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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

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

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.

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

New catalyst brings commercial high-efficiency zinc-air batteries closer to reality

The effective conversion from fossil fuel-based to renewable energy sources requires cost-efficient, high-capacity, rechargeable batteries. Zinc-air batteries (ZAB) can theoretically store large amounts of energy, but current technologies require the use of expensive noble metal catalysts, or agents that speed a chemical reaction, that underperform in charging and discharging reactions. A new metal-nitrogen-carbon catalyst has been developed for use in ZABs that outperform noble metal catalysts, improving the efficiency and practicality of ZAB technology. ZABs function by oxidizing zinc with oxygen from the air. Recent research demonstrated that a catalyst incorporating a combination of different non-noble metal atoms could increase the rate of discharging reactions and battery performance. With this evidence in mind, a group of researchers from Hunan University, University College London and the University of Oxford generated a non-noble metal-nitrogen-carbon catalyst from iron, cobalt and nickel (Fe, Co and Ni, respectively) to improve the charging, discharging and cost efficiency of ZABs. Importantly, the team also optimized a flexible carbon dot/polyvinyl alcohol (CD/PVA) film as a solid-state ZAB electrolyte, or battery component that transfers charged atoms, creating a flexible and stable high-performance battery that could potentially be used in wearable devices. The team published their study in the journal Nano Research Energy on May 17, 2024. “Rechargeable metal–air batteries are promising power sources, especially zinc-air batteries (ZABs) which offer high theoretical energy densities (1084 Wh kg−1), environmental friendliness, and cost effectiveness. Additionally, rechargeable ZABs are not only safe and stable but also portable and wearable. Significant research is currently focused on rechargeable and flexible ZABs,” said Huanxin Li, research fellow in the Department of Chemistry at the University of Oxford, senior author of the paper and leader of this project. ZABs discharge and charge through two reactions: the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER), respectively. These reactions are notoriously slow and require catalysts that speed the electrochemical reaction along, or electrocatalysts. While noble metals are capable of speeding the ORR and OER, issues with cost, suboptimal performance and the requirement of two different noble metals limited the overall practicality of ZAB technology. “Developing low-cost and efficient bifunctional non-noble electrocatalysts is crucial to the commercialization of rechargeable ZABs. Among various non-noble catalysts, metal-nitrogen-carbon (M-N-C) nanomaterials have attracted particular attention due to their low price, abundant reserves, excellent electrochemical activity and high stability,” said Dr. Li. Creating an electrocatalyst composed of three different metal atoms isn’t a trivial matter, however, due to the different interaction forces that occur with each metal atom. To address this issue, the team used zeolitic