Home Featured Articles List
Journal of Intelligent Construction

Smart aggregates: the future of infrastructure health monitoring

The proliferation of concrete infrastructure worldwide has been met with growing concerns over its durability and safety. Concrete structures are increasingly subjected to dynamic forces from natural disasters like earthquakes and environmental degradation, such as corrosion. These factors, coupled with the saturation of infrastructure projects, amplify the risks associated with structural failure. Consequently, there is a pressing need for effective structural health monitoring (SHM) systems that can preemptively identify and address these vulnerabilities. The development of piezoelectric smart aggregates (SAs) emerges as a promising solution to this critical challenge, paving the way for enhanced resilience in our built environments. Researchers from Tsinghua University, in collaboration with various institutions, have made significant progress in the development of piezoelectric SAs for SHM. Published in the Journal of Intelligent Construction on June 18, their review highlights the latest advancements in SA technology, emphasizing its potential in real-world applications. The review highlights significant advancements in piezoelectric SAs for SHM. SAs, embedded in concrete, are designed to monitor early-age concrete strength, detect impacts, and continuously assess structural health. The research emphasizes three main areas: technological advancements, expanded measurement ranges, and the integration of wireless communication. Notable developments include multidimensional SAs that improve detection accuracy and range, and wireless SAs (WSAs) that streamline data collection and reduce maintenance costs. Practical applications discussed include real-world scenarios such as crack monitoring and repair quality assessment in concrete structures. These innovations demonstrate the substantial benefits of SA technology in enhancing the durability and safety of infrastructure, providing a comprehensive solution for modern SHM needs. Dr. Pengfei Li, a key contributor to the research commented, "The advancements in piezoelectric SAs represent a significant leap forward in SHM. The integration of wireless technology and the development of multidimensional SAs provide a robust framework for ensuring the safety and longevity of modern infrastructures." The implementation of advanced piezoelectric SAs in SHM has profound implications for infrastructure maintenance and safety. These innovations enable continuous, real-time monitoring, allowing for early detection of potential issues and timely interventions. The advancements in SA technology promise to enhance the durability and reliability of structures, reduce maintenance costs, and improve overall safety, marking a new era in infrastructure management. This work was sponsored by the Open Research Fund Program of the State Key Laboratory of Hydroscience and Engineering (No. sklhse-2023-C-05) and the Natural Science Foundation of China (No. 52378267). See the article: Advances in the development of piezoelectric smart aggregates for structural health monitoring About Journal of Intelligent Construction Journal of Intelligent Construction (JIC), sponsored by Tsinghua University and the China National Committee on Large Dams, published by Tsinghua University Press (TUP) and exclusively available via SciOpen, is a peer-reviewed journal for publishing original research papers, case studies, reviews and comments regarding the use of novel technologies in all domains of civil engineering, e.g., hydraulic engineering, structural engineering, geotechnical engineering, transportation, and construction management. The journal focuses on the application of advanced theories, methodologies, and tools, such as machine learning, sensors, robotics, 5G, the Internet of Things, artificial intelligence, building information modelling, and computational methods, etc., in all stages of the construction life cycle, which makes the process more intelligent and efficient. The journal also covers other essential areas of civil engineering, e.g., planning and design, operation and maintenance, and disaster mitigation.
Physical Sciences and Engineering
Aging Research

