Presentations
Anastassia Alexandrova (UCLA)
Enzymes as molecular capacitors
Proteins have been shown to produce intramolecular electric fields, preorganized to help enzymatic catalysis. Using IR probes placed in proteins, and measuring their Stark shift, it became possible to assess the local fields at the location of the probe, and correlate those with the reactivity. The talk will show that in fact, 3-D fields in the entirety of the active site (as opposed to a particular bond) are relevant to catalysis. These fields are strongly heterogeneous and dynamic, and both properties are key to enzyme function. We therefore view protein dynamics from the point of view of the dynamics of the field that it creates, correlate global dynamical fields to reactivity, use these complex fields as protein design targets, and machine learn protein function form the portraits of the fields in their active sites. The talk will highlight several methods for field analysis, directly as a vector object, and indirectly via the scalar field of electronic charge density.
About: Anastassia Alexandrova is a Charles Clifford Professor in Chemistry and Biochemistry, and Professor of Materials Science and Engineering in UCLA. She obtained a B.S./M.S. Diploma from Saratov University, Russia, Ph.D. in physical chemistry from Utah State University, and was an American Cancer Society Postdoctoral Fellow at Yale. Anastassia joined the faculty of UCLA in 2010.
Martin Z. Bazant (MIT)
Unified quantum theory of electrochemical kinetics based on coupled ion-electron transfer
The Butler-Volmer (BV) equation, originally developed to fit Tafel's rate law for electrolysis, has become the standard model in electrochemistry, and yet a century later, it still lacks a clear microscopic basis. The first "quantum theory of electrolysis" was published by Gurney in 1932, in which electron transfer (ET) from the metal is a fast step coupled to classical proton transfer. In 1956, Marcus famously challenged this picture and developed the theory of ET coupled to solvent reorganization, rather than ion transfer. Modern quantum simulations of proton coupled electron transfer (PCET) combine these ideas and sum the Marcus ET rate over quantized vibronic states parametrized by the proton position. Here, we present a simple mathematical theory of coupled ion-electron transfer (CIET), which smoothly interpolates between Marcus-like and BV-like kinetics, depending on whether electron- or ion-transfer is rate limiting, respectively. CIET theory provides a convenient bridge between quantum chemistry and electrochemical engineering, as illustrated by examples of Li-ion batteries, electrodeposition and electrocatalysis, including the metal-work-function dependence of BV kinetics of hydrogen evolution.
About: Martin Z. Bazant is the E. G. Roos (1944) Professor of Chemical Engineering and Mathematics at the Massachusetts Institute of Technology and a member of the National Academy of Engineering, President of the International Electrokinetics Society, Director of the Center for Battery Sustainability, Chief Scientific Advisor for Saint-Gobain Research North America, and Chief Scientist and Co-founder of Lithios, Inc.
David N. Beratan (Duke University)
Moving and Sorting Electrons in Living Systems
The late 20th century defined a golden age for research in Chemistry at Caltech, recognized by five Nobel Prizes once our hero, Rudy Marcus, got the ball rolling 1992! I had the fun of landing among the giants of Chemistry for graduate studies in the fall of 1980. My offer letter perfectly summed up the place: "Overall, Caltech is rather unstructured and centered around the individual. It is a very pleasant environment. Caltech is close to the mountains and three quarters of an hour from the sea." The groups of Rudy Marcus, Harry Gray, Sunney Chan, Peter Dervan, and John Hopfield were drilling into the foundations of chemical and biological electron transfer, drawing on all of the tools of theory and experiment, and inventing new tools as needed. The community was fearlessness, it cultivated an environment of intensive interaction, and it was very serious about mentoring younger scientists. I will describe some of the research directions of my own group, inspired by a decade at Caltech and JPL. Our studies of redox reactions span length scales from nanometers to centimeters; the research examines the influence of tunneling pathway, flickering-resonance, multi-electron bifurcation landscapes, and multi-step hopping networks in biological electron transport. I will discuss these ideas and their connections to key experiments; I will also point to some of the puzzles of redox biochemistry that continue to challenge theory.