imidazolate frameworks (ZIFs), carbon-nitrogen frameworks that surround and arrange each of three metal atoms (Fe, Co and Ni), to uniformly anchor the catalytic atoms onto porous carbon at high heat. The team confirmed the distribution of the Fe, Co and Ni atoms via energy-dispersive X-ray spectroscopy (EDX), spherical aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (AC-HAADF-STEM) and electron energy loss spectroscopy (EELS). Overall, the ternary Fe-Co-Ni electrocatalyst outperformed bimetal electrocatalysts (FeNi, FeCo and CoNi) and platinum and ruthenium, two noble metal electrocatalysts, in the oxygen reduction and evolution reactions. The team believes that all three metal atoms of the ternary electrocatalyst are active and cooperating to increase catalytic activity, with Fe contributing the most to activity as the most abundant atom. The porous structure and increased surface area of the electrocatalyst likely also contributes to the enhanced catalytic activity. Overall, the team’s rechargeable ZAB achieved a specific capacity of 846.8 mAh·g Zn−1 and a impressive power density of 135 mW·cm–2 in liquid electrolyte. The ZAB also achieves a power density of 60 mW·cm–2 using the team’s optimized CD/PVA solid-state electrolyte, which exceeds reported results of solid-state ZABs with other catalysts. Importantly, the ZAB developed in the study was both durable and stable and capable of powering a fan and an LED screen and charging a mobile phone. The researchers are hopeful that their ternary Fe-Co-Ni electrocatalyst and CD/PVA electrolyte will spur investigations into new catalysts and electrolytes for practical, high-performance ZAB technologies. Other contributors include Shifeng Qin, Mengxue Cao and Zhongyuan Huang from the College of Chemistry and Chemical Engineering at Hunan University in Changsha, China; Kaiqi Li, Guanjie He and Ivan P. Parkin from the Department of Chemistry at the University College London in London, UK; and Wuhua Liu from Guizhou Dalong Huicheng New Material Co., Ltd, in Tongren, China. This research was supported by the National Natural Science Foundation of China (No. 21908049), China Postdoctoral Science Foundation (No. 2020M682560), Science and Technology Innovation Program of Hunan Province (No. 2020RC2024), Hunan Provincial Natural Science Foundation of China (No. 2022JJ40035), Chinese Universities Scientific Fund (No. 15052001), Engineering and Physical Sciences Research Council (EP/L015862/1), the joint PhD funding from China Scholarship Council and UCL Dean’s Prize. See the article: Fe-Co-Ni ternary single-atom electrocatalyst and stable quasi-solid-electrolyte enabling high-efficiency zinc-air batteries About Nano Research Energy Nano Research Energy is launched by Tsinghua University Press and exclusively available via SciOpen, aiming at being an international, open-access and interdisciplinary journal. We will publish research on cutting-edge advanced nanomaterials and nanotechnology for energy. It is dedicated to exploring various aspects of energy-related research that utilizes nanomaterials and nanotechnology, including but not limited to energy generation, conversion, storage, conservation, clean energy, etc. Nano Research Energy will publish four types of manuscripts, that is, Communications, Research Articles, Reviews, and Perspectives in an open-access form.
Nanoscience and Nanotechnology

