Annual Review of Physical Chemistry - Volume 75, 2024

Attosecond science requires a substantial rethinking of how to make measurements on very short timescales; how to acquire the necessary equipment, technology, and personnel; and how to build a set of laboratories for such experiments. This entails a rejuvenation of the author in many respects, in the laboratory itself, with regard to students and postdocs, and in generating funding for research. It also brings up questions of what it means to do attosecond science, and the discovery of the power of X-ray spectroscopy itself, which complements the short timescales addressed. The lessons learned, expressed in the meanderings of this autobiographical article, may be of benefit to others who try to reinvent themselves.

Low-resolution coarse-grained (CG) models provide remarkable computational and conceptual advantages for simulating soft materials. In principle, bottom-up CG models can reproduce all structural and thermodynamic properties of atomically detailed models that can be observed at the resolution of the CG model. This review discusses recent progress in developing theory and computational methods for achieving this promise. We first briefly review variational approaches for parameterizing interaction potentials and their relationship to machine learning methods. We then discuss recent approaches for simultaneously improving both the transferability and thermodynamic properties of bottom-up models by rigorously addressing the density and temperature dependence of these potentials. We also briefly discuss exciting progress in modeling high-resolution observables with low-resolution CG models. More generally, we highlight the essential role of the bottom-up framework not only for fundamentally understanding the limitations of prior CG models but also for developing robust computational methods that resolve these limitations in practice.

Water–metal oxide interfaces are central to many phenomena and applications, ranging from material corrosion and dissolution to photoelectrochemistry and bioengineering. In particular, the discovery of photocatalytic water splitting on TiO2 has motivated intensive studies of water-TiO2 interfaces for decades. So far, a broad understanding of the interaction of water vapor with several TiO2 surfaces has been obtained. However, much less is known about liquid water–TiO2 interfaces, which are more relevant to many practical applications. Probing these complex systems at the molecular level is experimentally challenging and is sometimes possible only through computational studies. This review summarizes recent advances in the atomistic understanding, mostly through computational simulations, of the structure and dynamics of interfacial water on TiO2 surfaces. The main focus is on the nature, molecular or dissociated, of water in direct contact with low-index defect-free crystalline surfaces. The hydroxyls resulting from water dissociation are essential in the photooxidation of water and critically affect the surface chemistry of TiO2.

Experimental studies of the collision phenomena of submicrometer particles is a developing field. This review examines the range of phenomena that can be observed with new experimental approaches. The primary focus is on single-particle impact studies enabled by charge detection mass spectrometry (CDMS) implemented using the Aerosol Impact Spectrometer (AIS) at the University of California, San Diego. The AIS combines electrospray ionization, aerodynamic lens techniques, CDMS, and an electrostatic linear accelerator to study the dynamics of particle impact over a wide range of incident velocities. The AIS has been used for single-particle impact experiments on positively charged particles of diverse composition, including polystyrene latex spheres, tin particles, and ice grains, over a wide range of impact velocities. Detection schemes based on induced charge measurements and time-of-flight mass spectrometry have enabled measurements of the impact inelasticity through the determination of the coefficient of restitution, measurements of the angular distributions of scattered submicrometer particles, and the chemical composition and dissociation of solute molecules in hypervelocity ice grain impacts.

Gas-phase anions present an ideal playground for the exploration of excited-state dynamics. They offer control in terms of the mass, extent of solvation, internal temperature, and conformation. The application of a range of ion sources has opened the field to a vast array of anionic systems whose dynamics are important in areas ranging from biology to star formation. Here, we review recent experimental developments in the field of anion photodynamics, demonstrating the detailed insight into photodynamical and electron-capture processes that can be uncovered. We consider the electronic and nuclear ultrafast dynamics of electronically bound excited states along entire reaction coordinates; electronically unbound states showing that photochemical concepts, such as chromophores and Kasha's rule, are transferable to electron-driven chemistry; and nonvalence states that straddle the interface between bound and unbound states. Finally, we consider likely developments that are sure to keep the field of anion dynamics buoyant and impactful.

