Publications
Citation information is available from Google Scholar profile.
Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning.
F. Hu, M. S. Chen, G. M. Rotskoff, M. W. Kanan, and T. E. Markland
ACS Cent. Sci., 10, 11, 2162–2170 (2024)
Nutmeg and SPICE: Models and Data for Biomolecular Machine Learning.
P. Eastman, B. P. Pritchard, J. D. Chodera, and T. E. Markland
J. Chem. Theory Comput., 20, 19, 8583-8593 (2024)
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations.
R. P. Pelaez, G. Simeon, R. Galvelis, A. Mirarchi, P. Eastman, P. Thölke, T. E. Markland, and G. De Fabritiis
J. Chem. Theory Comput., 20, 10, 4076-4087 (2024)
Enhancing Protein-Ligand Binding Affinity Predictions using Neural Network Potentials.
F. Sabanes Zariquiey, R. Galvelis, E. Gallicchio, J. D. Chodera, T. E. Markland, G. De Fabritiis
J. Chem. Inf. Model., 64, 5, 1481–1485 (2024)
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.
P. Eastman, R. Galvelis, R. P. Peláez, C. R. A. Abreu, S. E. Farr, E. Gallicchio, A. Gorenko, M. M. Henry, F. Hu, J. Huang, A. Krämer, J. Michel, J. A. Mitchell, V. S. Pande, J. PGLM Rodrigues, J. Rodriguez-Guerra, A. C. Simmonett, S. Singh, J. Swails, P. Turner, Y. Wang, I. Zhang, J. D. Chodera, G. De Fabritiis, and T. E. Markland
J. Phys. Chem. B, 128, 1, 109-116 (2024)
NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics.
R. Galvelis, A. Varela-Rial, S. Doerr, R. Fino, P. Eastman, T. E. Markland, J. D. Chodera, and G. De Fabritiis
J. Chem. Inf. Model., 63, 18, 5701–5708 (2023)
Developing machine-learned potentials to simultaneously capture the dynamics of excess protons and hydroxide ions in classical and path integral simulations.
A. O. Atsango, T. Morawietz, O. Marsalek, and T. E. Markland
J. Chem. Phys., 159, 074101 (2023)
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.
M. S. Chen, Y. Mao, A. Snider, P. Gupta, A. Montoya-Castillo, T. J. Zuehsldorff, C. M. Isborn, and T. E. Markland
J. Phys. Chem. Lett., 14, 29, 6610 (2023)
Electron transfer at electrode interfaces via a straightforward quasiclassical fermionic mapping approach.
K. A. Jung. J. Kelly, and T. E. Markland
J. Chem. Phys., 159, 014109 (2023)
Building insightful, memory-enriched models to capture long-time biochemical processes from short-time simulations.
A. J. Dominic III, T. Sayer, S. Cao, T. E. Markland, X. Huang, and A. Montoya-Castillo
Proc. Natl. Acad. Sci., 120 (12) e2221048120 (2023)
A derivation of the conditions under which bosonic operators exactly capture fermionic structure and dynamics.
A. Montoya-Castillo and T. E. Markland
J. Chem. Phys., 158, 094112 (2023)
An accurate and efficient Ehrenfest dynamics approach for calculating linear and nonlinear electronic spectra.
A. O. Atsango, A. Montoya-Castillo and T. E. Markland
J. Chem. Phys., 158, 074107 (2023)
Data-Efficient Machine Learning Potentials from Transfer Learning of Periodic Correlated Electronic Structure Methods: Liquid Water at AFQMC, CCSD, and CCSD(T) Accuracy.
M. S. Chen, J. Lee, H.-Z. Ye, T. C. Berkelbach, D. R. Reichman and T. E. Markland
J. Chem. Theory Comput. 19, 14, 4510 (2023)
SPICE: A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials.