Nanoparticle catalysts convert carbon dioxide to carbon monoxide to make useful compounds

As a greenhouse gas, carbon dioxide (CO2) contributes to climate change as it accumulates in the atmosphere. One way to reduce the amount of unwanted CO2 in the atmosphere is to convert the gas into a useful carbon product that can be used to generate valuable compounds. A recent study attached nanoparticle of beta phase molybdenum carbide (β-Mo2C) catalysts on a silicon dioxide (SiO2) support to speed the conversion of CO2 into more useful carbon monoxide (CO) gas. CO2 is a very stable molecule, which makes conversion of the greenhouse gas into other molecules challenging. Catalysts can be used in chemical reactions to lower the amount of energy required to form or break chemical bonds and are used in the reverse water gas shift (RWGS) reaction to convert CO2 and hydrogen gas (H2) into CO and water (H2O). Importantly, the CO gas produced by the reaction is called syngas, or synthesis gas, when combined with H2 and can be used as a carbon source to create other important compounds. Traditional catalysts in the RWGS reaction are made from precious metals, including platinum (Pt), palladium (Pd) and gold (Au), limiting the cost efficiency of the reaction. Because of this, new catalyst materials and formation methods are developed to increase the practicality of the RWGS reaction as a means of lowering atmospheric CO2 and generating syngas. In order to address the cost issues of traditional RWGS catalysts, a team of researchers from the University of Illinois in Urbana-Champaign studied the formation and catalytic activity of cheaper nanoparticle β-Mo2C catalysts on a SiO2 support to determine if the lower-cost catalyst could enhance activity levels of β-Mo2C with a silica oxide support in the RWGS reaction. The team published their study in Carbon Future on April 30. “Society is moving towards a carbon-neutral economy. Carbon dioxide is a greenhouse gas, thus any technology that can break down the carbon-oxide bond in this molecule and turn carbon into a value-added chemical could be of great interest. One important C1 chemical is carbon monoxide, which is an essential feedstock to produce a range of products, such as synthetic fuels and vitamin A,” said Hong Yang, Alkire chair professor in the Department of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign and senior author of the paper. Specifically, the researchers synthesized β-Mo2C nanoparticle catalysts absorbed onto a SiO2 support (β-Mo2C/SiO2). The amorphous structure of the SiO2 support was critical for nanoparticle formation, activity and stability of the β-Mo2C/SiO2 catalyst. The team additionally tested cesium (Ce), magnesium (Mg), titanium (Ti) and aluminum (Al) oxides as potential supports, but catalyst on SiO2 produced the best catalyst formation at the temperature of 650°C. “It appears the disordered nature of amorphous silica, which behaves like glue to catalyst nanoparticles, is a key factor of our success in achieving high metal loading and the corresponding high activity,” said Siying Yu, graduate student in the Department of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign and co-author of the paper. Importantly, the SiO2 catalyst support structure improves the catalytic activity of β-Mo2C 8-fold compared to bulk β-Mo2C. Even with improved catalytic activity, the β-Mo2C/SiO2 catalyst demonstrated high CO conversion and increased stability compared to bulk β-Mo2C in RWGS reactions. “A major discovery of our work is a new process for producing high metal-loading catalysts made of molybdenum carbide nanoparticles. Such metal carbide catalysts are developed for converting carbon dioxide into carbon oxide at high production rate and selectivity,” said Andrew Kuhn, former graduate student in the Department of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign and first author of the paper. The researchers performed their study under reaction conditions that favored conversion to CO gas, with a H2:CO2 ratio equal to 1:1. This ratio differs from the more commonly tested ratio of less than 3:1. Reactions were also performed at temperatures between 300 to 600°C. Under these conditions, the team produced more concentrated CO, which is more efficient for downstream compound synthesis. The team sees this research as a launching point for other catalysts that leverage support structures to increase activity. “Our ability to synthesize phase-pure metal carbide nanomaterials at high loading opens the door for the development of new catalysts for the process of CO2 utilization,” said Yang. “I hope through in-depth study of the synthesis-structure-property relationship of this catalyst we will soon be able to uncover new important applications for value-added conversion of CO2 and the sustainable development of our economy.” Other contributors include Rachel Park, Di Gao and Cheng Zhang from the Department of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign in Urbana, Illinois; and Yuanhui Zhang from the Department of Agricultural and Biological Engineering at the University of Illinois at Urbana-Champaign. This research was supported by the University of Illinois, Urbana-Champaign start-up fund. See the Article: Valorization of carbon dioxide into C1 product via reverse water gas shift reaction using oxide-supported molybdenum carbides 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

