Annual review of physical chemistry最新文献

Photoexcited molecules convert light into chemical and mechanical energy through changes in electronic and nuclear structure that take place on femtosecond timescales. Gas phase ultrafast electron diffraction (GUED) is an ideal tool to probe the nuclear geometry evolution of the molecules and complements spectroscopic methods that are mostly sensitive to the electronic state. GUED is a weak and passive probing tool that does not alter the molecular properties during the probing process and is sensitive to the spatial distribution of charge in the molecule, including both electrons and nuclei. Improvements in temporal resolution have enabled GUED to capture coherent nuclear motions in molecules in the excited and ground electronic states with femtosecond and subangstrom resolution. Here we present the basic theory of GUED and explain what information is encoded in the diffraction signal, review how GUED has been used to observe coherent structural dynamics in recent experiments, and discuss the advantages and limitations of the method.

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.

All solid materials are created via nucleation. In this evolutionary process, nuclei form in solution or at interfaces, expand by monomeric growth and oriented attachment, and undergo phase transformation. Nucleation determines the location and size of nuclei, whereas growth controls the size, shape, and aggregation of newly formed nanoparticles. These physical properties of nanoparticles can affect their functionalities, reactivities, and porosities, as well as their fate and transport. Recent advances in nanoscale analytical technologies allow in situ real-time observations, enabling us to uncover the molecular nature of nuclei and the critical controlling factors for nucleation and growth. Although a single theory cannot yet fully explain such evolving processes, we have started to better understand how both classical andnonclassical theories can work together, and we have begun to recognize the importance of connecting these theories. This review discusses the recent convergence of knowledge about the nucleation and growth of nanoparticles.

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.