Machine Learning Framework for Modeling Exciton Polaritons in Molecular Materials

Li, Xinyang; Lubbers, Nicholas Edward; Tretiak, Sergei; Barros, Kipton Marcos; Zhang, Yu

doi:10.1021/acs.jctc.3c01068

Title: Machine Learning Framework for Modeling Exciton Polaritons in Molecular Materials

Journal Article · 02 January 2024 · Journal of Chemical Theory and Computation

DOI: https://doi.org/10.1021/acs.jctc.3c01068 · OSTI ID:2280570

^[1];

^[1]

Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

A light–matter hybrid quasiparticle, called a polariton, is formed when molecules are strongly coupled to an optical cavity. Recent experiments have shown that polariton chemistry can manipulate chemical reactions. Polariton chemistry is a collective phenomenon, and its effects increase with the number of molecules in a cavity. However, simulating an ensemble of molecules in the excited state coupled to a cavity mode is theoretically and computationally challenging. Recent advances in machine learning (ML) techniques have shown promising capabilities in modeling ground-state chemical systems. Here, this work presents a general protocol to predict excited-state properties, such as energies, transition dipoles, and nonadiabatic coupling vectors with the hierarchically interacting particle neural network. ML predictions are then applied to compute the potential energy surfaces and electronic spectra of a prototype azomethane molecule in the collective coupling scenario. These computational tools provide a much-needed framework to model and understand many molecules’ emerging excited-state polariton chemistry.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences & Biosciences Division (CSGB)

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 2280570

Report Number(s):: LA-UR--23-25639

Journal Information:: Journal of Chemical Theory and Computation, Journal Name: Journal of Chemical Theory and Computation Journal Issue: 2 Vol. 20; ISSN 1549-9618

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

References (94)

