Abstract High-loading single-atom catalysts (SACs) have recently emerged as a frontier in electrochemical catalysis because of their complete active-site utilization, tunable coordination environment, and atomically defined structure. While it is widely recognized that the single-atomic site in SACs often presents extraordinary catalytic performance, their limited metal content and low active-site density still hinder large-scale implementation in practical electrochemical reactors. Overcoming this limitation requires the development of strategies to achieve high metal loading while preserving atomic dispersion and stability under operational conditions. In this Review, we comprehensively summarize recent advances in the synthesis of high-loading SACs, the state-of-the-art characterization techniques used to probe their atomic and electronic structures, and their applications in advanced electrochemical systems, such as CO2 electrolyzers, fuel cells, and zinc–air batteries. We critically analyze representative breakthroughs that bridge the gap between atomic-scale loading control and commercial-level performance, elucidating the correlations among metal loading, electronic structure modulation, and catalytic activity. Then, we offer perspectives on rational design strategies and emerging opportunities for integrating high-loading SACs into next-generation electrocatalytic reactors, with the aim of accelerating their transition from laboratory research to industrial deployment.
Since the first confirmed case in 1970, the monkeypox virus (MPXV) has emerged as a significant threat to global public health. The World Health Organization (WHO) has declared it a Public Health Emergency of International Concern (PHEIC) on two occasions. Despite decades of research, only tecovirimat has been approved by the European Medicines Agency (EMA) for the treatment of MPXV infection. The genome and structure are similar between MPXV and other orthopoxviruses (OPXVs), suggesting that the strategies used for other OPXVs may be applicable to MPXV. This review systematically summarizes the genome, structure, and critical stages in the life cycle of OPXVs, especially MPXV. A variety of antiviral agents against MPXV and other OPXVs are discussed according to their distinct mechanisms of action: 1) blocking viral entry and fusion, 2) inhibiting DNA replication and processing, 3) disrupting transcription and mRNA processing, 4) preventing virion assembly, maturation and release, 5) modulating immune responses, and 6) mechanism unknown. Overall, this article provides a systematic review of current research progress on potential therapeutic targets and agent for MPXV, aiming to offer innovative insights and strategies for the development of effective therapeutic agents against mpox.
Intracellular delivery of functional proteins is emerging as a powerful strategy to interrogate and control cellular pathways with high spatial and temporal precision. Recent advances in chemical biology now enable the design of cell-permeable proteins through precise chemical and biochemical modification, bringing the field closer to achieving intracellularly targeted biologics as a "new class of drugs". By overcoming the limitations of genetic manipulation, researchers create solutions for basic research and medicine. In this review, we outline the key motivations that drive intracellular protein delivery. We highlight central mechanistic paradigms for protein entry, important parameters influencing protein delivery, and summarize analytical tools to assess successful delivery. We outline different chemical and biochemical conceptional approaches that resulted in breakthrough studies to achieve functional protein transport. Finally, we discuss ongoing efforts, highlighting the challenges for future research on protein delivery.
Triarylboranes have emerged as powerful main-group catalysts for the reduction of organic molecules using a variety of reductants, including molecular hydrogen (H2), hydrosilanes, Hantzsch esters, and ammonia borane. This development has been largely enabled by the extensive structural diversification of triarylboranes, which allows for systematic tuning of the Lewis acidity and steric environment at the boron center. Since the seminal review of this area more than a decade ago, the field has undergone remarkable growth, prompting this comprehensive account covering three key directions: (1) triarylboranes that, unlike conventional B(C6F5)3, remain catalytically active in the presence of Lewis bases such as H2O, CO2, and CO, enabling the use of pure or crude H2; (2) diverse organic reductants, including ammonia borane, Hantzsch esters, cyclohexadienes, and other hydride donors; and (3) mechanistic insights into reductant activation and stereocontrol. Covering advances from 2016 to 2025, this review discusses innovations in borane design, substrate scope, functional-group tolerance, and mechanism across each reductant class. By unifying these related yet independent developments, it aims to provide synthetic chemists and theoreticians with timely insights into triarylborane-catalyzed homogeneous reductions, highlighting main-group catalysts as sustainable, practical alternatives to precious-transition-metal systems.
