Pub Date : 2026-03-01Epub Date: 2026-02-19DOI: 10.1016/S1872-5813(25)60610-4
Peng WANG , Yanling HAN , Yuanyuan LIU , Pengfei LU , Xiao LI
In this study, melamine and cyanuric acid were used as precursors to form supramolecular crystals via hydrogen-bond-assisted self-assembly followed by hydrothermal treatment. Subsequent high-temperature calcination yielded a novel brush-like three-dimensional carbon nitride. The brush-like 3D architecture was found to expose more accessible active sites, markedly accelerate electron transfer, and suppress the recombination of photogenerated charge carriers. The resulting superoxide (O–·2) and hydroxyl (·OH) radicals generated via electron reduction were identified as the key reactive species in the photocatalytic process. Moreover, the surface of the brush-like structure is enriched with nitrogen vacancies, which enhance the catalyst's ability to harvest visible light. The photocatalytic performance of the brush-like CNS-650 catalyst was evaluated for rhodamine B (RhB) degradation. Under red-light irradiation (660 nm), its degradation rate was 7.4 times higher than that of bulk CN. This work provides valuable insights into the design and application of efficient metal-free 3D photocatalysts.
{"title":"Metal-free brush-like 3D carbon nitride delivers efficient red-light-driven photocatalysis","authors":"Peng WANG , Yanling HAN , Yuanyuan LIU , Pengfei LU , Xiao LI","doi":"10.1016/S1872-5813(25)60610-4","DOIUrl":"10.1016/S1872-5813(25)60610-4","url":null,"abstract":"<div><div>In this study, melamine and cyanuric acid were used as precursors to form supramolecular crystals <em>via</em> hydrogen-bond-assisted self-assembly followed by hydrothermal treatment. Subsequent high-temperature calcination yielded a novel brush-like three-dimensional carbon nitride. The brush-like 3D architecture was found to expose more accessible active sites, markedly accelerate electron transfer, and suppress the recombination of photogenerated charge carriers. The resulting superoxide (O<sup>–·</sup><sub>2</sub>) and hydroxyl (<sup>·</sup>OH) radicals generated <em>via</em> electron reduction were identified as the key reactive species in the photocatalytic process. Moreover, the surface of the brush-like structure is enriched with nitrogen vacancies, which enhance the catalyst's ability to harvest visible light. The photocatalytic performance of the brush-like CNS-650 catalyst was evaluated for rhodamine B (RhB) degradation. Under red-light irradiation (660 nm), its degradation rate was 7.4 times higher than that of bulk CN. This work provides valuable insights into the design and application of efficient metal-free 3D photocatalysts.</div><div><span><figure><span><img><ol><li><span><span>Download: <span>Download high-res image (201KB)</span></span></span></li><li><span><span>Download: <span>Download full-size image</span></span></span></li></ol></span></figure></span></div></div>","PeriodicalId":15956,"journal":{"name":"燃料化学学报","volume":"54 3","pages":"Article 20250207"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147409571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Effective management of multi-purpose reservoirs requires precise planning and accurate data to balance competing objectives and constraints. Reservoir inflow forecasting is critical in this process, with deep learning models increasingly applied across various time scales, from hourly to annual predictions. This study integrated a two-layer stacked long short-term memory network with decomposed data and a rolling window technique to enhance multi-day reservoir inflow forecasting accuracy. The proposed framework was applied to the Lam Takhong Dam in northeastern Thailand, a tropical monsoon region characterized by distinct wet and dry seasons. The dataset included daily reservoir inflow, river discharge, and average rainfall records spanning multiple years. Four forecasting strategies were compared for up to 7-d predictions: multi-step prediction, rolling prediction, multi-step prediction with decomposition, and rolling prediction with decomposition. The results indicated that while all models performed similarly for short-term predictions, accuracy declined over longer forecasting horizons. The rolling window approach with decomposition consistently outperformed others, achieving an average correlation coefficient of 0.92 and an average Nash–Sutcliffe model efficiency coefficient of 0.78 at the 7-d forecasting horizon. These findings demonstrate the practical advantages of integrating decomposition into a dynamic forecasting framework, particularly in reducing error accumulation in extended hydrological predictions.
