Read interviews with the winners to learn more about their research and their hopes for future advances in physical chemistry.
The Journal of Physical Chemistry and PHYS Division Lectureship Awards honor the contributions of investigators who have made a major impact on the field of physical chemistry in the research areas associated with each section of the journal—The Journal of Physical Chemistry A, The Journal of Physical Chemistry B, and The Journal of Physical Chemistry C.
We are pleased to announce this year's winners:
- Prof. Brett Savoie, University of Notre Dame, United States
- Prof. Bei Ding, Shanghai Jiao Tong University, China
- Prof. Daniel Tabor, Texas A&M University, United States
The awards will be presented at ACS Fall 2025, taking place in Washington, D.C., from August 17-21, where the winners will be invited to speak as part of the PHYS division programing.
Read on to learn more about each recipient and read their winning papers.
Prof. Brett Savoie
2025 Winner, The Journal of Physical Chemistry A Award: Molecules, Clusters, and Aerosols
Prof. Savoie's research group focuses on methods development at the interface of machine learning with chemical and materials applications. A major research goal for his team is to accelerate the characterization and prediction of how materials degrade. This has led to the development of methods to predict the reaction networks that mediate degradation and new machine learning models that can assist all stages of materials development. These methods have been used to study lead-halide perovskites, plastics with tunable degradation profiles, and new battery electrolytes. Beyond modeling specific chemical phenomena, Brett is studying how AI can accelerate broader knowledge generation in research settings—improving reproducibility, enhancing experimental design, and extracting latent information from historical data and expert workflows.
On his journey to his independent research career, Prof. Savoie had the privilege of training under a series of world class mentors whose attentions he generally only poorly repaid. Marcetta Darensburg (TAMU) tolerated him in her lab as an undergraduate, Tobin Marks and Mark Ratner (Northwestern) patiently polished the rough stone during his Ph.D. work, and Tom Miller (Caltech) encouraged him to stay in academia during his postdoc. He started his independent career at Purdue in Chemical Engineering where his colleagues were unfailingly generous. He now holds the inaugural Coyle Mission Collegiate Chair of Engineering in the department of Chemical and Biomolecular Engineering at the University of Notre Dame and he is the director of the Notre Dame Scientific Artificial Intelligence (SAI) Initiative.
What is your history with the journal?
Some of my first papers in graduate school were published in JPC. I also remember relishing the opportunity to write a perspective article as a senior graduate student on OPVs, my field of study at the time. Conversely, JPC has published many of the articles and perspectives that were most formative in my training. JPC is a storied journal and I’m proud to have been able to make my own contributions over the years.
What inspired you to pursue your area of research?
I started my career at an extremely unique and exciting time for computational chemistry. My generation inherited decades of great methods development and theoretical work at a time when computing was catching up to make large-scale and high-throughput simulations possible. The scale of computational studies, the predictive possibilities, the level of integration with experiments—these all felt like they were at an inflection point. This made pursuing computational work somewhat inevitable in retrospect.
What’s next for your research?
If the prediction frontier seemed like it was moving quickly during my Ph.D., it is receding even more quickly in the midst of the opportunities being provided by AI. I’m really excited by the opportunities that we have in science and engineering. There are many problems that we simply had no purchase on that now seem plausible to solve. Some that we are working on that I think fit this description are predicting chemical structures from analytical spectra, multi-objective molecular design, designing materials with tailored degradation profiles, planning experiments in open-ended decision spaces, and in silico reaction discovery. Honestly, we’re a bit spoiled for choice with so many exciting problems to work on.
What physical chemistry problems are you hoping to see solved in the next decade?
