Osteoarthritis (OA) is a degenerative disease that is prone to occur in the middle-aged and elderly groups. It can erode articular cartilage and its affiliated organization, and seriously affect the life of patients. Hydrogels have good biocompatibility and excellent mechanical properties. Functional hydrogels can make up for the shortcomings of short drug action time and the difficulties to cure OA in common therapy approaches. In this article, we review the recent advances of hydrogel as a carrier to treat osteoarthritis from the aspects of drug treatment of osteoarthritis, cartilage defect repair, and synovial fluid repair. The anti-inflammatory and analgesic mechanism of drug release hydrogel, the mechanism of cartilage repair of cartilage defect repair hydrogel and the joint lubrication mechanism of joint lubrication hydrogel were discussed. On these bases, we also summarize the existing problems and propose further development direction of hydrogel in the treatment of OA.

With the increasingly serious energy crisis, the development of renewable clean energy as a substitute for fossil energy has always been the focus of scientific research. Biomass energy is the most promising alternative to fossil energy. This paper discusses the current situation and shortcomings of biomass energy utilization in five aspects: the source of biomass energy raw materials, the treatment of raw materials, biomass conversion technology, the application of biomass energy, and the development prospect of biomass energy. Although biomass energy research is booming, there are still some areas where improvements can be made: plants can be built close to the source of the feedstock to reduce feedstock costs; microalgae do not take up land and are a viable feedstock; feedstock pre-treatment needs to balance benefits and costs; for the choice of biomass conversion technology, a combination of biochemical and thermochemical conversion may be a good option; the application side of biomass energy can be biorefined to improve production efficiency, in addition, biofuel cells have great potential for development. This study aims to provide a theoretical basis and reference for the optimisation of existing technologies and future research and development of biomass energy.

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.

Chiplet technology is a new generation of integrated circuit technology that has emerged in recent years. It has been widely recognized by the industry due to its excellent characteristics such as improving yield, breaking the limit of reticle size, flexibility in chip architecture, and standardization of IP supply chain. To further promote the development of chiplet technology in China, this article summarizes the application scenarios of chiplet technology, analyzes various core component technologies, elaborates on various technical challenges that may arise in the development of chiplet technology, reviews the development of China’s chiplet standards, and finally, puts forward some suggestions for the development of chiplet technology in China.

This paper summarizes the application of robotics in the three aspects of rail transit, i.e., equipment manu-facturing, maintenance inspection, and operation services. Combined with the development status of intel-ligent robot technology in this field, we summarize the key technology and challenges of robots. Thus to propose the future direction of the cooperation of robotics and rail transit.

The recent advances made by graph-based deep learning have demonstrated its great potential in processing non-Euclidean structured data, and a large number of research efforts have attempted to apply graph embeddings or graph neural networks to vulnerability detection. This survey systematically investigates the vulnerability detection based on graph deep learning. Firstly, we summarize the four main stages of the vulnerability detection process, including data set, graph data preparation, graph deep learning model construction, and result evaluation. Then, starting from the effectiveness of graph-based deep learning vulnerability detection, we respectively expound the research results based on code patterns, code similarity and specific application scenarios. Finally, by sorting out and summarizing the existing research works, we analyze the challenges and foresee the trends in this research field.

Immune checkpoint antibody drugs have opened up a new era in the field of tumor treatment since the 20th century. In 2021, the global market share of antitumor monoclonal antibody drugs has reached 62 billion US dollars. In recent years, domestic enterprises have also accelerated their development in this field. However, a big gap still exists between these enterprises and international pharmaceutical giants. In this context, it is of vital significance to fully grasp the international research and development trends and the panorama of the R&D pipeline. The research topics of core articles in this research field in the past 10 years were analyzed, and the development trend of the field was revealed through the evolution of the research topics. Seven active research directions were identified. In-depth analysis of specific research directions was carried out through further data mining from professional databases and institutional websites. Comprehensive analysis indicated that three directions including the efficacy and safety surveillance of marketed antibody drugs and drug combination, new antibody drugs such as bispecific antibodies and antibody-drug conjugates, and new targets represented by 4-1BB have been the research hotspots and focuses in recent years. Adverse event monitoring of marketed drugs should be strengthened, and efforts should be stepped up to support the research and development of new antibody drugs.

