Kevin Spiekermann

Materials Science · Physical Sciences

12h-index926citations31works8.22yr avg
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Research Topics

Machine Learning in Materials Science(18), Computational Drug Discovery Methods(15), Advanced Chemical Physics Studies(5), Catalytic Processes in Materials Science(4), Catalysis and Oxidation Reactions(4)

Publications31 total

Transformer-Based Approach for Automated Functional Group Replacement in Chemical Compounds
arXiv (Cornell University)·2026Open Access
Transformer-Based Approach for Automated Functional Group Replacement in Chemical Compounds
ArXiv.org·2026Open Access
Revisiting a large and diverse data set for barrier heights and reaction energies: best practices in density functional theory calculations for chemical kinetics
Physical Chemistry Chemical Physics·2025· 8 cited
Accurately Predicting Barrier Heights for Radical Reactions in Solution Using Deep Graph Networks
The Journal of Physical Chemistry A·2024· 10 cited
High Accuracy Barrier Heights, Enthalpies, and Rate Coefficients for Chemical Reactions
Zenodo (CERN European Organization for Nuclear Research)·2024Open Access
When Do Quantum Mechanical Descriptors Help Graph Neural Networks to Predict Chemical Properties?
Journal of the American Chemical Society·2024· 55 cited
When Do Quantum Mechanical Descriptors Help Graph Neural Networks Predict Chemical Properties?
2024Open Access
When Do Quantum Mechanical Descriptors Help Graph Neural Networks Predict Chemical Properties?
2024· 1 citedOpen Access
When Do Quantum Mechanical Descriptors Help Graph Neural Networks Predict Chemical Properties?
2024Open Access
ConfSolv: Prediction of Solute Conformer-Free Energies across a Range of Solvents
The Journal of Physical Chemistry B·2023· 15 cited
Machine Learning Validation via Rational DatasetSampling with astartes
The Journal of Open Source Software·2023· 13 citedOpen Access
Dataset for "ConfSolv: Prediction of solute conformer free energies across a range of solvents"
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
Dataset for "ConfSolv: Prediction of solute conformer free energies across a range of solvents"
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
Comment on ‘Physics-based representations for machine learning properties of chemical reactions’
Machine Learning Science and Technology·2023· 12 citedOpen Access
Dataset for "ConfSolv: Prediction of solute conformer free energies across a range of solvents"
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
Automated reaction kinetics and network exploration (Arkane): A statistical mechanics, thermodynamics, transition state theory, and master equation software
International Journal of Chemical Kinetics·2023· 39 citedOpen Access
RMG-DB-11: Enumerating Reaction Space for Small Molecule Chemistry
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
RDB7-Rad
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
RMG-DB-11: Enumerating Reaction Space for Small Molecule Chemistry
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
RDB7-Rad
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
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Frequent Co-authors

William H. Green(21), Lagnajit Pattanaik(10), Angiras Menon(10), Haoyang Wu(5), Yi‐Pei Li(5), Frederik Sandfort(5), Xiaorui Dong(4), A. Mark Payne(4), Shih‐Cheng Li(4), Volker Settels(4), Zipei Tan(4), Florence H. Vermeire(4), Philipp Eiden(4), Ronnie H. Fang(3), Weiwei Gao(3), Liangfang Zhang(3), Matthew S. Johnson(3), Alon Grinberg Dana(3), Ryan J. Gillis(3), Mengjie Liu(3)