Low Threshold Polariton Lasing from a Solution‐Processed Organic Semiconductor in a Planar Microcavity Rajendran, Sai Kiran; Wei, Mengjie; Ohadi, Hamid Advanced Optical Materials, Vol. 7, Issue 12 https://doi.org/10.1002/adom.201801791	journal	April 2019
Modifying Chemical Landscapes by Coupling to Vacuum Fields Hutchison, James A.; Schwartz, Tal; Genet, Cyriaque Angewandte Chemie International Edition, Vol. 51, Issue 7 https://doi.org/10.1002/anie.201107033	journal	January 2012
Energy Transfer between Spatially Separated Entangled Molecules Zhong, Xiaolan; Chervy, Thibault; Zhang, Lei Angewandte Chemie International Edition, Vol. 56, Issue 31 https://doi.org/10.1002/anie.201703539	journal	June 2017
Constructing high-dimensional neural network potentials: A tutorial review Behler, Jörg International Journal of Quantum Chemistry, Vol. 115, Issue 16 https://doi.org/10.1002/qua.24890	journal	March 2015
Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties von Lilienfeld, O. Anatole; Ramakrishnan, Raghunathan; Rupp, Matthias International Journal of Quantum Chemistry, Vol. 115, Issue 16 https://doi.org/10.1002/qua.24912	journal	April 2015
Direct grid-based quantum dynamics on propagated diabatic potential energy surfaces Richings, Gareth W.; Habershon, Scott Chemical Physics Letters, Vol. 683 https://doi.org/10.1016/j.cplett.2017.01.063	journal	September 2017
Hybrid Light–Matter States in a Molecular and Material Science Perspective Ebbesen, Thomas W. Accounts of Chemical Research, Vol. 49, Issue 11 https://doi.org/10.1021/acs.accounts.6b00295	journal	October 2016
Machine Learning for Electronically Excited States of Molecules Westermayr, Julia; Marquetand, Philipp Chemical Reviews https://doi.org/10.1021/acs.chemrev.0c00749	journal	November 2020
Non-adiabatic Excited-State Molecular Dynamics: Theory and Applications for Modeling Photophysics in Extended Molecular Materials Nelson, Tammie R.; White, Alexander J.; Bjorgaard, Josiah A. Chemical Reviews, Vol. 120, Issue 4 https://doi.org/10.1021/acs.chemrev.9b00447	journal	February 2020
NEXMD Software Package for Nonadiabatic Excited State Molecular Dynamics Simulations Malone, Walter; Nebgen, Benjamin; White, Alexander Journal of Chemical Theory and Computation, Vol. 16, Issue 9 https://doi.org/10.1021/acs.jctc.0c00248	journal	July 2020
Ab Initio Molecular Cavity Quantum Electrodynamics Simulations Using Machine Learning Models Hu, Deping; Huo, Pengfei Journal of Chemical Theory and Computation, Vol. 19, Issue 8 https://doi.org/10.1021/acs.jctc.3c00137	journal	March 2023
NEXMD v2.0 Software Package for Nonadiabatic Excited State Molecular Dynamics Simulations Freixas, Victor M.; Malone, Walter; Li, Xinyang Journal of Chemical Theory and Computation, Vol. 19, Issue 16 https://doi.org/10.1021/acs.jctc.3c00583	journal	July 2023
Cavity Born–Oppenheimer Approximation for Correlated Electron–Nuclear-Photon Systems Flick, Johannes; Appel, Heiko; Ruggenthaler, Michael Journal of Chemical Theory and Computation, Vol. 13, Issue 4 https://doi.org/10.1021/acs.jctc.6b01126	journal	March 2017
Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error Faber, Felix A.; Hutchison, Luke; Huang, Bing Journal of Chemical Theory and Computation, Vol. 13, Issue 11 https://doi.org/10.1021/acs.jctc.7b00577	journal	October 2017
Extending the Representation of Multistate Coupled Potential Energy Surfaces To Include Properties Operators Using Neural Networks: Application to the 1,2 ¹ A States of Ammonia Guan, Yafu; Guo, Hua; Yarkony, David R. Journal of Chemical Theory and Computation, Vol. 16, Issue 1 https://doi.org/10.1021/acs.jctc.9b00898	journal	November 2019
