Based on the evolutionary law of the 50−year long−wave cycle of the world economy, this paper focuses on the core engine of the fifth long−wave cycle—the integrated circuit (IC) industry. It systematically sorts out the development history, current status of the industrial system, and global competitive pattern of China's IC industry from the "6th Five−Year Plan" to the "14th Five−Year Plan" periods. By analyzing the development achievements in key links such as electronic design automation (EDA), design, manufacturing, packaging and testing, equipment, materials, and memory, the paper identifies China's breakthroughs in chip autonomy in national security−related fields and the phased achievements of multiple enterprises ranking among the top 10 in relevant global fields. Meanwhile, it deeply analyzes the industry's existing problems, including homogeneous competition and internal friction caused by "small scale, dispersion, and weakness", lack of fault tolerance and trial−and−error mechanisms between upstream and downstream enterprises, imperfect data statistics and industrial standards, and insufficient transformation of "national efforts" into practical actions. Combined with the development trends of integrated circuits in the post−Moore era—extending Moore's Law, expanding Moore's Law, transcending Moore's Law, and enriching Moore's Law—the paper proposes that during the "15th Five−Year Plan" period, efforts should be made to build leading enterprises, improve coordination mechanisms, increase targeted investment, strengthen basic research, deepen international cooperation, and optimize talent training.

This paper provides a comprehensive review of the development, current status and future prospects of Tokamak-type nuclear fusion devices in the world. First, it expounds the advantages of fusion energy compared with other energy sources, such as its high safety, abundant fuel reserves, high energy density, no greenhouse gas emissions like carbon dioxide and environmental friendliness. Subsequently, it focuses on reviewing the historical development of the Tokamak, from the concept's inception in the 1950s to the current construction of the International Thermonuclear Experimental Reactor (ITER). It highlights the renowned tokamak devices that have made significant influential achievements and critical technological breakthroughs in the world, such as those that have validated the scientific feasibility of controlled nuclear fusion, achieved the highest fusion energy gain (Q), set world records for plasma triple products, reached the highest plasma temperatures, or revealed important physical phenomena, mechanisms, and new or advanced operation modes. Next, the paper also examines the critical scientific and technological challenges yet to be resolved for Tokamak fusion reactors, such as fuel cycles, tritium self - sufficiency, and materials issues. Finally, it offers perspectives on the future development direction of Tokamak fusion reactors and the commercialization prospects of fusion energy. This review aims to serve as a reference for the field of nuclear fusion research.

China's science and technology development has entered a critical stage of tackling key challenges and therefore needs to strengthen original innovation. Basic research is the source of original scientific and technological innovation, yet at present China's basic research faces problems such as oversized research teams, homogenized research directions, a lack of core capabilities, and consequently insufficient capacity for original innovation. At the national level, this manifests as team research that is neither specialized nor distinctive and often duplicative, along with an overall pattern that runs counter to diversity. The resulting "resource−driven" research paradigm leads to inefficient use of research resources. As a result, the research ecosystem is degraded, hindering the cultivation and growth of original innovation. This paper argues that, in the realm of basic research, a "small but excellent" paradigm—characterized by small teams that each play to their unique strengths and researchers who are highly specialized and each bring distinctive expertise—has high value for original innovation. Under resource constraints, it can also preserve the overall diversity of national research and the security of the national science and technology chain. Delivering the core value of basic research through rigorous, specialized exploration and original breakthroughs requires each team to focus on a distinctive direction and cultivate it deeply, while team members build deep expertise and tackle hard problems through years of sustained effort. This approach helps foster diversity in the research ecosystem and enables efficient resource allocation, thereby ensuring the resilience of China's scientific and technological development in international competition.

Envisioning the strategic demands for building a modernized powerful nation in 2040 and motivated by the integrated development of new materials, new productive forces, and emerging industries, this manuscript comprehensively analyzes the common requirements of national strategies, relevant policies, and action outlines regarding frontier-disruptive core technologies and critical material development. Based on the advancement and innovation of Materials Genome Engineering's core technologies setting a crucial foundation for key innovations in AI data infrastructure, foundational material models, R&D of new materials, and industrial applications, AI will further accelerate the development of high-throughput intelligent computing software/tools, drive paradigm shifts from high-throughput experimentation to autonomous experimentation, propel the evolution of material AI agents, construct data resource nodes/platforms with standardized specifications, advance new productivity and novel material industries, as well as foster educational paradigm transformation and next-generation talent cultivation. The convergence of Materials Genome Engineering and intelligent science is fundamentally reshaping the underlying logic of material science, technology, and education through a trinity model consisted of ''theoretical reconstruction, technological empowerment, and industrial traction''. This integration represents not merely disciplinary upgrading, but a systematic transformation encompassing scientific paradigms, industrial ecosystems, and talent development models. It will cultivate interdisciplinary professionals crucial for strategic fields such as advanced materials, emerging industries, and future-oriented sectors.