Microglial mitochondria: key players in Alzheimer’s Disease progression

Alzheimer's disease (AD) is marked by severe neurodegeneration and cognitive decline, presenting significant challenges for its prevention and treatment. Traditional hypotheses have focused on amyloid-beta plaques and Tau pathology, but recent findings point to a significant role for microglial dysfunction and mitochondrial impairment. Given these challenges, there is a pressing need for deeper research into the mechanisms underlying AD. A team from the Laboratory of Aging Neuroscience and Neuropharmacology at China Pharmaceutical University and Chungnam National University published a review in January 2024, in the journal Aging Research. This research explores the interaction between microglial dysfunction and mitochondrial impairment in AD, offering new insights into the disease's progression. The study reveals that microglia, the primary immune cells in the central nervous system, play a crucial role in AD progression. Under normal conditions, microglia maintain neuronal homeostasis and clear metabolic byproducts. However, in AD, mitochondrial dysfunction leads to abnormal microglial activity, resulting in neuroinflammation and neuronal loss. The researchers emphasize the importance of maintaining mitochondrial homeostasis for proper microglial function. They highlight how metabolic disturbances and energy dysregulation in microglia significantly contribute to AD development. Additionally, the study explores mechanisms underlying microglial activation and its effects on neuronal health, focusing on the interplay between inflammatory pathways and mitochondrial dynamics. These findings suggest that targeting microglial mitochondria could be a promising therapeutic strategy to mitigate AD progression, providing a new direction for developing treatments that address the disease's root causes. Dr. Jian Sima, lead author of the study, states, "Our findings highlight the intricate relationship between microglial activity and mitochondrial function in AD. By understanding this connection, we can develop targeted therapies that address the root causes of microglial dysfunction, potentially slowing or even halting disease progression." This research underscores the potential of targeting microglial mitochondria as a therapeutic strategy for AD. By restoring mitochondrial function in microglia, it may be possible to reduce neuroinflammation and neuronal loss, thereby improving cognitive function in AD patients. These findings pave the way for developing novel treatments that could significantly impact how we approach Alzheimer's therapy in the future. See the article: The interaction between microglial dysfunction and mitochondrial impairment in Alzheimer’s disease About Aging Research Aging Research is a peer-reviewed, Open Access publication sponsored by Jinan University and published by Tsinghua University Press. It publishes original research in all areas of aging, longevity, aging related diseases and health issues, specific accepting the unusual significance or broad conceptual or technical advances results, the innovative phenotypic reporting without relevant mechanisms, innovative clinical case reports and studies with negative results. Aging Research aims to foster interactions among different areas of this diverse field of research and to promote new and exciting ideas within and beyond the research community, to enable synergy and maximize scientific and societal impact.
Life Sciences and Medicine
Circular Economy

From trash to treasure: machine learning enhances organic waste recycling

Biological treatment methods such as anaerobic digestion, composting, and insect farming are essential for managing organic waste, converting it into valuable resources like biogas and organic fertilizers. However, these processes often face challenges due to their inherent complexity and instability, which can affect efficiency and product quality. Traditional control strategies have limited success in addressing these issues. Therefore, advanced methods like machine learning (ML) are being explored to enhance prediction, optimization, and monitoring of these biological treatments, aiming to improve overall performance and sustainability. A research team from Tongji University published a review in Circular Economy on June 20, 2024, exploring the application of ML in the biological treatment of organic wastes. The article, available online, delves into the effectiveness of various ML algorithms in optimizing processes such as anaerobic digestion, composting, and insect farming, aiming to enhance treatment efficiency and product quality. This review provides an in-depth evaluation of ML applications in biological treatment processes, focusing on key algorithms such as artificial neural networks, tree-based models, support vector machines, and genetic algorithms. The research demonstrates how ML can accurately predict treatment outcomes, optimize process parameters, and enable real-time monitoring, significantly improving the efficiency and stability of processes like anaerobic digestion, composting, and insect farming. For example, ML models have been successfully used to forecast biogas production, determine compost maturity, and optimize growth conditions in insect farming. Additionally, the study addresses the challenges faced in applying ML, including model selection, parameter adjustment, and the need for practical engineering validation. By overcoming these hurdles, ML has the potential to revolutionize biological waste treatment, making it more efficient, reliable, and sustainable. Dr. Fan Lü, the corresponding author, emphasized, "ML offers unprecedented opportunities to enhance the efficiency and stability of biological treatment processes. By leveraging advanced algorithms, we can better predict and optimize these complex systems, ultimately contributing to more sustainable waste management solutions." The application of ML in biological treatment holds significant potential for improving waste management practices. By optimizing processes and ensuring consistent product quality, ML can help reduce environmental impacts and enhance resource recovery. Future research should focus on overcoming current challenges, such as improving model explainability and conducting practical engineering validations, to fully harness the potential of ML in this field. All the authors are grateful to the National Natural Science Foundation of China (52270138) and the International Science and Technology Cooperation Program of Shanghai Science and Technology Innovation Action Plan (22230712200) for supporting the present work. See the article: Applications of machine learning tools for biological treatment of organic wastes: Perspectives and challenges About Circular Economy Circular Economy (CE) is an international fully open-access journal co-published by Tsinghua University Press and Elsevier and academically supported by the School of Environment, Tsinghua University. It serves as a sharing and communication platform for novel contributions and outcomes on innovative techniques, systematic analysis, and policy tools of global, regional, national, local, and industrial park's waste management system to improve the reduce, reuse, recycle, and disposal of waste in a sustainable way. It has been indexed by Ei Compendex, Scopus, Inspec, and DOAJ. At its discretion, Tsinghua University Press will pay the Open Access Fee for all published papers from 2022 to 2024.
Physical Sciences and Engineering
iEnergy

From grey to green: unveiling the future of renewable e-methanol for cleaner shipping fuels