Adding polymerized ionic liquid improves performance of perovskite solar cells

Perovskite solar cells, which use materials with the same crystal structure as perovskite, are lightweight, flexible, easy to manufacture, and inexpensive. They can be attached to many different surfaces and are a promising technology. However, current perovskite solar cells are not durable, and they tend to be inefficient. New research shows how additive engineering with a polymerized ionic liquid to the metal halide perovskite material can improve the solar cell’s function, helping to pave the way for the future wide adoption of perovskite solar cells. The research was published in Energy Materials and Devices on March 29. “The commonly employed solution processing method for fabricating perovskite layers introduces many defects in both the bulk and surface of the perovskite layer. These intrinsic defects within the perovskite absorption layer pose a significant constraint on the overall performance of the devices. Additive engineering has been demonstrated to be effective as a strategy for defect passivation and performance enhancement in perovskite solar cells,” said Qi Cao, a researcher at Northwestern Polytechnical University in Xi’an, China.  To further improve the ionic liquids added to perovskite solar cells, researchers can create polymerized or poly ionic liquids. In this study, researchers synthesized a poly ionic liquid called poly(4-styrenesulfonyl(trifluoremethylsulfonyl)imidepyridine), or PSFSIPPyri for short. The addition of PSFSIPPyri to the metal halide perovskite solar cell has many benefits. It can prevent halide ion migration, which helps maintain the crystal structure, and facilitate the fixation of organic and halide ions, which improves the solar cell’s stability. “To date, researchers have devoted considerable attention to the meticulous selection of additives that enhance the performance of perovskite solar cells. Among these, ionic liquids have received widespread attention. Ionic bonds in ionic liquids tend to be stronger and more stable, and they offer various tunable properties, including viscosity, polarity, and conductivity,” said Xuanhua Li, a researcher at Northwestern Polytechnical University. “This tunability makes it possible to fine-tune the ionic liquid properties to meet the specific requirements of the perovskite film, thereby optimizing device performance.” To test the success of the addition of PSFSIPPyri, researchers conducted comprehensive studies of the perovskite solar cells with the poly ionic liquid, especially for factors that are essential for the performance of the solar cells. The perovskite films were aged for 300 hours at 85°C and 60% relative humidity. The perovskite film with the poly ionic liquid had a slower rate of change than the control perovskite film. The corresponding device’s stability is also improved. In an 85°C high heat environment, the PSFSIPPyri-doped device maintained 84.5% of its efficiency after 1000 hours, while the control perovskite solar cell only maintained 43.6% of its initial efficiency. In an 85% high heat environment, the PSFSIPPyri-doped device also maintained 83.8% of its efficiency after 1000 hours, while the control only maintained 50.4% of its initial efficiency. Since perovskite solar cells are often less durable than alternatives, it was important to test the long-term durability of the perovskite solar cell with the addition of PSFSIPPyri. With the poly ionic liquid, the perovskite solar cell maintained 87.6% of its power conversion efficiency after 1,500 hours of continuous light, compared to the control which only maintained 61.1% of its power conversion efficiency. “Incorporating PSFSIPPyri as an additive leads to a significant enhancement in the power conversion efficiency of inverted perovskite solar cells from 22.06% to 24.62%. They also demonstrate excellent long-term operational stability,” said Cao. “This strategy illustrates the potential of poly ionic liquids as a promising additive for perovskite solar cells, offering both high performance and stability.” Other contributors include Xingyuan Chen, Tong Wang, Jiabao Yang, Xingyu Pu, Hui Chen, Bingxiu Xue, and Jianbo Yin at Northwestern Polytechnical University in Xi’an, China; Long Jiang at the CNPC Tubular Goods Research Institute in Xi’an, China. The National Natural Science Foundation of China, the Science, Technology, and Innovation Commission of Shenzhen Municipality, the Shaanxi Science Fund for Distinguished Young Scholars, and the Open Project of State Key Laboratory of Supramolecular Structure and Materials supported this research.   See the Article: Efficiency enhancement to 24.62% in inverted perovskite solar cells through poly (ionic liquid) bulk modification 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