This article focuses on amorphous matters and reviews recent advances in amorphous materials and physics. More recently, more than 30% of the lunar soil collected by China's Chang'e-5 mission was found to be glassy, further confirming the widespread existence of amorphous matter in the universe. Topological order and inhomogeneity may be hidden behind the seemingly chaotic structure of amorphous materials, so amorphous matters have strange genetic, sensitive and relaxation behaviors, and show a series of excellent physical and chemical properties, such as extreme stability, super-plasticity, super mechanical behavior and excellent soft magnetic properties. The new generation of Zr-based and Fe-based amorphous alloys developed based on order regulation and high flux technology are successfully applied to core components such as folding mobile phone hinges and new energy vehicle motors, indicating that amorphous matters have irreplaceable application advantages. The future development of amorphous matters should focus on introducing a new paradigm of material research, attaching importance to the importance of process innovation, promoting the cross-integration of multi-disciplinary fields, giving full play to the advantages of advanced characterization technology and large scientific devices, and creating a whole-chain innovation model for production, university and research, so as to actively promote the rapid development of amorphous materials and physics, and expand the application of amorphous matters in high-tech fields. Make the future of mankind a better place.

介绍了锂离子电池基本构造、工作原理及回收现状。详细阐述了当前研究中正极材料的主流回收方法，综述了废锂离子电池回收技术的研究进展，其中包括回收工艺发展、回收产品、对环境负担的影响，以及电池退役后的选择，如二次利用、直接再生修复电极材料、湿法或火法冶金回收材料等。从电池材料回收率，循环利用再生体系，电解液、隔膜和负极材料等综合回收方面对现有废旧锂离子电池回收处理与再利用技术提出了改进意见。

Deep-sea exploration is a key technology for developing marine resources, studying the evolution of the Earth, and protecting the Earth's ecosystem. This paper reviews the main progress of deep-sea exploration technology in the past seven years (2019–2025), including the fields of submersibles, sensors, communication, energy, etc., and looks ahead to the development trends in the next 5~10 years. Firstly, the importance and challenges of deep-sea exploration are introduced. Then, the current status of technologies in various aspects such as deep-sea submersibles, sensors and observations, sampling and analysis, communication and navigation, energy, as well as big data and artificial intelligence are described in detail. The analysis shows that intelligentization, long endurance, and in-situ experimental technologies will become the core directions, but the adaptability to high-pressure environments, energy supply, and data transmission remain the main bottlenecks. Subsequently, the future development trends such as intelligentization and autonomy, long endurance and energy innovation, and the cost revolution are discussed. It is expected that this paper will play a certain guiding role in promoting the sustainable development of deep-sea exploration technology.

矿产资源的开发和利用是维系现代社会经济发展和人类活动的重要基础。然而，近百年来各类矿产资源的开采和加工产生了大量尾矿矿渣，严重威胁着生态环境和人类社会的可持续发展。如何实现尾矿区的生态重建成为实现可持续矿业的关键。在分析传统尾矿生态修复技术不足的基础上，提出基于土壤发生学原理的尾矿生态修复新策略，即尾矿成土生态工程。具体而言，本策略将尾矿视为成土母质矿物，通过系统性生态工程手段加速成土过程，并逐步将其改造成具有多孔物理结构和化学缓冲特性，能够承载生态功能的稳定类土基质，从而实现对尾矿区的生态重建。尾矿成土生态工程需综合考虑尾矿的特性、本地微生物和植物物种资源及气候条件，因地制宜设计技术路线，构建成套技术体系。最后，基于现有研究进展，提出了尾矿成土的关键基础科学问题和技术应用前景。

智能建造数字化平台作为建筑行业数字化转型的关键支撑，在建筑信息模型（BIM）、云计算和大数据等核心技术的驱动下实现了突破性发展。从相关研究总体特征、相关研究现状和平台案例分析3个维度对2010—2023年的相关研究进行分析。研究发现，BIM技术通过三维可视化建模和全生命周期数据管理构建了平台的基础框架；云计算技术凭借其弹性计算资源和分布式处理能力为平台提供了强大的技术支撑；大数据技术则通过实时数据分析和智能决策优化了工程管理流程。以北京城市副中心项目为例，该平台创新性地采用“环状”数字集成交付模式，整合区块链数据确权技术，实现了政府投资项目设计-施工-运维全过程的数字化协同管理，有效解决了传统工程管理中的“三超”问题。然而当前研究仍存在明显局限，比如应用场景主要集中于单体项目层面，缺乏行业级系统整合；技术标准体系尚未统一，制约了数据互联互通；人工智能等新兴技术的融合应用研究相对不足。未来发展方向应着重于构建产业级集成平台，推动规模化应用；建立统一的技术标准和数据接口规范；深化人工智能、数字孪生等创新技术与传统建造技术的融合应用；探索数据资产交易机制，促进数据要素市场化。

