As a green,low-carbon,clean and efficient secondary energy source,hydrogen energy is an ideal choice for matching large-scale renewable energy and an important technological path to promote low-carbon energy transformation.The full industrial chain of hydrogen energy includes hydrogen production,storage and utilization.Hydrogen energy storage refers to the production of green hydrogen by reducing protons in water with green electricity or the production of hydrogen-containing compounds by reducing small molecules such as CO2 with green electricity.The conversion of hydrogen to electricity occurs through electrochemical reactions in relevant electrolytic cells or batteries,and the energy efficiency is closely related to the efficiency of the electrocatalytic processes in these electrochemical devices.This review focuses on the key electrochemical technologies of hydrogen energy,and based on the chemical changes of hydrogen elements,it is divided into three main processes in hydrogen electrochemistry,i.e.,electrochemical hydrogen production represented by electrolysis of water,electrochemical hydrogen storage represented by carbon dioxide and nitrogen electroreduction,and electrochemical hydrogen utilization represented by hydrogen fuel cells.Starting from the basic principles of electrochemistry,this short review covers the design concepts,related frontiers,and challenges of key electrocatalytic materials required for electrochemical hydrogen production,storage,and utilization.
The petrochemical industry serves as a cornerstone of the national economy and the transformation of hydrocarbon separation and conversion processes is particularly crucial.Utilizing membrane technology to remove specific molecules,enhance mass transfer,or intensify reaction processes holds promise for improving petrochemical process efficiency aligning with China's"Dual Carbon"strategic goals.Advanced inorganic microporous membranes,represented by metal-organic frameworks and zeolite molecular sieves,serve as a key approach for achieving efficient separation of hydrocarbon molecules.However,the cost issue associated with the large-scale production of microporous membranes still needs to be addressed.Integrating membrane separation with reaction processes to construct catalytic membrane reactors can break the thermodynamic equilibrium limitations of reactions,offering a promising solution to problems such as excessively long reaction processes and low efficiency in alkylation and epoxidation.Nevertheless,numerous challenges remain in the coupling mechanisms between membranes and catalysts,as well as in their stability.In the future,AI-driven design of membrane materials and processes,multi-source characterization to reveal cross-scale mass transfer mechanisms,and membrane-based process innovations in hydrocarbon separation and conversion will strongly promote the low-carbon restructuring of petrochemical processes,fostering high-quality development in the industry.
In today's increasingly intense global competition in science and technology,the fabrication of materials and devices with atomic precision has risen to the forefront of technological development.At the microscopic scale,the physical properties of materials are highly sensitive to subtle variations in their internal structures and atomic arrangements at boundaries,where quantum effects become particularly pronounced.In carbon-based systems,the extremely weak spin-orbit coupling and the highly delocalized π orbitals render carbon nanostructures highly promising candidates for magnetic quantum information materials.Leveraging the advantages of surface physics and chemistry to achieve the precise on-surface synthesis of carbon-based quantum magnets,the controlled manipulation of radicals,as well as the exploration and regulation of their electronic and spin states in interaction with the environment through multi-parameter probes,has become a fiercely competitive frontier of contemporary scientific research.Based on the 417th"Shuangqing Forum"organized by the National Natural Science Foundation of China(NSFC),this paper summarizes the current status,development trends,and opportunities and challenges in the study of carbon-based quantum magnets,and distills key research priorities and pressing scientific questions that need to be addressed in the future.
The precise synthesis and characterization of novel molecular carbon materials,such as cyclic and linear carbons,represent a forefront area of international scientific research and are closely related to major national strategic demands in fields such as advanced semiconductor materials and molecular electronic devices.Studies have shown that subtle differences in atomic-scale structures can lead to markedly distinct electromagnetic properties.To probe the intrinsic physicochemical properties of these carbon materials,precise synthesis is a prerequisite.However,due to their extremely high chemical reactivity,achieving atomic-level precision in the synthesis and characterization of molecular carbons remains a major challenge in the field.In recent years,on-surface synthesis methods—particularly tip manipulation techniques and high-resolution imaging enabled by scanning probe microscopy—have provided a powerful platform for constructing and characterizing these highly reactive carbon structures with atomic precision.This paper systematically summarizes recent advances in the on-surface synthesis of novel molecular carbon materials,with a focus on the synthetic pathways,structural analysis,and electronic characterization of linear and cyclic carbons.Finally,the challenges and future directions of this field are discussed,including large-scale synthesis,the construction of complex structures,property modulation,and potential applications.