About: David Beratan received his BS in Chemistry from Duke University and PhD from Caltech (with John Hopfield). He was then a post-doc and, later, a Member of the Technical staff at JPL. David is the R.J. Reynolds Professor of Chemistry at Duke University.
Emily A. Carter (Princeton University)
How Theoretical Physical Chemistry Can Help Sustain Life on Earth
I became a scientist not just because of an intrinsic love of mathematics and science. It was also because it gives my life purpose and meaning to know I could contribute to the advancement of our civilization, one of countless contributors over space and time. Theoretical physical chemistry is a luscious mix of physics, mathematics, computer science, chemistry, materials science, and more. The richness of the subject and the impact it can have are boundless. Today, I will touch on past, present, and future of the field, from the point of view of a multidisciplinarian across science and engineering. It will be an incomplete overview, of course, with examples selected from my own work, both theoretical methods development and applications, with an eye to the future. What can the next generation in our field do for the world?
About: Emily Carter is a distinguished scientist, leader, and educator, recognized for her pioneering contributions to quantum chemistry/dynamics, materials science, sustainable energy and carbon mitigation. She currently serves as Gerhard R. Andlinger Professor in Energy and the Environment at Princeton and Senior Strategic Advisor/Associate Laboratory Director at Princeton Plasma Physics Laboratory.
Bingqing Cheng (UC Berkeley)
Energy and forces are all you need
Standard machine learning interatomic potentials (MLIPs) often rely on short-range approximations, limiting their applicability to systems with significant electrostatics. We recently introduced the Latent Ewald Summation (LES) method, which learns long-range electrostatics from *just energy and force data*. We show that LES can effectively infer physical partial charges, polarization and Born effective charge (BEC) tensors, as well as achieve better accuracy compared to methods that explicitly learn charges. As demonstrations, we predict the infrared spectra of bulk water under zero or finite external electric fields, ionic conductivities of high-pressure superionic ice, and the phase transition and hysteresis in ferroelectric PbTiO3 perovskite.
About: Bingqing is an Assistant Professor at UC Berkeley. She obtained PhD from EPFL in 2019. She was a Junior Research Fellow at Trinity College, Cambridge, and an Assistant Professor at IST Austria. She has won Volker Heine Young Investigator Award, JCP Best Paper by an Emerging Investigator Award, and ERC starting grant.
Glenn H. Fredrickson (UC Santa Barbara)
Computing with Coherent State Fields: From Cold to Hot Bosons
A well-established representation of quantum many-body problems combines a second-quantized occupation number description with a Feynman path integral decomposition in time. For equilibrium studies, the density matrix is factorized in imaginary time using linear combinations of occupation number states known as coherent states (CS). Out of equilibrium, the time evolution operator is similarly discretized with CS along a real time Keldysh contour. For systems satisfying Bose statistics, a compact field-theoretic representation is obtained, involving two complex-conjugate CS fields in d+1 dimensions.
Bosonic CS field theories have served as the basis for investigating a wide range of quantum phenomena including superfluidity and quantum magnetism, and have been adapted to classical systems including reversibly bonding polymers and reaction-diffusion models. The analysis of such field theories has largely relied on analytical methods ranging from perturbation theory to renormalization group transformations. Such methods, however, often invoke uncontrolled approximations or are limited to homogeneous or weakly inhomogeneous systems.
We have recently developed stochastic methods and algorithms based on complex Langevin sampling for direct numerical attack of CS field theories, both quantum and classical. These "field-theoretic simulations" enjoy linear scaling with system size, provide direct access to free energies and finite temperature properties, and can accommodate strong inhomogeneities. This talk will report on progress gleamed from CS simulations of systems ranging from ultracold superfluid and supersolid assemblies of alkali atoms to "hot" reacting mixtures of dissimilar polymers.
About: Glenn H. Fredrickson is a soft matter theorist recognized for his work on self-assembling polymers, glasses, and field-theoretic simulations. He is a Distinguished Professor at UC Santa Barbara and a member of both the National Academy of Sciences and the National Academy of Engineering.