Nonadiabatic Excited-State Molecular Dynamics for Open-Shell Systems Zhang, Yu; Li, Linqiu; Tretiak, Sergei Journal of Chemical Theory and Computation, Vol. 16, Issue 4 https://doi.org/10.1021/acs.jctc.9b00928	journal	March 2020
Neural Network Based Quasi-diabatic Representation for S ₀ and S ₁ States of Formaldehyde Guan, Yafu; Xie, Changjian; Guo, Hua The Journal of Physical Chemistry A, Vol. 124, Issue 49 https://doi.org/10.1021/acs.jpca.0c08948	journal	November 2020
Entangled Photonic-Nuclear Molecular Dynamics of LiF in Quantum Optical Cavities Triana, Johan F.; Peláez, Daniel; Sanz-Vicario, José Luis The Journal of Physical Chemistry A, Vol. 122, Issue 8 https://doi.org/10.1021/acs.jpca.7b11833	journal	February 2018
Polariton-Mediated Electron Transfer via Cavity Quantum Electrodynamics Mandal, Arkajit; Krauss, Todd D.; Huo, Pengfei The Journal of Physical Chemistry B, Vol. 124, Issue 29 https://doi.org/10.1021/acs.jpcb.0c03227	journal	June 2020
Combining SchNet and SHARC: The SchNarc Machine Learning Approach for Excited-State Dynamics Westermayr, Julia; Gastegger, Michael; Marquetand, Philipp The Journal of Physical Chemistry Letters, Vol. 11, Issue 10 https://doi.org/10.1021/acs.jpclett.0c00527	journal	April 2020
Theory of Mode-Selective Chemistry through Polaritonic Vibrational Strong Coupling Li, Xinyang; Mandal, Arkajit; Huo, Pengfei The Journal of Physical Chemistry Letters, Vol. 12, Issue 29 https://doi.org/10.1021/acs.jpclett.1c01847	journal	July 2021
Polariton Decay in Donor–Acceptor Cavity Systems DelPo, Courtney A.; Khan, Saeed-Uz-Zaman; Park, Kyu Hyung The Journal of Physical Chemistry Letters, Vol. 12, Issue 40 https://doi.org/10.1021/acs.jpclett.1c02644	journal	October 2021
Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan The Journal of Physical Chemistry Letters, Vol. 6, Issue 12 https://doi.org/10.1021/acs.jpclett.5b00831	journal	June 2015
Machine Learning for Quantum Mechanical Properties of Atoms in Molecules Rupp, Matthias; Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole The Journal of Physical Chemistry Letters, Vol. 6, Issue 16 https://doi.org/10.1021/acs.jpclett.5b01456	journal	July 2015
Cavity Femtochemistry: Manipulating Nonadiabatic Dynamics at Avoided Crossings Kowalewski, Markus; Bennett, Kochise; Mukamel, Shaul The Journal of Physical Chemistry Letters, Vol. 7, Issue 11 https://doi.org/10.1021/acs.jpclett.6b00864	journal	May 2016
Excited-State Dynamics of Isocytosine: A Hybrid Case of Canonical Nucleobase Photodynamics Berenbeim, Jacob A.; Boldissar, Samuel; Siouri, Faady M. The Journal of Physical Chemistry Letters, Vol. 8, Issue 20 https://doi.org/10.1021/acs.jpclett.7b02032	journal	October 2017
Inclusion of Machine Learning Kernel Ridge Regression Potential Energy Surfaces in On-the-Fly Nonadiabatic Molecular Dynamics Simulation Hu, Deping; Xie, Yu; Li, Xusong The Journal of Physical Chemistry Letters, Vol. 9, Issue 11 https://doi.org/10.1021/acs.jpclett.8b00684	journal	May 2018
Nonadiabatic Excited-State Dynamics with Machine Learning Dral, Pavlo O.; Barbatti, Mario; Thiel, Walter The Journal of Physical Chemistry Letters, Vol. 9, Issue 19 https://doi.org/10.1021/acs.jpclett.8b02469	journal	September 2018
Deep Learning for Nonadiabatic Excited-State Dynamics Chen, Wen-Kai; Liu, Xiang-Yang; Fang, Wei-Hai The Journal of Physical Chemistry Letters, Vol. 9, Issue 23 https://doi.org/10.1021/acs.jpclett.8b03026	journal	November 2018
Investigating New Reactivities Enabled by Polariton Photochemistry Mandal, Arkajit; Huo, Pengfei The Journal of Physical Chemistry Letters, Vol. 10, Issue 18 https://doi.org/10.1021/acs.jpclett.9b01599	journal	August 2019
Photoinduced Electron Transfer in the Strong Coupling Regime: Waveguide–Plasmon Polaritons Zeng, Peng; Cadusch, Jasper; Chakraborty, Debadi Nano Letters, Vol. 16, Issue 4 https://doi.org/10.1021/acs.nanolett.6b00310	journal	March 2016
