基础研究的发现往往会催生一些革命性的工业基础，但从科学发现到最后走向产业需要很长的时间，在量子信息这种高科技领域表现得更加突出。因此，要统筹好基础研究、应用基础研究、产业商业化，也要统筹好长期和短期的关系。

Building a world power in science and technology requires support from excellent work styles and academic ethics. Based on the survey data of the national scientific and technological workers conducted by the China Association for Science and Technology, this paper analyzed the cultural, institutional, and individual causes behind the negative phenomena in the scientific community, such as weakened spiritual motivation and the spread of utilitarianism. It pointed out the harm of poor academic conduct to the academic ecosystem, talent cultivation, and public trust. The paper proposed paths to strengthen the governance of work styles and academic ethics through demonstration and guidance to promote the spirit of scientists, combating academic misconduct and formalism, and cultivating scientific and cultural confidence through education, so as to create a clean and positive innovation ecosystem and advance high-level scientific and technological self-reliance.

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.

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.

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.

In the context of global efforts to address climate change and China's determined march toward the twin goals of carbon peak and carbon neutrality, methane control and emission reduction have become key links in achieving sustainable development and climate targets. This paper analyzes the strategic layout for methane management and mitigation under these twin carbon objectives. To date, preliminary achievements have been made: A three-dimensional "air–space–ground" monitoring system enables precise localization of emission sources; upstream recovery rates in energy extraction have improved; source-control technologies for rice cultivation and livestock farming in agriculture have matured; and a methane-focused climate finance framework has injected fresh capital into reduction efforts. However, methane mitigation challenges remain severe. In the energy sector, methane leaks in traditional coal mining and fugitive emissions in oil and gas systems hinder the green transition; in agriculture, anaerobic processes in rice paddies and enteric fermentation and manure management in livestock farming lead to significant methane release; and in waste treatment, landfill disposal and anaerobic treatment of industrial wastewater generate large methane volumes. In response, this paper proposes a cross-sectoral collaboration that breaks down the boundaries among the energy, agriculture, and waste-treatment industries to build an integrated mitigation system. This approach balances energy security with the twin carbon goals by steadily steering the energy mix toward greener, lower-carbon sources while ensuring supply reliability. It also calls for leveraging educational, research, and talent advantages to establish national-level science and innovation platforms to tackle key technological challenges in methane control. Looking ahead, with sustained technological innovation, targeted policy optimization, and deep international cooperation, China is poised to overcome current methane-control obstacles, achieve substantial emission reductions, support its carbon-peak and neutrality goals, and contribute meaningfully to global climate governance.

Optical vacuum measurement technology, with its remarkable advantages in expanding measurement ranges and breaking through uncertainty limitations, has emerged as a key technology supporting innovation in strategic fields such as deep space exploration, semiconductor manufacturing, and advanced equipment development. This paper initiates from the interaction mechanism between photons and gas molecules, comprehensively introducing theoretical model innovations and experimental setup breakthroughs in quantum optical methods for retrieving vacuum parameters, including Fabry−Perot cavity optical interferometry, cold atom collisional loss, and spectral absorption. It systematically reviews the latest developments from fundamental research to engineering applications by international research institutions in this field. In-depth analysis reveals existing bottleneck issues within current quantum vacuum measurement technology systems. Subsequently, potential evolution directions for quantum vacuum measurement technology are prospected through technical pathways such as quantum vacuum standard establishment and miniaturized device integration.

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.

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.

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.

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.

Circular aptamers, as a class of nucleic acid molecules with closed-loop topological structures, have emerged as superior molecular recognition probes in fields such as food safety, environmental monitoring and disease diagnostics owing to their intrinsic exonuclease resistance, superior thermodynamic stability, and excellent compatibility with rolling circle amplification techniques. This article systematically reviews the synthesis methods, high-efficiency selection strategies, structure-function rational design, rolling circle amplification-driven ultrasensitive detection, and multivalent probe applications of circular aptamers. Furthermore, it provides insights into future directions, including large-scale efficient synthesis techniques, artificial intelligence-assisted structural design, and the development of dynamic selection models for analyzing interactions in complex biological matrices.