{"title":"Multi-step reservoir inflow prediction using a rolling window strategy and decomposed LSTM","authors":"Wandee Thaisiam , Pongbavorn Rattanapant , Pawit Kraisornnukhor , Papis Wongchaisuwat","doi":"10.1016/j.wse.2025.11.001","DOIUrl":"10.1016/j.wse.2025.11.001","url":null,"abstract":"<div><div>Effective management of multi-purpose reservoirs requires precise planning and accurate data to balance competing objectives and constraints. Reservoir inflow forecasting is critical in this process, with deep learning models increasingly applied across various time scales, from hourly to annual predictions. This study integrated a two-layer stacked long short-term memory network with decomposed data and a rolling window technique to enhance multi-day reservoir inflow forecasting accuracy. The proposed framework was applied to the Lam Takhong Dam in northeastern Thailand, a tropical monsoon region characterized by distinct wet and dry seasons. The dataset included daily reservoir inflow, river discharge, and average rainfall records spanning multiple years. Four forecasting strategies were compared for up to 7-d predictions: multi-step prediction, rolling prediction, multi-step prediction with decomposition, and rolling prediction with decomposition. The results indicated that while all models performed similarly for short-term predictions, accuracy declined over longer forecasting horizons. The rolling window approach with decomposition consistently outperformed others, achieving an average correlation coefficient of 0.92 and an average Nash–Sutcliffe model efficiency coefficient of 0.78 at the 7-d forecasting horizon. These findings demonstrate the practical advantages of integrating decomposition into a dynamic forecasting framework, particularly in reducing error accumulation in extended hydrological predictions.</div></div>","PeriodicalId":23628,"journal":{"name":"Water science and engineering","volume":"19 1","pages":"Pages 11-22"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147409666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-07DOI: 10.1016/j.wse.2025.11.004
Pascaline Nyirabuhoro , Jean Claude Ndayishimiye , Ning Rui , Damir Saldaev , Yuri Mazei , Xiao-fei Gao
Urban blue–green infrastructure (UBGI) is essential to addressing urbanization challenges. However, its potential to mitigate climate extremes remains unclear. This study assessed biodiversity and water conservation challenges in UBGI using testate amoebae (TA) as indicators of ecosystem health. The studied UBGI consists of 0.67 km2 of forested hills and 3 668 m2 of ponds, located in the 55 800-km2 city cluster in the Pearl River Delta, South China. The analysis incorporated a two-year (June 2021 and June 2022) dataset, comprising TA records from 27 soil samples, 30 pond water samples, and 30 pond sediment samples; 27 microspatial factors, including five factors representing weather conditions (WC), eight factors for air quality (AQ), and 14 factors for water quality (WQ); and four climate extreme scenarios (heatwaves, droughts, typhoons, and floods). Biodiversity and water quality concerns linked to interactions between urban emissions and aquatic ecosystems within UBGI were illuminated in the following three key findings: (1) biotope connectivity enabled redistributions of soil-specific TA (six out of 42 species) along hillslopes (moisture gradient) and pond lengths (hydrological gradient); (2) TA showed strong biotope adaptation, with stochastic processes explaining 69.3% of community variations in water and 78.8% in sediment; and (3) UBGI showed limited effectiveness in mitigating urban emissions, such as CO and NH3, particularly when TA were adversely impacted by WC driven by climate extremes and when WQ was adversely influenced by AQ. The findings suggest that TA are reliable bioindicators, informing UBGI performance and supporting climate-resilient interventions to monitor cross-border pollution and its effects at the biotope level.