Magnetic single atoms and single molecules on surfaces provide an important material platform for building spin qubits,quantum computing and quantum simulation.In particular,recent rapid progress in on-surface synthesis and the emergence of carbon-based quantum magnets offer possibilities for constructing large-scale arrays of spin qubits.In order to detect and control single-spin qubits,it is urgent to develop electron spin resonance based on the scanning tunneling microscopy(ESR-STM).This review aims to introduce the current progress of ESR-STM in the quantum sensing,quantum control,and quantum simulation of single surface magnetic atom spins,the coherent control of atomic spin-based multi-qubit platforms,the detection and coherent control of quantum states of surface magnetic molecules,and the detection of delocalized π-electron spins in single charged organic molecules.By summarizing the capabilities and limitations of ESR-STM for constructing and detecting single-spin qubits and multi-qubit systems,we propose new routes for creating qubits and qubit arrays based on on-surface synthesized quantum magnets,which lay a solid foundation for realizing spin-qubit-based quantum computing model devices.
Graphene nanoribbons(GNRs)have been predicted to exhibit tunable semiconductor behavior and intrinsic magnetism due to their unique quantum-limited domain effects and edge-state properties,which have shown promising applications in nanoelectronics,spintronics and quantum computing.However,conventional"top-down"preparation methods face severe challenges in realizing GNRs with widths less than 10 nm and atomically precise edges.In this review,we focus on the design and atomically precise synthesis of magnetic GNRs using a bottom-up strategy,and systematically describe the surface-assisted synthesis of armchair graphene nanoribbons(AGNRs)and zigzag graphene nanoribbons(ZGNRs),with a special emphasis on how to overcome the difficulties inherent in the synthesis of ZGNRs to obtain purely serrated edges.In addition,we will provide insights into the technological pathways to stabilize and characterize magnetic edge states through nitrogen(N)atom doping and functionalization with nitronyl nitroxide radicals(NIT).The innovative Janus GNRs(Janus graphene nanoribbons,JGNRs)design scheme,whereby a unilateral ferromagnetic ground state is achieved by introducing structural asymmetry,will also be presented.Finally,this review will summarize the key performance characterization techniques for magnetic GNRs and look into the future challenges and opportunities in mitigating substrate interactions,enabling large-scale preparation,enhancing device integration,and exploring novel functionalization strategies.
On-surface carbon-based quantum magnets have emerged as a promising platform for quantum information technologies due to their spatially delocalized spin states and high tunability,attracting significant research interest in recent years.This review systematically examines the theoretical challenges and recent advances in this field.We begin by outlining the strategic importance and development trends of surface quantum magnets,highlighting the paradigm shift from localized to delocalized magnetic interactions in carbon-based systems.We then identify three key scientific challenges:accurate computation of strongly correlated electronic structures,precise characterization of spin spatial distributions,and predictive modeling of dynamic responses under external fields and environmental influences.The review summarizes established theoretical methodologies,including AI-assisted high-level density functional theory,cluster-model-based scanning tunneling microscopy simulation,and first-principles quantum dissipative dynamics approaches,demonstrating their applications through representative case studies utilizing our in-house software platforms(REST and QUICK).Finally,we prospect future research directions,proposing that integrated development of precise electronic structure methods,spectroscopic imaging techniques,and non-equilibrium quantum dynamics simulations,combined with versatile computational platforms,will enable rational design of on-surface carbon-based quantum magnets and accelerate the development of quantum functional devices and platforms.
The rapid development of Generative Artificial Intelligence(GenAI)has exerted a broad and far-reaching influence on disciplines that rely heavily on data as a core research input.Against this backdrop,this paper investigates the transformation of financial research under the impact of GenAI from the dual perspectives of paradigm transformation and theoretical extension.Using a bibliometric approach that integrates semantic clustering with large language models,this study provides a comprehensive overview of how GenAI has spread within financial research.From the standpoint of research paradigms,this study analyses the roles of GenAI in data synthesis,hypothesis generation and simulation-based validation,and identifies both the new research opportunities it creates and the methodological risks it entails,including bias amplification,logical hallucinations and opacity.From the perspective of theoretical extension,the paper discusses how GenAI supports the expansion and deepening of core frameworks related to information asymmetry,behavioral finance and corporate governance.Finally,this study highlights four key directions that warrant further investigation:enhancing methodological reliability,strengthening causal identification,examining behavioral patterns under human-AI collaboration and improving the conceptualization of AI-related risks in finance.