In 5G/6G radio-over-fiber (RoF) networks, remote radio units (RUs) require multi-beamforming functionality to ensure reliable access for ubiquitous mobile terminals. To meet this requirement, multi-core fibers (MCFs) have emerged as a promising solution for RoF links due to their advantages of supporting multiple channels and maintaining excellent inter-channel delay consistency. Here, we proposes a remote optical true-time-delay multi-beamforming architecture based on MCFs, which is suitable for 5G RoF networks. The architecture utilizes MCFs as the link, while deploying chirped fiber Bragg gratings with equal dispersion spacing to provide equal-space time delays at the centralized unit. By independently tuning the wavelengths of each optical carriers, the corresponding beam direction can be continuously adjusted, enabling centralized multi-beam control. To validate the feasibility of this architecture, we use a 2-km 7-core fiber as the RoF link for experiment and build a 2×2 remote beamforming system. Experimental results demonstrate that by tuning the wavelength of each optical carrier, independent control of each beam direction can be achieved. Compared to single-mode fibers, MCF reduces inter-channel delay jitter by more than an order of magnitude, with a maximum delay jitter of 1.7 ps, ensuring long-term stability of the beam direction. Furthermore, the inter-core crosstalk of MCF has a negligible impact on both the preset delays and the signal-to-noise ratio of broadband wireless signals. This architecture provides a feasible and stable solution for realizing remote beamforming, offering significant application value for 5G/6G mobile access networks.

Searchable encryption is a key technology for enabling data encrypted search, and it has significant application value for cloud storage. However, existing schemes generally adopt a single-user model and are vulnerable to insider keyword guessing attacks, which exposes cloud data to the risk of privacy leakage. Therefore, there is an urgent need to design a searchable encryption scheme that support multi-user models and provide higher security to meet the privacy-preserving of cloud data. In response, this paper proposes an authenticated ciphertext retrieval scheme for cloud data access control. In terms of access control, the scheme embeds attributes into users' secret key to generate search trapdoor and incorporates access policies into the keyword ciphertext. The matching of attributes and access policies is achieved through threshold secret sharing techniques, thus establishing a fine-grained retrieval permission control mechanism. To enhance security, the secret key of the data owner is embedded into the keyword ciphertext to provide ciphertext authentication, effectively preventing insider keyword guessing attacks. Performance analysis shows that the trapdoor generation algorithm in our proposed scheme are computationally efficient, while the user secret key has relatively low storage overhead, making our scheme suitable for cloud storage applications.

Soil antibiotic pollution has become a significant issue in China's agricultural environment, impacting ecosystem health and food safety. This study, based on the Geographically Optimal Similarity (GOS) model, systematically predicts the spatial distribution of soil antibiotics in Chinese farmlands and explores the impact of agricultural management measures on soil antibiotic residues through scenario analysis. The results indicate that the average antibiotic concentration in China's farmland soil is approximately 16.9 ng/g, with distinct regional variations. The eastern and central regions generally show higher soil antibiotic concentrations, which are primarily associated with irrigation and fertilization management intensity. When the amount of organic fertilizer is reduced by more than 40%, the soil antibiotic concentration significantly decreases; conversely, when the irrigation area increases by more than 60%, the concentration of soil antibiotics increases rapidly. The study suggests that optimizing agricultural management measures, particularly reasonable fertilization and irrigation in high-risk areas, can effectively control soil antibiotic pollution and promote agricultural environmental protection and sustainable agricultural development.

Research institutes are an important component of the national innovation system construction. At present, state-owned research institutes mainly implement the system of institute director responsibility under the leadership of the Party committee, while non-state-owned research institutes mainly adopt the system of institute director responsibility under the leadership of the board of directors. To achieve the transfer and transformation from science to technology, and from technology to industry, it is necessary to accelerate the exploration of new management systems for research institutes and improve their governance systems. From a management perspective, the main problems existing in research institutes have been identified, manifested as a lack of structured decision-making mechanisms, incomplete governance systems, poor integration with market factors, difficulty in accessing social capital, and poor achievement transformation. It has been proposed that for different types of research institutes, the core governance concept of enterprise management can be used as a reference to construct a governance framework for "SAER" structured management, improve the mechanism of structured management, establish a council or strategic guidance committee, fully leverage the role of academic and evaluation committees, and open up effective channels for connecting with market resources. At the same time, it is pointed out that the role of the Party committee in directing and managing the overall situation should be leveraged to achieve optimal management efficiency and maximize scientific research output.

While inventing the theory of relativity, Einstein also created a unique philosophical epistemology (a pluralistic tensionalism or pluralistic tensionism with rich connotations and broad extensions, consisting of mild empiricism, conventionalism for constructing the foundation of scientific theory, holism in meaning, scientific rationalism, and realism as a research program) and methodology (exploratory deduction, principle of logical simplicity, quasi aesthetic principle, visual thinking, and cosmic religious thinking or method). The marriage of science and philosophy can be said to be a perfect match and complementary in his scientific career and innovation process. Scientists can be inspired by it and get lessons from it.