Dynamics of Strongly Coupled Modes between Surface Plasmon Polaritons and Photoactive Molecules: The Effect of the Stokes Shift Baieva, Svitlana; Hakamaa, Ossi; Groenhof, Gerrit ACS Photonics, Vol. 4, Issue 1 https://doi.org/10.1021/acsphotonics.6b00482	journal	December 2016
Tunable Third-Harmonic Generation from Polaritons in the Ultrastrong Coupling Regime Barachati, Fábio; Simon, Janos; Getmanenko, Yulia A. ACS Photonics, Vol. 5, Issue 1 https://doi.org/10.1021/acsphotonics.7b00305	journal	August 2017
Can Ultrastrong Coupling Change Ground-State Chemical Reactions? Martínez-Martínez, Luis A.; Ribeiro, Raphael F.; Campos-González-Angulo, Jorge ACS Photonics, Vol. 5, Issue 1 https://doi.org/10.1021/acsphotonics.7b00610	journal	November 2017
Polaritonic Chemistry with Organic Molecules Feist, Johannes; Galego, Javier; Garcia-Vidal, Francisco J. ACS Photonics, Vol. 5, Issue 1 https://doi.org/10.1021/acsphotonics.7b00680	journal	October 2017
Exact States and Spectra of Vibrationally Dressed Polaritons Zeb, M. Ahsan; Kirton, Peter G.; Keeling, Jonathan ACS Photonics, Vol. 5, Issue 1 https://doi.org/10.1021/acsphotonics.7b00916	journal	November 2017
Development and use of quantum mechanical molecular models. 76. AM1: a new general purpose quantum mechanical molecular model Dewar, Michael J. S.; Zoebisch, Eve G.; Healy, Eamonn F. Journal of the American Chemical Society, Vol. 107, Issue 13 https://doi.org/10.1021/ja00299a024	journal	June 1985
Mechanism and Dynamics of Azobenzene Photoisomerization Schultz, Thomas; Quenneville, Jason; Levine, Benjamin Journal of the American Chemical Society, Vol. 125, Issue 27 https://doi.org/10.1021/ja021363x	journal	July 2003
Suppressing photochemical reactions with quantized light fields Galego, Javier; Garcia-Vidal, Francisco J.; Feist, Johannes Nature Communications, Vol. 7, Issue 1 https://doi.org/10.1038/ncomms13841	journal	December 2016
Conductivity in organic semiconductors hybridized with the vacuum field Orgiu, E.; George, J.; Hutchison, J. A. Nature Materials, Vol. 14, Issue 11 https://doi.org/10.1038/nmat4392	journal	September 2015
The road towards polaritonic devices Sanvitto, Daniele; Kéna-Cohen, Stéphane Nature Materials, Vol. 15, Issue 10 https://doi.org/10.1038/nmat4668	journal	July 2016
Room-temperature polariton lasing in an organic single-crystal microcavity Kéna-Cohen, S.; Forrest, S. R. Nature Photonics, Vol. 4, Issue 6 https://doi.org/10.1038/nphoton.2010.86	journal	April 2010
Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning Smith, Justin S.; Nebgen, Benjamin T.; Zubatyuk, Roman Nature Communications, Vol. 10, Issue 1 https://doi.org/10.1038/s41467-019-10827-4	journal	July 2019
Resonant catalysis of thermally activated chemical reactions with vibrational polaritons Campos-Gonzalez-Angulo, Jorge A.; Ribeiro, Raphael F.; Yuen-Zhou, Joel Nature Communications, Vol. 10, Issue 1 https://doi.org/10.1038/s41467-019-12636-1	journal	October 2019
Room temperature organic exciton–polariton condensate in a lattice Dusel, M.; Betzold, S.; Egorov, O. A. Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-16656-0	journal	June 2020
Learning local equivariant representations for large-scale atomistic dynamics Musaelian, Albert; Batzner, Simon; Johansson, Anders Nature Communications, Vol. 14, Issue 1 https://doi.org/10.1038/s41467-023-36329-y	journal	February 2023
Plasmon mediated coherent population oscillations in molecular aggregates Timmer, Daniel; Gittinger, Moritz; Quenzel, Thomas Nature Communications, Vol. 14, Issue 1 https://doi.org/10.1038/s41467-023-43578-4	journal	December 2023