I feel like the last decade in digital physical chemistry was the decade of the molecule. This wasn’t exclusively true, but I think it is fair to say that there was a major focus on being able to predict more things about molecules, and to a great extent it delivered on that goal. I think that the next decade will be the decade of the reaction. We’ve made comparatively less progress on reaction problems and some of the prerequisites were delivered by the decade of the molecule. For example, exceptions abound but reaction modeling is still mainly done in a descriptive mode (rather than a predictive mode) to rationalize experimental results. I think we are poised to reverse that—to routinely predict some classes of reaction outcomes, optimize reaction conditions, and even discover new reaction mechanisms in a predictive fashion. At least I would like us to try. Reactions and molecules are the two defining objects in chemistry, so I think that’s a safe bet.
Prof. Bei Ding
2025 Winner, The Journal of Physical Chemistry B Award: Biophysics, Biomaterials, Liquids, and Soft Matter
Bei Ding is currently a principal investigator at the Center for Ultrafast Science and Technology at Shanghai Jiao Tong University, China. Prof. Ding earned her B.S. in Chemistry from Peking University, and her Master's degree in Optics and Ph.D. in Physical Chemistry from the University of Michigan, Ann Arbor. Prof. Ding works closely with her students to address fundamental physical chemistry questions in biological systems, aiming to understand their functionalities using ultrafast techniques such as transient UV/Vis absorption, transient IR absorption, and 2D IR.
Over the past several years, her group has been fascinated by a small blue-light photoreceptor known as the BLUF domain. Step by step, they have resolved the mechanisms of three reaction motifs within the BLUF domain, namely proton-coupled electron transfer, proton rocking, and proton translocation. Currently, they are investigating the structural dynamics of the BLUF domain using site-specific infrared probes and 2DIR. They are also expanding their scope to collaborate with researchers to design artificial photoenzymes for asymmetric organic chemical reactions.
What is your history with the journal?
The Journal of Physical Chemistry B (JPCB) has played a pivotal role in my academic journey. My first article (with Prof. Zhan Chen during my Ph.D.) and my first perspective (with Prof. Feng Gai during my postdoc training) were both published in JPCB. In 2024, we were invited to contribute a perspective for the JPCB Virtual Special Issue titled "Women Scientists in China," focusing on our work in the field of BLUF domains. This perspective was selected as the Cover Paper and the ACS Editor’s Choice, and the recognition was a great source of encouragement for me and my students. BLUF domains are highly amenable to mutagenesis and serve as versatile model systems for exploring various proton transfer processes, such as proton rocking and proton relay, which are ubiquitous yet elusive in protein machines.
What inspired you to pursue your area of research?
During my Ph.D. and postdoc, I focused on nonlinear optical spectroscopy and multidimensional spectroscopy, with training in physical chemistry and optics. When choosing a research topic, I look for intriguing physical chemistry questions that are key to the functions of biological systems and can be addressed by advanced spectroscopy. For example, when we first looked into BLUF domains, we read a lot of theoretical papers about proton-coupled electron transfer. These papers helped us design mutants that provide information unobtainable from the wild type, eventually helping us clarify the photoswitching function of BLUF domains. Similarly, in our current study of cryptochromes, we explore how cryptochromes in different species use electron transfer chains to control the lifetimes of the signaling state, leading to functional differences between nocturnal and diurnal species. This approach makes our research interdisciplinary in nature; therefore, I encourage students to learn basic knowledge from other fields, and we hold regular seminars in our group to facilitate interdisciplinary learning.
What’s next for your research?
Our group currently has two key research focuses. On one hand, we are developing transient 2D IR spectroscopy based on high-repetition-rate lasers to study photo-activated structural changes in photoceptors. While conventional 2D IR spectroscopy measures coupling between nearby chemical groups and is sensitive to inter-group distances, transient 2D IR adds another time dimension triggered by a UV/Vis pulse, allowing measurement of subtle structural changes in proteins after photoactivation. The low signal-to-noise ratio of 2D IR has limited its application in biological systems, yet the growing availability of high-repetition-rate lasers may soon overcome this limitation. On the other hand, our research has expanded from natural photoenzymes to artificial ones. We are broadening the scope of reactions and the types of cofactor photochemistry studied. This work requires close collaboration with organic chemists, applying our accumulated knowledge in physical chemistry mechanisms to inspire new design ideas and to address bottlenecks in other fields.