Atmospheric aerosols facilitate reactions between ambient gases and dissolved species. Here, we review our efforts to interrogate the uptake of these gases and the mechanisms of their reactions both theoretically and experimentally. We highlight the fascinating behavior of N2O5 in solutions ranging from pure water to complex mixtures, chosen because its aerosol-mediated reactions significantly impact global ozone, hydroxyl, and methane concentrations. As a hydrophobic, weakly soluble, and highly reactive species, N2O5 is a sensitive probe of the chemical and physical properties of aerosol interfaces. We employ contemporary theory to disentangle the fate of N2O5 as it approaches pure and salty water, starting with adsorption and ending with hydrolysis to HNO3, chlorination to ClNO2, or evaporation. Flow reactor and gas-liquid scattering experiments probe even greater complexity as added ions, organic molecules, and surfactants alter the interfacial composition and reaction rates. Together, we reveal a new perspective on multiphase chemistry in the atmosphere.

Dynamical reweighting techniques aim to recover the correct molecular dynamics from a simulation at a modified potential energy surface. They are important for unbiasing enhanced sampling simulations of molecular rare events. Here, we review the theoretical frameworks of dynamical reweighting for modified potentials. Based on an overview of kinetic models with increasing level of detail, we discuss techniques to reweight two-state dynamics, multistate dynamics, and path integrals. We explore the natural link to transition path sampling and how the effect of nonequilibrium forces can be reweighted. We end by providing an outlook on how dynamical reweighting integrates with techniques for optimizing collective variables and with modern potential energy surfaces.

By superlocalizing the positions of millions of single molecules over many camera frames, a class of super-resolution fluorescence microscopy methods known as single-molecule localization microscopy (SMLM) has revolutionized how we understand subcellular structures over the past decade. In this review, we highlight emerging studies that transcend the outstanding structural (shape) information offered by SMLM to extract and map physicochemical parameters in living mammalian cells at single-molecule and super-resolution levels. By encoding/decoding high-dimensional information—such as emission and excitation spectra, motion, polarization, fluorescence lifetime, and beyond—for every molecule, and mass accumulating these measurements for millions of molecules, such multidimensional and multifunctional super-resolution approaches open new windows into intracellular architectures and dynamics, as well as their underlying biophysical rules, far beyond the diffraction limit.

Micrometer-sized compartments play significant roles in driving heterogeneous transformations within atmospheric and biochemical systems as well as providing vehicles for drug delivery and novel reaction environments for the synthesis of industrial chemicals. Many reports now indicate that reaction kinetics are accelerated under microconfinement, for example, in sprays, thin films, droplets, aerosols, and emulsions. These observations are dramatic, posing a challenge to our understanding of chemical reaction mechanisms with potentially significant practical consequences for predicting the complex chemistry in natural systems. Here we introduce the idea of kinetic confinement, which is intended to provide a conceptual backdrop for understanding when and why microdroplet reaction kinetics differ from their macroscale analogs.

Genomes are self-organized and self-maintained as long, complex macromolecules of chromatin. The inherent heterogeneity, stochasticity, phase separation, and chromatin dynamics of genome operation make it challenging to study genomes using ensemble methods. Various single-molecule force-, fluorescent-, and sequencing-based techniques rooted in different disciplines have been developed to fill critical gaps in the capabilities of bulk measurements, each providing unique, otherwise inaccessible, insights into the structure and maintenance of the genome. Capable of capturing molecular-level details about the organization, conformational changes, and packaging of genetic material, as well as processive and stochastic movements of maintenance factors, a single-molecule toolbox provides an excellent opportunity for collaborative research to understand how genetic material functions in health and malfunctions in disease. In this review, we discuss novel insights brought to genomic sciences by single-molecule techniques and their potential to continue to revolutionize the field—one molecule at a time.