Methanol is a crucial chemical feedstock and a potential green fuel, particularly for the shipping industry. Currently, its production predominantly relies on fossil feedstocks, leading to high greenhouse gas emissions. With the global push towards decarbonization, there is an urgent need to explore cleaner alternatives like renewable e-methanol. Based on these challenges, there is a need for in-depth research to develop sustainable methanol production methods. A team of researchers from Tsinghua University, the Tsinghua-Sichuan Energy Internet Research Institute, and the Methanol Institute conducted a study, published in July 2024 in iEnergy. The study investigates the feasibility of producing renewable e-methanol using different carbon sources, including bio-carbon, direct air capture (DAC), fossil fuel carbon capture (FFCC), and fossil sources. By comparing the lifecycle greenhouse gas emissions and production costs of these e-methanols, the research aims to identify the most promising pathways for commercializing green methanol. The study evaluates the lifecycle greenhouse gas emissions and production costs of four types of renewable e-methanol, each using different carbon sources: bio-carbon, DAC, FFCC, and fossil sources. The findings reveal that renewable e-methanol significantly reduces greenhouse gas emissions, with bio-carbon and DAC methods showing negative emissions. However, the production costs of renewable e-methanol (ranging from 4167 to 10250 CNY per tonne) are currently 2-4 times higher than conventional methanol. Key factors influencing cost-effectiveness include the availability of green carbon sources and the e-hydrogen cost depending on power generation and chemical process flexibility. The study suggests that the declining e-hydrogen costs and appropriate carbon taxes, could pave the way for blue methanol to initially compete with fossil fuels in the shipping industry. As the industry advances, green renewable methanol is poised to further enhance its competitiveness, ultimately replacing diesel and heavy fuel oil and driving substantial emission reductions. Dr. Jin Lin, a lead researcher at Tsinghua University, stated, "Our findings underscore the potential of renewable e-methanol to serve as a sustainable fuel alternative. By addressing the cost and availability of e-hydrogen and green carbon, we can pave the way for its commercial adoption and contribute to global decarbonization efforts." Renewable e-methanol has promising applications in the shipping industry, where it can replace diesel and heavy fuel oil, reducing carbon emissions significantly. Future research and policy efforts should focus on lowering e-hydrogen costs and enhancing the supply of green carbon sources. The successful commercialization of renewable e-methanol could play a critical role in achieving global sustainability goals. This work was supported by the National Natural Science Foundation of China (U22A20220) and the China Postdoctoral Science Foundation (2023M741887). See the article: Feasibility study of renewable e-methanol production: A substitution pathway from blue to green About iEnergy iEnergy (Published by Tsinghua University Press), has multiple meanings, intelligent energy, innovation for energy, internet of energy, and electrical energy due to “i” is the symbol of current. iEnergy, publishing quarterly, is a cross disciplinary journal aimed at disseminating frontiers of technologies and solutions of power and energy. The journal publishes original research on exploring all aspects of power and energy, including any kind of technologies and applications from power generation, transmission, distribution, to conversion, utilization, and storage. iEnergy provides a platform for delivering cutting-edge advancements of sciences and technologies for the future-generation power and energy systems.
Information Sciences
Energy Materials and Devices

