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Found 5 papers, 2 papers with code
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Recent studies suggested that these models could be useful in chemistry and materials science.
SELFIES and the future of molecular string representations
We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science.
A reproducibility study of "Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space"
The main claims of the paper are that this GA outperforms other generative techniques (as measured by the penalized logP) and that a neural network-based adaptive penalty increases the diversity of the generated molecules.
Materials Cloud, a platform for open computational science
Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling.
Materials Science Computational Physics J.2; I.6; H.4
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
The review also includes a general overview of the different ML techniques, but as most applications in porous materials use supervised ML our review is focused on the different approaches for supervised ML.