水处理、能源转化和生物医药等领域对高效分离膜的需求日益迫切。无论是海水淡化、电池隔膜，还是人工离子通道，核心都依赖于纳米孔膜对特定离子的精准筛选。科学界长期以来将这种选择性理解为几何作用：水合离子被紧紧包裹在水分子外衣之中，能否通过孔道主要取决于“身体尺寸”与孔径是否匹配。然而，随着纳米孔尺度越来越小，这一解释逐渐显得不足，因为实际观测到的选择性规律往往无法用几何大小简单说明。

2025年8月26日，江门中微子实验（JUNO）成功完成2万t液体闪烁体灌注，并正式运行取数。经过10余年准备和建设，JUNO成为国际上首个运行的超大规模和超高精度中微子专用大科学装置。

分析了激光无线能量传输（laser wireless power transmission，LWPT）技术的基本原理、发展背景及未来应用。该技术基于受激辐射原理，将电能转化为激光能量，经过大气或真空介质传输后，最终由激光电池将光能高效转换为电能，具备高方向性、高能量密度、远距离传输等优势。在低空产业领域，LWPT可为无人机、飞行汽车等提供持续能源补给，显著提升续航能力与作业效率；在商业航天领域，其可为卫星、空间站及深空探测器构建灵活的能量传输网络，支撑长期太空任务。展望未来，LWPT技术与激光通信、卫星遥感定位等技术结合，可实现能源与信息的协同传输，构建交通–信息–能源三网融合的智能化蓝图，推动交通系统向高效化、自动化迈进。这一目标的实现，需依托多行业深度合作与持续技术创新，并同步推进跨领域协同研发及标准规范制定。通过推动该技术的发展，有望催生能源传输领域的革命性变革，为现代社会的发展提供坚实的支撑。

夜幕降临时，几位科学家正乘坐中国载人深海潜水器“奋斗者”号向深渊进发。随着潜水器逐渐下潜，在深不可测的黑暗中，上海交通大学极端环境微生物学家赵维殳瞥见了散发着绿、黄、橙3色荧光的发光生物。抵达万米海底后，研究人员打开探照灯，一片“深邃神秘的蓝色”随即映入眼帘，到处漂浮着形形色色的浮游生物。Weishu Zhao回忆道，“那一刻，我幡然领悟，（深海）一定是一个超乎人类想象的奇特世界”

Drug discovery, as the core driving force of the modern pharmaceutical industry, faces the difficulty of the traditional model's "high investment, long cycle, and low output, " urgently requiring breakthroughs to address increasingly complex health demands. The rapid development of artificial intelligence (AI) technology has brought revolutionary changes to drug discovery, significantly enhancing efficiency and success rates in areas such as protein structure prediction, protein design, antibody drug design, and small molecule drug development. This article focuses on the domestic and international progress of AI in these key domains, providing an in-depth analysis of AI breakthrough in protein structure prediction and its potential applications in target discovery and virtual screening. It explores the closed-loop model of AI-driven protein design, from structure prediction to functional innovation, and examines AI's role in antibody sequence optimization, affinity maturation, and novel antibody design. Additionally, it reviews the latest achievements of AI in small molecule drug target identification, virtual screening, and ADMET optimization. The article also highlights challenges in AI applications, including data quality, model interpretability, and experimental validation, while envisioning future directions such as multimodal data integration, dynamic behavior prediction, and automated platforms. By comprehensively analyzing the current state and challenges of AI-enabled drug discovery, this article aims to offer scientific perspectives and insights to accelerate new drug creation and enhance human health and well-being. It seeks to provide readers with a thorough and insightful view of technological issues in AI-empowered drug discovery, stimulate thinking about future directions, and promote the more effective application of AI technologies in this field, ultimately benefiting human health through an accelerated drug development process.

Biological carbon fixation is crucial to the Earth's carbon cycle and is one of the effective ways to transform CO₂ and manage carbon emissions. Chemoautotrophs, with their unique metabolic strategies and environmental adaptability, play an important role in this process. They are able to convert CO₂ into valuable organic products, solving the problem of limited CO₂ utilization. However, the carbon fixation potential of chemoautotrophs in controlled systems has not been fully explored. This review illustrates the possible challenges of stable culture of chemoautotrophic bacteria in bioreactor. Based on this, a series of physical, chemical and biological methods are proposed to regulate the carbon metabolism of chemoautotrophic bacteria and improve their carbon fixation efficiency. Further, the application prospects of chemoautotrophic carbon fixation in controlled systems are expected, including improving the primary productivity of natural ecosystems, reducing carbon emissions in specific sites, and producing high−value microbial by−products. This review highlights the advantages and challenges of these applications, providing important insights into carbon capture, fixation and conversion by chemoautotrophs.

