About

Peter Rossky holds the Harry C. & Olga K. Wiess Chair in Natural Sciences and is a Professor of Chemistry at Rice University. He is a member of the National Academy of Sciences. His research areas include Theory & Computation, Spectroscopy & Imaging. Further details about his background, specific contributions, or career history are not provided on the page.

Research topics

• Computer Science
• Artificial Intelligence
• Physics
• Biological system
• Materials science
• Optics
• Nanotechnology
• Optoelectronics
• Computational physics
• Chemistry
• Photochemistry
• Quantum mechanics
• Chemical physics
• Atomic physics
• Molecular physics

Selected publications

• The Curious Case of Dual Emission in 9,10-Bis(phenylethynyl)anthracene

  ChemRxiv · 2026-02-09

  articleOpen access

  The photophysics of molecular crystals are governed by the interplay of molecular packing, electronic coupling, and lattice disorder.9,10-Bis(phenylethynyl)anthracene (BPEA) is a benchmark system for singlet fission and solid-state triplet-triplet annihilation (TTA), yet its optical spectra display long-standing anomalies, including dual absorption and emission features that defy conventional excitonic interpretations.Here, we resolve these puzzles using steady-state and time-resolved spectroscopy combined with exciton-charge-transfer (CT) vibronic modeling, molecular dynamics simulations, and first-principles electronic structure calculations.We show that the characteristic double-band absorption of crystalline BPEA arises from electronic mixing between Frenkel excitons and low-lying CT states, rather than polymorphism or conventional H-aggregate behavior.In contrast, the anomalous low-energy emission originates from structural defects associated with Xshaped BPEA dimers, whose stabilized CT character yields emissive states decoupled from the bulk exciton manifold.These trap states act as inherent dopants to suppress singlet fission while enhancing CT-triplet-pair mixing, creating efficient TTA hotspots and directly linking packing defects to increased upconversion efficiency.

  PublisherOA PDFDOI

• The Curious Case of Dual Emission in 9,10-Bis(phenylethynyl)anthracene

  Journal of the American Chemical Society · 2026-04-04

  articleOpen accessCorresponding

  The photophysics of molecular crystals are governed by the interplay of molecular packing, electronic coupling, and lattice disorder. 9,10-Bis(phenylethynyl)anthracene (BPEA) is a benchmark system for singlet fission and solid-state triplet-triplet annihilation (TTA), yet its optical spectra display long-standing anomalies, including dual absorption and emission features that defy conventional excitonic interpretations. Here, we resolve these puzzles using steady-state and time-resolved spectroscopy combined with exciton-charge-transfer (CT) vibronic modeling, molecular dynamics simulations, and first-principles electronic structure calculations. We show that the characteristic double-band absorption of crystalline BPEA arises from electronic mixing between Frenkel excitons and low-lying CT states rather than polymorphism or conventional H-aggregate behavior. In contrast, the anomalous low-energy emission originates from structural defects associated with X-shaped BPEA dimers, whose stabilized CT character yields emissive states decoupled from the bulk exciton manifold. These trap states act as inherent dopants to suppress singlet fission while enhancing CT-triplet-pair mixing, creating efficient TTA hotspots and directly linking packing defects to increased upconversion efficiency.

  PublisherDOI

• A Bond-Based Machine Learning Model for Molecular Polarizabilities and A Priori Raman Spectra

  Journal of Chemical Theory and Computation · 2024-11-05 · 3 citations

  articleSenior authorCorresponding

  The use of machine learning (ML) algorithms in molecular simulations has become commonplace in recent years. There now exists, for instance, a multitude of ML force field algorithms that have enabled simulations approaching ab initio level accuracy at time scales and system sizes that significantly exceed what is otherwise possible with traditional methods. Far fewer algorithms exist for predicting rotationally equivariant, tensorial properties such as the electric polarizability. Here, we introduce a kernel ridge regression algorithm for machine learning of the polarizability tensor. This algorithm is based on the bond polarizability model and allows prediction of the tensor components at the cost similar to that of scalar quantities. We subsequently show the utility of this algorithm by simulating gas phase Raman spectra of biphenyl and malonaldehyde using classical molecular dynamics simulations of these systems performed with the recently developed MACE-OFF23 potential. The calculated spectra are shown to agree very well with the experiments and thus confirm the expediency of our algorithm as well as the accuracy of the used force field. More generally, this work demonstrates the potential of physics-informed approaches to yield simple yet effective machine learning algorithms for molecular properties.