Single-atom catalysts (SACs) have emerged as a rapidly advancing frontier in heterogeneous catalysis because of their unique electronic structures, maximized atomic efficiency, and tunable catalytic properties. Increasing evidence shows that SACs are inherently dynamic under working conditions with their coordination environment, electronic structure, and spatial configuration continuously adapting in response to reactants, intermediates, or external stimuli. These dynamic properties critically influence catalytic activity, selectivity, and stability, challenging conventional design paradigms and opening new opportunities for performance optimization. This review provides a comprehensive overview of the active-site evolution in SACs under reaction conditions. We discuss the fundamental mechanisms underlying atomic migration, coordination changes, and reaction-induced interconversion of desaturated single-atom states. We also highlight strategies to harness and control these processes through support engineering and coordination modulation, enabling the rational design of desaturated active sites. Finally, we outline major challenges and future directions, including the use of in situ/operando characterization, multiscale modeling, and machine learning, to accelerate the rational design of high-performance SACs. By elucidating the fundamental aspects of SAC active site evolution, this Review provides critical insights and design principles to advance the development of high-performance SACs.
Expanding the chemical and structural diversity of polycyclic aromatic hydrocarbons (PAHs) represents a significant aspirational goal in organic chemistry, materials science, and chemical biology, as it enables precise modulation of their molecular properties for a wide range of applications. Conventional approaches to PAH diversification typically rely on lengthy multistep sequences involving prefunctionalized aromatic substrates and strong oxidants, which limits efficiency and substrate generality. In contrast, retrosynthetic disconnection strategies based on cycloaddition-cycloreversion (retro-cycloaddition) or cycloaddition-rearomatization processes offer a conceptually distinct and streamlined approach to PAH construction and modification. These methods enable atom- and step-economical transformations directly from simple, unfunctionalized PAH templates, thereby circumventing the need for preinstalled functional groups. Recent advances have demonstrated that such disconnection strategies enable diverse transformations, including regioselective PAH growth via bay-, M- and L-region annulative π-extension (APEX) reactions, K-region aza-APEX reactions, formal C-H amination, ring-expansion through dearomative atom insertion, and π-extension via two-carbon fragment exchange. This review summarizes these developments and highlights the emerging potential of cycloaddition-based retrosynthetic logic as a unifying platform for the diversification and molecular editing of PAHs.
In oxic environments, the stable form of manganese is an insoluble MnO2 mineral. However, the uncatalyzed oxidation of soluble Mn(II) is very slow. Consequently, this oxidation, a key part of the global manganese cycle, is largely under biological control, being carried out by bacteria and fungi. Dormant spores of many Bacillus species employ multicopper oxidase enzymes (MCOs) that use oxygen directly to oxidize Mn(II) and form MnO2 minerals. This presents a biochemical conundrum, because MCOs work through single electron transfers from their substrates, whereas conversion of Mn(II) to MnO2 is a 2-electron oxidation, involving one-electron steps with high kinetic barriers due to high reduction potentials. How is this accomplished? Expression and purification of the first bacterial manganese oxidizing MCO complex Mnx created a new chapter in the field of inorganic biochemistry: protein-controlled manganese biomineralization. This review documents the history of genetic studies in Bacillus sp. that led to production of the enzymatic complex Mnx responsible for Mn biomineralization. Biochemical and cryoelectron microscopy structural studies then showed how Mnx has solved the problem of high kinetic barriers to Mn oxidation by exploiting the stabilizing effect of hydroxo- and oxo-bridging in binuclear Mn complexes in all three oxidation states, II, III, and IV. We offer an outlook for future directions of manganese biomineralization research, connecting it to broader quests in the fields of geochemistry and geomicrobiology.
Halide perovskites are emerging semiconductor materials that can be synthesized from solution at a low cost. Recently, they have garnered significant attention for radiation detection applications owing to their incorporation of high atomic number elements, which enable efficient attenuation of photons and particles. Substantial progress has been made in leveraging perovskite semiconductors for radiation detection and imaging, although significant challenges remain. This Review uniquely addresses current gaps by providing a comprehensive analysis of characterization protocols, radiation-induced damage mechanisms, and self-healing behaviors in perovskite-based detectors. We critically evaluate the impact of beam calibration, ion migration, and air ionization artifacts on performance metrics such as sensitivity and detection limits, factors that have often been overlooked in prior reviews. Furthermore, we explore the radiation hardness of perovskite architectures under high-energy photon and particle exposure, offering insights into their operational reliability in extreme environments. To overcome current limitations, we highlight emerging material systems, including hybrid metal chalcogenides, MXenes, and metal-organic frameworks, which demonstrate enhanced stability, reduced toxicity, and multifunctionality. By integrating these perspectives, this Review establishes a foundation for advancing perovskite radiation detectors toward robust, scalable, and application-ready technologies.