{"title":"Biodiversity and water conservation challenges in urban blue–green infrastructure under climate extremes","authors":"Pascaline Nyirabuhoro , Jean Claude Ndayishimiye , Ning Rui , Damir Saldaev , Yuri Mazei , Xiao-fei Gao","doi":"10.1016/j.wse.2025.11.004","DOIUrl":"10.1016/j.wse.2025.11.004","url":null,"abstract":"<div><div>Urban blue–green infrastructure (UBGI) is essential to addressing urbanization challenges. However, its potential to mitigate climate extremes remains unclear. This study assessed biodiversity and water conservation challenges in UBGI using testate amoebae (TA) as indicators of ecosystem health. The studied UBGI consists of 0.67 km<sup>2</sup> of forested hills and 3 668 m<sup>2</sup> of ponds, located in the 55 800-km<sup>2</sup> city cluster in the Pearl River Delta, South China. The analysis incorporated a two-year (June 2021 and June 2022) dataset, comprising TA records from 27 soil samples, 30 pond water samples, and 30 pond sediment samples; 27 microspatial factors, including five factors representing weather conditions (WC), eight factors for air quality (AQ), and 14 factors for water quality (WQ); and four climate extreme scenarios (heatwaves, droughts, typhoons, and floods). Biodiversity and water quality concerns linked to interactions between urban emissions and aquatic ecosystems within UBGI were illuminated in the following three key findings: (1) biotope connectivity enabled redistributions of soil-specific TA (six out of 42 species) along hillslopes (moisture gradient) and pond lengths (hydrological gradient); (2) TA showed strong biotope adaptation, with stochastic processes explaining 69.3% of community variations in water and 78.8% in sediment; and (3) UBGI showed limited effectiveness in mitigating urban emissions, such as CO and NH<sub>3</sub>, particularly when TA were adversely impacted by WC driven by climate extremes and when WQ was adversely influenced by AQ. The findings suggest that TA are reliable bioindicators, informing UBGI performance and supporting climate-resilient interventions to monitor cross-border pollution and its effects at the biotope level.</div></div>","PeriodicalId":23628,"journal":{"name":"Water science and engineering","volume":"19 1","pages":"Pages 85-96"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147409684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-12DOI: 10.1016/j.wse.2026.01.001
Krishna Kumar , Raman Sharma , S.K. Goyal
Biocarriers play a critical role in moving bed biofilm reactor (MBBR) and sequencing batch biofilm reactor (SBBR) wastewater treatment systems by providing surfaces for biofilm development. Although a wide variety of carrier materials and geometries are used, the literature remains fragmented, with most studies focusing on individual carriers and lacking a systematic understanding of how carrier characteristics govern treatment performance across different operational conditions. Additionally, review articles comparing biocarrier efficacy in synthetic wastewater systems are limited. This review article synthesizes the performance of various biocarriers in synthetic wastewater treatment and evaluates their efficiency in reducing chemical oxygen demand (COD), ammonia, and total nitrogen (TN). Reported removal efficiencies range from 68% to 96% for COD, up to 99% for ammonia, and 40.0%–97.5% for TN, depending on carrier design and reactor configuration. Carrier-specific surface areas typically range from 250 m2/m3 to 2 800 m2/m3. Analysis reveals that performance is significantly influenced by carrier features such as shape, material, surface roughness, porosity, and specific surface area. Notably, carriers with higher porosity and rough surfaces generally promote superior biofilm formation and pollutant removal, although optimization of surface area may compromise mechanical strength and long-term durability. Operational parameters, such as loading rate, filling ratio, and temperature, also interact with carrier design to determine overall treatment efficiency. While existing studies offer valuable insights, comparative research that links design parameters to treatment performance across varying conditions remains scarce. Future studies should prioritize quantifying relationships between carrier geometry, material properties, and biological activity, as well as developing standardized testing protocols to enable more reliable cross-study comparisons.
{"title":"Performance of different biocarriers in MBBR and SBBR systems for wastewater treatment: A review","authors":"Krishna Kumar , Raman Sharma , S.K. Goyal","doi":"10.1016/j.wse.2026.01.001","DOIUrl":"10.1016/j.wse.2026.01.001","url":null,"abstract":"<div><div>Biocarriers play a critical role in moving bed biofilm reactor (MBBR) and sequencing batch biofilm reactor (SBBR) wastewater treatment systems by providing surfaces for biofilm development. Although a wide variety of carrier materials and geometries are used, the literature remains fragmented, with most studies focusing on individual carriers and lacking a systematic understanding of how carrier characteristics govern treatment performance across different operational conditions. Additionally, review articles comparing biocarrier efficacy in synthetic wastewater systems are limited. This review article synthesizes the performance of various biocarriers in synthetic wastewater treatment and evaluates their efficiency in reducing chemical oxygen demand (COD), ammonia, and total nitrogen (TN). Reported removal efficiencies range from 68% to 96% for COD, up to 99% for ammonia, and 40.0%–97.5% for TN, depending on carrier design and reactor configuration. Carrier-specific surface areas typically range from 250 m<sup>2</sup>/m<sup>3</sup> to 2 800 m<sup>2</sup>/m<sup>3</sup>. Analysis reveals that performance is significantly influenced by carrier features such as shape, material, surface roughness, porosity, and specific surface area. Notably, carriers with higher porosity and rough surfaces generally promote superior biofilm formation and pollutant removal, although optimization of surface area may compromise mechanical strength and long-term durability. Operational parameters, such as loading rate, filling ratio, and temperature, also interact with carrier design to determine overall treatment efficiency. While existing studies offer valuable insights, comparative research that links design parameters to treatment performance across varying conditions remains scarce. Future studies should prioritize quantifying relationships between carrier geometry, material properties, and biological activity, as well as developing standardized testing protocols to enable more reliable cross-study comparisons.</div></div>","PeriodicalId":23628,"journal":{"name":"Water science and engineering","volume":"19 1","pages":"Pages 97-109"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147409685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-11-11DOI: 10.1016/j.emcon.2025.100596
Soha Salah , Päivi Myllynen , Petra Přibylová , Petr Kukučka , Liisa Laatio , Elina Sieppi , Maria Kummu , Saranya Palaniswamy , Khaled Abass
Background
Human exposure to flame retardants, particularly PBDEs, is detectable in maternal plasma and linked to various adverse health outcomes, but the influence of parental lifestyle and diet on these levels remains poorly understood.
