Theoretical and Computational Chemistry

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Uni-Mol: A Universal 3D Molecular Representation Learning Framework

Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu, Zhewei Wei, Linfeng Zhang, Guolin Ke

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Chemistry

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Parameterized Molecular Cavity Quantum Electrodynamics Approach to Simulate van der Waals Interactions

Sebastian Montillo Vega, Sanchari Sannigrahi, Braden Weight, Pengfei Huo

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Chemistry

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Trends In Computational Metabolomics In The Past Five Years (2021–2025)

Daniel Domingo-Fernández, David Healey, Tobias Kind, August Allen, Viswa Colluru, Biswapriya B. Misra

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Chemistry

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Confidently uncertain: Probabilistic machine learning to predict soil biotransformation half-lives

Moritz Salz, José Andrés Cordero Solano, Kathrin Fenner, Jasmin Hafner

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Chemistry

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PhaseTransfer: A transfer learning framework for efficient phase diagram mapping

Eduardo González-García, Albert J Markvoort, Nadia Erkamp, Tom F.A de Greef

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Chemistry

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Graph machine learning can estimate drug concentrations in whole blood from forensic screening results

Tetiana Lutchyn, Marie Mardal, Michael Nedahl, Benjamin Ricaud

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Chemistry

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Developing and benchmarking Sage 2.3.0 with the AshGC neural network charge model

Lily Wang, Irfan Alibay, Simon Boothroyd, Chapin Cavender, Joshua Horton, Alexandra McIsaac, Joshua Mitchell, Matthew Thompson, Jeffrey Wagner, Brent Westbrook, John Chodera, Daniel Cole, Michael Shirts, David Mobley

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Chemistry

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StereoMolGraph: Stereochemistry-Aware Molecular and Reaction Graphs

Maxim Papusha, Kai Leonhard

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Chemistry

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GPU-Accelerated Analytic Coulomb- and Exchange Gradients for Hartree Fock and Density Functional Theory

Vladimir Mironov, Alexander Paul, Dmitry Morozov, Ruslan Mallaev, Michael Perelshtein, Roman Ellerbrock

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Chemistry

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Accurate and Robust Analysis of Molecular Kinetics with Random Features

Hauke Sprink, Yanchen Zhu, Antonia S.J.S Mey, Feliks Nüske

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Chemistry

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Simulation of charge distribution and microstructure in semicrystalline polymeric ionic-electronic conductors using classical simulation at constant electrochemical potential

Zixuan Wei, Hesam Makki, Paola Carbone, Alessandro Troisi

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Chemistry

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ChemTSv3: Generalizing Molecular Design via Flexible Search Space Control

Satoru Fujii, Yuki Murakami, Tatsuya Yoshizawa, Shoichi Ishida, Nobuo Cho, Masateru Ohta, Teruki Honma, Kazuki Yoshizoe, Masato Sumita, Koji Tsuda, Kei Terayama

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Chemistry

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DAR-GNN: Dynamic Anchor Relational Graph Neural Network for Efficient ADMET Property Prediction with Left-Censored Labels

Haowen Shi, Yichen Zong

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Theoretical and Computational Chemistry

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Uni-Mol: A Universal 3D Molecular Representation Learning Framework

Most Cited

Uni-Mol: A Universal 3D Molecular Representation Learning Framework

Latest Content Latest Content

Parameterized Molecular Cavity Quantum Electrodynamics Approach to Simulate van der Waals Interactions

Trends In Computational Metabolomics In The Past Five Years (2021–2025)

Confidently uncertain: Probabilistic machine learning to predict soil biotransformation half-lives

PhaseTransfer: A transfer learning framework for efficient phase diagram mapping

Graph machine learning can estimate drug concentrations in whole blood from forensic screening results

Developing and benchmarking Sage 2.3.0 with the AshGC neural network charge model

StereoMolGraph: Stereochemistry-Aware Molecular and Reaction Graphs

GPU-Accelerated Analytic Coulomb- and Exchange Gradients for Hartree Fock and Density Functional Theory

Accurate and Robust Analysis of Molecular Kinetics with Random Features

Simulation of charge distribution and microstructure in semicrystalline polymeric ionic-electronic conductors using classical simulation at constant electrochemical potential

ChemTSv3: Generalizing Molecular Design via Flexible Search Space Control

DAR-GNN: Dynamic Anchor Relational Graph Neural Network for Efficient ADMET Property Prediction with Left-Censored Labels

Latest Content