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.

The application of artificial intelligence(AI) in the military field has recently further improved the overall response ability and execution efficiency of information-based joint operations. Electronic countermeasures combat operations take place in an invisible space, it is more urgent for troops to get AI technology support in a fast-changing electromagnetic situation. By sorting out the main application modes of AI technology in military field, this paper systematically studies the application path of AI in electronic countermeasures from a perspective of operational integrity and puts forward specific thoughts and suggestions for combat command，warfare method application，equipment research and development, and intelligent cooperation, so as to accurately serve the electromagnetic field struggle and improve intelligent combat ability.

In January 2023, the latest report of American Cancer Statistics in 2023 was published in CA: A Cancer Journal for Clinicians. This report elaborated on the cancer prevalence in America under the COVID-19 pandemic for the first time, described the secular trends in the burden of major cancers, and projected the cancer cases and deaths in 2023. We analyzed the pattern of cancers distribution by geographic area, time, and characteristics of the populations in China and America according to systematical interpretation of the report combined with the cancer statistics in China. We also summarized the current challenges in the development of cancer prevention and control system in China, and provided insights for its construction depending on assessing advancements and underlying reasons of that in America.

With the development of the information technology era, metaverse has gradually become the third internet revolution, and the metaverse terminal is an important component of it. This article describes the development trends and key technologies of the hardware part of the metaverse terminal in terms of micro displays, optical systems, and perceptual interactions. In terms of the micro display technology, two technologies, silicon based OLED and MicroLED, are mainly discussed; in terms of optical systems, the main topics discussed are surface relief grating waveguide technology, volume holographic waveguide technology, and metasurface waveguide technology; in terms of perceptual interaction, the interaction technology of gesture recognition and EEG recognition is mainly discussed.

Graph neural network (GNN) is another major development after convolutional neural network, and it belongs to an emerging deep learning method in the field of artificial intelligence. It mainly preserves the topological information in graph data through end-to-end learning from graph to prediction, and overcomes the defect that traditional deep learning cannot be applied to non-Euclidean data. This paper demonstrates the advantages of GNN for processing complex non-Euclidean data through the application progress of GNN in brain-related mental and nervous system diseases. GNN shows great potential in the medical field, furthermore, the network structure of the syndrome differentiation system of Traditional Chinese Medicine (TCM) is similar to the structure of the brain active area, and it is highly compatible with the schematic unstructured data processed by GNN, so GNN has great application prospect in the field of TCM. This article summarizes the application of GNN in the field of TCM and brain-related mental and nervous system diseases, and analyzes the advantages of TCM diagnosis and treatment models from the theoretical level, in order to explore and build a GNN-based model for fitting with the thinking mode of "syndrome differentiation and treatment" and realizing the objective diagnosis in TCM. It provides new means for solving the problems of complex relationship representation in TCM and mining the individual characteristics of patients. And it also provides a favorable tool for revealing the potential mechanism of TCM from multiple perspectives, and developing and improving the science of TCM.

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.

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.

With the development of industrial production, the emission of volatile organic compounds and pollutant components continue to increase. A variety of technologies and processes for treatment of VOCs have emerged. This paper briefs the typical characteristics of VOCs, summarizes and compares corresponding physical, chemical and biological treatment technologies, and summarizes in detail the treatment technologies such as adsorption, plasma and biological methods. The traditional treatment technology has low cost, mature technology and large processing capacity, but it can not meet the current situation of industrial production, especially decomposition of a variety of mixed polluting gases. Emerging technologies and combined technologies have the advantages of high purification efficiency, no secondary pollution and low energy consumption, which will be a continuous research hotspot in the future. By analyzing the current emission characteristics of VOCs and the corresponding treatment technologies, this paper discusses the most significant advantages and disadvantages of each technology as well as the difficulties that need to be overcome in the future. Finally, the future improvement direction and trend of VOCs treatment methods are put forward.