What physical chemistry problems are you hoping to see solved in the next decade?
Over the next decade, the field of physical chemistry is highly likely to drive breakthroughs in understanding protein dynamic mechanisms. Traditional structural biology methods and even advanced tools like AlphaFold fall short in unraveling the dynamic mechanisms of protein machines. However, emerging advanced spectroscopic techniques—such as serial femtosecond crystallography with XFEL, transient 2D IR spectroscopy, and femtosecond stimulated Raman spectroscopy—offer new perspectives by providing dynamic structural information of proteins with femtosecond time resolution. When combined with state-of-the-art computational methods (e.g., excited-state electronic structure calculations and QM/MM calculations), these techniques can generate extensive experimental and computational databases on protein dynamics. Integrating these with cutting-edge machine learning approaches could distill key patterns in protein dynamic structures and accelerate de novo design. This holds great promises for drug development and biological regulation.
Prof. Daniel Tabor
2025 Winner, The Journal of Physical Chemistry C Award: Energy, Materials, and Catalysis
Prof. Tabor is currently an Assistant Professor in the Department of Chemistry at Texas A&M University. He received his B.S. in Chemistry from the University of Texas at Austin in 2011. He then attended the University of Wisconsin—Madison for his Ph.D. (2016) and from 2016-2019, he was a postdoc at Harvard University. Daniel began his independent career on the faculty at Texas A&M in the Fall of 2019. The Tabor Research Group primarily focuses on the computational design of organic and polymeric materials, developing new computational spectroscopy methods, building models to understand mechanochemistry, and scientific machine learning methods.
The group engages in both independent methods development and extensive collaborations with other experimental and computational groups. These collaborators include the Lutkenhaus group (in TAMU Chemical Engineering), the Mittal Group (also TAMU ChemE), the Fang group (TAMU Chemistry), and the Center for the Mechanical Control of Chemistry, led by James Batteas. In addition, they collaborate with individuals across the country on their spectroscopy work, including Nathan Kidwell at the College of William and Mary and Timothy Zwier at Sandia National Laboratory.
What is your history with the journal?
JPCA was the first place I published, with my undergraduate research on the calculation enthalpies of formation of combustion radicals in John F. Stanton’s group. As a graduate student, my first first-author paper as a graduate student was published in JPCL. This journal was a “home” for our spectroscopy experiment-theory collaboration. Since starting as independent faculty member, both the spectroscopy and machine learning wings of the group have published results in the journal. I think that this speaks to the breadth of what is covered in the JPC journals, and I expect our group will continue to find a home here for years to come.
What inspired you to pursue your area of research?
There are two main threads that motivate our research. First, we want to develop methods that help with the interpretation of current state-of-the-art experiments (in both spectroscopy and materials), because if we understand the fundamentals of what’s happening in the system at the molecular level, then we (and others) can make informed decisions about what future materials to make and what kinds of design principles that could be develop. Second, we are motivated by how large chemical (or polymer, or material) space is, and so we need to develop methods that help us navigate more efficiently through chemical space.
What’s next for your research?
On the spectroscopy side of the group, we are working on larger systems than ever before, and this has required us to learn a lot about new areas (for us), such as enhanced sampling, coarse-grained simulations, and dealing with rare event sampling methods. On the materials discovery and design space, we’re working on designing molecules and polymers that are predicted to satisfy several objectives simultaneously, and we’re also working on developing user-friendly tools so that anyone can do a high-throughput organic materials design campaign.
What physical chemistry problems are you hoping to see solved in the next decade?
There are so many, but I hope to see a comprehensive, transferable, and fast way for predicting and understanding molecular and materials stability (this is such a huge issue in energy applications). I’d also love to see a full-dimensional simulated vibrational-rotational (if you can even call it that) spectrum of CH5+ that matches experiment. I also hope that physical chemistry become more integrated with autonomous chemical laboratories. There are many more!
Learn About Last Year's Winners