In recent years,continuous advances in on-surface synthesis have led to the emergence of carbon-based quantum materials with rich structures and precisely tunable properties.The novel physical behaviors exhibited by carbon-based quantum materials—such as nontrivial topology,quantum magnetism,and strong electronic correlations—provide abundant material platforms for future spintronics,quantum computing,and quantum information science.Because these materials possess atomic-level precision as well as structurally complex and variable motifs,and because their electronic and spin states are easily influenced by the surrounding environment,multi-domain detection and global analysis of their properties become particularly important.This paper focuses on cutting-edge characterization techniques for on-surface synthesized carbon-based quantum materials and reviews advances in the ex-situ macroscopic characterizations and the in-situ microscopic characterizations.Emphasis is placed on new spectroscopic and spectrographic methods integrated with scanning probe microscopy to explore,across spatial,energetic,and temporal dimensions,the chemical structure,electronic states,vibrational modes,spin states,and their dynamics in carbon-based materials.We also point out future trends in constructing carbon-based spin qubits,integrating comprehensive measurement platforms,and ensuring device environmental compatibility,thereby further expanding the application prospects of carbon-based quantum materials.
Quantum sensing is driving the chemical and biological measurements into a new era.This paper systematically introduces the underlying logic and representative systems of quantum chemical measurements.Quantum chemical measurement employs the superposition or entanglement of quantum systems—such as electrons,photons,atoms,and molecules—as probes.These probes are initialized,manipulated,and read out via optical and microwave techniques,enabling the transduction of physical-field signals generated by chemical and biological systems into precisely decodable quantum signals,and thereby allowing in situ,real-time,and high-precision measurement and imaging.This interdisciplinary direction achieves a deep integration of quantum physics,analytical chemistry,and biological physics,signifying a profound transformation of chemical metrology from classical measurements to quantum sensing.
Traditional single-target,single-molecule therapies have shown clear limitations in the treatment of complex diseases,often yielding insufficient efficacy and rapid resistance.Increasing evidence indicates that such diseases are driven by the coordinated dysregulation of multiple signaling pathways,making combination strategies an essential approach.Clinically,rationally designed combinations have demonstrated significant benefits:Dual BRAF/EGFR inhibition enhances objective response rates through synthetic lethality,SHP2/MEK co-inhibition overcomes KRAS mutation—driven resistance,and PD1/CTLA4 blockade markedly prolongs survival in metastatic melanoma.Advances in artificial intelligence(AI)are accelerating combination drug discovery.Leveraging large-scale databases such as DrugComb,predictive models like XGBoost achieve high accuracy(AUROC 0.83 across 22 000 samples),while systems such as DECREASE reduce experimental dose—response testing by over 80%without compromising precision,substantially lowering time and cost.Beyond multi-target applications,innovative strategies are also emerging at the single-target level.For example,orthosteric—allosteric dual-site modulation of PPARγ synergistically enhances efficacy while mitigating side effects,offering new directions for metabolic disease interventions.Immunotherapy has become a leading clinical frontier,with nearly half of approved immune checkpoint inhibitor indications involving combination regimens—either with chemotherapy,targeted therapies,or dual checkpoint blockade—underscoring the value of immune co-regulation.Looking forward,the development of combination therapies requires multidisciplinary integration.Knowledge graph—based approaches can uncover novel synergistic mechanisms,while multi-omics—driven computational platforms combining structural biology,pharmacology,and clinical data will enhance model generalizability.Addressing challenges such as data heterogeneity and limited interpretability through standardized frameworks will be critical for translation from high-throughput prediction to mechanistic insight.The convergence of AI and experimental medicine promises to shorten development cycles,reduce clinical attrition,and drive the evolution of combination drug discovery toward a precision-and mechanism-based paradigm.
