33 citations · 84 across the 10 of their papers we have counts for
12 papers
Sampling Free Energy Landscapes of Ionic Colloidal Crystal Systems using Machine-Learned Proxy Collective Variables
Michael S. Chen, Stefano Sacanna, Glen M. Hocky
Charged colloids coated with a polymer brush can be designed to preferentially self-assemble into different crystal structures by varying easy-to-tune experimental conditions. For…
Streamlining Analysis and Design of Two-Dimensional Electronic Spectroscopy using Machine Learning
Nicholas I. Hausman, Joseph Kelly, Michael S. Chen +5
Two-dimensional electronic spectroscopy (2DES) offers unique insights into the coupling between electronic and nuclear motion and dynamics, making it a key technique in diverse fie…
PACSim: A Flexible Simulation Framework for Polymer-Attenuated Coulombic Self-Assembly
Philipp Höllmer, Nicole Smina, John P. Marquardt +4
Polymer-Attenuated Coulombic Self-Assembly (PACS) is a flexible experimental approach for generating crystals from simple colloidal building blocks. The central components are char…
Two-dimensional electronic spectroscopy in the condensed phase using equivariant transformer accelerated molecular dynamics simulations
Joseph Kelly, Frank Hu, Arianna Damiani +10
Two-dimensional electronic spectroscopy (2DES) provides rich information about how the electronic states of molecules, proteins, and solid-state materials interact with each other…
On the design space between molecular mechanics and machine learning force fields
Yuanqing Wang, Kenichiro Takaba, Michael S. Chen +14
A force field as accurate as quantum mechanics (QM) and as fast as molecular mechanics (MM), with which one can simulate a biomolecular system efficiently enough and meaningfully e…
Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning
Frank Hu, Michael S. Chen, Grant M. Rotskoff +2
Rapid determination of molecular structures can greatly accelerate workflows across many chemical disciplines. However, elucidating structure using only one-dimensional (1D) NMR sp…
Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning
Abid Khan, Prateek Vaish, Yaoqi Pang +8
The ability to perform ab initio molecular dynamics simulations using potential energies calculated on quantum computers would allow virtually exact dynamics for chemical and bioch…
Elucidating the role of hydrogen bonding in the optical spectroscopy of the solvated green fluorescent protein chromophore: using machine learning to establish the importance of high-level electronic structure
Michael S. Chen, Yuezhi Mao, Andrew Snider +5
Hydrogen bonding interactions with chromophores in chemical and biological environments play a key role in determining their electronic absorption and relaxation processes, which a…
Machine learning potentials from transfer learning of periodic correlated electronic structure methods: Application to liquid water with AFQMC, CCSD, and CCSD(T)
Michael S. Chen, Joonho Lee, Hong-Zhou Ye +3
Obtaining the atomistic structure and dynamics of disordered condensed phase systems from first principles remains one of the forefront challenges of chemical theory. Here we explo…
Optically induced anisotropy in time-resolved scattering: Imaging molecular scale structure and dynamics in disordered media with experiment and theory
Andrés Montoya-Castillo, Michael S. Chen, Sumana L. Raj +6
Time-resolved scattering experiments enable imaging of materials at the molecular scale with femtosecond time resolution. However, in disordered media they provide access to just o…
AENET-LAMMPS and AENET-TINKER: Interfaces for Accurate and Efficient Molecular Dynamics Simulations with Machine Learning Potentials
Michael S. Chen, Tobias Morawietz, Hideki Mori +2
Machine learning potentials (MLPs) trained on data from quantum-mechanics based first-principles methods can approach the accuracy of the reference method at a fraction of the comp…
Exploiting machine learning to efficiently predict multidimensional optical spectra in complex environments
Michael S. Chen, Tim J. Zuehlsdorff, Tobias Morawietz +2
The excited state dynamics of chromophores in complex environments determine a range of vital biological and energy capture processes. Time-resolved, multidimensional optical spect…