Todd Gingrich (Northwestern University)
Exploring chemical reaction networks with DMRG
Chemical processes exhibit chaotic, high-dimensional dynamics as molecules undergo reactions and diffusion. In the special case of a closed, isolated system, the complex dynamical processes relax into a comparatively simple equilibrium steady-state probability distribution. When the stochastic chemical kinetics describes a nonequilibrium process, how can we computationally study the steady state? The traditional answer is to sample trajectories. In this talk, I will discuss how the tensor network techniques (DMRG & TDVP) from quantum many-body problems are naturally repurposed to study many-body stochastic chemical kinetics. The strategy can be especially useful for probing rare event problems.
About: Todd Gingrich received the Schuster Prize at Caltech in 2008 before venturing to Oxford, Berkeley, MIT, and now Northwestern, where he is an Assistant Professor of Chemistry. He has received Northwestern's Distinguished Teaching Award and Sloan, Dreyfus, NSF CAREER, and APS Oppenheim Awards for research on nonequilibrium statistical mechanics.
Sharon Hammes-Schiffer (Princeton University)
Proton-Coupled Electron and Energy Transfer Processes
The coupled motions of electrons and protons play a critical role in a wide range of chemical and biological processes. This talk will present fundamental insights gained from our theory on proton-coupled electron transfer (PCET) and our more recently developed theory on proton-coupled energy transfer (PCEnT). These theories include the quantum mechanical effects of the electrons and transferring protons, as well as the motions of the donor-acceptor modes and solvent or protein environment. Analytical expressions have been derived for the rate constants and kinetic isotope effects for comparison to experiment. These theories have been applied to photoexcitation of anthracene-phenol-pyridine triads. Photoinduced PCET in these triads exhibits inverted region behavior, where the more thermodynamically favorable process is slower. This behavior is explained in terms of nonadiabatic transitions between pairs of excited vibronic states. Nonequilibrium dynamics simulations identified two distinct PCET pathways following photoexcitation of the anthracene: the electron transfers from phenol to anthracene to generate a charge-separated state or the electron transfers from phenol to pyridine to generate a local electron-proton transfer (LEPT) state. Subsequent experiments identified the LEPT state that was predicted by theory. The associated mechanism was revealed to be a new mechanism called PCEnT because it does not entail charge transfer to the anthracene but rather occurs via electronic energy transfer from anthracene to phenol-pyridine, coupled to proton tunneling. Our PCEnT theory explains how this energy transfer can occur in the absence of detectable spectral overlap between the donor emission and acceptor absorption spectra.
About: Sharon Hammes-Schiffer received her B.A. in Chemistry from Princeton University and her Ph.D. in Chemistry from Stanford University, followed by two years at AT&T Bell Laboratories. Her academic career has included faculty positions at various universities. She is currently the A. Barton Hepburn Professor of Chemistry at Princeton University. She is Editor-in-Chief of Chemical Reviews and is on the Editorial Board for PNAS.
Aditi S. Krishnapriyan (UC Berkeley)
Machine learning methods for atomistic simulations: Leveraging data at scale with generative models and knowledge distillation
Recent advances in large-scale atomistic datasets, such as Open Molecules 2025, offer new opportunities for machine learning (ML) methods in atomistic simulations. These datasets provide opportunities to develop ML approaches with improved scalability and generalization, with an aim towards enabling simulations over broader time and length scales. In this talk, I will highlight two promising directions enabled by large-scale data: (1) knowledge distillation, which improves the speed-accuracy tradeoff in ML force fields by extracting computationally efficient, specialized models from large-scale "foundation" models, and (2) generative modeling approaches informed by statistical physics principles (e.g., least action methods), to accelerate sampling of dynamic pathways and improve the diversity of generated atomistic configurations.
About: Aditi Krishnapriyan is an Assistant Professor at UC Berkeley in Chemical and Biomolecular Engineering (CBE), Electrical Engineering and Computer Sciences (EECS), and Berkeley AI Research; as well as a faculty scientist in the Applied Mathematics division at Lawrence Berkeley National Laboratory.