With the convergence and innovation of emerging information technologies, Digital Twin (DT) technology has become a key enabler for digital transformation and the evolution of intelligent systems. It has been widely applied and received significant attention in fields such as industrial manufacturing, smart cities, and intelligent transportation. However, existing research on traditional DT technologies has predominantly focused on the modeling and analysis of physical entities ("objects"), with limited systematic integration of "human" and "environmental" factors. The lack of exploration into human−environment interactions makes it difficult for current digital twin frameworks to meet the advanced demands of complex intelligent systems for multi−level, comprehensive interaction capabilities. In view of this, this paper innovatively introduces the "object−human−environment" interactive vision and comprehensively and systematically analyzes the research frontiers and progress of digital twin technology from the three core dimensions of intelligent physical entity (object), intelligent individual (human), and virtual−real fusion environment (environment). Firstly, the paper analyzes the traditional digital twin technology system with "object" as the core and focuses on its theoretical origin, framework, and application. Secondly, it discusses the definition, development context, national policies, and core technologies of digital people driven by AI. Finally, expand the vision to the dimension of "environment" and explore the application practice of "environment" in multiple scenes of the meta−universe, deeply discuss the deep integration and interaction mechanism of the three elements of "object", "human" and "environment", reveal how the three interact and promote each other, and provide support for the construction of the meta−universe. Furthermore, this study discusses the current research challenges and future development trends of digital twin technology from the perspective of "Object−Human−Environment" interaction and proposes three key research directions: (1) developing an intelligent, multi−layered data fusion framework; (2) exploring AIGC−enabled intelligent virtual−real mapping and native virtual evolution; and (3) constructing novel virtual economy architectures and intelligent governance systems. The research outcomes provide both theoretical foundations and practical insights for building next−generation digital twin systems characterized by multi−agent collaborative perception, multimodal intelligent interaction, and closed−loop integration of virtual and real environments.

The accurate and efficient extraction of building from remote sensing images is fundamental for applications such as fine urban management, high−precision mapping, and land resource investigation. It is essential to investigate how to leverage image features for intelligent interpretation. This study introduces a global self−attention network with edge−enhancement (E−GSANet) for remote sensing building extraction. The network integrate the edge enhancement module into the encoder backbone, providing the network with a priori knowledge about boundaries, and then establish long−distance dependency relationships between features using the global self−attention feature expression module, enabling the fusion of salient features with edge−enhanced features. A stepwise up−sampling decoding module is designed to fusing the shallow features with rich spatial detail information and the deep features with high−order semantic information to obtain accurate extraction results of buildings. The comparison experiments between E−GSANet and the current mainstream methods is conducted based on two open−source remote sensing building datasets. The quantitative analysis and qualitative demonstrations prove that E−GSANet achieves optimal results across all evaluation metrics, yielding more complete building extractions, precise edges, and higher accuracy. Additionally, network structure ablation experiments and analysis demonstrate the effectiveness of each module.

Post−disaster restoration and reconstruction after major disasters is an open and complex mega−system project. This paper attempts to interpret the historical development of post−disaster restoration and reconstruction in China from the system engineering perspective. First, we define major disaster events and provide classification and outline significant catastrophic events since 1949. Secondly, we use Hall's three−dimensional morphology and Wuli−Shili−Renli system approach to construct the system structure of post−disaster restoration and reconstruction from three dimensions: development stages, critical activities, and science and technology. Then, by examining the specific measures of post−disaster restoration and reconstruction in typical catastrophic events and their relationship with the evolution of human−environment interactions, the traditional, sustainable and intelligent patterns of post−disaster restoration and reconstruction systems are revealed. Finally, the historical experiences of China's post−disaster restoration and reconstruction are summarized in five aspects: institutional advantages and legal guarantees, cross−departmental coordination and information sharing, intelligent monitoring and precise needs assessment, infrastructure and cultural construction, and catastrophe relief and insurance.

Ice lithography (IL) is an emerging micro/nanofabrication technique based on electron beam interaction with cryogenic materials, which enables direct writing and transfer of nanoscale patterns through localized electron beam irradiation on solid ice resists formed by gas condensation on cryogenic substrates. Since its inception, this technology has rapidly evolved with distinctive advantages: Firstly, the low electron sensitivity of ice resists permits in situ observation during processing, facilitating high-precision overlay alignment. Secondly, ice films demonstrate exceptional conformal coverage on non-planar substrates, overcoming the planarization constraints inherent to conventional lithography. Thirdly, the solvent-free removal of ice resists via thermal desorption establishes an environmentally benign process, particularly advantageous for processing sensitive and fragile materials. This review systematically examines the historical development of IL, comprehensively summarizes key advancements in technical characteristics, fabrication accuracy, equipment evolution, and process applications, while providing prospects for future directions. It aims to stimulate interdisciplinary research and explore the application potential of this novel technology in emerging fields including three-dimensional optoelectronic devices, biosensing platforms, and flexible electronics.

Calcium-based batteries have attracted increasing attention as promising candidates for next-generation energy storage, owing to the natural abundance of calcium (approximately 2500 times more abundant than lithium in the Earth's crust), its high volumetric capacity (2073 mA·h·cm-3), and favourable environmental profile. Despite these advantages, their development remains hindered by several fundamental challenges, including inefficient and irreversible calcium metal plating/stripping, narrow electrochemical stability windows of electrolytes, and the scarcity of high-performance cathode materials. Here we provide a comprehensive overview of recent progress in calcium-based battery research, with a focus on calcium metal anode design, rational electrolyte design, development of cathode chemistries, and advances in cell configurations. We critically examine the underlying mechanisms and representative strategies proposed to address current bottlenecks, and discuss emerging opportunities for calcium-based systems in grid-scale and extreme-environment applications. This Review aims to offer a clear perspective on the path toward practical calcium-based batteries and to inspire future research directions for unlocking their full potential.

