Annual review of physical chemistry最新文献

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.

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.

We review our recent quantum stochastic model for spectroscopic lineshapes in the presence of a coevolving and nonstationary background population of excitations. Starting from a field theory description for interacting bosonic excitons, we derive a reduced model whereby optical excitons are coupled to an incoherent background via scattering as mediated by their screened Coulomb coupling. The Heisenberg equations of motion for the optical excitons are then driven by an auxiliary stochastic population variable, which we take to be the solution of an Ornstein-Uhlenbeck process. Here, we present an overview of the theoretical techniques we have developed as applied to predicting coherent nonlinear spectroscopic signals. We show how direct (Coulomb) and exchange coupling to the bath give rise to distinct spectral signatures and discuss mathematical limits on inverting spectral signatures to extract the background density of states.

Gas-phase molecular spectroscopy is a natural playground for accurate quantum-chemical computations. However, the molecular bricks of life (e.g., DNA bases or amino acids) are challenging systems because of the unfavorable scaling of quantum-chemical models with the molecular size (active electrons) and/or the presence of large-amplitude internal motions. From the theoretical point of view, both aspects prevent the brute-force use of very accurate but very expensive state-of-the-art quantum-chemical methodologies. From the experimental point of view, both features lead to congested gas-phase spectra, whose assignment and interpretation are not at all straightforward. Based on these premises, this review focuses on the current status and perspectives of the fully a priori prediction of the spectral signatures of medium-sized molecules (containing up to two dozen atoms) in the gas phase with special reference to rotational and vibrational spectroscopies of some representative molecular bricks of life.

Chemical physics plays a large role in determining the isotopic compositions of gases in Earth's atmosphere, which in turn provide fundamental insights into the sources, sinks, and transformations of atmospheric gases and particulates and their influence on climate. This review focuses on the kinetic and photolysis isotope effects relevant to understanding the isotope compositions of atmospheric ozone, carbon dioxide, methane, nitrous oxide, and other gases and their historical context. The discussion includes non-mass-dependent isotope compositions of oxygen-containing species and a brief overview of the recent growth of clumped isotope measurements at natural isotopic abundances, that is, of molecules containing more than one rare isotope. The intention is to introduce chemistry researchers to the field of using isotope compositions as tracers of atmospheric chemistry and climate both today and back in time through ice and rock records and to highlight the outstanding research questions to which experimental and theoretical physical chemists can contribute.

Upconverting nanoparticles (UCNPs) compose a class of luminescent materials that utilize the unique wavelength-converting properties of lanthanide (Ln) ions for light-harvesting applications, photonics technologies, and biological imaging and sensing experiments. Recent advances in UCNP design have shed light on the properties of local color centers, both intrinsic and controllably induced, within these materials and their potential influence on UCNP photophysics. In this review, we describe fundamental studies of color centers in Ln-based materials, including research into their origins and their roles in observed photodarkening and photobrightening mechanisms. We place particular focus on the new functionalities that are enabled by harnessing the properties of color centers within Ln-doped nanocrystals, illustrated through applications in afterglow-based bioimaging, X-ray detection, all-inorganic nanocrystal photoswitching, and fully rewritable optical patterning and memory.

Atmospheric aerosols exert a significant but highly uncertain effect on the global climate, and roughly half of these particles originate as small clusters formed by collisions between atmospheric trace vapors. These particles typically consist of acids, bases, and water, stabilized by salt bridge formation and a network of strong hydrogen bonds. We review spectroscopic studies of this process, focusing on the clusters likely to be involved in the first steps of particle formation and the intermolecular interactions governing their stability. These studies typically focus on determining structure and stability and have shown that acid-base chemistry in the cluster may violate chemical intuition derived from solution-phase behavior and that hydration of these clusters is likely to be complex to describe. We also suggest fruitful areas for extension of these studies and alternative spectroscopic techniques that have not yet been applied to this problem.

The photoacid dynamics of fluorescent proteins include both electronic excited- and ground-state mechanisms of proton transfer. The associated characteristic timescales of these reactions range over many orders of magnitude, and the tunneling, barrier crossing, and relevant thermodynamics have in certain cases been linked to coherent nuclear motion. We review the literature and summarize the experiments and theory that demonstrate proton tunneling in the electronic ground state of the green fluorescent protein (GFP). We also discuss the excited-state proton-transfer reaction of GFP that takes place on the picosecond timescale. Although this reaction has been investigated using several vibrational spectroscopic methods, the interpretation remains unsettled. We discuss recent advances as well as remaining questions, in particular those related to the vibrational mode couplings that involve low-frequency modulations of chromophore vibrations on the timescale of proton transfer.

Light-driven phenomena in organic molecular aggregates underpin several mechanisms relevant to optoelectronic applications. Modeling these processes is essential for aiding the design of new materials and optimizing optoelectronic devices. In this review, we cover the use of different atomistic models, excited-state dynamics, and transport approaches for understanding light-activated phenomena in molecular aggregates, including radiative and nonradiative decay pathways. We consider both intra- and intermolecular mechanisms and focus on the role of conical intersections as facilitators of internal conversion. We explore the use of the exciton models for Frenkel and charge transfer states and the electronic structure methods and algorithms commonly applied for excited-state dynamics. Throughout the review, we analyze the approximations employed for the simulation of internal conversion, intersystem crossing, and reverse intersystem crossing rates and analyze the molecular processes behind single fission, triplet-triplet annihilation, Dexter energy transfer, and Förster energy transfer.