Unlocking solar efficiency: a leap in perovskite solar cell technology

Perovskite solar cells (PSCs) are celebrated for their exceptional photovoltaic performance and affordability. However, the high cost of charge transport materials remains a major obstacle to their commercialization. Conventional materials like 2,2',7,7'-Tetrakis[N,N-di(4-methoxyphenyl)amino]-9,9'-spirobifluorene (Spiro-OMeTAD), are expensive and complex to produce. Therefore, developing low-cost, efficient alternatives is essential to make PSCs more economically viable. Addressing these issues is crucial for advancing solar technology and achieving broader adoption. Hence, this study focuses on creating cost-effective hole transport materials to overcome these barriers and enhance the commercial potential of PSCs. Researchers from Huaqiao University and Qufu Normal University have unveiled a pioneering advancement in the field of solar energy. Their study (DOI: 10.26599/EMD.2024.9370036), published in June 2024 in the esteemed journal Energy Materials and Devices, introduces three novel hole transport materials that could redefine the efficiency of n-i-p PSCs. These materials, meticulously designed and synthesized, exhibit remarkable properties that have the potential to surpass the current benchmarks in solar cell performance, offering a promising step towards the future of renewable energy. This study presents the development of three cost-effective hole transport materials (HTMs), 4,4'-(3,3'-bis(4-methoxy-2,6-dimethylphenyl)-[2,2'-bithiophene]-5,5'-diyl)bis(N,N-bis(4-methoxyphenyl)aniline) (TP-H), 4,4'-(3,3'-bis(4-methoxy-2,6-dimethylphenyl)-[2,2'-bithiophene]-5, 5'-diyl)bis(3-methoxy-N,N-bis(4-methoxyphenyl)aniline) (TP-OMe), and 4,4'-(3,3'-bis(4-methoxy-2,6-dimethylphenyl)-[2,2'-bithiophene]-5,5'-diyl)bis(3-fluoro-N,N-bis(4-methoxyphenyl)aniline) (TP-F), using a bithiophene core. These materials were designed to enhance molecular crystallinity and solubility, crucial for effective hole transport in PSCs. TP-F, in particular, achieved a power conversion efficiency (PCE) exceeding 24%, attributed to its fluorine atom substitution, which enhanced intermolecular packing, lowered the highest occupied molecular orbital (HOMO) energy level, and improved hole mobility and conductivity. These improvements reduced defect states and minimized trap-mediated recombination in PSCs. The study highlights the potential of the 3,3'-bis(4-methoxy-2,6-dimethylphenyl)-2,2'-bithiophene core structure for creating efficient, low-cost HTMs, demonstrating significant advancements in PSC technology and paving the way for more commercially viable solar energy solutions. Dr. Wei Gao, a leading researcher in the study, stated, "The development of these novel HTMs marks a significant step towards making PSCs more commercially viable. The enhanced efficiency and reduced costs of these materials could accelerate the adoption of PSCs in the solar energy market, providing a more sustainable and cost-effective energy solution." The implications of this research are profound, as it opens up new avenues for the commercial production of high-efficiency, low-cost PSCs. The successful integration of TP-F into PSCs demonstrates the potential for these materials to significantly reduce production costs while maintaining high performance. This advancement could lead to broader adoption of solar energy technologies, contributing to global efforts in sustainable energy development and reducing reliance on fossil fuels. This work was financially supported by the National Natural Science Foundation of China (Grant Nos. U23A20371, U21A2078, and 22179042), the Natural Science Foundation of Fujian Province (Grant No. 2023J06034), the Natural Science Foundation of Xiamen, China (Grant No. 3502Z20227036), and the Scientific Research Funds of Huaqiao University (Grant No. 605-50Y23024). See the article: Bithiophene-based cost-effective hole transport materials for efficient n–i–p perovskite solar cells  About Energy Materials and Devices Energy Materials and Devices is launched by Tsinghua University, published quarterly by Tsinghua University Press, exclusively available via SciOpen, aiming at being an international, single-blind peer-reviewed, open-access and interdisciplinary journal in the cutting-edge field of energy materials and devices. It focuses on the innovation research of the whole chain of basic research, technological innovation, achievement transformation and industrialization in the field of energy materials and devices, and publishes original, leading and forward-looking research results, including but not limited to the materials design, synthesis, integration, assembly and characterization of devices for energy storage and conversion etc.
Physical Sciences and Engineering
Food & Medicine Homology