Objective
To monitor PBDEs in maternal and cord plasma samples and examine their relationships with parental health determinants - specifically dietary intake, environmental exposure, and lifestyle factors-in a Northern Finland population for the first time.
Methods
Maternal and cord plasma samples from 102 NUGEN cohort pairs were collected during caesarean sections at Oulu University Hospital. Plasma samples were analysed for PBDE congeners (BDE-47, BDE-66, BDE-85, BDE-99, BDE-100, BDE-153, BDE-154, BDE-183, BDE-209), DBDPE, and chlorinated flame retardants (sDP, aDP), with lipid adjustment. Total cord BFRs were calculated as the sum of all congeners quantified in cord plasma, and total maternal BFRs were calculated analogously using maternal plasma.
Results
PBDE congeners with the highest detection frequencies were maternal BDE-28 (42 %), BDE-47 (42 %), BDE-153 (100 %); and cord BDE-28 (50 %), BDE-47 (52 %), BDE-153 (95 %), BDE-154 (33 %). Maternal smoking was inversely associated with cord BDE-28 (−0.80 [−1.50, −0.09]). Higher paternal education was negatively associated with cord BDE-28 (−0.93 [−1.58, −0.27]), BDE-153 (−0.21 [−0.43, −0.005]), and BDE-154 (−4.34 [−8.00, −0.68]). High vegetable intake was inversely associated with cord BDE-154 (−3.99 [−7.76, −0.22]), while high meat intake was positively associated with total cord BFRs (0.42 [0.06, 0.78]), cord BDE-47 (0.67 [0.13, 1.21]), and maternal BDE-47 (0.77 [0.16, 1.37]).
Conclusion
PBDE levels were higher in cord than maternal samples but lower than in other European countries. Findings support maternal-to-child PBDE transfer and reveal associations with lifestyle, diet, and sociodemographic factors, including paternal variables-a notable gap in prior research.
{"title":"Monitoring and assessing the association of polybrominated diphenyl ethers (PBDEs) and flame retardants (Dechlorane Plus and DBDPE) with parental lifestyle factors in a mother–child cohort of the Finnish population (NUGEN)","authors":"Soha Salah , Päivi Myllynen , Petra Přibylová , Petr Kukučka , Liisa Laatio , Elina Sieppi , Maria Kummu , Saranya Palaniswamy , Khaled Abass","doi":"10.1016/j.emcon.2025.100596","DOIUrl":"10.1016/j.emcon.2025.100596","url":null,"abstract":"<div><h3>Background</h3><div>Human exposure to flame retardants, particularly PBDEs, is detectable in maternal plasma and linked to various adverse health outcomes, but the influence of parental lifestyle and diet on these levels remains poorly understood.</div></div><div><h3>Objective</h3><div>To monitor PBDEs in maternal and cord plasma samples and examine their relationships with parental health determinants - specifically dietary intake, environmental exposure, and lifestyle factors-in a Northern Finland population for the first time.</div></div><div><h3>Methods</h3><div>Maternal and cord plasma samples from 102 NUGEN cohort pairs were collected during caesarean sections at Oulu University Hospital. Plasma samples were analysed for PBDE congeners (BDE-47, BDE-66, BDE-85, BDE-99, BDE-100, BDE-153, BDE-154, BDE-183, BDE-209), DBDPE, and chlorinated flame retardants (sDP, aDP), with lipid adjustment. Total cord BFRs were calculated as the sum of all congeners quantified in cord plasma, and total maternal BFRs were calculated analogously using maternal plasma.