Polariton condensates for classical and quantum computing Kavokin, Alexey; Liew, Timothy C. H.; Schneider, Christian Nature Reviews Physics, Vol. 4, Issue 7 https://doi.org/10.1038/s42254-022-00447-1	journal	April 2022
Phase transition of a perovskite strongly coupled to the vacuum field Wang, Shaojun; Mika, Arkadiusz; Hutchison, James A. Nanoscale, Vol. 6, Issue 13 https://doi.org/10.1039/C4NR01971G	journal	January 2014
Comparing molecules and solids across structural and alchemical space De, Sandip; Bartók, Albert P.; Csányi, Gábor Physical Chemistry Chemical Physics, Vol. 18, Issue 20 https://doi.org/10.1039/C6CP00415F	journal	January 2016
Novel photochemistry of molecular polaritons in optical cavities Bennett, Kochise; Kowalewski, Markus; Mukamel, Shaul Faraday Discussions, Vol. 194 https://doi.org/10.1039/C6FD00095A	journal	January 2016
Theory for polariton-assisted remote energy transfer Du, Matthew; Martínez-Martínez, Luis A.; Ribeiro, Raphael F. Chemical Science, Vol. 9, Issue 32 https://doi.org/10.1039/C8SC00171E	journal	January 2018
Machine learning enables long time scale molecular photodynamics simulations Westermayr, Julia; Gastegger, Michael; Menger, Maximilian F. S. J. Chemical Science, Vol. 10, Issue 35 https://doi.org/10.1039/C9SC01742A	journal	January 2019
Predicting phosphorescence energies and inferring wavefunction localization with machine learning Sifain, Andrew E.; Lystrom, Levi; Messerly, Richard A. Chemical Science, Vol. 12, Issue 30 https://doi.org/10.1039/D1SC02136B	journal	January 2021
Theory and modeling of light-matter interactions in chemistry: current and future Weight, Braden M.; Li, Xinyang; Zhang, Yu Physical Chemistry Chemical Physics, Vol. 25, Issue 46 https://doi.org/10.1039/D3CP01415K	journal	January 2023
Perspective: Nonadiabatic dynamics theory Tully, John C. The Journal of Chemical Physics, Vol. 137, Issue 22 https://doi.org/10.1063/1.4757762	journal	December 2012
Non-adiabatic dynamics of molecules in optical cavities Kowalewski, Markus; Bennett, Kochise; Mukamel, Shaul The Journal of Chemical Physics, Vol. 144, Issue 5 https://doi.org/10.1063/1.4941053	journal	February 2016
Machine learning of molecular properties: Locality and active learning Gubaev, Konstantin; Podryabinkin, Evgeny V.; Shapeev, Alexander V. The Journal of Chemical Physics, Vol. 148, Issue 24 https://doi.org/10.1063/1.5005095	journal	June 2018
Construction of diabatic energy surfaces for LiFH with artificial neural networks Guan, Yafu; Fu, Bina; Zhang, Dong H. The Journal of Chemical Physics, Vol. 147, Issue 22 https://doi.org/10.1063/1.5007031	journal	December 2017
Hierarchical modeling of molecular energies using a deep neural network Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton The Journal of Chemical Physics, Vol. 148, Issue 24 https://doi.org/10.1063/1.5011181	journal	June 2018
Non-adiabatic molecular dynamics of molecules in the presence of strong light-matter interactions Zhang, Yu; Nelson, Tammie; Tretiak, Sergei The Journal of Chemical Physics, Vol. 151, Issue 15 https://doi.org/10.1063/1.5116550	journal	October 2019
Deep learning for UV absorption spectra with SchNarc: First steps toward transferability in chemical compound space Westermayr, J.; Marquetand, P. The Journal of Chemical Physics, Vol. 153, Issue 15 https://doi.org/10.1063/5.0021915	journal	October 2020
Machine learning of double-valued nonadiabatic coupling vectors around conical intersections Richardson, Jeremy O. The Journal of Chemical Physics, Vol. 158, Issue 1 https://doi.org/10.1063/5.0133191	journal	January 2023
Lightweight and effective tensor sensitivity for atomistic neural networks Chigaev, Michael; Smith, Justin S.; Anaya, Steven The Journal of Chemical Physics, Vol. 158, Issue 18 https://doi.org/10.1063/5.0142127	journal	May 2023