  PublisherDOI

• A Bond-Based Machine Learning Model for Molecular Polarizabilities and A Priori Raman Spectra

  arXiv (Cornell University) · 2024-10-18

  preprintOpen accessSenior author

  The use of machine learning (ML) algorithms in molecular simulations has become commonplace in recent years. There now exists, for instance, a multitude of ML force field algorithms that have enabled simulations approaching ab initio level accuracy at time scales and system sizes that significantly exceed what is otherwise possible with traditional methods. Far fewer algorithms exist for predicting rotationally equivariant, tensorial properties such as the electric polarizability. Here, we introduce a kernel ridge regression algorithm for machine learning of the polarizability tensor. This algorithm is based on the bond polarizability model and allows prediction of the tensor components at the cost similar to that of scalar quantities. We subsequently show the utility of this algorithm by simulating gas phase Raman spectra of biphenyl and malonaldehyde using classical molecular dynamics simulations of these systems performed with the recently developed MACE-OFF23 potential. The calculated spectra are shown to agree very well with the experiments and thus confirm the expediency of our algorithm as well as the accuracy of the used force field. More generally, this work demonstrates the potential of physics-informed approaches to yield simple yet effective machine learning algorithms for molecular properties.

  PublisherOA PDFDOI

• A Molecular Expression for “Line Tension”

  Langmuir · 2024-05-03

  articleSenior author

  “Line tension”, a concept that features in an additional term to the Young’s equation, was introduced to describe the size dependence of contact angles of nanodroplets on surfaces. Although this concept describes the observations in a succinct, elegant manner, theorists have long had misgivings about the physical interpretation of the phenomenon. Papers have been published that attempt to nail down its value, which is reportedly very small (∼10 pN) and evidently even the sign has been uncertain. Attempts to interpret it in a mechanical manner analogous to interfacial tension, i.e., due to the curvature of the three-phase contact line, have run into conceptual problems that require invocations of ever more complex models. In this work, we have used molecular simulations to systematically relate “line tension” to the additional free energy per unit length of the three-phase line and found no direct relation. However, when we rederived the Young’s equation without ignoring the interfacial molecules, we found a physically satisfying explanation for the size dependence of the contact angle of nanodroplets without invoking the curvature of the three-phase contact line. The new model does not have the elegant form of the modified Young’s equation, but each parameter in it has an unambiguous physical interpretation. An approximate form of this model, linearized in the inverse droplet radius, yields a quantity that is mathematically analogous to what is conventionally called “line tension”, but unpacked at the molecular level, showing that it is unrelated to a restoring force associated with the curvature of the macroscopic three-phase contact line.

  PublisherDOI

• IR Spectroscopy of Carboxylate-Passivated Semiconducting Nanocrystals: Simulation and Experiment

  The Journal of Physical Chemistry C · 2024-05-17 · 7 citations

  preprintOpen accessSenior authorCorresponding

  The surfaces of colloidal nanocrystals are frequently passivated with carboxylate ligands that exert significant effects on their optoelectronic properties and chemical stability. The binding geometries of these ligands are often experimentally investigated using vibrational spectroscopy, but the interpretation of the IR signal is usually not trivial. Here, using machine-learning (ML) algorithms trained on DFT data, we simulate an IR spectrum of a lead-rich PbS nanocrystal passivated with butyrate ligands. We obtain good agreement with the experimental signal and demonstrate that the observed line shape stems from a very wide range of “tilted-bridge”-type geometries and does not indicate the coexistence of “bridging” and “chelating” binding modes as has been previously assumed. This work illustrates the limitations of empirical spectrum assignment and demonstrates the effectiveness of ML-driven molecular dynamics simulations in reproducing the IR spectra of nanoscopic systems.

  PublisherOA PDFDOI

• Exploring Configurations of Nanocrystal Ligands Using Machine-Learned Force Fields

  The Journal of Physical Chemistry Letters · 2023-08-08 · 6 citations

  articleSenior authorCorresponding

  Semiconducting nanocrystals passivated with organic ligands have emerged as a powerful platform for light harvesting, light-driven chemical reactions, and sensing. Due to their complexity and size, little structural information is available from experiments, making these systems challenging to model computationally. Here, we develop a machine-learned force field trained on DFT data and use it to investigate the surface chemistry of a PbS nanocrystal interfaced with acetate ligands. In doing so, we go beyond considering individual local minimum energy geometries and, importantly, circumvent a precarious issue associated with the assumption of a single assigned atomic partial charge for each element in a nanocrystal, independent of its structural position. We demonstrate that the carboxylate ligands passivate the metal-rich surfaces by adopting a very wide range of "tilted-bridge" and "bridge" geometries and investigate the corresponding ligand IR spectrum. This work illustrates the potential of machine-learned force fields to transform computational modeling of these materials.

