Chemical Reviews最新文献

Soft materials are polymer networks that can be easily deformed by external forces. Incorporating dynamic bonds into these networks imparts various functionalities─such as self-healing, recyclability, and 3D printability─by enabling fast and reversible bond formation. However, the relatively short lifetimes of dynamic bonds compared with permanent covalent bonds can compromise the mechanical robustness of the material. This review highlights design strategies that harness dynamic bonds effectively to achieve both functionality and mechanical robustness in soft materials. We first survey the types of dynamic bonds and their characteristic lifetimes, followed by introducing analytical methods to quantify the network dynamicity. Since the required degree of dynamicity varies depending on the target functionality, we further discuss how to incorporate appropriate dynamic bonds for functionality. Through this, we aim to provide design guidelines for soft materials that combine functionalities with mechanical toughness for reliable use in advanced applications.

Vanadium oxides cystallize in a diverse array of structures and compositions arising from the redox versatility of vanadium, variable covalency of V–O bonds, and myriad coordination geometries. Their open frameworks present abundant interstitial sites that enable insertion of guest-ions. In such compounds, V3d electron and spin localization and disorder couple strongly to structural preferences. The rich structural diversity manifests as a “rugged” free energy landscape with multiple interconvertible polymorphs. Such a landscape sets up structural, electronic, and magnetic transitions that underpin the promise of these materials as ion-insertion battery electrodes; compact primitives for brain-inspired computing, and heterogeneous catalysts. Here, we examine the structural and compositional diversity, electronic instabilities, defect dynamics, structure transformations, mechanical properties, and surface structure of vanadium oxides using single crystals as a distinctive lens. Single crystals enable the measurement of structure–function correlations without the ensemble and orientational averaging inevitable in polycrystalline materials. Their well-defined surfaces further enable examination of facet-dependent reactivity toward molecular adsorbates, ion fluxes, and lattice (mis)matched solids. We provide a comprehensive account of vanadium-oxide single-crystal studies, from delineation of common structural motifs to single-crystal growth techniques, topochemical modification strategies, mechanisms underpinning electronic instabilities, and implementation as electrothermal neurons and battery electrode materials.

Monocrystalline solids have been broadly used in many fields, including batteries, electronics, and optics. Monocrystalline cathode materials have regained intensive study in recent years because of their potential to stabilize the cathode-electrolyte interphase at elevated voltages and/or reduce gassing from high capacity nickel-rich cathode materials; thus, more energy can be extracted from the same materials, except that they are converted into grain boundary-free particles, or so-called “single crystals” in the battery field. This work reviews the history, current progress, and future trends of single crystal cathodes for lithium-based batteries with a focus on cost-effective synthesis, scaleup, and manufacturing. Much work is needed to reduce manufacturing costs of single crystal cathodes, from the selection of precursors and synthesis routes to morphology control and equipment design. This review highlights the importance of cost-oriented fundamental research and processing science to accelerate battery materials manufacturing and establish a resilient manufacturing chain for versatile energy storage technologies.

Carbonylation reactions constitute one of the most powerful and widely utilized strategies for synthesizing carbonyl-containing compounds in organic chemistry. Among the mechanistic pathways explored, two-electron transfer (TET) processes have been extensively developed and industrially applied. However, besides their obvious advantages, their intrinsic limitations, such as reliance on precious metal catalysts and restricted compatibility with alkyl substrates, have prompted increasing interest in single-electron transfer (SET) alternatives. Alternatively, SET-mediated carbonylation bypasses the traditional oxidative addition step, generating highly reactive radical intermediates under milder reaction conditions, thus providing enhanced selectivity and broader substrate compatibility. This review offers a comprehensive overview of SET-mediated carbonylation chemistry from 2000 to July 2025, emphasizing mechanistic insights, catalytic systems, and synthetic applications. The objective is to establish a conceptual foundation for understanding recent advances and inspire further exploration into novel reactivity paradigms based on SET strategies within the realm of carbonylation chemistry.

Molecular dynamics simulations hold great promise for providing insight into the microscopic behavior of complex molecular systems. However, their effectiveness is often constrained by long timescales associated with rare events. Enhanced sampling methods have been developed to address these challenges, and recent years have seen a growing integration with machine learning techniques. This Review provides a comprehensive overview of how they are reshaping the field, with a particular focus on the data-driven construction of collective variables. Furthermore, these techniques have also improved biasing schemes and unlocked novel strategies via reinforcement learning and generative approaches. In addition to methodological advances, we highlight applications spanning different areas, such as biomolecular processes, ligand binding, catalytic reactions, and phase transitions. We conclude by outlining future directions aimed at enabling more automated strategies for rare-event sampling.