Kohn–Sham approach to quantum electrodynamical density-functional theory: Exact time-dependent effective potentials in real space Flick, Johannes; Ruggenthaler, Michael; Appel, Heiko Proceedings of the National Academy of Sciences, Vol. 112, Issue 50 https://doi.org/10.1073/pnas.1518224112	journal	December 2015
Atoms and molecules in cavities, from weak to strong coupling in quantum-electrodynamics (QED) chemistry Flick, Johannes; Ruggenthaler, Michael; Appel, Heiko Proceedings of the National Academy of Sciences, Vol. 114, Issue 12 https://doi.org/10.1073/pnas.1615509114	journal	March 2017
Manipulating molecules with quantum light Kowalewski, Markus; Mukamel, Shaul Proceedings of the National Academy of Sciences, Vol. 114, Issue 13 https://doi.org/10.1073/pnas.1702160114	journal	March 2017
Quantum theory of collective strong coupling of molecular vibrations with a microcavity mode Pino, Javier del; Feist, Johannes; Garcia-Vidal, Francisco J. New Journal of Physics, Vol. 17, Issue 5 https://doi.org/10.1088/1367-2630/17/5/053040	journal	May 2015
Unified representation of molecules and crystals for machine learning Huo, Haoyan; Rupp, Matthias Machine Learning: Science and Technology, Vol. 3, Issue 4 https://doi.org/10.1088/2632-2153/aca005	journal	November 2022
Theory of the Contribution of Excitons to the Complex Dielectric Constant of Crystals Hopfield, J. J. Physical Review, Vol. 112, Issue 5 https://doi.org/10.1103/PhysRev.112.1555	journal	December 1958
Exact Solution for an N -Molecule—Radiation-Field Hamiltonian Tavis, Michael; Cummings, Frederick W. Physical Review, Vol. 170, Issue 2 https://doi.org/10.1103/PhysRev.170.379	journal	June 1968
Approximate Solutions for an N -Molecule-Radiation-Field Hamiltonian Tavis, Michael; Cummings, Frederick W. Physical Review, Vol. 188, Issue 2 https://doi.org/10.1103/PhysRev.188.692	journal	December 1969
Coherence in Spontaneous Radiation Processes Dicke, R. H. Physical Review, Vol. 93, Issue 1 https://doi.org/10.1103/PhysRev.93.99	journal	January 1954
Diffusion quantum Monte Carlo approach to the polaritonic ground state Weight, Braden M.; Tretiak, Sergei; Zhang, Yu Physical Review A, Vol. 109, Issue 3 https://doi.org/10.1103/PhysRevA.109.032804	journal	March 2024
On representing chemical environments Bartók, Albert P.; Kondor, Risi; Csányi, Gábor Physical Review B, Vol. 87, Issue 18 https://doi.org/10.1103/PhysRevB.87.184115	journal	May 2013
Efficient and accurate machine-learning interpolation of atomic energies in compositions with many species Artrith, Nongnuch; Urban, Alexander; Ceder, Gerbrand Physical Review B, Vol. 96, Issue 1 https://doi.org/10.1103/PhysRevB.96.014112	journal	July 2017
Organic polaritons enable local vibrations to drive long-range energy transfer Sáez-Blázquez, R.; Feist, J.; Fernández-Domínguez, A. I. Physical Review B, Vol. 97, Issue 24 https://doi.org/10.1103/PhysRevB.97.241407	journal	June 2018
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert Physical Review Letters, Vol. 108, Issue 5 https://doi.org/10.1103/PhysRevLett.108.058301	journal	January 2012
Cavity-Controlled Chemistry in Molecular Ensembles Herrera, Felipe; Spano, Frank C. Physical Review Letters, Vol. 116, Issue 23 https://doi.org/10.1103/PhysRevLett.116.238301	journal	June 2016
Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces Behler, Jörg; Parrinello, Michele Physical Review Letters, Vol. 98, Issue 14 https://doi.org/10.1103/PhysRevLett.98.146401	journal	April 2007
Cavity-Induced Modifications of Molecular Structure in the Strong-Coupling Regime Galego, Javier; Garcia-Vidal, Francisco J.; Feist, Johannes Physical Review X, Vol. 5, Issue 4 https://doi.org/10.1103/PhysRevX.5.041022	journal	November 2015