Guided by the dual carbon goal, the green and low-carbon transformation of China's energy industry has become an inevitable requirement. This study clarifies the challenges of the development of renewable energy, summarizes the typical operating modes of developing renewable energy businesses based on traditional energy businesses of the current energy industry. In addition, an in-depth analysis is conducted on the relevant issues caused by the rapid development of the renewable energy industry, and corresponding suggestions are put forward to ensure the effectiveness of energy industry investment in renewable energy assets. Furthermore, this study clarifies the development direction of the integration of renewable energy and oil gas production and provides decision-making references for the high-quality synergy development of renewable energy and traditional energy businesses under the dual carbon goal.

This paper summarizes the common practice patterns of artificial intelligence application in criminal investigation, mainly including video investigation, individual identification, data retrieval, information mining, auxiliary interrogation, evidence evaluation, etc., which brings multi-dimensional lock, situation and finger integration, and full chain support to the investigation department. Then this paper analyzes a series of risks and challenges accompanied by the application of artificial intelligence in criminal investigation, such as black box effect, precision deviation, algorithm overstep, open panorama, investigation secret room and so on. Some suggestions are put forward, such as anchoring the basic stance of human-oriented and human-computer integration, promoting the integration of data-driven and knowledge-guided methods, enhancing the ethical adaptation of artificial intelligence application in criminal investigation, and optimizing the legal system of artificial intelligence application in criminal investigation.

The discovery of bilayer nickelate superconductor La₃Ni₂O₇ under high pressure has attracted worldwide attention, in which theoretical research plays a vital role. So far, theoretical calculations show that the two e_g Ni 3d_x2-y2 and 3d_z2 orbitals in La₃Ni₂O₇ are crucial to the formation of superconductivity, while the O₂ p orbital also appears on the Fermi surface. Multi-orbital models have been proposed based on the above analysis. Various calculations show that La₃Ni₂O₇ has a s^± wave pairing symmetry although other pairing symmetries can be obtained. Theoretical calculations shows that the superconducting mechanism is unconventional and closely related to antiferromagnetic fluctuation. The vacancy of apical oxygen has a significant impact on the occurrence of superconductivity. The discovery of trilayer nickelate superconductor La₄Ni₃O₁₀ under pressure has further enriched the family of nickelate superconductors. And its electronic band structure, multi-orbital model, superconducting pairing symmetry and so on have been investigated and explored theoretically.

Taking citric acid-modified pepper straw-based biochar as the object, an optimal process for the adsorption process of methylene blue was studied. The dosage of modified carbon, methylene blue concentration, adsorption time, temperature, solution pH, and shaker speed were taken as investigation factors and methylene blue adsorption as investigation index, the Plackett-Burman (P-B) design was used to screen out the factors of significant effects. And further combined with the Box-Behnken Design (BBD) response surface method, the significant factors were optimized and verified and analyzed to obtain the optimal adsorption process parameters. The results showed that among the selected 6 factors, the order of significance affecting the adsorption capacity of methylene blue was modified carbon dosage > methylene blue concentration > shaking table rotation speed. The interaction effect between the significant factors was as follows: dosage of modified carbon and rotating speed of shaking table > dosage of modified carbon and concentration of methylene blue > concentration of methylene blue and rotating speed of shaking table. After optimization, the optimum adsorption conditions were obtained as follows: the dosage of modified carbon was 45.40 mg, the concentration of methylene blue was 86.00 mg/L, and the rotating speed of the shaking table was 130 r/min. Under these conditions, the adsorption capacity of methylene blue could reach 41.03 mg/g, the difference between the verified value and the model predicted value of 42.24 mg/g was 2.87%, therefore, the P-B/BBD method is stable and effective in optimizing the adsorption process of modified biochar for methylene blue, which provides a data reference for optimizing the adsorption process of carbon materials.

In recent years, the rapid development of artificial intelligence has had an important impact on mental health services such as psychological counseling and psychological assessment. In this paper the accuracy and methods of artificial intelligence in psychological assessment as well as ethical issues are reviewed. Based on the development of multi-modal and psychological intervention technology, the future application research of artificial intelligence in psychological assessment is forecast. It is believed that the application of artificial intelligence in psychological assessment in the future will pay more attention to individual needs and interdisciplinary cooperation. It will be more widely used in information collection, data analysis, humancomputer interaction technology, and non-invasive regulatory technology cooperation, and the ethical research of artificial intelligence will play a more important role in the future.

