new stable materials. Advanced learning_resource paper US/UK en - ### [MatGL](/frontier/research-feeds/matgl/index.md) by [Materials Virtual Lab (UC San Diego)](https://matgl.ai/) MatGL: graph deep learning library for materials property prediction and interatomic potentials. Advanced learning_resource docs US/global en - ### [matminer](/frontier/research-feeds/matminer/index.md) by [Hacking Materials group (Lawrence Berkeley National Laboratory)](https://hackingmaterials.lbl.gov/) matminer documentation: Python library for mining materials data and generating features for ML models. Advanced learning_resource docs US en - ### [PaiNN](/frontier/research-feeds/painn/index.md) by [Kristof T. Schütt et al. (Technische Universität Berlin)](https://www.tu.berlin) arXiv HTML version of the PaiNN paper (2021) on equivariant message passing for molecular property prediction. Advanced–Expert learning_resource paper EU-DE en - ### [SchNet: A continuous-filter convolutional neural network for modeling quantum interactions](/frontier/research-feeds/schnet/index.md) by [Kristof T. Schütt et al. (Technische Universität Berlin)](https://www.tu.berlin) arXiv paper (2017) introducing SchNet, a continuous-filter convolutional network for modelling quantum interactions in molecules. Advanced–Expert learning_resource paper West en - ### [SchNet: a deep learning architecture for molecules and materials](/frontier/research-feeds/schnet-2/index.md) by [Kristof T. Schütt et al. (Technische Universität Berlin)](https://www.tu.berlin) arXiv paper (2017) "SchNet - a deep learning architecture for molecules and materials", using continuous-filter convolutions to predict molecular energies and forces. Advanced–Expert learning_resource paper Global (TU Berlin/Max Planck; en [Plain-text Markdown copy](/science-medicine/materials-chemistry/index.md)