Utilizing food as medicine: a modern exploration of an old practice

While this concept may have been the norm hundreds of years ago, many present-day societies are overfed and undernourished, leading to floods of health issues in many populations. Getting back to the basics might be a large part of the solution  We’ve all heard “you are what you eat,” but mostly we hear it used to describe the unfortunate health effects one might have after a prolonged unhealthy diet. However, it can go the other way around. Using the text of Yinshan Zhengyao, researchers are bringing an old established concept of using food to treat ailments under the light of a modern context, with the added benefits of the current knowledge of genetics and metabolism to help propel the teachings of Yinshan Zhengyao into the public eye once again. Researchers published their results in Food and Medicine Homology on 19 June 2024. “Yinshan Zhengyao is the world’s first authoritative nutritional treatise, compiled by Hu Sihui, a dietitian of the Yuan dynasty. This work embodies the traditional Chinese medicinal concept of ‘homology of food and medicine,’ rich in the cultural heritage of the Chinese nation,” said, Min-Hui Li, researcher and author of the study. Yinshan Zhengyao comprises 174 medicinal plants across 55 unique plant families and 111 genera. These plants are indispensable to the culture of traditional Chinese medicine (TCM). Another highly important piece of this traditional Chinese text is the power of the mind and mood over the human body. Cheerfulness and tranquility are aspects that are emphasized in Yinshan Zhengyao, as the mind-body connection can be as important as the fuel taken in by an individual. “In Yinshan Zhengyao, dietary therapies are particularly interesting for their effects on regulating digestion, respiration, endocrine, and nervous system functions, as well as protecting and regulating various organs,” said Li. The foundation of this text is to provide treatment (and prevention) of chronic diseases through the use of plants, but also by instilling the importance of quality food in society. By viewing food as medicine, greater emphasis and care are put into the preparation and consumption of food by “putting the food to work” not only as a source of energy but as a source of longevity. In TCM, diseases come from imbalances in the body. For example, kidneys are seen as organs that work closely with the reproductive system and the regulation of fluid metabolism. Modern discoveries show that kidneys, in addition to being an important part of the urinary system, are also related to maintaining fluid balance and endocrine function. Treating one part of the body can have a cascade of effects that one might not have imagined would be related, such as lumbar pain or limb weakness as a result of renal (kidney) issues. With the Yinshan Zhengyao text hailing back to the early 14th century, modern medicines and therapies can be used in conjunction with the plant and diet information available from this early work on diet, health and nutrition. Professor Min-Hui Li and his team propose the integration of modern information to explore and analyze healthcare’s use of medicine and parallel food sources. By studying modern applications of health and medicine, like the human genome, metabolism and regulatory networks and relationships, researchers aim to continue helping the forward movement of enhancing human health along with bringing the idea of food as medicine into a larger, more modern lens. Hui Niu, Aruhan, Chun-Hong Zhang and Min-Hui Li of the Department of Pharmacy at Baotou Medical College with Hui Niu and Min-Hui Li also of the Inner Mongolia Autonomous Region Hospital of Traditional Chinese Medicine and the Inner Mongolia Traditional Chinese & Mongolian Medical Research Institute, Seesregdorj Surenjidiin of the Mongolian National University of Medical Sciences, and Li-Ming Zhang of the Ningcheng County of Traditional Chinese and Mongolian Medicine Hospital contributed to this research. The National Key Research and Development Program of China, Special Survey of Basic Scientific and Technological Resources, China Agriculture Research System of MOF and MARA, “Innovation Team Development Plan” of Colleges and Universities in Inner Mongolia Autonomous, Inner Mongolia Autonomous Region Chinese Medicine, Young and Middle-Aged Leading Talents Cultivation Project and National Natural science Foundation of China made this research possible. See the article: Yinshan Zhengyao: exploring the power of food and inheriting healthy thoughts About Food & Medicine Homology Food & Medicine Homology is a peer-reviewed, cross-disciplinary, open access journal dedicated to cutting-edge research integrating findings in food science and medicine. The journal publishes papers dealing with plants, animals and microorganisms, reporting the food resources and base materials with nutritional and medicinal values and health-promoting effects that are discovered and confirmed using modern scientific theories and technologies, and providing insights into their health-promoting functions, underlying molecular mechanisms of action and regulatory modes.
Life Sciences and Medicine
Tsinghua Science and Technology

Focusing Ability Enhancement in Broadside Direction of Array: From UCA to UCCA

A new method to combat the degradation of the radial focusing ability of near-field beams in the broadside of circular arrays, providing a way to further enlarge the near-field region for 6G communications Benefits of emerging near-field communications: The progression of 5G mobile communication commercialization has spurred anticipation for 6G communication. To support emerging applications like digital twins, holographic video, and augmented reality (AR), extremely large-scale antenna array (ELAA) is regarded as key candidates for future 6G mobile communication due to its potential to enhance spectrum efficiency. “Compared with 5G massive multiple-input multiple-output (MIMO) systems, 6G ELAA not only entails an increase in the number of antennas, but also signifies a fundamental shift in electromagnetic field from far-field planar waves to near-field spherical waves.” Said by Prof. Linglong Dai, a Full Professor in the Department of Electronic Engineering of Tsinghua University, “The spherical-wave-based near-field communications brought new possibilities for performance enhancement of wireless communications.” In contrast to far-field massive MIMO systems primarily relying on the orthogonality of far-field beams in the angular domain, the spherical wave propagation characteristics enable near-field beams to possess the additional radial focusing ability. In such a way, multiple users could be simultaneously served by different near-field beams, which is promising to further enhance the spectrum efficiency in multi-user communications. Degradation of radial focusing ability with UCA: To enable more users to benefit from near-field communications, it is desired to expand the near-field range through array topology design. However, existing research on classical circular arrays claimed that, while significantly expanding the near-field range in the azimuthal dimension, circular array faces reduced near-field range in the broadside direction, rendering users unable to fully exploit near-field communication gains. Methods: To overcome this challenge, a novel method was proposed in a recent article [1] of Prof. Dai’s research team, where the classical UCA topology was generalized into UCCA to enhance the radial focusing ability of arrays. “As the elevation angle increases, the phase differences of electromagnetic waves between different antennas are decreasing in spherical-wave model, resulting the declining radial focusing ability”, noted by Zidong Wu, one team member of Prof. Dai’s lab. To address this, the article proposes to generalize UCA into UCCA, transforming single-ring array configurations into multi-ring array configurations to further increase the phase difference of electromagnetic waves, thereby enhancing the resolution near-field beams of ELAA. Through numerical simulations, it is demonstrated that UCCA-based ELAA could not only improve the spatial utilization efficiency while also significantly enhancing radial beam focusing capability. With the improvement of radial focusing capability, UCCA can significantly expand the near-field range in the broadside direction, providing new possibilities for enhancing the performance of multi-user near-field communication systems. For more information, please pay attention to the research homepage: http://oa.ee.tsinghua.edu.cn/dailinglong/.   [1] Z. Wu and L. Dai, “Focusing ability enhancement in broadside direction of array: From UCA to UCCA,” Tsinghua Science and Technology, vol. 29, no. 5, pp. 1593-1603, May 2024. See the article: Focusing Ability Enhancement in Broadside Direction of Array: From UCA to UCCA About Tsinghua Science and Technology Tsinghua Science and Technology is sponsored by Tsinghua University and published bimonthly, 2023 Impact Factor of 5.2, ranking in Q1 in the "Computer Science, Software Engineering", "Computer Science, Information System", and "Engineering, Electrical & Electronic" areas in SCIE, according to JCR 2023. This journal aims at presenting the achievements in computer science, electronic engineering, and other IT fields. This journal has been indexed by SCIE, EI, Scopus, etc. Contributions all over the world are welcome.
Information Sciences
Carbon Future

