Results 21 to 30 of about 3,070,839 (358)
Fuelling the Digital Chemistry Revolution with Language Models
CHIMIA, 2023 The RXN for Chemistry project, initiated by IBM Research Europe – Zurich in 2017, aimed to develop a series of digital assets using machine learning techniques to promote the use of data-driven methodologies in synthetic organic chemistry.
Antonio Cardinale +12 more
doaj +1 more source
Trade-offs between number fluctuations and response in nonequilibrium chemical reaction networks [PDF]
, 2023 We study the response of chemical reaction networks driven far from equilibrium to logarithmic perturbations of reaction rates. The response of the mean number of a chemical species is observed to be quantitively limited by number fluctuations as well as the maximum thermodynamic driving force.
arxiv +1 more source
Autonomous chemical research with large language models
The Naturalist, 2023 Transformer-based large language models are making significant strides in various fields, such as natural language processing^ 1 – 5 , biology^ 6 , 7 , chemistry^ 8 – 10 and computer programming^ 11 , 12 .
Daniil A. Boiko +3 more
semanticscholar +1 more source
A generative model for molecule generation based on chemical reaction trees [PDF]
, 2021 Deep generative models have been shown powerful in generating novel molecules with desired chemical properties via their representations such as strings, trees or graphs. However, these models are limited in recommending synthetic routes for the generated molecules in practice. We propose a generative model to generate molecules via multi-step chemical
arxiv +1 more source
Stirring Speeds Up Chemical Reaction [PDF]
, 2021 We consider absorbing chemical reactions in a fluid flow modeled by the coupled advection-reaction-diffusion equations. In these systems, the interplay between chemical diffusion and fluid transportation causes the enhanced dissipation phenomenon. We show that the enhanced dissipation time scale, together with the reaction coupling strength, determines
arxiv +1 more source
Uncertainty-aware First-principles Exploration of Chemical Reaction Networks [PDF]
J. Phys. Chem. A 2024, 128, 4532-4547, 2023 Exploring large chemical reaction networks with automated exploration approaches and accurate quantum chemical methods can require prohibitively large computational resources. Here, we present an automated exploration approach that focuses on the kinetically relevant part of the reaction network by interweaving (i) large-scale exploration of chemical ...
arxiv +1 more source
Chemical reaction planar fronts with a viscoelastic reaction product [PDF]
, 2021 A stress-affected chemical reaction front propagation is considered utilizing the concept of a chemical affinity tensor. A reaction between an elastic solid and diffusing constituents, localized at the reaction front, is considered. As a result of the reaction, the elastic constituent transforms into viscoelastic one.
arxiv +1 more source
Química Nova, 2008 A diagnostic instrument was developed to evaluate the basic chemistry concepts held by freshmen students of the three Chemistry undergraduate courses offered by the University of São Paulo.
Carmen Fernandez +3 more
doaj +1 more source
Nature Communications, 2021 Machine learning algorithms offer new possibilities for automating reaction procedures. The present paper investigates automated reaction’s prediction with Molecular Transformer, the state-of-the-art model for reaction prediction, proposing a new ...
Dávid Péter Kovács +2 more
doaj +1 more source
Prediction of chemical reaction yields using deep learning
Machine Learning: Science and Technology, 2020 Artificial intelligence is driving one of the most important revolutions in organic chemistry. Multiple platforms, including tools for reaction prediction and synthesis planning based on machine learning, have successfully become part of the organic ...
P. Schwaller +3 more
semanticscholar +1 more source