</div></div><div><h3>Results</h3><div>PBDE congeners with the highest detection frequencies were maternal BDE-28 (42 %), BDE-47 (42 %), BDE-153 (100 %); and cord BDE-28 (50 %), BDE-47 (52 %), BDE-153 (95 %), BDE-154 (33 %). Maternal smoking was inversely associated with cord BDE-28 (−0.80 [−1.50, −0.09]). Higher paternal education was negatively associated with cord BDE-28 (−0.93 [−1.58, −0.27]), BDE-153 (−0.21 [−0.43, −0.005]), and BDE-154 (−4.34 [−8.00, −0.68]). High vegetable intake was inversely associated with cord BDE-154 (−3.99 [−7.76, −0.22]), while high meat intake was positively associated with total cord BFRs (0.42 [0.06, 0.78]), cord BDE-47 (0.67 [0.13, 1.21]), and maternal BDE-47 (0.77 [0.16, 1.37]).</div></div><div><h3>Conclusion</h3><div>PBDE levels were higher in cord than maternal samples but lower than in other European countries. Findings support maternal-to-child PBDE transfer and reveal associations with lifestyle, diet, and sociodemographic factors, including paternal variables-a notable gap in prior research.</div></div>","PeriodicalId":11539,"journal":{"name":"Emerging Contaminants","volume":"12 1","pages":"Article 100596"},"PeriodicalIF":6.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145518824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-10-29DOI: 10.1016/j.dt.2025.09.025
Bojun Tan , Jinkang Dou , Jing Zhang , Xiong Yang , Jiatong Ren , Changwei Tang , Jian Su , Gen Zhang , Siwei Song , Qinghua Zhang , Binghui Duan , Hongchang Mo , Minghui Xu , Xianming Lu , Bozhou Wang , Ning Liu
The pursuit of heat-resistant energetic materials (HREMs) with thermal stability beyond 450 °C presents a significant challenge that has yet to be achieved. In this work, we develop an innovative electronic delocalization strategy to design and synthesize a planar dizwitterionic diamino-bistriazolotetrazine, designated as TYX-1. The unique structural feature of TYX-1, including a nitrogen-rich fused ring system, planar conformation, and dizwitterionic configuration, combined with its hydrogen-bonded organic framework (HOF) structure, confer exceptional thermal stability (The onset temperature is 428 °C, and the peak temperature is 473 °C), high density (1.84 g/cm3), and remarkable detonation performance (detonation velocity: 8616 m/s). Furthermore, TYX-1 exhibits an impressive insensitivity (impact sensitivity > 40 J; friction sensitivity > 360 N), surpassing all previously reported HREMs. Theoretical calculations and single-crystal clearly indicate that the delocalized π electrons within the dizwitterionic bistriazolotetrazine rings and the HOF structure of TYX-1 are pivotal in ensuring its high thermal stability and high energy density. The discovery of TYX-1 marks a significant advancement in the field of HREMs and is anticipated to catalyze substantial progress in various high-temperature applications reliant on energetic materials.