In view of the spectrum planning of China's carrier rocket, the positioning, rocket generation and scale divi-sion of carrier rocket system are put forward, and the focus of carrier rocket type spectrum planning is the third and 3.5 generations of medium and large disposable carrier rockets, as well as the fourth generation of reusable carrier rockets. This paper analyzes the technical development demand and capability development demand of the carrier rockets, and defines the power matching, rocket configuration, launch cost, carrying capacity, payload envelope and launch capacity of the carrier rockets. According to the technical developmen-tal needs and capability needs of the launch vehicles, 7 kinds of launch vehicles of the third generation ex-pendable launch vehicle spectrum, 6 kinds of launch vehicles of the 3.5 generation expendable launch vehicle spectrum, and 2 kinds of launch vehicles of the fourth generation reusable launch vehicle spectrum are pro-posed, respectively. Meanwhile, the evolution and replacement strategy of the second, third, 3.5 and fourth generations are proposed, namely the second launch vehicle is suggested to use until around year 2030, the third launch vehicle is suggested to use until around 2035, and the 3.5 and fourth generation launch vehicles are suggested to use around 2045 when the second and third generation launch vehicles are finally replaced.

With the rapid economic and social development, China's groundwater pollution becomes serious and urgently needs repairing. However, due to the diversity of pollution and complexity of hydrogeological conditions, many of the remediation techniques actually used are not the best option. At present, researchers have tried to establish and optimize the technical evaluation system of groundwater pollution remediation using a variety of evaluation methods, such as multi-criteria decision analysis method (MCDA), life cycle assessment method (LCA), cost-benefit analysis method (CBA), etc. Aiming at the problem that China still lacks perfect standards and legal norms to guide remediation decision-making this paper reviews the research progress of groundwater pollution remediation technology evaluation methods by means of literature research and compares and analyzes the advantages and disadvantages of different evaluation methods. The results show that MCDA has obvious advantages. In addition, when using AHP to construct the evaluation system, selection of evaluation indicators and determination of index weights have a significant impact on the evaluation results of groundwater remediation technology. In a word, in order to optimize the existing evaluation methods it is necessary to conduct more in-depth research on selection of evaluation indicators, determination of index weights, and organic combination of evaluation methods according to the actual situation in China.

As a non-carbon clean energy, geothermal energy plays an important role in promoting the development goals of carbon peak and carbon neutrality due to its advantages of stable and continuous supply. The utilization of geothermal energy is generally divided into geothermal power generation, geothermal direct utilization and geothermal energy storage. Since 2010, global geothermal direct utilization has grown exponentially, with the installed capacity of geothermal direct utilization and annual heat utilization of about 108 GWt and 283,580 GWh, respectively. China has long ranked first in the world in terms of geothermal direct utilization. The geothermal heat pump system shows an exponential growth of about 16% every year, and the geothermal heat pump system accounts for about 72% and 60% of the installed capacity and heat utilization of the global direct utilization of geothermal heat, respectively. The average annual growth rate of geothermal power generation from 2010 to 2020 is about 4% restricted by high-temperature geothermal resources. Geothermal energy storage is the frontier field of geothermal utilization. Europe and the United States have deployed the "HEATSTORE" and "Geothermal Battery" energy storage projects respectively. The geothermal energy storage project deployed by the Geothermal Team of the Chinese Academy of Sciences has also entered the stage of key technology research and demonstration projects construction. As a huge natural energy storage, geothermal storage is the most suitable basis for storing energy and realizing a stable supply of thermal energy in a multi-energy complementary system. It can save other energy sources across seasons, realize efficient and large-scale energy storage across seasons, and improve energy utilization efficiency. Therefore, it can help achieve the development goals of carbon peak and carbon neutrality.

Based on the research progress in real-world clinical study and artificial intelligence technology domestically and internationally, aiming at the issues of the concepts, methods, and technologies for conducting high-quality TCM real world clinical research, this article focuses on the challenges and solutions for the transformation of real world research paradigms, the establishment of clinical problem-oriented research models, the quality of real world data, and the methodology of inferring high-quality causal evidences. With a view to fully understanding the importance and difficulty of real world TCM research for the high-quality development of TCM from the ontological perspective of TCM clinical diagnosis and treatment, it is expected to provide reference for establishing a new real-world research system with TCM characteristics and creating a new model of TCM clinical research.