P. Eastman, P. Kumar Behara, D. L. Dotson, R. Galvelis, J. E. Herr, J. T. Horton, Y. Mao, J. D. Chodera, B. B. Pritchard, Y. Wang, G. De Fabritiis and T. E. Markland
Scientific Data, 10, 11 (2023)
2D spectroscopies from condensed phase dynamics: Accessing third-order response properties from equilibrium multi-time correlation functions.
K. A. Jung and T. E. Markland
J. Chem. Phys., 157, 094111 (2022)
Optically induced anisotropy in time-resolved scattering: Imaging molecular scale structure and dynamics in disordered media with experiment and theory.
A. Montoya-Castillo, M. S. Chen, S. L. Raj, K. A. Jung, K. S. Kjaer, T. Morawietz, K. J. Gaffney, T. B. van Driel and T. E. Markland
Phys. Rev. Lett., 129, 056001 (2022)
Tuning solvent organization and electrostatic environment via structural modification of solutes: Amide vs. non-amide carbonyls.
S. D. E. Fried, C. Zheng, Y. Mao, T. E. Markland and S. G. Boxer
J. Phys. Chem. B, 126, 31, 5876-5886 (2022)
A two-directional vibrational probe reveals different electric field orientations in solution and an enzyme active site.
C. Zheng, Y. Mao, J. Kozuch, A. O. Atsango, Z. Ji, T. E. Markland and S. G. Boxer
Nature Chem., 14, 891–897 (2022)
A framework for automated structure elucidation from routine NMR spectra.
Z. Huang, M. S. Chen, C. P. Woroch, T. E. Markland, and M. W. Kanan
Chem. Sci., 12, 15329 (2021)
Characterizing and contrasting structural proton transport mechanisms in azole hydrogen bond networks using ab initio molecular dynamics.
A. O. Atsango, M. E. Tuckerman and T. E. Markland
J. Phys. Chem. Lett., 12, 8749 (2021)
AENET-LAMMPS and AENET-TINKER: Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials
M. S. Chen, T. Morawietz, H. Mori, T. E. Markland and N. Artrith
J. Chem. Phys., 155, 074801 (2021)
Persistent homology metrics reveal quantum fluctuations and reactive atoms in path integral dynamics.
Y. Hu, P. Ounkham, O. Marsalek, T. E. Markland, B. Krishmoorthy and A. E. Clark
Front. Chem., 9, 624937 (2021)
Excited state diabatization on the cheap using DFT: Photoinduced electron and hole transfer.
Y. Mao, A. Montoya-Castillo and T. E. Markland
J. Chem. Phys., 153, 244111 (2020)
Exploiting machine learning to efficiently predict multidimensional optical spectra in complex environments.
M. S. Chen, T. J. Zuehlsdorff, T. Morawietz, C. M. Isborn and T. E. Markland
J. Phys. Chem. Lett., 11, 7559-7568 (2020)
Elucidating the proton transport pathways in liquid imidazole.
Z. Long, A. O. Atsango, J. A. Napoli, T. E. Markland and M. E. Tuckerman
J. Phys. Chem. Lett., 11, 6156-6163 (2020)
On the Advantages of Exploiting Memory in Markov State Models for Biomolecular Dynamics.
S. Cao, A. Montoya-Castillo, W. Wang, T. E. Markland and X. Huang
J. Chem. Phys., 153, 014105 (2020)
Resolving heterogeneous dynamics of excess protons in aqueous solution with rate theory.
S. Roy, G. K. Schenter, J. A. Napoli, M. D. Baer, T. E. Markland and C. J. Mundy
J. Phys. Chem. B, 124, 27, 5665-5675 (2020)
Part of the Peter J. Rossky Festschrift special issue.
Quantum kinetic energy and isotope fractionation in aqueous ionic solutions.
L. Wang, M. Ceriotti and T. E. Markland
Phys. Chem. Chem. Phys., 22, 10490-10499 (2020)
Part of the Frontiers in Molecular Simulation of Solvated Ions, Molecules and Interfaces collection honoring the contributions of Prof. Michiel Sprik and also highlighted as 2020 PCCP HOT article.