{"title":"Ultra heat-resistant hydrogen-bonded organic framework: Breaking the thermal stability limit of high-energy materials","authors":"Bojun Tan , Jinkang Dou , Jing Zhang , Xiong Yang , Jiatong Ren , Changwei Tang , Jian Su , Gen Zhang , Siwei Song , Qinghua Zhang , Binghui Duan , Hongchang Mo , Minghui Xu , Xianming Lu , Bozhou Wang , Ning Liu","doi":"10.1016/j.dt.2025.09.025","DOIUrl":"10.1016/j.dt.2025.09.025","url":null,"abstract":"<div><div>The pursuit of heat-resistant energetic materials (HREMs) with thermal stability beyond 450 °C presents a significant challenge that has yet to be achieved. In this work, we develop an innovative electronic delocalization strategy to design and synthesize a planar dizwitterionic diamino-bistriazolotetrazine, designated as TYX-1. The unique structural feature of TYX-1, including a nitrogen-rich fused ring system, planar conformation, and dizwitterionic configuration, combined with its hydrogen-bonded organic framework (HOF) structure, confer exceptional thermal stability (The onset temperature is 428 °C, and the peak temperature is 473 °C), high density (1.84 g/cm<sup>3</sup>), and remarkable detonation performance (detonation velocity: 8616 m/s). Furthermore, TYX-1 exhibits an impressive insensitivity (impact sensitivity > 40 J; friction sensitivity > 360 N), surpassing all previously reported HREMs. Theoretical calculations and single-crystal clearly indicate that the delocalized π electrons within the dizwitterionic bistriazolotetrazine rings and the HOF structure of TYX-1 are pivotal in ensuring its high thermal stability and high energy density. The discovery of TYX-1 marks a significant advancement in the field of HREMs and is anticipated to catalyze substantial progress in various high-temperature applications reliant on energetic materials.</div></div>","PeriodicalId":58209,"journal":{"name":"Defence Technology(防务技术)","volume":"57 ","pages":"Pages 300-306"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147453813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-10-03DOI: 10.1016/j.aiia.2025.10.001
Zhijian Chen , Jianjun Yin , Sheikh Muhammad Farhan , Lu Liu , Ding Zhang , Maile Zhou , Junhui Cheng
As automation becomes increasingly adopted to mitigate labor shortages and boost productivity, autonomous technologies such as tractors, drones, and robotic devices are being utilized for various tasks that include plowing, seeding, irrigation, fertilization, and harvesting. Successfully navigating these changing agricultural landscapes necessitates advanced sensing, control, and navigation systems that can adapt in real time to guarantee effective and safe operations. This review focuses on obstacle avoidance systems in autonomous farming machinery, highlighting multi-functional capabilities within intricate field settings. It analyzes various sensing technologies, LiDAR, visual cameras, radar, ultrasonic sensors, GPS/GNSS, and inertial measurement units (IMU) for their individual and collective contributions to precise obstacle detection in fluctuating field conditions. The review examines the potential of multi-sensor fusion to enhance detection accuracy and reliability, with a particular emphasizing on achieving seamless obstacle recognition and response. It addresses recent advancements in control and navigation systems, particularly focusing on path-planning algorithms and real-time decision-making. It enables autonomous systems to adjust dynamically across multi-functional agricultural environments. The methodologies used for path planning, including adaptive and learning-based strategies, are discussed for their ability to optimize navigation in complicated field conditions. Real-time decision-making frameworks are similarly evaluated for their capacity to provide prompt, data-driven reactions to changing obstacles, which is critical for maintaining operational efficiency. Moreover, this review discusses environmental and topographical challenges like variable terrain, unpredictable weather, complex crop arrangements, and interference from co-located machinery that hinder obstacle detection and necessitate adaptive, resilient system responses. In addition, the paper emphasizes future research opportunities, highlighting the significance of advancements in multi-sensor fusion, deep learning for perception, adaptive path planning, model-free control strategies, artificial intelligence, and energy-efficient designs. Enhancing obstacle avoidance systems enables autonomous agricultural machinery to transform modern farming by increasing efficiency, precision, and sustainability. The review highlights the potential of these technologies to support global efforts for sustainable agriculture and food security, aligning agricultural innovation with the needs of a swiftly growing population.