Artificial intelligence to be used for the detection of common eye disease

Dry Eye Disease (DED) is one of the more common eye diseases, affecting up to 30% of the world’s population. This disease can affect many different types of people and can wind up being a great hindrance to their overall quality of life. Early screening and prognosis is vital to the patient’s progression with the disease. However, this can be difficult. In this study, researchers aim to use artificial intelligence (AI) to aid in early screening and prognosis of DED. Not only can the use of AI make screening more accessible for individuals, but it can also aid patients in personalized therapeutic intervention.  Researchers published their results in Big Data Mining and Analytics on April 22. DED can affect a wide array of people, including those who wear contact lenses, makeup, stay up late, look at screens for a long time and are over 30 years old. Symptoms of this disease are dry eyes, irritation and burning, tears, eye fatigue and pain. One can easily see how this disease has the potential to drastically impact a large portion of the modern world’s population. Here is where the combined efforts of ophthalmic disease detection and the world of computer scientists and engineers can help. “By addressing challenges, imparting insights, and delineating future research pathways, it contributes substantially to the advancement of ophthalmic disease detection through sophisticated technological modalities,” said Mini Han Wang, author and researcher. There are seven facets to this AI-based disease detection. Timely intervention via the AI screening process and correct prognosis is the first part. The use of exhaustive surveys for DED through AI is another, and this is a supporting principle to ensure a level of thoroughness and trustworthiness throughout the process. A systematic approach follows, as well as the marriage of computer science and engineering with ophthalmology. Then, the standards for DED detection must be devised and upheld for future researchers and practitioners, which will naturally lead to the advancement of the field. Finally, all the research, methodologies and tools must be compiled so researchers, scholars and practitioners can have all of the information currently out there available to them. While the ophthalmologists set the guidelines regarding the framework of the disease and flags for diagnosis, the AI does a lot of the heavy lifting. Ideally, this AI would use images and videos taken from a user’s cell phone to help reach users across the world. The AI can then utilize these images, as well as risk factors in the patient’s life, to make a smart and well-informed prognosis. Further, AI continuously learns and can help propel research forward by contributing to predictive models for DED. The use of AI detection for DED holds a lot of promise, especially considering the risk factors are often normal activities in many people’s everyday lives. To make the detection methods accessible enough and accurate enough, further research needs to be done. “However, there are still challenges for engineers to select the diagnostic standards and combinations of different types of datasets. By using trustworthy algorithms, images and videos captured from phones for accessibility purposes, a holistic approach to healthcare for early screening is possible,” said Wang. With continued testing and collaboration between engineers and ophthalmologists, there is great potential for this method of testing to be useful in contributing to early screening of DED and subsequent therapeutic actions taken for the patient to reduce a worsening condition or to recover some quality of life. Mini Han Wang and Xiangrong Yu of the Zhuhai People’s Hospital with Mini Han Wang also of the Department of Ophthalmology and Visual Sciences at the Chinese University of Hong Kong, The Faculty of Data Sciences at City University of Macau and the Department of big data at the Zhuhai Institute of Advanced Technology at the Chinese Academy of Sciences, Lumin Xing of the First Affiliated Hospital of Shandong First Medical University, Yi Pan of the Shenzhen Institute of Advanced Technology Chinese Academy of Sciences, Feng Gu of the College of Staten Island at the City University of New York, Junbin Fang at the Department of Optoelectronic Engineering at Jinan University, Chi Pui Pang, Kelvin KL Chong, Carol Yim-Lui Cheung and Xulin Liao of the Department of Ophthalmology and Visual Sciences at The Chinese University of Hong Kong, Xiaoxiao Fang with the Zhuhai Aier Eye Hospital, Jie Yang of the College of Artificial Intelligence at Chongqing Industry and Trade Polytechnic, Ruoyu Zhou and Wenjian Liu with the Faculty of Data Science at City University of Macao, Xiaoshu Zhou with the Centre for Science and Technology Exchange and Cooperation between China and Portuguese-Speaking Countries, and Fengling Wang with the School of Artificial Intelligence at Hezhou Univeristy contributed to this research. The National Natural Science Foundation of China Natural, the Shenzhen Key Laboratory of Intelligent Bioinformatics, the Shenzhen Science and Technology Program, the Guangdong Basic and Applied Basic Research Foundation, the Zhuhai Technology and Research Foundation, the Project of Humanities and Social Science of MOE, the Science and Technology Research Program of Chongqing Municipal Education Commission and the Natural Science Foundation of Chongqing China made this research possible. See the Article: AI-Based Advanced Approaches and Dry Eye Disease Detection Based on Multi-Source Evidence: Cases, Applications, Issues, and Future Directions About Big Data Mining and Analytics Big Data Mining and Analytics (Published by Tsinghua University Press) discovers hidden patterns, correlations, insights and knowledge through mining and analyzing large amounts of data obtained from various applications. It addresses the most innovative developments, research issues and solutions in big data research and their applications. Big Data Mining and Analytics is indexed and abstracted in ESCI, EI, Scopus, DBLP Computer Science, Google Scholar, INSPEC, CSCD, DOAJ, CNKI, etc.
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An effective method for improving energy storage performance in (Bi0.5Na0.5)TiO3-based lead-free relaxor ferroelectrics