Accurate and efficient DFT-based diabatization for hole and electron transfer using absolutely localized molecular orbitals.
Y. Mao, A. Montoya-Castillo and T. E. Markland
J. Chem. Phys., 151, 164114 (2019)
Hiding in the crowd: Spectral signatures of overcoordinated hydrogen bond environments.
T. Morawietz, A. Urbina, P. K. Wise, X. Wu, W. Lu, D. Ben-Amotz and T. E. Markland
J. Phys. Chem. Lett., 10, 6067-6073 (2019)
Optical spectra in the condensed phase: Capturing anharmonic and vibronic features using dynamic and static approaches.
T. J. Zuehlsdorff, A. Montoya-Castillo, J. A. Napoli, T. E. Markland and C. M. Isborn
J. Chem. Phys., 51, 074111 (2019)
Efficient construction of generalized master equation memory kernels for multi-state systems from nonadiabatic quantum-classical dynamics.
W. C. Pfalzgraff, A. Montoya-Castillo, A. Kelly and T. E. Markland
J. Chem. Phys., 150, 244109 (2019)
Tracking aqueous proton transfer by 2D-IR spectroscopy and ab initio molecular dynamics simulations.
R. Yuan, J. A. Napoli, C. Yan, O. Marsalek, T. E. Markland and M. D. Fayer
ACS Cent. Sci., 5, 1269-1277 (2019)
Associated summary article by Martin ZanniBeyond Badger's rule: the origins and generality of the structure-spectra relationship of aqueous hydrogen bonds.
M. A. Boyer, O. Marsalek, J. P. Heindel, T. E. Markland, A. B. McCoy and S. S. Xantheas
J. Phys. Chem. Lett., 10, 918-924 (2019)
i-PI 2.0: A universal force engine for advanced molecular simulations.
V. Kapil, M. Rossi, O. Marsalek, R. Petraglia, Y. Litman, T. Spura, B. Cheng, A. Cuzzocrea, R. H. Meissner, D. M. Wilkins, P. Juda, S. P. Bienvenue, J. Kessler, I. Poltavsky, S. Vandenbrande, J. Wieme, C. Corminboeuf, T. D. Kuhne, D. E. Manolopoulos, T. E. Markland, J. O. Richardson, A. Tkatchenko, G. A. Tribello, V. Van Speybroeck and M. Ceriotti
Comp. Phys. Comm., 236, 214-223 (2019)
On the exact continuous mapping of fermions.
A. Montoya-Castillo and T. E. Markland
Sci. Rep., 8, 12929 (2018)
The quest for accurate liquid water properties from first principles.
L. R. Pestana, O. Marsalek, T. E. Markland and T. Head-Gordon
J. Phys. Chem. Lett., 9, 5009-5016 (2018)
Unraveling electronic absorption spectra using nuclear quantum effects: Photoactive yellow protein and green fluorescent protein chromophores in water.
T. J. Zuehlsdorff, J. A. Napoli, J. M. Milanese, T. E. Markland and C. M. Isborn
J. Chem. Phys., 149, 024107 (2018)
The interplay of structure and dynamics in the Raman spectrum of liquid water over the full frequency and temperature range.
T. Morawietz, O. Marsalek, S. R. Pattenaude, L. M. Streacker, D. Ben-Amotz and T. E. Markland
J. Phys. Chem. Lett., 9, 851-857 (2018)
Decoding the spectroscopic features and timescales of aqueous proton defects.
J. Napoli, O. Marsalek and T. E. Markland
J. Chem. Phys., 148, 222833 (2018)
Selected as an Editor's Pick
Nuclear quantum effects enter the mainstream.
T. E. Markland and M. Ceriotti
Nature Rev. Chem., 2, 0109 (2018)
Proton network flexibility enables robustness and large electric fields in the ketosteroid isomerase active site.
