Annual review of physical chemistry最新文献

Chemical manifestations of strong light-matter coupling have recently been a subject of intense experimental and theoretical studies. Here we review the present status of this field. Section 1 is an introduction to molecular polaritonics and to collective response aspects of light-matter interactions. Section 2 provides an overview of the key experimental observations of these effects, while Section 3 describes our current theoretical understanding of the effect of strong light-matter coupling on chemical dynamics. A brief outline of applications to energy conversion processes is given in Section 4. Pending technical issues in the construction of theoretical approaches are briefly described in Section 5. Finally, the summary in Section 6 outlines the paths ahead in this exciting endeavor.

Surface-enhanced Raman scattering (SERS), a powerful technique for trace molecular detection, depends on chemical and electromagnetic enhancements. While recent advances in instrumentation and substrate design have expanded the utility, reproducibility, and quantitative capabilities of SERS, some challenges persist. In this review, advances in quantitative SERS detection are discussed as they relate to intermolecular interactions, surface selection rules, and target molecule solubility and accessibility. After a brief introduction to Raman scattering and SERS, impacts of surface selection rules and enhancement mechanisms are discussed as they relate to the observation of activation and deactivation of normal Raman modes in SERS. Next, experimental conditions that can be used to tune molecular affinity to and density near SERS substrates are summarized and considered while tuning these parameters is conveyed. Finally, successful examples of quantitative SERS detection are discussed, and future opportunities are outlined.

The atomic specificity of X-ray spectroscopies provides a distinct perspective on molecular electronic structure. For 3d metal coordination and organometallic complexes, the combination of metal- and ligand-specific X-ray spectroscopies directly interrogates metal-ligand covalency-the hybridization of metal and ligand electronic states. Resonant inelastic X-ray scattering (RIXS), the X-ray analog of resonance Raman scattering, provides access to all classes of valence excited states in transition-metal complexes, making it a particularly powerful means of characterizing the valence electronic structure of 3d metal complexes. Recent advances in X-ray free-electron laser sources have enabled RIXS to be extended to the ultrafast time domain. We review RIXS studies of two archetypical photochemical processes: charge-transfer excitation in ferricyanide and ligand photodissociation in iron pentacarbonyl. These studies demonstratefemtosecond-resolution RIXS can directly characterize the time-evolving electronic structure, including the evolution of the metal-ligand covalency.

As the volume of data associated with scientific research has exploded over recent years, the use of digital infrastructures to support this research and the data underpinning it has increased significantly. Physical chemists have been making use of eScience infrastructures since their conception, but in the last five years their usage has increased even more. While these infrastructures have not greatly affected the chemistry itself, they have in some cases had a significant impact on how the research is undertaken. The combination of the human effort of collaboration to create open source software tools and semantic resources, the increased availability of hardware for the laboratories, and the range of data management tools available has made the life of a physical chemist significantly easier. This review considers the different aspects of eScience infrastructures and explores how they have improved the way in which we can conduct physical chemistry research.

This review focuses on a recent class of path-integral-based methods for the simulation of nonadiabatic dynamics in the condensed phase using only classical molecular dynamics trajectories in an extended phase space. Specifically, a semiclassical mapping protocol is used to derive an exact, continuous, Cartesian variable path-integral representation for the canonical partition function of a system in which multiple electronic states are coupled to nuclear degrees of freedom. Building on this exact statistical foundation, multistate ring polymer molecular dynamics methods are developed for the approximate calculation of real-time thermal correlation functions. The remarkable promise of these multistate ring polymer methods, their successful applications, and their limitations are discussed in detail.

Optical microscopy has become an invaluable tool for investigating complex samples. Over the years, many advances to optical microscopes have been made that have allowed us to uncover new insights into the samples studied. Dynamic changes in biological and chemical systems are of utmost importance to study. To probe these samples, multidimensional approaches have been developed to acquire a fuller understanding of the system of interest. These dimensions include the spatial information, such as the three-dimensional coordinates and orientation of the optical probes, and additional chemical and physical properties through combining microscopy with various spectroscopic techniques. In this review, we survey the field of multidimensional microscopy and provide an outlook on the field and challenges that may arise.

In the past two decades, machine learning potentials (MLPs) have reached a level of maturity that now enables applications to large-scale atomistic simulations of a wide range of systems in chemistry, physics, and materials science. Different machine learning algorithms have been used with great success in the construction of these MLPs. In this review, we discuss an important group of MLPs relying on artificial neural networks to establish a mapping from the atomic structure to the potential energy. In spite of this common feature, there are important conceptual differences among MLPs, which concern the dimensionality of the systems, the inclusion of long-range electrostatic interactions, global phenomena like nonlocal charge transfer, and the type of descriptor used to represent the atomic structure, which can be either predefined or learnable. A concise overview is given along with a discussion of the open challenges in the field.

Multidimensional optical spectra are measured from the response of a material system to a sequence of laser pulses and have the capacity to elucidate specific molecular interactions and dynamics whose influences are absent or obscured in a conventional linear absorption spectrum. Interpretation of complex spectra is supported by theoretical modeling of the spectroscopic observable, requiring implementation of quantum dynamics for coupled electrons and nuclei. Performing numerically correct quantum dynamics in this context may pose computational challenges, particularly in the condensed phase. Semiclassical methods based on calculating classical trajectories offer a practical alternative. Here I review the recent application of some semiclassical, trajectory-based methods to nonlinear molecular vibrational and electronic spectra.

Advances in atomic, molecular, and optical physics techniques allowed the cooling of simple molecules down to the ultracold regime ([Formula: see text]1 mK) and opened opportunities to study chemical reactions with unprecedented levels of control. This review covers recent developments in studying bimolecular chemistry at ultralow temperatures. We begin with a brief overview of methods for producing, manipulating, and detecting ultracold molecules. We then survey experimental works that exploit the controllability of ultracold molecules to probe and modify their long-range interactions. Further combining the use of physical chemistry techniques such as mass spectrometry and ion imaging significantly improved the detection of ultracold reactions and enabled explorations of their dynamics in the short range. We discuss a series of studies on the reaction KRb + KRb → K₂ + Rb₂ initiated below 1 μK, including the direct observation of a long-lived complex, the demonstration of product rotational state control via conserved nuclear spins, and a test of the statistical model using the complete quantum state distribution of the products.

We review a suite of stochastic vector computational approaches for studying the electronic structure of extended condensed matter systems. These techniques help reduce algorithmic complexity, facilitate efficient parallelization, simplify computational tasks, accelerate calculations, and diminish memory requirements. While their scope is vast, we limit our study to ground-state and finite temperature density functional theory (DFT) and second-order many-body perturbation theory. More advanced topics, such as quasiparticle (charge) and optical (neutral) excitations and higher-order processes, are covered elsewhere. We start by explaining how to use stochastic vectors in computations, characterizing the associated statistical errors. Next, we show how to estimate the electron density in DFT and discuss effective techniques to reduce statistical errors. Finally, we review the use of stochastic vectors for calculating correlation energies within the second-order Møller-Plesset perturbation theory and its finite temperature variational form. Example calculation results are presented and used to demonstrate the efficacy of the methods.