Next-generation advanced high/pulsed power capacitors urgently require dielectric materials with outstanding energy storage performance. (Bi0.5Na0.5)TiO3-based material, a typical lead-free ferroelectrics, has the characteristics of high polarization strength and excellent component compatibility, making it emerge as a potential candidate for energy storage applications. Researchers have made an interesting breakthrough in the modification of the BNT-based ferroelectrics, an effective method for various properties such as relaxor features and energy storage performance. The new method utilizes a high-entropy concept to create A-site BNT-based high-entropy relaxor ferroelectrics, and add B-site disorder on this basis, which can further improve the ion disorder to reduce short-range order. Thus, it is easier to form isolated and weak coupled polar nanoclusters in the dielectric matrix. This characteristic makes it obtain a high relaxor feature and delayed saturation polarization under an electric field, which is beneficial for good energy storage performance. This represents an important advancement over existing methods. The traditional approach to creating relaxor ferroelectrics (RFEs), which normally relies on doping heterogeneous ions to cause local compositional inhomogeneity and ion disorder to obtain polar nanoregions (PNRs). “But the solid solubility is limited, even though BNT has good component compatibility,” Neng-Neng Luo, the leader of the research team said, “the Gibbs phase rule tells us it is hard to further improve the ion disorder and relaxor feature by chemical doping.” This method overcomes this limitation by constructing a high entropy single-phase solid solution. Meanwhile, on the basis of the A-site disorder, an additional B-site disorder further breaks the size of PNRs and weakens the coupling between PNRs. The highly broken and weak coupled PNRs may restrict their growth into micro-domains under high electric fields, thereby leading to slimmer P–E loops and further prolonged polarization saturation. This innovation not only provides new ideas for the design of ferroelectric materials, but proves that a B-site modification strategy based on the A-site high-entropy disorder is also an effective way of improving energy storage density. Additionally, it could explain the domain change process of ferroelectric energy storage ceramics under an electric field. Meanwhile, the research team is optimistic about the application of their work. They believe that the method, requiring no complex fabrication processes, could readily be achieved inhigh energy storage density with ultra-high efficiency. The team published their work in Journal of Advanced Ceramics on 14 March, 2024. This is an important development in the field of dielectric energy storage materials, and its potential applications are vast. The researchers’ work highlights the power of combining advanced materials with innovative design concepts to achieve breakthroughs with far-reaching consequences. This work was supported by the Guangxi Natural Science Fund for Distinguished Young Scholars (Grant No. 2022GXNSFFA035034), National Natural Science Foundation of China (Grant Nos. 52072080 and U22A20127), and National Key Research and Development Program of China (Grant No. 2022YFC2408600). JOURNAL Journal of Advanced Ceramics ARTICLE TITLE Excellent energy storage performance in Bi0.5Na0.5TiO3-based lead-free high-entropy relaxor ferroelectrics via B-site modification About the Authors Dr. Nengneng Luo is a professor in School of Resources, Environment and Materials, Guangxi University. He received his PhD degree in Chemistry from Tsinghua University in 2015. He studied at the Pennsylvania State University as a joint-training PhD student from 2013 to 2014. His research activity is focused on designing novel high-performance lead-free (anti)ferroelectric materials and their application for energy storage/piezoelectric sensor, and finding the correlations between microstructure (such as crystal structure, domain wall, defect, etc.) and physical performance. Miss Kaihua Yang is a master graduate student of School of Resources, Environment and Materials, Guangxi University. Her research focuses on developing new lead-free ferroelectric materials for energy storage applications.