L. Wang, S. D. Fried and T. E. Markland
J. Phys. Chem. B., 121 (42), 9807-9815 (2017)
Unravelling the influence of quantum proton delocalization on electronic charge transfer through the hydrogen bond.
C. Schran, O. Marsalek and T. E. Markland
Chem. Phys. Lett., Frontiers, 678, 289-295 (2017)
Quantum Dynamics and Spectroscopy of Ab Initio Liquid Water: The Interplay of Nuclear and Electronic Quantum Effects.
O. Marsalek and T. E. Markland
J. Phys. Chem. Lett., 8, 1545-1551 (2017)
Electrostatic control of regioselectivity in Au(I)-catalyzed hydroarylation.
V. M. Lau, W. C. Pfalzgraff, T. E. Markland and M. W. Kanan
J. Am. Chem. Soc., 139 (11), 4035-4041 (2017)
Generalized Quantum Master Equations In and Out of Equilibrium: When Can One Win?
A. Kelly, A. Montoya-Castillo, L. Wang and T. E. Markland
J. Chem. Phys. 144, 184105 (2016)
Simulating Nuclear and Electronic Quantum Effects in Enzymes.
L. Wang, C. M. Isborn, and T. E. Markland
Methods in Enzymology, 577, 389-418 (2016)
Unraveling the dynamics and structure of functionalized self-assembled monolayers on gold using 2D IR spectroscopy and MD simulations.
C. Yan, R. Yuan, W. C. Pfalzgraff, J. Nishida, L. Wang, T. E. Markland, M. D. Fayer
Proc. Natl. Acad. Sci., 113 (18), 4929-4934 (2016)
Associated Commentary by Marty Zanni.Nuclear Quantum Effects in Water and Aqueous Systems: Experiment, Theory, and Current Challenges.
M. Ceriotti, W. Fang, P. G. Kusalik, R. H. McKenzie, M. A. Morales, A. Michaelides and T. E. Markland
Chem. Rev., 116 (13), 7529-7550 (2016)
Ab initio molecular dynamics with nuclear quantum effects at classical cost: ring polymer contraction for density functional theory.
O. Marsalek and T. E. Markland
J. Chem. Phys. 144, 054112 (2016)
Nonadiabatic dynamics in atomistic environments: harnessing quantum-classical theory with generalized quantum master equations.
W. C. Pfalzgraff, A. Kelly and T. E. Markland
J. Phys. Chem. Lett., 6, 4743-4748 (2015)
Accurate nonadiabatic quantum dynamics on the cheap: making the most of mean field theory with master equations.
A. Kelly, N. J. Brackbill and T. E. Markland
J. Chem. Phys. 142, 094110 (2015)
Quantum delocalization of protons in the hydrogen bond network of an enzyme active site.
L. Wang, S. D. Fried, S. G. Boxer and T. E. Markland
Proc. Natl. Acad. Sci., 111 (52), 18454-18459 (2014)
Quantum fluctuations and isotope effects in ab initio descriptions of water.
L. Wang, M. Ceriotti and T. E. Markland
J. Chem. Phys., 141, 104502 (2014)
*Selected for JCP Editors' Choice Collection 2014Multiple Time Step Integrators in Ab Initio Molecular Dynamics.
N. Luehr, T. E. Markland and T. J. Martinez
J. Chem. Phys., 140, 084116 (2014)
Interface limited growth of heterogeneously nucleated ice in supercooled water.
R. A. Nistor, T. E. Markland, B. J. Berne
J. Phys. Chem. B, 118 (3), 752-760 (2014)
Efficient and accurate surface hopping for long time nonadiabatic quantum dynamics.
A. Kelly and T. E. Markland
J. Chem. Phys. 139, 014104 (2013)
Efficient methods and practical guidelines for simulating isotope effects.
M. Ceriotti and T. E. Markland
J. Chem. Phys. 138, 014112 (2013)
Ring Polymer Molecular Dynamics: Quantum Effects in Chemical Dynamics from Classical Trajectories in an Extended Phase Space.
