Machine learning-based neural network potentials often cannot describe long-range interactions. Here the authors present an approach for building neural network potentials that can describe the ...
Protein molecules can have complicated structures that dictate their functions. Christoph Burgstedt/Science Photo Library via Getty Images Although the Nobel Prizes in physics and chemistry are ...
Six popular machine learning models. (a) Decision tree; (b) feedforward neural network (Trans: transformation; Activ Func: activation functions); (c) convolution neural network (Conv: convolution; ...
The key idea behind our framework is that life produces molecules with purpose, while nonliving chemistry does not. Cells ...
(Nanowerk News) Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of ...
A machine-learning tool can easily spot when chemistry papers are written using the chatbot ChatGPT, according to a scientific study. The study in Cell Reports Physical Science said that a specialised ...
Machine-learning tools have taken us closer to understanding electrons and how they behave in chemical interactions, following news that UK-based AI company DeepMind, owned by Google’s parent company ...
Researchers at Stony Brook University’s Materials Science and Chemical Engineering Department have been using computers that are capable of learning to recognize various steps in the complex movement ...
Imagine you’re a materials scientist and your job is to discover a new material, a combination of atoms no one has ever made. Maybe you’re looking for a metal-organic framework (MOF). They have a lot ...
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Explainable AI supports improved nickel catalyst design for converting carbon dioxide into methane
The conversion of carbon dioxide into clean fuels is regarded as an important route toward carbon neutrality. CO 2 methanation, in particular, has drawn increasing interest due to its favorable ...
Achieving autonomous multi-step synthesis of novel molecular structures in chemical discovery processes is a goal shared by many researchers. In this Comment, we discuss key considerations of what an ...
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