Aiming at the problems of current SG-CIM (state grid-common information model) such as difficult to achieve automatic update iteration and low efficient mining of new elements, an SG-CIM model automatic mapping technology based on BERT model and blocking filtering is proposed. On the basis of the existing SG-CIM, an SG-CIM knowledge map and data table knowledge graph are constructed at first. Secondly, by studying the entity alignment method based on BERT model and blocking filtering, the mapping relationship between the two knowledge graphs is established. Finally, the effectiveness of the proposed method is verified by experimental analysis of the text mapping effect. Results show that the accuracy of BERT model after finetuning on a self-made data set is more than 95%. This method lays a foundation for subsequent mining of new elements and automatic updating iteration of SG-CIM.

Plant soil negative feedback phenomena, such as continuous cropping obstacles, can lead to frequent diseases and decreased quality of medicinal plants. Rhizosphere microorganisms are important participants in the process of negative feedback between medicinal plants and soil. Therefore, elucidating the relationship between microorganisms and plants is crucial for clarifying the mechanism of negative feedback between medicinal plants and soil and solving continuous cropping obstacles. This article discusses the regulatory mechanism of the metabolism of root exudates of medicinal plants under continuous cropping conditions on the rhizosphere microbiota, as well as the formation mechanism of continuous cropping obstacles mediated by rhizosphere microbiota in the negative feedback between medicinal plants and soil. It clarifies the core regulatory role of rhizosphere microbiota in the feedback between medicinal plants and soil, as well as its correlation with the formation of continuous cropping obstacles. Taking plant soil feedback as the starting point, it further explores the plant soil microbial interaction system. It is proposed to slow down the negative feedback effect of plant soil from the aspects of improving planting mode, exploring molecular mechanism, biological pest control, etc., in order to provide theoretical support for solving the obstacles of continuous cultivation of medicinal plants.

Software-defined networking(SDN) is a new network architecture that simplifies the development of new applications and services through a centralized software-oriented management approach and has become a research hotspot for the next-generation Internet. To address the security issues in SDN, this paper reviews the existing solutions in terms of the 3-layer architecture of SDN and analyzes the technical challenges faced by SDN security. In particular, it firstly introduces the definition of SDN and the 3-layer architecture then reviews the research advances on security related to SDN. Next, it summarises the security issues and solutions to the application layer, control layer and data layer, respectively. Finally, it provides an outlook on the challenges that SDN security future research may encounter.

Ultrafast science employs ultrafast light sources and ultrafast measurement as the main approaches to understand, apply and control macroscopic matter through the measurement and manipulation of ultrafast kinetic processes of microscopic particles. As one of the most important frontiers in international science and technology, the development of ultrafast science will provide an important impetus for original innovation in numerous disciplines. Its breakthroughs will help to address many important issues related to the vital national needs and public health. This paper focuses on the research of ultrafast laser technology, ultrafast measurement technology and ultrafast dynamics in ultrafast science, mainly introducing their development status, frontier application and future prospect. In-depth analysis of the problems facing the development of ultrafast science in China is provided, and specific recommendations are proposed to promote its development, including strengthening top-level design, promoting industrialization, improving the evaluation mechanism for talent cultivation, supporting major scientific and technological infrastructures, and participating in international big science programs.

In 2023 the development of large generative AI models achieved a series of breakthroughs. This paper reviews the key technologies of large models that have received significant attention, including the emergent abilities of large language model(LLM), development of multimodal LLMs, as well as alignment and knowledge enhancement techniques of large models. The paper also introduces the vertical applications of generative AI in various fields such as healthcare and education, and its role in advancing the development of AI agents and metaverse technologies. Additionally, the challenges and developmental trends in generative AI are discussed, including issues related to data privacy, biased values, copyright disputes, and fake news propagation.

Triboelectric nanogenerator (TENG) has become an emerging platform technology for achieving mechano-electrical energy conversion, with huge application potentials in a variety of fields. For the past decade, through extensive efforts, significant progress on the research of TENG has been made worldwide, including both fundamental scientific research and application technology of TENGs. Therefore, this article aims to review the representative achievements of TENGs in fundamental findings and technological innovations and look forward to the faster development of TENGs.