It is the obligation of the parties to the Convention on Biological Diversity to update and revise the National Biodiversity Strategies and Action Plans (NBSAPs). COP15 decision required all parties to revise or update NBSAPs in alignment with the Kunming−Montreal Global Biodiversity Framework including national targets communicated in a standardized format. China's strategic position in biodiversity conservation has been continuously rising. In January 2024, the China's Biodiversity Conservation Strategy and Action Plan (2023−2030) was officially released. This article reviews the main considerations and elements changed in the update and revision of the NBSAP, and introduces the main contents of the NBSAP, including four priority areas: mainstreaming biodiversity, responding to the threat of biodiversity loss, sustainable utilization and benefit sharing of biodiversity, and modernization of biodiversity governance capacity. Topical issues and newly added priority actions have been analyzed and interpreted. This article also summaries the main implications and practical significance of the NBSAP. A Chinese solution for promoting the implementation of the Kunming−Montreal Global Biodiversity Framework was submitted. NBSAP was connected with domestic policies in the field of biodiversity, guiding local levels to carry out conservation practices, and providing a reference for analyzing and responding to new focuses and new issues in future biodiversity conservation work.

The impact of global warming and how to deal with it are topics of widespread concern across various sectors of society. This paper focuses on the impacts of global climate change on dryland. Over the past fifty years, the temperature has risen at the rate of 0.32℃ /decade, and climate warming has enhanced the evaporation capacity and consequently expanded the world's arid regions by approximately 2.61×10⁶ km². The frequency and severity of droughts has also increased, with an average of 251 meteorological droughts occurring in 34 major river basins. The drought heatwave compound events and flash droughts are becoming more common. The duration of heat waves has extended from 8 to 12 days on average. With climate warming, the water availability has decreased with increased water uncertainty. Concurrently, greenhouse gas emissions increased and carbon sequestration reduced. Desertification has aggravated, and poverty?stricken area has expanded. In light of these challenges, it is recommended to vigorously advocate carbon emission reduction strategies to curb the pace of climate warming, strengthen international cooperation, formulate a global action plan to mitigate the continuous expansion of arid areas, build a cooperation mechanism to address climate change in terms of policy, management, education, science and technology, finance and other aspects, and solve the "double dilemma" of desertification and poverty in multiple ways.

The soil carbon reservoir, the largest terrestrial carbon pool, plays a critical role in regulating atmospheric CO₂ concentrations and climate change. Conventional research paradigms often treat soil organic carbon (SOC) and soil inorganic carbon (SIC) separately, limiting the predictive capability for soil carbon cycle dynamics. This review systematically synthesizes the formation and sequestration mechanisms of SOC and SIC. SOC stability is maintained by a complex "multi−assemblage" involving chemical recalcitrance, physical protection, mineral associated stabilization, and microbial regulation (e.g., the Microbial Carbon Pump, MCP). In contrast, SIC dynamics are governed by chemical precipitation−dissolution equilibria, biologically driven processes, and physical transport, with its perceived role evolving from a 'static geologic reservoir' to a 'dynamic carbon sink'. A key advancement is the revelation of deep biogeochemical coupling between SOC and SIC: CO₂ released from SOC decomposition drives the formation of secondary carbonates, while pH and Ca²⁺ concentration regulated by SIC dissolution, in turn, feedback on SOC stability and microbial activity. Building on this, we propose a novel "SOC−SIC−Climate" tripartite coupling framework, elucidating their dynamic pathways—including synergistic enhancement, trade−off compensation, and critical instability—under the forcing of external factors (climate, minerals, biology, human activities). Finally, translating mechanistic understanding into practice, we propose region−specific regulation and carbon management strategies (e.g., calcium cycle regulation, Microbially Induced Carbonate Precipitation (MICP)) tailored to different climate zones and land−use types. This aims to transform soil from a passive sink into an actively managed climate buffer, providing a scientific foundation for advancing Earth system theory and optimizing carbon neutrality pathways.

In recent years, light−driven micro/nanomotors have emerged as a novel type of miniature power device, leveraging their adjustable energy input, reversible switching state and remote operability. They have demonstrated broad application prospects in water environment treatment, biomedical fields, and biosensing. This paper aims to systematically summarize the research progress of light−driven micro/nanomotors, elucidate their propulsion mechanisms, and highlight typical applications driven by different types of light (ultraviolet, visible, and near−infrared light). Despite the substantial potential of light−driven micro/nanomotors in various domains, they still face numerous technical challenges, such as low propulsion efficiency, limited motion control precision, and issues with the biocompatibility of materials. Future research directions may include the integration of multiple driving methods, enhancement of light energy conversion efficiency, and development of biocompatible materials. These efforts will promote the performance improvement and application expansion of light−driven micro/nanomotors, bringing revolutionary changes to environmental protection and biomedical fields. By overcoming current technical obstacles, light−driven micro/nanomotors are expected to play a more significant role in future scientific research and practical applications.