Oxygenic photosynthesis, the process that converts light energy into chemical energy, is traditionally associated with the absorption of visible light by chlorophyll molecules. However, recent studies have revealed a growing number of organisms capable of using far-red light (700–800 nm) to drive oxygenic photosynthesis. This phenomenon challenges the conventional understanding of the limits of this process. In this review, we briefly introduce the organisms that exhibit far-red photosynthesis and explore the different strategies they employ to harvest far-red light. We discuss the modifications of photosynthetic complexes and their impact on the delivery of excitation energy to photochemical centers and on overall photochemical efficiency. Finally, we examine the solutions employed to drive electron transport and water oxidation using relatively low-energy photons. The findings discussed here not only expand our knowledge of the remarkable adaptation capacities of photosynthetic organisms but also offer insights into the potential for enhancing light capture in crops.

The phase state of aerosol particles can impact numerous atmospheric processes, including new particle growth, heterogeneous chemistry, cloud condensation nucleus formation, and ice nucleation. In this article, the phase transitions of inorganic, organic, and organic/inorganic aerosol particles are discussed, with particular focus on liquid-liquid phase separation (LLPS). The physical chemistry that determines whether LLPS occurs, at what relative humidity it occurs, and the resultant particle morphology is explained using both theoretical and experimental methods. The known impacts of LLPS on aerosol processes in the atmosphere are discussed. Finally, potential evidence for LLPS from field and chamber studies is presented. By understanding the physical chemistry of the phase transitions of aerosol particles, we will acquire a better understanding of aerosol processes, which in turn impact human health and climate.

Cell membranes are incredibly complex environments containing hundreds of components. Despite substantial advances in the past decade, fundamental questions related to lipid-lipid interactions and heterogeneity persist. This review explores the complexity of lipid membranes, showcasing recent advances in vibrational spectroscopy to characterize the structure, dynamics, and interactions at the membrane interface. We include an overview of modern techniques such as surface-enhanced infrared spectroscopy as a steady-state technique with single-bilayer sensitivity, two-dimensional sum-frequency generation spectroscopy, and two-dimensional infrared spectroscopy to measure time-evolving structures and dynamics with femtosecond time resolution. Furthermore, we discuss the potential of multiscale molecular dynamics (MD) simulations, focusing on recently developed simulation algorithms, which have emerged as a powerful approach to interpret complex spectra. We highlight the ongoing challenges in studying heterogeneous environments in multicomponent membranes via current vibrational spectroscopic techniques and MD simulations. Overall, this review provides an up-to-date comprehensive overview of the powerful combination of vibrational spectroscopy and simulations, which has great potential to illuminate lipid-lipid, lipid-protein, and lipid-water interactions in the intricate conformational landscape of cell membranes.

The discovery of more than 200 gas-phase chemical compounds in interstellar space has led to the speculation that this nonterrestrial synthesis may play a role in the origin of life. These identifications were possible because of laboratory spectroscopy, which provides the molecular fingerprints for astronomical observations. Interstellar chemistry produces a wide range of small, organic molecules in dense clouds, such as NH2COCH3, CH3OCH3, CH3COOCH3, and CH2(OH)CHO. Carbon (C) is also carried in the fullerenes C60 and C70, which can preserve C-C bonds from circumstellar environments for future synthesis. Elusive phosphorus has now been found in molecular clouds, the sites of star formation, in the molecules PO and PN. Such clouds can collapse into solar systems, although the chemical/physical processing of the emerging planetary disk is uncertain. The presence of molecule-rich interstellar starting material, as well as the link to planetary bodies such as meteorites and comets, suggests that astrochemical processes set a prebiotic foundation.

Photon upconversion is a process that combines low-energy photons to form useful high-energy photons. There are potential applications in photovoltaics, photocatalysis, biological imaging, etc. Semiconductor quantum dots (QDs) are promising for the absorption of these low-energy photons due to the high extinction coefficient of QDs, especially in the near infrared (NIR). This allows the intriguing use of diffuse light sources such as solar irradiation. In this review, we describe the development of this organic-QD upconversion platform based on triplet-triplet annihilation, focusing on the dark exciton in QDs with triplet character. Then we introduce the underlying energy transfer steps, starting from QD triplet photosensitization, triplet exciton transport, triplet-triplet annihilation, and ending with the upconverted emission. Design principles to improve the total upconversion efficiency are presented. We end with limitations in current reports and proposed future directions. This review provides a guide for designing efficient organic-QD upconversion platforms for future applications, including overcoming the Shockley-Queisser limit for more efficient solar energy conversion, NIR-based phototherapy, and diagnostics in vivo.

