Geoffrey Hutchison

University of Pittsburgh — United States

Materials Science · Physical Sciences

35h-index26.9kcitations190works15.22yr avg
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Research Topics

Machine Learning in Materials Science(61), Computational Drug Discovery Methods(55), Organic Electronics and Photovoltaics(45), Conducting polymers and applications(41), Molecular Junctions and Nanostructures(39)

Publications190 total

Avogadro
Zenodo (CERN European Organization for Nuclear Research)·2026Open Access
TurtleMol: Flexible Generation of Complex Molecular Systems for Computational Chemistry
2025Open Access
The seventh blind test of crystal structure prediction: structure generation methods
Acta Crystallographica Section B Structural Science Crystal Engineering and Materials·2024· 65 citedOpen Access
<tt>cclib</tt> 2.0: An updated architecture for interoperable computational chemistry
The Journal of Chemical Physics·2024· 4 citedOpen Access
QupKake: Integrating Machine Learning and Quantum Chemistry for Micro-p <i>K</i> <sub>a</sub> Predictions
Journal of Chemical Theory and Computation·2024· 20 citedOpen Access
Meta-Analysis of Molecular Design Strategies for Non-Fullerene Acceptor Based Organic Solar Cell Materials
2024· 2 citedOpen Access
QupKake: Integrating Machine Learning and Quantum Chemistry for micro-pKa Predictions
2023· 5 citedOpen Access
Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences
Journal of Chemical Information and Modeling·2023· 10 citedOpen Access
Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences
2023Open Access
Conformer Generation for Structure-Based Drug Design: How Many and How Good?
Journal of Chemical Information and Modeling·2023· 38 citedOpen Access
Determining best practices for using genetic algorithms in molecular discovery
The Journal of Chemical Physics·2023· 21 citedOpen Access
Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences
2023Open Access
Tutorial: Determining Best Practices for Using Genetic Algorithms in Molecular Discovery
2023Open Access
Conformer Generation for Structure Based Drug Design: How Many and How Good?
2023Open Access
Screening Efficient Tandem Organic Solar Cells with Machine Learning and Genetic Algorithms
The Journal of Physical Chemistry C·2023· 40 citedOpen Access
Best Practices for Using Genetic Algorithms in Molecular Discovery
2023· 2 citedOpen Access
Using genetic algorithms to discover novel ground-state triplet conjugated polymers
Physical Chemistry Chemical Physics·2023· 6 citedOpen Access
Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences
2022Open Access
Designing Efficient Tandem Organic Solar Cells with Machine Learning and Genetic Algorithms
2022· 1 citedOpen Access
Using Genetic Algorithms to Discover Novel Ground- State Triplet Conjugated Polymers
2022· 1 citedOpen Access
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Frequent Co-authors

Mark A. Ratner(9), Tobin J. Marks(9), Noel M. O’Boyle(7), Héctor D. Abruña(5), Tim Vandermeersch(4), Ilana Y. Kanal(3), Casey M. Campbell(3), Shaopeng Zhang(3), Tara Y. Meyer(3), Lucian Chan(3), Garrett M. Morris(3), Yasuyuki Kiya(3), Jay C. Henderson(3), Craig A. James(2), Chris Morley(2), Marcus D. Hanwell(2), David Lonie(2), Antonio Facchetti(2), Myung‐Han Yoon(2), Rajarshi Guha(2)