David T. Limmer (UC Berkeley)
A twist on electron transfer theory
I will present the results of an extension of Marcus' theory of electron transfer for imperfect metallic electrodes like those made from low dimensional materials. I will show how weakly correlated electrons in an electrode screen charges in solution nonlocally, resulting in unexpected electronic contributions to the reorganization energy of outer sphere electron transfer. This theory explains observations of twist dependent electron transfer kinetics in bilayer graphene and predicts doping dependent kinetics in monolayer graphene that has been recently confirmed experimentally.
About: David Limmer is a Professor of Chemistry at UC Berkeley. He is the recipient of the DOE Early Career Award and Alfred P. Sloan Fellowship. David is the founder and director for CECAM-US-WEST, and author of Statistical Mechanics and Stochastic Thermodynamics, a graduate textbook on statistical mechanics.
Shaul Mukamel (UC Irvine)
Monitoring elementary molecular events and conical intersections by ultrafast X-ray pulses and quantum light
Novel X-ray pulse sources from free-electron lasers and high-harmonic generation setups enable the monitoring of elementary events molecular such as the ultrafast passage through conical intersections on unprecedented temporal, spatial and energetic scales. The attosecond duration of X-ray pulses, their large bandwidth, and the atomic selectivity of core X-ray excitations offer new windows into photochemical processes based on monitoring time resolved electronic coherence. We show how the Orbital Angular Momentum of twisted X-ray light can be leveraged to detect vibronic coherences and time evolving chirality emerging at conical intersections due to the bifurcation of molecular wavepackets.
Employing quantum light in multidimensional spectroscopy is opening up many exciting opportunities to enhance the signal-to-noise ratio, improve the combined temporal, spatial, and spectral resolutions, and simplify nonlinear optical signals by selecting desired transition pathways in second and third order signals. We show how photoelectron signals generated by time-energy entangled photon pairs can monitor ultrafast excited state dynamics of molecules with high joint spectral and temporal resolutions, not subjected to the Fourier uncertainty limitation of classical light.
About: Distinguished Professor of Chemistry and Physics & Astronomy - University of California, Irvine. Ph.D. (1976) Tel Aviv University. Former faculty: Rice University, Weizmann Institute of Science, University of Rochester. Member: American Academy of Arts and Sciences; National Academy of Sciences. Pioneered ultrafast multidimensional spectroscopy techniques for monitoring elementary molecular events.
Ahmad K. Omar (UC Berkeley)
Pattern Formation, Phase Transitions, and Interfacial Phenomena Far from Equilibrium
Living systems across all scales constantly consume and convert chemical energy to sustain the biological processes essential to life. From the rhythmic pulsing of developing embryos to active intracellular protein transport, the stunning dynamism of these processes can often seem beyond the grasp of simple theoretical descriptions. Thermodynamics is among the most successful frameworks in the physical sciences precisely because it can describe how and why systems in or near equilibrium undergo radical changes. Yet many living or active processes are decidedly out of equilibrium. Moreover, materials at the core of our modern energy technologies are often subject to operating conditions that push them far from equilibrium. As a result, there is a pressing need to extend, develop, and introduce genuinely nonequilibrium perspectives in the physical sciences. In this talk, I will provide a broad overview of my group's recent efforts toward understanding pattern formation, phase coexistence, and interfacial phenomena for systems arbitrarily far from equilibrium. Beginning from microscopic dynamics and systematically coarse-graining to the fields of interest, we can identify clear limits in which classical thermodynamic theories – e.g., Maxwell constructions, capillary wave theory, and classical nucleation barriers – are recovered but with new physical interpretations. Our perspective identifies the crucial role of both linear and nonlinear transport coefficients and offers an entirely mechanical formulation for determining these coefficients. Finally, we will offer hope for translating these findings to physical intuition that may guide experiments.
About: Ahmad Omar is an Assistant Professor of Materials Science and Engineering at UC Berkeley where his research group uses theory and computation to better understand soft materials out of equilibrium. Ahmad joined the Berkeley faculty in 2021 after postdoctoral studies also at Berkeley and graduate studies at Caltech.