S. Habershon, D. E. Manolopoulos, T. E. Markland and T. F. Miller
Annu. Rev. Phys. Chem., 64, 387-413 (2013)
Unraveling quantum mechanical effects in water using isotopic fractionation.
T. E. Markland and B. J. Berne
Proc. Natl. Acad. Sci., 109, 7988-7991 (2012)
Growing point-to-set length scale correlates with growing relaxation times in model supercooled liquids.
G. M. Hocky, T. E. Markland and D. R. Reichman
Phys. Rev. Lett. 108 225506 (2012)
Theory and simulations of quantum glass forming liquids.
T. E. Markland, J. A. Morrone, K. Miyazaki, B. J. Berne, D. R. Reichman and E. Rabani
J. Chem. Phys., 136, 074511 (2012)
Reduced density matrix hybrid approach: Application to electronic energy transfer.
T. C. Berkelbach, T. E. Markland and D. R. Reichman
J. Chem. Phys., 136, 084104 (2012)
Isotope effects in water as investigated by neutron diffraction and path integral molecular dynamics.
A. Zeidler, P. S. Salmon, H. E. Fischer, J. C. Neuefeind, J. M. Simonson and T. E. Markland
J. Phys. Condens. Mat. 24, 284126 (2012)
Reduced density matrix hybrid approach: An efficient and accurate method for adiabatic and non-adiabatic quantum dynamics.
T. C. Berkelbach, D. R. Reichman and T. E. Markland
J. Chem. Phys. 136, 034113 (2012)
Reply to Comment on: Oxygen as a Site Specific Probe of the Structure of Water and Oxide Materials
A. Zeidler, P. S. Salmon, H. E. Fischer, J. C. Neuefeind, J. M. Simonson, H. Lemmel, H. Rauch, and T. E. Markland
Phys. Rev. Lett., 108, 259604 (2012)
Oxygen as a Site Specific Probe of the Structure of Water and Oxide Materials.
A. Zeidler, P. S. Salmon, H. E. Fischer, J. C. Neuefeind, J. M. Simonson, H. Lemmel, H. Rauch, and T. E. Markland
Phys. Rev. Lett., 107, 145501 (2011)
Quantum fluctuations can promote or inhibit glass formation.
T. E. Markland, J. A. Morrone, B. J. Berne, K. Miyazaki, E. Rabani and D. R. Reichman
Nature Phys., 7, 134-137 (2011)
Associated News and Views article by Franceso ZamponiEfficient multiple time scale molecular dynamics: Using colored noise thermostats to stabilize resonances.
J. A. Morrone, T. E. Markland, M. Ceriotti and B. J. Berne
J. Chem. Phys. 134, 014103 (2011)
Efficient stochastic thermostatting of path integral molecular dynamics.
M. Ceriotti, M. Parrinello, T. E. Markland and D. E. Manolopoulos
J. Chem. Phys. 133, 124104 (2010)
A fast path integral method for polarizable force fields.
G. S. Fanourgakis, T. E. Markland and D. E. Manolopoulos
J. Chem. Phys. 131, 094102 (2009)
Competing quantum effects in the dynamics of a flexible water model.
S. Habershon, T. E. Markland and D. E. Manolopoulos
J. Chem. Phys. 131, 024501 (2009)
A refined ring polymer contraction scheme for systems with electrostatic interactions.
T. E. Markland and D. E. Manolopoulos
Chem. Phys. Lett. 464, 256-261 (2008)
An efficient ring polymer contraction scheme for imaginary time path integral simulations.
T. E. Markland and D. E. Manolopoulos
J. Chem. Phys. 129, 024105 (2008)
Quantum diffusion of hydrogen and muonium atoms in liquid water and hexagonal ice.
T. E. Markland, S. Habershon and D. E. Manolopoulos
J. Chem. Phys. 128, 194506 (2008)