Highest power efficiency achieved in flexible solar cells using new fabrication technique

Flexible solar cells have many potential applications in aerospace and flexible electronics, but low energy conversion efficiency has limited their practical use. A new manufacturing method has increased the power efficiency of flexible solar cells made from perovskite, a class of compounds with a specific crystalline structure that facilitates the conversion of solar energy into electricity. Current flexible perovskite solar cells (FPSCs) suffer from lower power conversion efficiency than rigid perovskite solar cells because of the soft and inhomogeneous characteristics of the flexible base material, made of polyethylene terephthalate (PET), the perovskite films of FPSCs are built upon. FPSCs also have lower durability than rigid solar cells that use glass as a base substrate. Pores in flexible solar cell substrates allow water and oxygen to invade the perovskite materials, causing them to degrade. To address these issues with current FPSC technology, a team of material scientists from the State Key Laboratory of Power System Operation and Control at Tsinghua University and the Center for Excellence in Nanoscience at the National Center for Nanoscience and Technology in Beijing, China developed a new fabrication technique that increases the efficiency of FPSCs, paving the way for use of the technology on a much larger scale. The team published their study on March 31 in iEnergy, published by Tsinghua University Press. “Increasing the power conversion efficiency of FPSCs is crucial for several reasons: higher efficiency… makes FPSCs more competitive with other solar cell technologies, decreases the cost per watt of generated electricity… and resources needed to produce the same amount of electrical power and increases the range of applications where FPSCs can be practically used, including aerospace and flexible electronics where space and weight are at a premium,” said Chenyi Yi, associate professor in the State Key Laboratory of Power System Operation and Control at Tsinghua University and senior author of the paper. Specifically, the team developed a new chemical bath deposition (CBD) method of depositing tin oxide (SnO2) on a flexible substrate without requiring a strong acid, which many flexible substrates are sensitive to. The new technique allowed the researchers more control over tin oxide growth on the flexible substrate. Tin oxide serves as an electron transport layer in the FPSC, which is critical for power conversion efficiency. “This CBD method differs from previous research by using SnSO4 tin sulfate rather than SnCl2 tin chloride as a tin precursor for depositing SnO2, making the new method… compatible with acid-sensitive flexible substrates,” said Yi. Importantly, the new fabrication method also addresses some of the durability concerns over FPSCs. “The residual SO42- sulfate left over after the SnSO4-based CBD additionally benefits the stability of the PSCs because of the strong coordination between Pb2+ lead from perovskite and SO42- from SnO2. As a result, we can fabricate higher quality SnO2 to achieve more efficient and stable FPSCs,” said Yi. The team achieved a new benchmark for highest power conversion efficiency for FPSCs at 25.09% and was certified at 24.90%. The durability of the SnSO4-based flexible solar cells was also demonstrated by cells maintaining 90% of their power conversion efficiency after the cells were bent 10,000 times. SnSO4-based flexible solar cells also showed improved high-temperature stability compared to SnCl2-based flexible solar cells. The new fabrication method developed by the research team produced reproducible results and allows manufacturers to reuse the chemical bath, increasing the practicality of scalable FPSC production. “The ultimate goal is to transition these high-efficiency FPSCs from laboratory scale to industrial production, enabling widespread commercial application of this technology in various fields, from wearable technology, portable electronics and aerospace power sources to large-scale renewable energy solutions,” said Yi. Other contributors include Ningyu Ren, Liguo Tan, Minghao Li, Junjie Zhou, Yiran Ye and Boxin Jiao from the State Key Laboratory of Power System Operation and Control in the Department of Electrical Engineering at Tsinghua University in Beijing, China; and Liming Ding from the Center for Excellence in Nanoscience (CAS) in the Key Laboratory of Nanosystem and Hierarchical Fabrication (CAS) at the National Center for Nanoscience and Technology in Beijing, China. This research was supported by the National Key Research and Development Program of China (2022YFB3803304); National Natural Science Foundation of China (U23B20153, U23A20138); Tsinghua University Initiative Scientific Research Program (20221080065, 20223080044); Independent Innovative Research Program (ZK20230101); Department of Electrical Engineering, Tsinghua University, State Key Laboratory of Power System and Generation Equipment (nos. SKLD21Z03 and SKLD20M03); China Postdoctoral Science Foundation (2023M741888); Chinese Thousand Talents Program for Young Professionals; State Grid Corporation of China, National Bio Energy Co. Ltd., grant no. 52789922000D.   ARTICLE TITLE 25% – Efficiency flexible perovskite solar cells via controllable growth of SnO2   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.
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