The dual pressures of urbanization and climate change are intensifying the urban heat island effect, carbon emissions, and air pollution, posing significant challenges to environmental sustainability and urban livability. As the demand for multiobjective coordinated management of urban ecological environments continues to increase, integrating heat, carbon, and pollution into a unified framework for comprehensive assessment has become a key direction for future urban planning and policy−making. This article systematically compares and analyzes the consistency between global development agendas and the goals of reducing urban heat, carbon, and pollution, highlighting the significant potential and advantages of new−generation information technologies in intelligent optimization and coordinated scheduling, data fusion and analysis, real−time monitoring and feedback, and decision support and simulation. From the new perspective of urban spatial form, it comprehensively reviews the specific content, challenges, and future issues in conducting multi−scale, multi−dimensional "heat−carbon−pollution" multi−objective coordinated reduction planning. It provides innovative solutions for multi−objective coordinated management and sustainable development of "heat−carbon−pollution" in Chinese cities.

地球系统科学是当今世界最具挑战性的前沿科学领域之一。总结分析了近半个世纪以来，国际科学理事会（ICSU）主导实施的一系列全球变化国际大科学计划：世界气候研究计划、国际地圈-生物圈计划、生物多样性计划、国际全球环境变化人文因素计划、地球系统科学联盟、未来地球的可持续发展研究计划。探讨了在这些计划的推动下，地球系统科学的发展过程及其对促进人类社会可持续发展的贡献；指出了中国参与国际大科学计划具有提升国际影响力等重要意义，并提出了开辟专门经费渠道等具体建议。

随着中国污染控制进入深水区和“双碳”目标的提出，传统污染源治理技术在碳污协同减排和多介质污染协同控制等方面面临诸多挑战，亟需探索环境治理新范式。针对城市环境复合污染治理难题，将污染控制由排放源拓展至环境过程，论述了通过人工手段强化城市环境的自净功能，利用自然界的光、热、风、氧、水等条件实现污染物的环境过程净化，耦合气-水-土多介质人工强化环境自净技术构建“自净城市”，有望成为环境保护工作新的增长点，从而巩固当前污染源排放控制的成果，保障环境质量持续改善。在此基础上，对污染物环境过程净化、自净城市的理论与技术进行了介绍，如将气–水–土多介质人工强化环境自净技术在城市区域进行多场景、多过程、全方位应用，以提升城市环境容量，持续改善城市环境质量，并对城市环境污染物自净过程与机制、人工强化自净材料与技术、多介质环境自净应用策略与方案、城市环境自净能力评估4方面提出了发展建议。

At present, a new round of scientific and technological revolution and industrial transformation is advancing at an accelerated pace, with breakthroughs in cutting−edge fields reshaping the global landscape. The scientific and technological development of China during the 15th Five−Year Plan period is not only a crucial stage for itself to achieve the goal of building a world power in science and technology, but also will play an important role in the global pattern of scientific and technological development, exerting a significant and far−reaching impact on the world. How to accurately position itself in the complex and volatile international situation, make forward−looking plans, and scientifically map out the roadmap for scientific and technological development during the 15th Five−Year Plan period is a key issue that China must strive to address at present. In the next 5−10 years, China will face a complex situation where the intensification of strategic games among major powers, the acceleration of scientific and technological industrial transformation, and the arduous task of economic and social transformation are intertwined: science and technology have become the main battlefield of national strength competition, international cooperation has weakened, and security risks have risen; the frontiers of science and technology are advancing in depth, and disruptive technologies are intersecting and integrating, nurturing new industrial forms; China's economy is transforming towards high quality, and security risks in fields such as energy and food are prominent. The construction of a strong science and technology country during the 15th Five−Year Plan period should focus on six aspects: first, strengthen organized basic research; second, coordinate and strengthen the tackling of key core technologies; third, strengthen the dominant position of enterprises in innovation; fourth, promote the integrated development of education, science and technology, and talents; fifth, improve the ecological environment for scientific and technological innovation; sixth, strengthen open innovation and cooperation.

