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Tee SY, Kong J, Koh JJ, Teng CP, Wang X, Wang X, Teo SL, Thitsartarn W, Han MY, Seh ZW. Structurally and surficially activated TiO 2 nanomaterials for photochemical reactions. NANOSCALE 2024. [PMID: 39268929 DOI: 10.1039/d4nr02342k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/15/2024]
Abstract
Renewable fuels and environmental remediation are of paramount importance in today's world due to escalating concerns about climate change, pollution, and the finite nature of fossil fuels. Transitioning to sustainable energy sources and addressing environmental pollution has become an urgent necessity. Photocatalysis, particularly harnessing solar energy to drive chemical reactions for environmental remediation and clean fuel production, holds significant promise among emerging technologies. As a benchmark semiconductor in photocatalysis, TiO2 photocatalyst offers an excellent solution for environmental remediation and serves as a key tool in energy conversion and chemical synthesis. Despite its status as the default photocatalyst, TiO2 suffers from drawbacks such as a high recombination rate of charge carriers, low electrical conductivity, and limited absorption in the visible light spectrum. This review provides an in-depth exploration of the fundamental principles of photocatalytic reactions and presents recent advancements in the development of TiO2 photocatalysts. It specifically focuses on strategic approaches aimed at enhancing the performance of TiO2 photocatalysts, including improving visible light absorption for efficient solar energy harvesting, enhancing charge separation and transportation efficiency, and ensuring stability for robust photocatalysis. Additionally, the review delves into the application of photodegradation and photocatalysis, particularly in critical processes such as water splitting, carbon dioxide reduction, nitrogen fixation, hydrogen peroxide generation, and alcohol oxidation. It also highlights the novel use of TiO2 in plastic polymerization and degradation, showcasing its potential for converting plastic waste into valuable chemicals and fuels, thereby offering sustainable waste management solutions. By addressing these essential areas, the review offers valuable insights into the potential of TiO2 photocatalysis for addressing pressing environmental and energy challenges. Furthermore, the review encompasses the application of TiO2 photochromic systems, expanding its scope to include other innovative research and applications. Finally, it addresses the underlying challenges and provides perspectives on the future development of TiO2 photocatalysts. Through addressing these issues and implementing innovative strategies, TiO2 photocatalysis can continue to evolve and play a pivotal role in sustainable energy and environmental applications.
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Affiliation(s)
- Si Yin Tee
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
| | - Junhua Kong
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
| | - Justin Junqiang Koh
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
| | - Choon Peng Teng
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
| | - Xizu Wang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
| | - Xiaobai Wang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
| | - Siew Lang Teo
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
| | - Warintorn Thitsartarn
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
| | - Ming-Yong Han
- Institute of Molecular Plus, Tianjin University, Tianjin 300072, China.
| | - Zhi Wei Seh
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore.
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Ma L, Wang C, Xiang L, Liu J, Dang C, Wu H. Chinese cities show different trend toward carbon peak. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 934:173156. [PMID: 38763197 DOI: 10.1016/j.scitotenv.2024.173156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/25/2024] [Accepted: 05/09/2024] [Indexed: 05/21/2024]
Abstract
Understanding the disparities in carbon emission trend among cities is critical for achieving carbon peak goal. However, the status and trends of carbon peaking and reduction in various city types are still unclear. Therefore, this study classified 315 Chinese cities according to their economic and industrial structure by SOM-K-means, aiming to evaluate the trends and dynamic drivers of carbon peaking progress in different city types. The findings reveal a decline in carbon emissions in 110 cities (34.9 %) since 2020. Notably, all city types show potential for carbon reduction and achieving carbon peaking. Specifically, resource-based cities and high-end service cities have the most effect on reducing emissions, with 48.4 % and 42.1 % of the cities declining in carbon emissions. Energy-based and heavy industrial cities face heightened pressure to reduce carbon emissions. Additionally, in high-end service cities, energy efficiency and investment intensity contribute to emission reduction, while industrial structure adjustment decrease carbon emissions in resource-based cities. Furthermore, enhancing energy efficiency effects and R&D intensity are effective ways to significantly reduce carbon emissions in heavy industrial cities. We conclude that differentiating carbon reduction pathways for different cities should constitute be a breakthrough in achieving the goal of carbon peaking. These insights provide recommendations for cities that have yet to reach their carbon peak for both China and other developing countries.
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Affiliation(s)
- Le Ma
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Hubei Luojia Laboratory, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.
| | - Chao Wang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Hubei Luojia Laboratory, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.
| | - Longgang Xiang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Hubei Luojia Laboratory, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.
| | - Jingjing Liu
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Hubei Luojia Laboratory, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.
| | - Chaoya Dang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Hubei Luojia Laboratory, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.
| | - Huayi Wu
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Hubei Luojia Laboratory, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.
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Song C, Liu D, Ren L, Han J, Jin Y, Cheng Y, Li X, Zhang H. Research on speed sensorless control strategy of permanent magnet synchronous motor based on fuzzy super-twisting sliding mode observer. Sci Prog 2024; 107:368504241228106. [PMID: 38312046 PMCID: PMC10846125 DOI: 10.1177/00368504241228106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Aiming at the problems of poor adjustment effect, weak anti-disturbance ability, and low robustness of the traditional sliding mode algorithm for permanent magnet synchronous motor speed sensorless, a permanent magnet synchronous motor speed observation method combining super-twisting sliding mode control algorithm and fuzzy control is proposed to accelerate the convergence speed of the system and improve the anti-disturbance ability. Fuzzy rules are used to solve the problem of obtaining the upper bound of the boundary function in the super-twisting algorithm. Moreover, the fuzzy algorithm is used to output the variable sliding mode gain instead of the fixed sliding mode coefficient to improve the system robustness and suppress the jitter. The simulation results show that the overshoot of the control system is 4%, the lag time is not more than 0.003 ms, the speed error is not more than 1%, and the response and adjustment time is not more than 0.02 s. The proposed control strategy improves the tracking accuracy and response speed of the system, suppresses the sliding mode chattering, and enhances the anti-interference ability of the system.
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Affiliation(s)
- Chao Song
- College of Electrical and Information Engineering, Beihua University, Jilin, China
| | - Dejun Liu
- Engineering Training Center, Beihua University, Jilin, China
| | - Letian Ren
- College of Electrical and Information Engineering, Beihua University, Jilin, China
| | - Junjie Han
- College of Electrical and Information Engineering, Beihua University, Jilin, China
| | - Yuqi Jin
- College of Electrical and Information Engineering, Beihua University, Jilin, China
| | - Yanming Cheng
- College of Electrical and Information Engineering, Beihua University, Jilin, China
| | - Xiang Li
- College of Electrical and Information Engineering, Beihua University, Jilin, China
| | - Hao Zhang
- College of Electrical and Information Engineering, Beihua University, Jilin, China
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