Mass spectrometry imaging (MSI) is a tool-of-choice for mapping and understanding the spatial organization of biomolecules, including small metabolites, lipids, peptides, and many others. As the MSI instrument and spatial biology inquiries evolve, researchers and practitioners are constrained by the inherent trade-offs in spatial resolution, chemical detail, and acquisition time. Here, we review how the rapidly growing interplay between MSI and machine learning/artificial intelligence (ML/AI)-powered computational approaches is addressing these issues. We begin by highlighting key steps in MSI experiments and summarizing major ML/AI paradigms in the context of MSI data, providing a foundation to review how ML/AI impact each step in the MSI workflow, starting with methods to accelerate data acquisition. We then discuss emerging applications of dimensionality reduction, segmentation, and various supervised/unsupervised learning approaches to extract useful chemical insights from high-dimensional MSI data. Approaches to leverage multimodal imaging to guide the acquisition process or provide a more informative integrated analysis are discussed. We conclude with a forward-looking discussion on the state of computation and MSI, spanning ML-enabled instrumentation, scaling measurements to 3D and large cohorts, and the integration of MSI with other spatial omic data.
Lipid bilayer membranes are essential cellular permeability barriers that strictly limit the passage of polar molecules and macromolecules, thereby compartmentalizing cellular biochemistry and limiting the accessible chemical space for therapeutics. Membrane-traversing peptides (MTPs) are a diverse group of peptides defined by the ability to traverse synthetic or cellular membranes without causing permeabilization and without the assistance of specific transport proteins. These peptides fundamentally defy classical thermodynamic models of membrane permeability as they can cross lipid bilayers and deliver large polar cargoes, including peptides and proteins, into cells, despite having high net charge and low hydrophobicity. In this review, we challenge the idea of single, discrete mechanisms to describe how peptides traverse membranes and define a broad mechanistic landscape shaped by the conserved properties of MTPs and the unique physical chemistry and polymorphic phase behavior of lipid bilayers. We describe experimental assays and model systems that can be used to study MTP translocation and cargo delivery in synthetic systems and living cells. We use information obtained from comprehensive databases to consider the shared physical chemical space of MTPs. We also discuss key unanswered questions regarding mechanism, specificity, endosomal escape, and in vivo performance. Finally, we discuss illustrative examples and emerging translational applications of MTPs in intracellular drug delivery and molecular therapeutics. Together, these perspectives underscore the dual importance of MTPs as probes for fundamental biophysical studies of cell membranes and as promising tools to expand the universe of druggable intracellular targets.
Macrocycles and medium-sized rings have myriad uses in various applied fields. Effective and scalable methods for their synthesis are therefore of high value. Ring expansion reactions are important in this context, as they allow larger rings to be "grown" from more easily accessible smaller ring systems, while avoiding inefficient end-to-end cyclization reactions. This review is focused on successive ring expansion strategies, in which two (or more) ring expansion steps have been performed in sequence to enable the synthesis of functionalized macrocycles and medium-sized rings.
Aberrant O-glycosylation is a prominent feature of cancer and contributes directly to multiple hallmarks of malignant transformation. Cancer-associated O-glycans include both truncated structures that are unique to mucin-type O-glycosylation and more elongated terminal motifs that function as ligands for glycan-binding proteins. Instead of representing a simple binary change from elongated to truncated structures, it is increasingly understood that these glycans decorate the cancer cell surface with a heterogeneous pattern of truncated, elongated, capped, and partially processed glycoforms, which coexist even on individual proteins and within the tumor glycocalyx. Functionally, truncated aberrant O-GalNAc glycans, such as Tn, STn, and T perturb epithelial differentiation, barrier integrity, signaling, and immunosuppression through interactions with glycan binding receptors, such as Siglecs and MGL. In addition, more elongated O-glycans, including Lewis antigens, interact with selectins promoting metastasis and cellular trafficking. Moreover, individual GalNAc-transferase isoenzymes, governing site-specific O-glycosylation, are emerging as context-dependent regulators of oncogenic processes through glycosylation of selected proteins. These observations establish cancer-associated O-glycans as context-dependent molecular drivers of tumor progression and promising therapeutic entry points. In this review, we discuss the expression, regulation, and functions of cancer-associated O-glycans, their roles in glycan-binding protein biology, and emerging therapeutic strategies that may enable a new generation of glycan-directed precision treatments in oncology.