Artificial Intelligence (AI), as a core driver propelling socioeconomic development, is triggering a dual paradigm shift in scientific research (AI for Science, AI4S) and engineering technology (AI for Engineering, AI4E). This paper systematically elaborates on the driving forces, mechanisms, and practical pathways for the paradigm shift in digital ecosystem network development driven by AI4E. It points out that the traditional development paradigm of digital ecosystem networks faces a fundamental conflict between "rigid architectures and diversified scenarios", necessitating reconstruction with the goals of being "hyper-converged, highly trustworthy, and integrated". The paper introduces the critical foundations, technological underpinnings, and operational mechanisms for this AI4E-driven paradigm shift in digital ecosystem networks. It delineates the main characteristics of the new paradigm from perspectives including mindset, methodology, practical norms, and developmental pathways. Furthermore, it presents practical explorations of AI4E-empowered transformation: proposing the Polymorphic Intelligent Network Environment (PINE) based on Generative AI to forge the "second curve" of network technology systems; introducing On-Wafer Generative Vari-Structure Computing to foster new "chip species" of intelligent computing power; promoting endogenous safety and security (ESS) to empower the resilience engineering of digital system networks, thereby enhancing the endogenous security of AI application systems; and advocating for the construction of the "Hyper-Converged Networks and Intelligent Computing Testbed" as a major scientific facility. This testbed will validate the scientific conjecture that "structure determines efficiency/security/diversity", providing support for building an independent knowledge system, advancing independent sci-tech innovation, and deepening reforms in self-reliant talent training. The study provides both a theoretical framework and technological pathways for the paradigm evolution of digital ecosystem networks in the AI era.

探讨了人工智能的学科体系，从人工智能的定义出发，提出人工智能的学科体系是由人工智能的科学基础、人工智能技术方法和人工智能应用3部分组成，并认为人工智能的科学基础是符号主义、连接主义和行为主义，人工智能的主要技术是基于知识的人工智能技术、基于数据的人工智能技术、人工智能的算法和人工智能的算力，而人工智能的技术要素为知识、数据、算法和算力，人工智能的应用领域涉及经济、科技、民生、社会和其他领域。

Following the full value chain of "feedstocks–technologies–processes–products," biomanufacturing is rapidly advancing toward high efficiency and sustainability. This review first analyzes the limitations of traditional grain−based feedstocks and highlights the latest developments in sustainable raw material systems—including non−food resources, biomass, and one−carbon substrates—which collectively support the establishment of a secure and robust feedstock base for biomanufacturing. On the technology side, we systematically examine advances in foundational tools such as gene editing, metabolic engineering, computational design, and artificial intelligence (AI), emphasizing their roles in the precise design of chassis cells, industrial enzymes, and high−performance microbial strains. These technologies are driving biomanufacturing toward higher efficiency, modularization, and intelligence. At the process level, key innovations in intelligent cell factories, precision fermentation, online monitoring, digital twins, and the domestic development of smart equipment are discussed, highlighting the transition from experience−driven operations to model−driven and intelligent decision−making. On the product side, we summarize industrialization progress and application prospects across pharmaceuticals, food, chemicals, and materials. Finally, we address critical bottlenecks facing China's biomanufacturing—such as limited autonomy in strain development and reliance on imported high−end equipment—and propose directions for key technological breakthroughs, providing guidance for future technology roadmaps and industrial development.

广域长距离高性能传输技术在中国“东数西算”工程构建全国一体化算力网背景下具备重要的战略价值。3个趋势对广域分布式算力协同范式提出新需求：对算力资源要求极高的人工智能（AI）大模型智能应用的兴起；高端高性能图形处理单元（GPU）芯片被禁运限制单中心算力资源；中国各地建设的算力集群形成算力分散分布态势。广域长距离高性能传输技术是上述新范式的关键技术。从支撑广域分布式算力协同新范式、技术路线、承载网络、研究难点、成本5个方面进行讨论，结合深圳到宁夏中卫2100 km实网实验结果，将现有远程直接内存访问（remote direct memory access，RDMA）技术基于广域全光网进行长距离优化的方案是短期内可行性高、成本低且利于开展研究的最佳方案之一，通过优化基于融合以太网的远程直接内存访问（RDMA over Converged Ethernet，RoCE）可以在广域全光网上实现“广域光数直达”逼近物理层通信性能指标。

This paper expounds the necessity and feasibility of the application of hydrogen energy in aviation field, reviews the research and development history of hydrogen aviation power at home and abroad, looks forward to the development prospect of hydrogen aviation power, points out that the development of hydrogen aviation power needs the reconstruction of the whole industrial chain, the innovation of the whole chain, the whole process test and the establishment of a new national system, and puts forward some suggestions, such as firm confidence in promoting the development of hydrogen aviation, building a national strategic scientific and technological force of hydrogen aviation, building an innovative development ecology of hydrogen aviation, and implementing the national science and technology project of hydrogen aviation.

The intelligence of unmanned vessel systems is undergoing a profound transformation from remote control to embodied autonomous forms, with the core being the realization of advanced intelligent behavior through multimodal perception, environmental interaction, and closed−loop learning. This paper systematically reviews the key advances of embodied intelligence in unmanned vessels, highlighting that semantic control loops, digital twin validation, and evaluation systems are moving from methodological exploration to engineering integration, and have already begun to provide preliminary application support in port and inland waterway scenarios. However, current technologies still face bottlenecks in perception stability, rule interpretability, and deployment resources. Therefore, this paper recommends focusing on breakthroughs in strengthening autonomous closed−loop intelligence systems, establishing standard and trustworthy validation environments, and promoting lightweight and collaborative deployment to enhance system reliability, compliance, and scalability, providing support for the development of intelligent ship technology and the implementation of our marine strategy.