Nanocarbon catalyst design unlocks new avenue for sustainable fuel additive production

Vehicle exhaust from fossil fuel combustion constitutes a main source of air pollutants like carbon dioxide and carbon monoxide. To mitigate air pollution, researchers are looking into additive to fuels like dimethoxymethane (DMM). But DMM production brings its own environmental hazards. In their paper published June 21 in Carbon Future, a Chinese research team demonstrated how a series of phosphorous-modified nanocarbon catalysts could advance green DMM production. Unique fuel properties of this diesel blend fuel include high oxygen content and chemical stability as well as low toxicity. A blend of DMM and conventional diesel fuels has been shown to reduce soot formation by as much as 80%. Commercially, DMM is produced via an established two step-process of methanol oxidation forming formaldehyde, followed by coupling with methanol. However, this conventional synthetic route is complex and environmentally unfriendly due to the complicated sequenced reactions and the use of hazardous acidic catalysts. To overcome these drawbacks, researchers have been exploring alternative methods to produce DMM. In one promising route, the use of non-metallic nanocarbon materials as catalyst enables the production of DMM in one step. Non-metallic nanocarbon-based catalysts have emerged in recent years as sustainable, reliable alternatives to the metal catalysts that have traditionally been used as supports in chemical reactions. “One-step synthesis of DMM via selective oxidation of methanol under the catalysis of nanocarbon is a green and sustainable but challenging chemical process,” said Wei Qi from the University of Science and Technology of China. “Nanocarbon materials have demonstrated notable activity and stability in various catalytic reactions.” However, achieving one-step synthesis of DMM via methanol conversion requires striking a delicate balance between redox (oxidation-reduction reaction) and acid sites, and there are still many unanswered questions regarding nano carbon catalysts.   For instance, the performance of nanocarbon materials is significantly influenced by functional groups on the surface — but, so far, nanocarbon materials exhibit uncontrollable surface functional groups, which complicates the identification of active sites for different types of reactions. Recent studies have shown how modifying nanocarbons with nonmetallic heteroatom can effectively adjust surface characteristics and redox/acidic catalytic activity to achieve highly efficient and selective DMM synthetic routes. Expanding on this line of research, the Chinese research team prepared a series of phosphorus-modified carbon catalysts for the one-step synthesis of DMM from methanol. With this approach, the team achieved high methanol conversion and DMM formation rate simultaneously. Through extensive characterization and corresponding control experiments, their research revealed that the covalent linkage of phosphorus and nanocarbon (namely a bond where a carbon atom and a phosphorus atom share a pair of electrons) is a key factor contributing to high DMM selectivity, which indicates efficiency and precision with a catalyst converts raw materials into the fuel additive products. “This work provided not only a novel and sustainable carbon-based catalyst for the one step synthesis of DMM but also deep insights into the rational design of nanocarbon catalyst for related reaction system,” Qi said. Their publication provided a new idea for the design of novel nanocarbon materials as well as a potential green catalyst for the efficient selective conversion of methanol to DMM. The research was supported by the natural Science Foundation of Liaoning province of China, China Baowu Low Carbon Metallurgy Innovation Foundation and Shccig-Qinling program. Other contributors include Xueya Dai, Pengqiang Yan, Yunli Bai and Miao Guo from the Institute of Metal Research at the Chinese Academy of Sciences. Dai and Bai are also associated with the University of Science and Technology of China.   See the article: Phosphorus modified onion-like carbon catalyzed methanol conversion to dimethoxymethane: The unique role of C–P species About Carbon Future Carbon Future is an open access, peer-reviewed and international interdisciplinary journal, published by Tsinghua University Press and exclusively available via SciOpen. Carbon Future reports carbon-related materials and processes, including catalysis, energy conversion and storage, as well as low carbon emission process and engineering. Carbon Future will publish Research Articles, Reviews, Minireviews, Highlights, Perspectives, and News and Views from all aspects concerned with carbon. Carbon Future will publish articles that focus on, but not limited to, the following areas: carbon-related or -derived materials, carbon-related catalysis and fundamentals, low carbon-related energy conversion and storage, low carbon emission chemical processes.
Physical Sciences and Engineering
Journal of Advanced Ceramics