Bioelectric phenomena in biological materials arise from intricate molecular structures and hierarchical organizations, resulting in diverse electrical properties. Understanding the structure-function relationship at each hierarchical level is crucial for elucidating these mechanisms. A multidisciplinary approach combining advanced experimental tools and computational simulations helps bridge the gap between observation and theory. Crystallographic studies highlight the importance of lattice symmetry in classifying electrical characteristics, playing a significant role in understanding bioelectricity. Investigating the electrical properties of biological building blocks, including amino acids, peptides, proteins, tissues, and viruses, reveals significant insights. These biological components exhibit diverse electrical behaviors due to their unique structural arrangements. Understanding these phenomena from the nanoscale to the macroscale is essential for comprehending bioelectricity and developing biomedical and wearable devices. This review provides insights into bioelectricity by discussing the bioelectrical properties of biological building blocks, categorizing their hierarchical structures, and analyzing their underlying mechanisms. Our review will clarify the relationship between fundamental structures and bioelectrical properties, and provide insights for designing novel biotechnologies and future applications.
Abstract Proton-conducting reversible solid oxide cells (P-RSOCs) are emerging as a transformative platform for efficient and flexible conversion between electricity and chemical fuels, including hydrogen and syngas. Their intermediate-temperature operation (400–600 °C) offers a compelling combination of high energy efficiency, rapid reaction kinetics, and strong compatibility with renewable electricity and industrial waste heat, positioning P-RSOCs as a promising technology for a carbon-neutral energy future. At the heart of these devices lies the proton-conducting electrolyte, which governs proton transport, chemical stability, interfacial compatibility, and long-term durability. Despite remarkable advances in electrolyte development, fundamental challenges in understanding and controlling proton transport, chemical stability, and electrode-electrolyte interactions continue to constrain practical deployment. This review presents a comprehensive and critical assessment of the current state of proton-conducting electrolytes for P-RSOCs, with emphasis on proton transport mechanisms, composition–structure–property relationships, stability limitations, and interfacial compatibility. We examine advances in perovskite-based and emerging alternative electrolyte families, while highlighting key strategies─including aliovalent doping, interfacial engineering, microstructure design, and advanced fabrication─for overcoming persistent limitations. Emerging operando characterization and computational approaches are further discussed as powerful tools for uncovering dynamic transport and degradation mechanisms and accelerating materials discovery. By integrating fundamental insights with materials-design strategies, this review identifies critical knowledge gaps and opportunities to guide the development of robust, high-performance electrolytes. Ultimately, we envision that such advances will help unlock the full potential of P-RSOCs as a versatile platform for sustainable energy conversion, storage, and renewable-fuel production.
Abstract This review aims to integrate advancements in the rational design of Cu nanoclusters (NCs) from the past decade. Atomically precise Cu NCs have emerged as promising materials for highly active catalysis, due to their low cost and high efficiency as well as well-defined structures. The absolute monodispersity of Cu NCs provides direct insights into fundamental catalytic research, including the identification of active sites, the establishment of structure–activity relationships at atomic level, the modulation of metal-kernel structures and ligands for selectivity, and the exploration of catalytic mechanisms. In this review, we summarize strategies for developing Cu NC catalysts, including ligand engineering, oxidation state modulation, heteroatom doping, and theoretical prediction. Subsequently, we sum up the fast-growing advances of Cu NCs catalysts in terms of catalytic activities, identification of active sites and fundamental mechanisms. The catalytic applications mainly involve electrocatalysis, photocatalysis, and organic transformations. Finally, we provide comprehensive commentaries on the challenges and future perspectives in rational design of Cu NCs and its commercialization as catalysts.
Ammonia (NH3) plays a crucial role in the agricultural sector as a fertilizer and is a dense hydrogen carrier that offers a potential renewable and carbon-free energy source. These significant advantages necessitate the development of efficient NH3 synthesis and separation systems. Conventionally, the Haber-Bosch (HB) process involves synthesis at high temperature (>673 K, 100-200 bar) and separation of NH3 from the equilibrium-limited reaction mixture through condensation at low temperatures. Among various alternative NH3 separation techniques, adsorption approaches in porous solids have been investigated as a potentially more energy-efficient method. However, identifying the optimal porous materials for reversible NH3 separation with high NH3 capacity remains challenging. This review discusses the potential of porous solid adsorbents, such as zeolites, metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs), porous organic polymers (POPs), carbons, and their composite materials with NH3 absorbents like ionic liquids and metal halides, for NH3 separation and other potential uses like storage and sensing. The review also discusses active sites for adsorption, and adsorbent structural and mechanical properties. It also emphasizes NH3 selectivity over N2 and H2, highlighting the solid sorbent's reversibility, stability, and regeneration conditions. Future directions for NH3 adsorption research are highlighted.