金属材料腐蚀防护技术的创新是实现有效防护的关键。防护技术的发展经历了从单一涂层保护到多元化防护策略的转变。当前，阴极保护、涂层保护、材料改良和表面处理等技术已广泛应用于各种工程设施的腐蚀控制。纳米技术、自修复材料、生物诱导的矿化等前沿技术的应用，为金属材料腐蚀防护提供了新的解决方案。

In 2025, unmanned aerial vehicle technology will develop in directions such as intelligence, autonomy, systemaltization, and low−cost becoming the core driving force for the large−scale application of low−altitude economy and the construction of a global intelligent airspace system. This paper systematically elaborates on the development trends of unmanned aerial vehicle technology in 2025 from multiple dimensions including unmanned aerial vehicle technology innovation, key unmanned aerial vehicle technologies, unmanned aerial vehicle application verification, anti−unmanned aerial vehicle tactics, and unmanned aerial vehicle management policies. At the critical stage of the global implementation of low−altitude economy on a large scale, the optimization of communication networking efficiency, the intelligent collaboration of heterogeneous platforms, and the construction of a secure and trustworthy airspace system have become the forefront of global technological competition and jointly promote the formation of a new ecosystem of the unmanned aerial vehicle industry where humans, machines, and objects are integrated. In the future, unmanned aerial vehicles will be driven by distributed collaboration and based on intelligent safe airspace, continuously injecting strong new technological impetus for the high−quality development and digital transformation of the low−altitude economy.

Embodied intelligence represents a new stage in the evolution of artificial intelligence, marking a transition from "perception−cognition" to an integrated paradigm of "perception−cognition−action." The Vision−Language−Action (VLA) model provides a critical technological pathway for enabling autonomous agent operation in the real world by unifying visual perception, language understanding, and action generation. This paper systematically reviews the development trajectory and representative achievements of VLA technologies, and summarizes their architectural paradigm, which includes multi−modal perception, semantic fusion mechanisms, reinforcement and imitation learning, world models, and hierarchical action output. By considering application scenarios such as autonomous driving, human–computer interaction, and industrial equipment, we further analyze the core challenges faced by VLA development, including the scarcity of data resources, limited generalization and transferability, insufficient interpretability, and increasing computational demands, and we outline the future development trends.

Autonomous and intelligent unmanned surface vehicles (USVs) have a wide range of applications in science, commerce, and military fields. Due to the underactuated nature commonly possessed by USVs and the complexity of the maritime environment, the path planning for USVs remains an extremely challenging issue and is also a key technology for USVs. This paper reviews the existing algorithms and the latest research on traditional global and local path planning, intelligent path planning, swarm path planning, and path optimization for USVs. The various constraints considered in USV path planning are summarized and the innovative points, performance, limitations, and practical application scenarios of various path planning methods are analyzed comparatively. The importance of evaluating path under multi−constraint conditions is analyzed and emphasized. Based on existing problems and future trends, some suggestions for future research are proposed.

Major depressive disorder is a prevalent psychological disorder, and screening is currently based on depression diagnostic scales and physician interviews. Based on artificial intelligence technology, computer−aided depression detection is an emerging approach to depression screening. Aiming at the current status and shortcomings of traditional measurement tools, this paper reviews current computer−aided depression detection methods, discusses the current research status of depression detection datasets and depression detection methods based on multimodal data such as facial pictures, speech, and text, and summarizes and outlooks the advantages and challenges of computer−aided depression detection. Computer−aided depression detection can provide a relatively simple and standardized screening method with the potential to synergize with the widely used scale screening and physician diagnosis, but still faces the challenges of the insufficient interpretation of model parameters and features, the Chinese dataset to be expanded, and the small sample size of the existing dataset. In the future, researchers need to further improve the sample size and model accuracy of depression detection datasets, conduct theoretical and experimental analyses of feature extraction and model construction, and promote the clinical application of computer−aided depression detection.

Helium is a strategically key resource closely tied to national development and is one of China's extremely scarce mineral resources. Currently, the assessments of helium generation often rely on test results from core or field samples, making it difficult to conduct continuous, comprehensive evaluations of a region. To address this issue, considering that the helium generation is a function of the concentrations of radioactive elements uranium or thorium and time, a method for assessing helium resource based on natural gamma−ray spectrometry logging is proposed. By employing gamma detectors to measure the gamma spectra resulting from natural radioactivity in rock layers and analyzing the variations in gamma spectra caused by different radioactive nuclides, it becomes feasible to continuously determine the uranium and thorium content of each stratum. This result can then be utilized to analyse the helium release content of rock minerals, identify primary helium−bearing rocks, and evaluate the potential helium resources within the strata. Currently, this approach is being applied to forecast helium resource distribution and conduct strategic assessments in the Gucheng, Yakela, Tuofutai, Hetianhe area, as well as across the entire Tarim Basin. In the future, it is necessary to further refine the determination of the helium generation amount in crystalline basement, absolute ages of helium−releasing minerals, and the process of helium dissipation in gas reservoirs during the use of this method.