CO₂ reduction using renewable H₂ represents an emerging approach for minimizing dependency on fossil fuels and reducing the carbon footprint while providing chemicals and fuels. In this context, CO₂ hydrogenation using Fe-based oxide, which exhibits outstanding capabilities in both reverse water gas shift (RWGS) and Fischer–Tropsch synthesis (FTS) reactions, integrated with zeolite has been a promising method for heavy hydrocarbon (C₅₊) production. This review investigates the critical roles of promoter, zeolite topology and acidity, and synthesis methods in optimizing product distribution and their contributions to active site proximity. It has been found that the catalyst integration manner and the interaction between the basic sites of Fe-based oxide and the acidic sites of zeolites significantly influence catalytic performance. In addition, the proximity of active sites, a crucial factor in tandem catalysis, can be controlled via different catalyst synthesis methods, dispersion on mesoporous supports, or using encapsulated structures that can provide the confinement effect while guiding the reaction sequence. Furthermore, the choice of alkali promoters (Na vs K) is very important since each can alter electronic properties, reduction behavior, and hydrocarbon distribution due to different electronegativity and ionic radii. While Na could hamper all reduction steps and diffuses into bulk iron oxide, K remains mainly on the surface, increasing electron density and facilitating iron carbide formation. Besides, integrating spectroscopic imaging techniques with proximity metrics will enhance the understanding of active site spatial distribution. To bridge the gap between lab-scale results and industrial applications, advanced computational methods coupled with artificial intelligence (AI) and machine learning (ML) techniques are required to monitor and analyze catalyst behavior and optimize large-scale production. The findings of this study provide a comprehensive understanding of catalyst design principles with emphasis on the importance of the proximity of active sites, offering insights for the next generation of efficient CO₂ hydrogenation catalysts for industrial-scale fuel production.

The active sites at the unliganded forms of many of Nature’s most proficient catalysts of metabolic reactions do not show a good fit for the enzymatic transition state; this fit is created by utilization of substrate binding energy to drive protein conformational changes that move side chains to positions that provide optimal transition-state stabilization. Static protein X-ray crystal structures of enzyme Michaelis complexes provide a critical starting point for determination of the roles of these side chains in stabilizing the enzymatic transition state but provide little insight into the catalytic role of the substrate-driven protein conformational change. Important elements of the mechanism of action of nature’s most proficient enzyme catalysts are therefore only revealed after examination of the structure for unliganded enzyme active sites and their substrate-driven transformations to structured forms that are complementary to reaction transition states. There have been few studies to determine the effect on enzyme activity of site-directed substitution of protein side chains that participate in substrate-driven enzyme conformational changes. The fascinating effects of these substitutions were probed by site-directed substitution of amino acid side chains that take part in conformational changes during catalysis by triosephosphate isomerase, glycerol phosphate dehydrogenase, and orotidine 5′-monophosphate decarboxylase.

Circularly polarized luminescence (CPL)─the emission of circularly polarized light from luminescent chiral nonracemic matter─has garnered unprecedented attention in the past decade. Once a niche technique used for the characterization of excited states, CPL has evolved to a powerful and widespread tool for developing functional materials with multiple applications. The development of novel CPL emitters is costly and time-consuming because the key CPL quantities (dissymmetry factor, g_lum, and CPL brightness, B_CPL) often elude simple structure-to-property relationships based on existing knowledge. Today, research in the field is aided by quantum chemistry calculations which offer insight into CPL properties and serve as a predictive tool for the rational design of efficient CPL-active materials. The present review is divided into three sections: (1) a comprehensive presentation of the theoretical foundation of CPL calculations, electronic structure description, environment effects, vibronic modulation, band shape broadening, and aggregate simulation; (2) an extensive literature survey, organized according to a structural criterion; and (3) a critical reassessment of literature data, accompanied by a statistical analysis, aimed at offering the best practices for accurate CPL calculations and identifying the key structural and electronic features that enable the simulation-guided design of novel CPL emitters.

Crystallization-driven self-assembly (CDSA) offers precise control over the size, shape, and hierarchical organization of polymeric nanostructures by harnessing the crystallization of a core-forming block. Unlike conventional self-assembly, CDSA favors the formation of low-curvature morphologies, such as fibers and platelets, with exceptional uniformity. This review highlights key CDSA strategies, including seeded growth, self-seeding, and polymerization-induced CDSA, along with factors influencing assembly, such as polymer composition, solvent, temperature, and additives. We summarize advanced characterization techniques─spanning light scattering, microscopy, spectroscopy and fluorescence imaging─and computational approaches, including Monte Carlo and Brownian dynamics simulations, for understanding assembly mechanisms and predicting morphologies. Finally, we discuss emerging applications in biomedicine, catalysis, optoelectronics, and functional materials, and outline future challenges in precision control, multitechnique characterization, and scalable synthesis. By integrating mechanistic insights, advanced characterization, and application-driven design, this review establishes a comprehensive foundation for future development of CDSA-based functional materials.

RNA splicing is orchestrated by a complex and exceptionally dynamic RNA–protein machine, called the spliceosome. Stepwise, large-scale structural and compositional remodeling of the spliceosome enables splicing and ensures its fidelity. While cryogenic electron microscopy provided structural information on numerous splicing cycle intermediates, allowing large-scale rearrangements to be inferred on a comparative basis, all-atom simulations complement and enrich structural studies by capturing the dynamic nature of the spliceosome on a finer but equally important scale. Here, we review the current understanding of the spliceosome’s function attained by enriching experimental insights with computation. We focus on splicing factors mediating the spliceosome’s dynamic behavior, key for splicing cycle progression, and discuss computational challenges on the path toward more accurate large-scale simulations that could further bridge the gap between computational and experimental data. A synergistic interplay between experiment and computation is vital for obtaining high-accuracy structural ensembles of the spliceosome and its components and for addressing unresolved mechanistic and biological questions related to splicing. Such integrative approaches also hold promise for advancing the design of splicing-targeted therapeutics and gene modulation technologies for treating diseases linked to splicing dysregulation.