Viral outbreaks such as SARS-CoV, MERS-CoV, and COVID-19 underscore the urgent need for rapid, sensitive, and scalable diagnostic technologies. Current standard methods, including nucleic acid amplification tests and immunoassays, offer complementary strengths but face limitations in cost, turnaround time, and early-stage detection. Surface-enhanced Raman spectroscopy (SERS) has emerged as a promising alternative, leveraging plasmonic nanostructures to amplify weak Raman signals and provide molecular "fingerprints" of viral components with single-molecule sensitivity. This review provides a comprehensive overview of SERS-based virus detection, highlighting the fundamental principles of Raman enhancement, the role of substrates and hotspots, and analyte-specific challenges. We categorize sensing strategies into direct detection of intact viruses and components, affinity-based approaches using antibodies, aptamers, or viral receptors, and labeled methods that amplify specificity and multiplexing. Advances in nanofabrication, receptor engineering, and machine learning have significantly improved sensitivity, reproducibility, and classification accuracy, with detection limits reaching down to a few viral particles per milliliter. Despite these advances, challenges remain in handling biological complexity, ensuring reproducibility, and translating assays into clinical practice. We conclude by outlining opportunities for integrating SERS with portable devices, standardized spectral libraries, and artificial intelligence, paving the way toward rapid, robust, and deployable viral diagnostics for future pandemic preparedness.
Artificial intelligence (AI) is fundamentally transforming materials discovery, shifting the paradigm from labor-intensive trial-and-error approaches to data-driven, automated workflows. This review examines emerging AI methodologies for accelerated materials discovery, with particular emphasis on how computational design, data infrastructure, synthesis planning, and autonomous experimentation can be connected into experimentally grounded workflows. We begin by surveying generative models for inverse materials design, tracing the evolution from early variational autoencoders and generative adversarial networks to recent diffusion models, Bayesian flow networks, flow-based architectures, transformer-based methods, and large language model-driven approaches for the de novo generation of crystalline materials with targeted properties. We then discuss physics-informed and data-efficient AI strategies that incorporate domain knowledge to enhance the model generalizability and robustness in low-data regimes. The emergence of multimodal foundation models, which integrate heterogeneous data modalities including crystal structures, text, and spectroscopic information into unified representations, is examined as a key enabler for cross task generalization. We further review AI-driven synthesis planning algorithms and autonomous self-driving laboratories that bridge the persistent gap between the computational design and experimental realization. Critical infrastructure challenges, including database limitations, FAIR data principles, and knowledge-graph construction, are also addressed. By highlighting both demonstrated capabilities and persistent limitations, this review aims to guide the reliable application of AI toward materials discovery workflows that connect candidate generation, synthesis feasibility, experimental feedback, and data provenance.
Aerosol particles, profoundly influenced by human activities, play pivotal roles in air quality and climate. The formation and growth of new atmospheric particles is a leading source of high-concentration aerosol particles in urban environments and also the largest source of uncertainties in global climate predictions. Recent advances in experimental and theoretical research have dramatically improved our understanding of urban new particle formation (NPF), showing that the abundant anthropogenic pollutants in complex urban atmospheres enable the fast formation of new particles that are highly selective toward the gaseous precursors and chemical processes. The uniqueness of urban atmospheres causes the underrepresentation of urban NPF in regional and global models, while the evolving urban environments complicate the prediction of future environmental and climate effects of NPF. In this review, we link the latest molecular-level chemical mechanisms and implications on climate predictions and air pollution control by assessing the methodology to investigate urban NPF, sorting out the latest mechanistic findings, and discussing their implementation in three-dimensional models.
Higher-order cycloadditions, defined as pericyclic reactions involving more than 6π-electrons, have emerged as powerful and mechanistically diverse reactions that allow for the construction of larger and more complex polycyclic ring systems beyond the classical Diels-Alder reaction. This review provides a comprehensive overview of the development, scope, and fundamental principles governing higher-order cycloadditions involving 8π-18π-electrons. Key advances in transition-metal-, Lewis-acid-, organo-, and enzyme-catalyzed higher-order cycloadditions are highlighted with emphasis on how modern catalyst design enables control over periselectivity and stereoselectivity. Mechanistic insights from density functional theory, molecular dynamics, and experimental reaction designs are discussed to illustrate how higher-order cycloadditions challenge and refine modern pericyclic theory. Together, these developments showcase the growing synthetic and conceptual significance of higher-order cycloadditions in modern chemistry.