  PublisherDOI

• Accumulation and ordering of P3HT oligomers at the liquid–vapor interface with implications for thin-film morphology

  Physical Chemistry Chemical Physics · 2023-01-01 · 1 citations

  articleSenior authorCorresponding

  The morphology of semiconducting polymer thin films is known to have a profound effect on their opto-electronic properties. Although considerable efforts have been made to control and understand the processes which influence the structures of these systems, it remains largely unclear what physical factors determine the arrangement of polymer chains in spin-cast films. Here, we investigate the role that the liquid-vapor interfaces in chlorobenzene solutions of poly(3-hexylthiophene) [P3HT] play in the conformational geometries adopted by the polymers. Using all-atom molecular dynamics (MD), and supported by toy-model simulations, we demonstrate that, with increasing concentration, P3HT oligomers in solution exhibit a strong propensity for the liquid-vapor interface. Due to the differential solubility of the backbone and side chains of the oligomers, in the vicinity of this interface, hexyl chains and the thiophene rings, have a clear orientational preference with respect to the liquid surface. At high concentrations, we additionally establish a substantial degree of inter-oligomer alignment and thiophene ring stacking near the interface. Our results broadly concur with the limited existing experimental evidence and we suggest that the interfacial structure can act as a template for film structure. We argue that the differences in solvent affinity of the side chain and backbone moieties are the driving force for the anisotropic orientations of the polymers near the interface. This finer grained description contrasts with the usual monolithic characterization of polymer units. Since this phenomenon can be controlled by concurrent chemical design and the choice of solvents, this work establishes a fabrication principle which may be useful to develop more highly functional polymer films.

  PublisherDOI

• SOLVATION OF SPECIES OF VARYING POLARITY IN SUPERCRITICAL WATER: A COMPUTER SIMULATION STUDY

  2023-01-01

  articleSenior author

  Molecular dynamics computer simulation is used to examine supercritical water's ability to solvate species of varying polarity along the reaction coordinate for the S_N2 reaction of Cl^- and CH₃Cl at several conditions of density and temperature. At the critical temperature and reduced densities down to 0.5, the solute-solvent interactions are sufficiently strong to preserve solvent structure near the chloride ion with coordination numbers as high as in ambient water. We examine how these coordination numbers and the chloride-water hydrogen bonds eventually break down under extreme conditions of low densities and high temperatures.

  PublisherDOI

• Imaging Heterogeneous 3D Dynamics of Individual Solutes in a Polyelectrolyte Brush

  Langmuir · 2023-06-08 · 7 citations

  articleCorresponding

  Understanding molecular transport in polyelectrolyte brushes (PEBs) is crucial for applications such as separations, drug delivery, anti-fouling, and biosensors, where structural features of the polymer control intermolecular interactions. The complex structure and local heterogeneity of PEBs, while theoretically predicted, are not easily accessed with conventional experimental methods. In this work, we use 3D single-molecule tracking to understand transport behavior within a cationic poly(2-(N,N-dimethylamino)ethyl acrylate) (PDMAEA) brush using an anionic dye, Alexa Fluor 546, as the probe. The analysis is done by a parallelized, unbiased 3D tracking algorithm. Our results explicitly demonstrate that spatial heterogeneity within the brush manifests as heterogeneity of single-molecule displacements. Two distinct populations of probe motion are identified, with anticorrelated axial and lateral transport confinement, which we believe to correspond to intra- vs inter-chain probe motion.

  PublisherDOI

Recent grants

• QUANTUM SIMULATION OF CHEMICAL DYNAMICS IN CONDENSED PHASES

  NSF · $311k · 2015–2017

• Quantum Simulation of Chemical Dynamics in Condensed Phases

  NSF · $438k · 2006–2010

• Collaborative Research: Ordering Processes in Water, Aqueous Solutions, and Water-Biomolecule Systems

  NSF · $420k · 2009–2013

• NIH Grant R01GM049204

  NIH · $582k · 1999

• Quantum Simulation of Chemical Dynamics in Condensed Phases

  NSF · $470k · 2009–2013

Frequent coauthors

• Pablo G. Debenedetti

  Princeton University

  57 shared

• Nicolás Giovambattista

  The Graduate Center, CUNY

  49 shared

• László Túri

  Eötvös Loránd University

  34 shared

• Keith P. Johnston

  The University of Texas at Austin

  30 shared

• Andrew L. Ferguson

  University of Chicago

  25 shared

• Athanassios Z. Panagiotopoulos

  25 shared

• Daniel Laría

  University of Buenos Aires

  21 shared

• Paul F. Barbara

  21 shared