Jian Qin (Stanford University)
Structural correlation and loop formation in randomly crosslinked polymers
Polymer gelation is an abrupt transition between liquid and solid states that is preceded by a gradual proliferation of finite clusters. Resolving the statistics and evolution of these clusters is prerequisite to any quantitative theory of gelation. Despite many years of efforts, our current understanding is mainly derived from the classical theory of Flory-Stockmayer (FS). It is well recognized that the FS theory neglects the formation of loops, which facilitates the evaluation of statistical weights for clusters. Incorporating loop statistics is challenging partially because of the need to enumerate crosslinking patterns. In this talk, we show that, the coherent state theory (CST) avoids the explicit enumeration of crosslinking patterns and gives the correct statistical weights. Systematic field theoretical expansion shows that the mean-field theory, i.e. saddle point approximation, is equivalent to the FS theory, while the Gaussian fluctuation theory automatically produces loops. Explicit expressions on structure factor of associative polymers and the density of loops are presented. The applications are demonstrated by studying association of phantom chains, chains in dilute solution, and chains in dense melts. The joint effects of loop formation and excluded volume and the implication on the shift of gel point are discussed.
About: Jian Qin is an Associate Professor of Chemical Engineering in Stanford University. He did postdoc work in University of Chicago and PSU after receiving PhD from University of Minnesota. His research applies statistical mechanics to the modeling of polymeric materials, emergent behaviors in soft matter, and electrolytes.
Joseph E. Subotnik (Princeton University)
A Phase Space Approach to Electronic Structure Theory
The Born-Oppenheimer approximation is the cornerstone of chemistry, the idea that electronic structure and molecular orbitals are defined relative to a stationary set of coordinates for the nuclei. This premise is based on the important differences in mass between electrons and nuclei, and the all important fact that nuclei move much slower than electrons and appear effectively frozen on the time scale of electronic fluctuations. Nevertheless, it is known that the Born-Oppenheimer approximation breaks down quite often, quite famously in the context of photochemistry and/or Marcus's theory of electron transfer. Slightly less well known is the fact that a classical BO theory does not conserve momentum (linear or angular) even when there is no obvious breakdown. In this talk, I will discuss this failure of the BO approximation, offer up phase space approximations as an improvement to restore conservation, and then suggest a new paradigm for understanding how nuclear entanglement with electronic degrees of freedom may well lead to chiral induced spin selectivity (an exciting phenomenon discovered in recent years) and other magnetic field effects.
About: Joe Subotnik is a Professor of Chemistry at Princeton University.
Gregory A. Voth (University of Chicago)
Thirty Years of Adventure in the Study of Multiscale Phenomena (And Can We Learn from Machine Learning?)
Thirty years ago I become very interested in "multiscale" problems in molecular science. These problems are characterized by several (at least three) coupled scales. I recognized that the statistical mechanical basis to treat such problems. We then pursued "bottom-up" advances in theoretical and computational methodology that that were designed to simulate complex (biomolecular and other soft matter) systems across such multiple length and time scales. This bottom-up approach provided a systematic connection between all-atom (AA) molecular dynamics, coarse-grained (CG) modeling, and mesoscopic phenomena. At the heart of these concepts are methods for deriving CG models from molecular structures and their underlying atomic-scale interactions. A most recent direction of our work in recent years has been the concept of the "ultra-coarse-grained" (UCG) model and its associated computational implementation. In the UCG approach, the CG sites or "beads" can have internal states, much like quantum mechanical states, so the UCG model involves a conceptual abstraction beyond simply Newtonian or Langevin dynamics for the CG beads. The presence of the CG site internal states also greatly expands the possible range of systems amenable to accurate CG modeling, including quite heterogeneous systems such as aggregation of hydrophobes in solution, liquid-vapor and liquid-solid interfaces, and complex self-assembly processes such as occur for large multi-protein complexes. Recent breakthroughs in coarse-graining – in particular by employing developments in machine learning – will be one focus of my talk, along with some key applications.
About: Gregory A. Voth is the Haig P. Papazian Distinguished Professor of Chemistry at the University of Chicago. He is a leader in the development and application of new methods to study the structure and dynamics of complex condensed phase systems, including biomolecules, liquids, and materials.