Molecular dynamics (MD) enables the study of physical systems with excellent spatiotemporal resolution but suffers from severe timescale limitations. To address this, enhanced sampling methods have been developed to improve the exploration of configurational space. However, implementing these methods is challenging and requires domain expertise. In recent years, integration of machine learning (ML) techniques into different domains has shown promise, prompting their adoption in enhanced sampling as well. Although ML is often employed in various fields primarily due to its data-driven nature, its integration with enhanced sampling is more natural with many common underlying synergies. This review explores the merging of ML and enhanced MD by presenting different shared viewpoints. It offers a comprehensive overview of this rapidly evolving field, which can be difficult to stay updated on. We highlight successful strategies such as dimensionality reduction, reinforcement learning, and flow-based methods. Finally, we discuss open problems at the exciting ML-enhanced MD interface.

In the past two decades, machine learning potentials (MLPs) have driven significant developments in chemical, biological, and material sciences. The construction and training of MLPs enable fast and accurate simulations and analysis of thermodynamic and kinetic properties. This review focuses on the application of MLPs to reaction systems with consideration of bond breaking and formation. We review the development of MLP models, primarily with neural network and kernel-based algorithms, and recent applications of reactive MLPs (RMLPs) to systems at different scales. We show how RMLPs are constructed, how they speed up the calculation of reactive dynamics, and how they facilitate the study of reaction trajectories, reaction rates, free energy calculations, and many other calculations. Different data sampling strategies applied in building RMLPs are also discussed with a focus on how to collect structures for rare events and how to further improve their performance with active learning.

Recent theoretical and algorithmic developments have improved the accuracy with which path integral dynamics methods can include nuclear quantum effects in simulations of condensed-phase vibrational spectra. Such methods are now understood to be approximations to the delocalized classical Matsubara dynamics of smooth Feynman paths, which dominate the dynamics of systems such as liquid water at room temperature. Focusing mainly on simulations of liquid water and hexagonal ice, we explain how the recently developed quasicentroid molecular dynamics (QCMD), fast-QCMD, and temperature-elevated path integral coarse-graining simulations (Te PIGS) methods generate classical dynamics on potentials of mean force obtained by averaging over quantum thermal fluctuations. These new methods give very close agreement with one another, and the Te PIGS method has recently yielded excellent agreement with experimentally measured vibrational spectra for liquid water, ice, and the liquid-air interface. We also discuss the limitations of such methods.

Large strides have been made in designing an ever-increasing set of modern organic materials of high functionality and thus, often, of high complexity, including semiconducting polymers, organic ferroelectrics, light-emitting small molecules, and beyond. Here, we review how broadly applied thermal analysis methodologies, especially differential scanning calorimetry, can be utilized to provide unique information on the assembly and solid-state structure of this extensive class of materials, as well as the phase behavior of intrinsically intricate multicomponent systems. Indeed, highly relevant insights can be gained that are useful, e.g., for further materials-discovery activities and the establishment of reliable processing protocols, in particular if combined with X-ray diffraction techniques, spectroscopic tools, and scanning electron microscopy enabled by vapor-phase infiltration staining. We, hence, illustrate that insights far richer than simple melting point– and glass-transition identification can be obtained with differential scanning calorimetry, rendering it a critical methodology to understand complex matter, including functional macromolecules and blends.

Quantum information promises dramatic advances in computing last seen in the digital revolution, but quantum hardware is fragile, noisy, and resource intensive. Chemistry has a role in developing new materials for quantum information that are robust to noise, scalable, and operable in ambient conditions. While molecular structure is the foundation for understanding mechanism and reactivity, molecular structure/quantum function relationships remain mostly undiscovered. Using singlet fission as a specific example of a multielectron process capable of producing long-lived spin-entangled electronic states at high temperatures, I describe how to exploit molecular structure and symmetry to gain quantum function and how some principles learned from singlet fission apply more broadly to quantum science.