Joel M. Bowman

Emory University — United States

Physics and Astronomy · Physical Sciences

89h-index32.1kcitations726works3.92yr avg
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Research Topics

Advanced Chemical Physics Studies(482), Spectroscopy and Quantum Chemical Studies(234), Spectroscopy and Laser Applications(207), Quantum, superfluid, helium dynamics(186), Atmospheric Ozone and Climate(171)

Publications726 total

“Gold-Standard” Δ-Machine Learned Transferable Potential for Linear Alkanes
The Journal of Physical Chemistry Letters·2025Open Access
"Gold-Standard" $Δ$-Machine Learned and Transferable Potential for Linear Alkanes
arXiv (Cornell University)·2025Open Access
The energy landscape of folding in <i>n</i>-C14H30 described by a machine-learned potential
The Journal of Chemical Physics·2025· 1 cited
The IR spectrum of liquid water in the OH(D)-stretch region and beyond using q-AQUA-pol and the quantum local monomer theory
Molecular Physics·2025
Revisiting the H<sub>5</sub>O<sub>2</sub><sup>+</sup> IR Spectrum with VSCF/VCI and the Influence of Mark Johnson’s Experiments in Advancing the Theory of Protonated Water Clusters
The Journal of Physical Chemistry A·2025· 1 citedOpen Access
Theoretical and quantum mechanical deconstruction of vibrational energy transfer pathways modified by collective vibrational strong coupling
Nature Communications·2025· 7 citedOpen Access
1595-P: Region-Specific Effects of Early Aging on Glucose Metabolism in the Brain
Diabetes·2025
1681-P: Estrogen Modulates Obesity Effects on Neurobehavioral Phenotypes in a Female Mouse Model of Alzheimer’s Disease
Diabetes·2025
A perspective marking 20 years of using permutationally invariant polynomials for molecular potentials
The Journal of Chemical Physics·2025· 7 citedOpen Access
Quantum Nature of Ubiquitous Vibrational Features Revealed for Ethylene Glycol
Journal of Chemical Theory and Computation·2025· 5 citedOpen Access
Extending atomic decomposition and many-body representation with a chemistry-motivated approach to machine learning potentials
Nature Computational Science·2025· 7 citedOpen Access
Targeted Transferable Machine-Learned Potential for Linear Alkanes Trained on C<sub>14</sub>H<sub>30</sub> and Tested for C<sub>4</sub>H<sub>10</sub> to C<sub>30</sub>H<sub>62</sub>
Journal of Chemical Theory and Computation·2025· 4 citedOpen Access
A Perspective Marking 20 Years of UsingPermutationally Invariant Polynomials forMolecular Potentials
2025· 1 citedOpen Access
Stable isotope equilibria in the dihydrogen-water-methane-ethane-propane system. Part 1: Path-integral calculations with CCSD(T) quality potentials
Geochimica et Cosmochimica Acta·2025· 3 citedOpen Access
The quantum nature of ubiquitous vibrational features revealed for ethylene glycol
arXiv (Cornell University)·2025· 1 citedOpen Access
Dynamics Calculations of the Flexibility and Vibrational Spectrum of the Linear Alkane C<sub>14</sub>H<sub>30</sub>, Based on Machine-Learned Potentials
The Journal of Physical Chemistry A·2024· 4 citedOpen Access
Castrate-resistant prostate cancer response to taxane is determined by an HNF1-dependent apoptosis resistance circuit
Cell Reports Medicine·2024· 4 citedOpen Access
Extending the atomic decomposition and many-body representation, a chemistry-motivated monomer-centered approach for machine learning potentials
arXiv (Cornell University)·2024· 1 citedOpen Access
Quantum mechanical deconstruction of vibrational energy transfer rate and pathways modified by collective vibrational strong coupling
arXiv (Cornell University)·2024Open Access
On the nature of hydrogen bonding in the H2S dimer
Nature Communications·2024· 13 citedOpen Access
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Frequent Co-authors

Bastiaan J. Braams(10), Stuart Carter(6), Xinchuan Huang(6), Gábor Czakó(6), Benjamin C. Shepler(5), Lawrence B. Harding(4), Yimin Wang(4), George C. Schatz(3), Kurt M. Christoffel(2), Qi Yu(2), Bina Fu(2), Aron Kuppermann(2), Béla Gazdy(2), Yimin Wang(2), Qiyan Sun(2), Dave Townsend(1), Sridhar A. Lahankar(1), S. K. Lee(1), Steven D. Chambreau(1), Arthur G. Suits(1)