The development of therapeutics for central nervous system(CNS)disorders is markedly lagging behind other disease areas,characterized by an exceptionally high failure rate in late-stage clinical trials.This review addresses the central challenge of creating effective combination therapies for complex CNS diseases,where single-target agents often fall short.We propose a shift from traditional empirical methods towards a rational design paradigm and explore three key enabling strategies.First,we discuss modernizing Traditional Chinese Medicine(TCM)formulations by applying multi-omics and artificial intelligence to deconvolute their multi-component,multi-target mechanisms,thus transforming them into a source for rational drug combination discovery.Second,we highlight the role of stimuli-responsive nanocarriers in achieving spatiotemporally controlled drug delivery,which allows for targeted and sequential drug release in response to the dynamic disease microenvironment.Finally,we examine how large-scale biomedical data and patient subtyping can inform the development of personalized combination regimens.Integrating these approaches,from deciphering ancient formulations to deploying advanced delivery systems and leveraging big data,presents a promising path to accelerate the development of effective,rationally designed combination therapies for CNS diseases.
Bispecific antibodies with combined targets can recognize two or more epitopes on the same or different targets.This field has undergone a gradual evolution from initial attention to bispecific antibodies to the approval of BiTE(bispecific T-cell engager)therapy by the U.S.Food and Drug Administration(FDA),achieving significant progress over the past two decades.Owing to advancements in protein engineering technologies and great efforts in preclinical research,bispecific antibodies have been continuously developed and optimized to improve their efficacy and to reduce toxicity.This article focuses on the current development challenges,potential solutions,and future directions of bispecific antibodies in anticancer therapy.
The 2023 Central Financial Work Conference highlighted the importance of five key areas of finance—technology finance,green finance,inclusive finance,pension finance,and digital finance—as the core components of building a strong financial system.At its essence,finance functions as a market mechanism.Advancing these five key areas requires moving beyond the traditional"risk-return"paradigm and innovatively designing mechanisms that endogenize the social functions of financial services,thereby incorporating social benefits such as technological innovation,green development,and common prosperity into the institutional framework.This paper,drawing on major national priorities and the frontiers of academic research,proposes the basic principles and a preliminary theoretical framework for institutional development in these five areas.It systematically reviews the practical challenges and institutional issues in each of the five areas and identifies the corresponding fundamental scientific questions.Given the complexity of the financial system,institutional design across these areas constitutes a systems-level project involving wide-ranging and demanding scientific challenges.Advancing research in these areas will support the development of a new financial system that integrates market efficiency with social value.
Natural medicines,embodying millennia of clinical practice,represent one of the key strategic resources for addressing major health challenges.Natural product-derived therapeutics,particularly Traditional Chinese Medicine formulas,exhibit distinct advantages in the prevention and treatment of chronic complex diseases owing to their multi-component,multi-target,and multi-process regulatory features,and thus hold substantial promise for establishing new therapeutic systems for chronic complex diseases.Leveraging China's abundant natural medicinal resources,the systematic development of a theoretical and technological framework with indigenous characteristics is of major strategic importance for the future of the national biopharmaceutical industry.In this context,this article focuses on the development of natural product-derived multi-target combination drugs and discusses their principal characteristics,mechanistic basis,integrative effects,and development pathways.The aim is to build an independent innovation system rooted in China's natural medicinal resources and the strengths of Traditional Chinese Medicine,thereby providing insights and references for transforming and advancing new drug discovery paradigms.
Current research is expanding toward the extremely macroscopic,delving into the extremely microscopic,advancing toward extreme conditions,and making efforts in highly integrated and cross-disciplinary fields,continuously pushing the boundaries of human cognition.Focusing on the development needs of major equipment for exploration in extreme environments from the deep sea,deep space,deep earth,deep cavities,and polar regions named the'Four Depths and One Pole',the forum engaged in in-depth discussions on the basic research of physical intelligent system(PIS).PISs in extreme environments need to achieve autonomous and collaborative operations under extreme conditions such as ultra-high pressure,large temperature variations,and strong interference.This involves the core content of the collaborative design of materials-structure/mechanism-function of physical intelligent structure;autonomous perception-drive-control-self-healing mechanisms;the foundation of artificial intelligence(AI)models under scarce data conditions;trusted communication and swarm intelligence;and system-level verification in extreme environments.This paper systematically reviews the status,development trends,and challenges of PIS in typical extreme application scenarios.Based on the characteristics of structural mobility,intelligence of the body,intelligent analysis of the environment,and multi-system collaboration,it further distills the key scientific issues of PIS in terms of the tolerance of intelligent structure bodies,the robustness of individual intelligent systems,and the stability of collaborative intelligent systems.This paper also explores the frontier directions of the development of PIS in extreme environments.