Self-assembled Na-doped zinc oxide for the detection of lung cancer biomarker VOCs at low concentrations

Developing high-performance gas sensors for the detection of lung cancer markers at low concentrations is a crucial step towards achieving early lung cancer monitoring through breath tests. Metal Oxide Semiconductors (MOS) have long been sensitive to Volatile Organic Compounds (VOCs), demonstrating excellent performance characteristics. However, the concentration of characteristic VOCs for lung cancer detection based on breath tests (such as formaldehyde, isopropanol, acetone, and ammonia) is typically less than 1ppm. Most metal oxides struggle to respond at such low concentrations, which can impact the early diagnosis of lung cancer. Gas sensors based on metal oxide semiconductors (MOS) have shown promise in detecting VOCs, but their effectiveness at very low concentrations remains a challenge. The concentration of lung cancer biomarker VOCs (such as formaldehyde, isopropanol, acetone, and ammonia) in breath samples are often below 1 ppm, making it difficult for most metal oxides to generate a high response. Overcoming this limitation is essential for improving early lung cancer diagnosis. To address the above-mentioned challenges, a team of material scientists led by Professor Chao Zhang from the Institute of Surface Engineering at Yangzhou University, China, recently outlined the development of alkali metal ion doped ZnO nanoneedles, specifically doped with sodium Na ions, assisted by citric acid. This approach aims to enhance the performance of metal oxide-based electrochemical gas sensors, enabling high responsiveness for detecting VOCs at low concentrations." The team published their study in Journal of Advanced Ceramics on April 30, 2024. “Metal ion doping is effectively used to improve the sensing performance of ZnO. Specially, ZnO is highly sensitive to alkali metal elements and exhibits good doping stability, which will make it easier for ions to be doped into the lattice of ZnO, leading to the formation of more oxygen vacancies. In addition, the solubility of alkali metals in the ZnO lattice is closely related to the radius of the dopant ions, and a low concentration of doping will make it difficult to generate the acceptor energy level. Na ions have a higher radius than Zn ions and show high solubility. It is favorable to improve the stable concentration of Na doping, leading to the formation of the shallow acceptor level.” said Chao Zhang, senior author of the study. The researchers used a solvothermal method to fabricate three-dimensional nanoneedles of Na-doped ZnO with different amounts of citric acid. The team evaluated the gas sensing properties of Na-doped ZnO to lung cancer biomarkers at sub-ppm concentrations, the preparation method was optimized, and the optimum ratio of citric acid and Na ion was obtained. The experimental showed that the Na-doped ZnO gas sensor exhibited a high sensitivity (~ 21.3@5ppm/50% RH) to lung cancer biomarker VOCs at low concentrations, which is 7 times higher than that of pure ZnO. In addition, the resulting gas sensor exhibited excellent selectivity for formaldehyde, good humidity resistance, and reliable repeatability at an optimal temperature of 225°C. In addition, the researchers explained the mechanism of the improved gas-sensitive performance. the Na ions replaced the Zn ion centers to produce more oxygen vacancies, which increased the concentration of oxygen defects (Ov= 20.98%), and the target gas adsorption sites were increased. Moreover, Na was introduced as an impurity energy level to become the acceptor energy level close to the top of the valence band, which was in contact with the valence band of the pure ZnO, which lowered the width of bandgap, and further stimulated the electron leaps, thus improving the gas-sensitive performance. This work was supported by the Outstanding Youth Foundation of Jiangsu Province of China (No. BK20211548), the Yangzhou Science and Technology Plan Project (No. YZ2023246), the Qinglan Project of Yangzhou University, and the Research Innovation Plan of Graduate Education Innovation Project in Jiangsu Province (No. KYCX23_3530). See the article: Urchin-like Na-doped zinc oxide nanoneedles for low-concentration and exclusive VOC detections About Journal of Advanced Ceramics Journal of Advanced Ceramics (JAC) is an international journal that presents the state-of-the-art results of theoretical and experimental studies on the processing, structure, and properties of advanced ceramics and ceramic-based composites. JAC is Fully Open Access, monthly published by Tsinghua University Press on behalf of the State Key Laboratory of New Ceramics and Fine Processing (Tsinghua University) and the Advanced Ceramics Division of the Chinese Ceramic Society, and exclusively available via SciOpen. JAC has been indexed in SCIE (IF = 16.9, top 1/28, Q1), Scopus, and Ei Compendex.
Ceramics
CAAI Artificial Intelligence Research