Exciton-polariton Bose-Einstein condensation Deng, Hui; Haug, Hartmut; Yamamoto, Yoshihisa Reviews of Modern Physics, Vol. 82, Issue 2 https://doi.org/10.1103/RevModPhys.82.1489	journal	May 2010
Cold atoms in cavity-generated dynamical optical potentials Ritsch, Helmut; Domokos, Peter; Brennecke, Ferdinand Reviews of Modern Physics, Vol. 85, Issue 2 https://doi.org/10.1103/RevModPhys.85.553	journal	April 2013
Comparison of quantum and semiclassical radiation theories with application to the beam maser Jaynes, E. T.; Cummings, F. W. Proceedings of the IEEE, Vol. 51, Issue 1 https://doi.org/10.1109/PROC.1963.1664	journal	January 1963
Machine learning of accurate energy-conserving molecular force fields Chmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel E. Science Advances, Vol. 3, Issue 5 https://doi.org/10.1126/sciadv.1603015	journal	May 2017
Tilting a ground-state reactivity landscape by vibrational strong coupling Thomas, A.; Lethuillier-Karl, L.; Nagarajan, K. Science, Vol. 363, Issue 6427 https://doi.org/10.1126/science.aau7742	journal	February 2019
Manipulating matter by strong coupling to vacuum fields Garcia-Vidal, Francisco J.; Ciuti, Cristiano; Ebbesen, Thomas W. Science, Vol. 373, Issue 6551 https://doi.org/10.1126/science.abd0336	journal	July 2021
Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials Shapeev, Alexander V. Multiscale Modeling & Simulation, Vol. 14, Issue 3 https://doi.org/10.1137/15M1054183	journal	January 2016
Plasmon-exciton-polariton lasing Ramezani, Mohammad; Halpin, Alexei; Fernández-Domínguez, Antonio I. Optica, Vol. 4, Issue 1 https://doi.org/10.1364/optica.4.000031	journal	December 2016
Learning local equivariant representations for large-scale atomistic dynamics Albert, Musaelian,; Simon, Batzner,; Anders, Johansson, Materials Cloud https://doi.org/10.24435/materialscloud:fr-ts	dataset	January 2022
Theoretical Advances in Polariton Chemistry and Molecular Cavity Quantum Electrodynamics Mandal, Arkajit; Taylor, Michael; Weight, Braden https://doi.org/10.26434/chemrxiv-2022-g9lr7	preprint	December 2022
Spin-Flip TDDFT for Photochemistry Herbert, John; Mandal, Aniket https://doi.org/10.26434/chemrxiv-2022-gj75d	preprint	March 2022
Nonadiabatic Derivative Couplings Calculated Using Information of Potential Energy Surfaces without Wavefunctions: Ab Initio and Machine Learning Implementations Chen, Wen-Kai; Wang, Sheng-Rui; Liu, Xiang-Yang Molecules, Vol. 28, Issue 10 https://doi.org/10.3390/molecules28104222	journal	May 2023
Dataset for Machine Learning Framework for Modeling Exciton-Polaritons in Molecular Materials Li, Xinyang; Lubbers, Nicholas; Tretiak, Sergei Zenodo https://doi.org/10.5281/zenodo.7076420	dataset	January 2023

Similar Records

Theoretical Advances in Polariton Chemistry and Molecular Cavity Quantum Electrodynamics

Journal Article · 2023 · Chemical Reviews · OSTI ID:1996166

Mandal, Arkajit; Taylor, Michael A.D.; Weight, Braden M.; +3 more

Ab initio methods for polariton chemistry

Journal Article · 2023 · Chemical Physics Reviews · OSTI ID:2582106

Foley, Jonathan; McTague, Jonathan; DePrince, A.

Simulating the Excited-State Dynamics of Polaritons with Ab Initio Multiple Spawning

Journal Article · 2023 · Journal of Physical Chemistry. A, Molecules, Spectroscopy, Kinetics, Environment, and General Theory · OSTI ID:2404885

Rana, Bhaskar; Hohenstein, Edward G.; Martínez, Todd J.

Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
cavities
energy
molecular structure
molecules
polaritons

Title: Machine Learning Framework for Modeling Exciton Polaritons in Molecular Materials

Citation Formats

References (94)

Similar Records

Related Subjects