Sweeping review reveals impact of integrating artificial intelligence technologies into photovoltaic systems

Artificial intelligence is poised to bring photovoltaic systems into a new era through revolutionary improvements in efficiency, reliability, and predictability of solar power generation. In their paper published on May 8 in CAAI Artificial Intelligence Research, a research team from Chinese and Malaysian universities explored the impact of artificial intelligence (AI) technology on photovoltaic (PV) power generation systems and their applications from a global perspective. “The overall message is an optimistic outlook on how AI can lead to more sustainable and efficient energy solutions,” said Xiaoyun Tian from Beijing University of Technology. “By improving the efficiency and deployment of renewable energy sources through AI, there is significant potential to reduce global carbon emissions and to make clean energy more accessible and reliable for a broader population.” The team, which included researchers from Beijing University of Technology, Chinese Academy of Sciences, Hebei University, and the Universiti Tunku Abdul Rahman, focused their review on pivotal applications of AI in maximum power point tracking, power forecasting and fault detection within PV systems. The maximum power point (MPP) refers to the specific operating juncture where a PV cell or an entire PV array yields its peak power output under prevailing illumination conditions. Tracking and exploiting the point of maximum power, mainly by adjusting the operating point of the PV array to maximize output power, is an important problem in solar PV systems. Traditional methods are plagued by defects, resulting in issues like reduced efficiency, wear on hardware and suboptimal performance during sudden weather changes. The researchers reviewed publications demonstrating how AI techniques can achieve high performance in solving the MPP tracking problem. They compiled publication methods that presented both single and hybrid AI methods to solve the tracking problem, exploring the advantages and disadvantages of each approach. The team reviewed publications that presented AI algorithms applied in PV power forecasting and defect detection technologies. Power forecasting, which refers to predicting the production of PV power over a certain incoming period, is crucial for PV grid integration because the share of solar energy in the mix increases every year as well as the PV generation has intermittent nature that may impact the grid stability. Fault detection in PV systems can detect and locate various types of failures in the PV system, such as environmental changes, panel damage and wiring failures. For large-scale PV systems, traditional manual inspection is almost impossible and passive. AI algorithms can step in where manual inspection falls short, identifying deviations from normal operating conditions that may indicate faults or anomalies proactively. The research team combed through the literature that presented single and hybrid AI methods to solve both problems. By comparing AI-driven techniques, the team explored and presented advantages and disadvantages of each approach. While integrating AI technology optimizes and improves the operational efficiency of PV systems, new challenges continue to arise. These challenges are driven by issues such as revised standards for achieving carbon neutrality, interdisciplinary cooperation, and emerging smart grids. The researchers highlighted some emerging challenges and the need for advanced solutions in AI, such as transfer learning, few-shot learning and edge computing. According to the paper’s authors, the next steps should focus on further research directed towards advancing AI techniques that target the unique challenges of PV systems; practical implementation of AI solutions into existing PV infrastructure on a wider scale; scaling up successful AI integration; developing supportive policy frameworks that encourage the use of AI in renewable energy; increasing awareness about the benefits of AI in enhancing PV system efficiencies; and ultimately aligning these technological advancements with global sustainability targets. “AI-driven techniques are essential for the future development and widespread adoption of solar-energy technologies globally,” Tian said. The research was supported by the National Key R&D Program of China and Fundamental Research Grant Scheme of Malaysia. The grants are parked under China-Malaysia Intergovernmental Science, Technology and Innovation Cooperative Program 2023. Other contributors include Jiaming Hu, Kang Wang and Dachuan Xu from Beijing University of Technology; Boon-Han Lim from Universiti Tunku Abdul Rahman; Feng Zhang from Hebei University; and Yong Zhang from Shenzhen Institute of Advanced Technology, the Chinese Academy of Science. See the article: A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems About CAAI Artificial Intelligence Research CAAI Artificial Intelligence Research (CAAI AIR) is an Open Access, peer-reviewed scholarly journal, published by Tsinghua University Press, released exclusively on SciOpen. CAAI AIR aims to publish the state-of-the-art achievements in the field of artificial intelligence and its applications, including knowledge intelligence, perceptual intelligence, machine learning, behavioral intelligence, brain and cognition, AI chips and applications, etc. Original research and review articles on but not limited to the above topics are welcome. The journal is completely Open Access with no article processing fees for authors.      
Information Sciences
Total 98