{"title":"A comprehensive review of obstacle avoidance for autonomous agricultural machinery in multi-operational environment","authors":"Zhijian Chen , Jianjun Yin , Sheikh Muhammad Farhan , Lu Liu , Ding Zhang , Maile Zhou , Junhui Cheng","doi":"10.1016/j.aiia.2025.10.001","DOIUrl":"10.1016/j.aiia.2025.10.001","url":null,"abstract":"<div><div>As automation becomes increasingly adopted to mitigate labor shortages and boost productivity, autonomous technologies such as tractors, drones, and robotic devices are being utilized for various tasks that include plowing, seeding, irrigation, fertilization, and harvesting. Successfully navigating these changing agricultural landscapes necessitates advanced sensing, control, and navigation systems that can adapt in real time to guarantee effective and safe operations. This review focuses on obstacle avoidance systems in autonomous farming machinery, highlighting multi-functional capabilities within intricate field settings. It analyzes various sensing technologies, LiDAR, visual cameras, radar, ultrasonic sensors, GPS/GNSS, and inertial measurement units (IMU) for their individual and collective contributions to precise obstacle detection in fluctuating field conditions. The review examines the potential of multi-sensor fusion to enhance detection accuracy and reliability, with a particular emphasizing on achieving seamless obstacle recognition and response. It addresses recent advancements in control and navigation systems, particularly focusing on path-planning algorithms and real-time decision-making. It enables autonomous systems to adjust dynamically across multi-functional agricultural environments. The methodologies used for path planning, including adaptive and learning-based strategies, are discussed for their ability to optimize navigation in complicated field conditions. Real-time decision-making frameworks are similarly evaluated for their capacity to provide prompt, data-driven reactions to changing obstacles, which is critical for maintaining operational efficiency. Moreover, this review discusses environmental and topographical challenges like variable terrain, unpredictable weather, complex crop arrangements, and interference from co-located machinery that hinder obstacle detection and necessitate adaptive, resilient system responses. In addition, the paper emphasizes future research opportunities, highlighting the significance of advancements in multi-sensor fusion, deep learning for perception, adaptive path planning, model-free control strategies, artificial intelligence, and energy-efficient designs. Enhancing obstacle avoidance systems enables autonomous agricultural machinery to transform modern farming by increasing efficiency, precision, and sustainability. The review highlights the potential of these technologies to support global efforts for sustainable agriculture and food security, aligning agricultural innovation with the needs of a swiftly growing population.</div></div>","PeriodicalId":52814,"journal":{"name":"Artificial Intelligence in Agriculture","volume":"16 1","pages":"Pages 139-163"},"PeriodicalIF":12.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145264762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-10-02DOI: 10.1016/j.aiia.2025.10.003
Liuyan Feng , Changsu Xu , Han Tang , Zhongcai Wei , Xiaodong Guan , Jingcheng Xu , Mingjin Yang , Yunwu Li
With the rapid advancement of information technology, the intelligent and unmanned applications of agricultural machinery and equipment have become a central focus of current research. Navigation technology is central to achieving autonomous driving in agricultural machinery and plays a key role in advancing intelligent agriculture. However, although some studies have reviewed aspects of agricultural machinery navigation technologies, a comprehensive and systematic overview that clearly outlines the developmental trajectory of these technologies is still lacking. At the same time, there is an urgent need to break through traditional navigation frameworks to address the challenges posed by complex agricultural environments. Addressing this gap, this study provides a comprehensive overview of the evolution of navigation technologies in agricultural machinery, categorizing them into three stages: assisted navigation, autonomous navigation, and intelligent navigation, based on the level of autonomy in agricultural machinery. Special emphasis is placed on the brain-inspired navigation technology, which is an important branch of intelligent navigation and has attracted widespread attention as an emerging direction. It innovatively mimics the cognitive and learning abilities of the brain, demonstrating high adaptability and robustness to better handle uncertainty and complex environments. Importantly, this paper innovatively explores six potential applications of brain-inspired navigation technology in the agricultural field, highlighting its significant potential to enhance the intelligence of agricultural machinery. The review concludes by discussing current limitations and future research directions. The findings of this study aim to guide the development of more intelligent, adaptive, and resilient navigation systems, accelerating the transformation toward fully autonomous agricultural operations.
{"title":"Application of navigation technology in agricultural machinery: A review and prospects","authors":"Liuyan Feng , Changsu Xu , Han Tang , Zhongcai Wei , Xiaodong Guan , Jingcheng Xu , Mingjin Yang , Yunwu Li","doi":"10.1016/j.aiia.2025.10.003","DOIUrl":"10.1016/j.aiia.2025.10.003","url":null,"abstract":"<div><div>With the rapid advancement of information technology, the intelligent and unmanned applications of agricultural machinery and equipment have become a central focus of current research. Navigation technology is central to achieving autonomous driving in agricultural machinery and plays a key role in advancing intelligent agriculture. However, although some studies have reviewed aspects of agricultural machinery navigation technologies, a comprehensive and systematic overview that clearly outlines the developmental trajectory of these technologies is still lacking. At the same time, there is an urgent need to break through traditional navigation frameworks to address the challenges posed by complex agricultural environments. Addressing this gap, this study provides a comprehensive overview of the evolution of navigation technologies in agricultural machinery, categorizing them into three stages: assisted navigation, autonomous navigation, and intelligent navigation, based on the level of autonomy in agricultural machinery. Special emphasis is placed on the brain-inspired navigation technology, which is an important branch of intelligent navigation and has attracted widespread attention as an emerging direction. It innovatively mimics the cognitive and learning abilities of the brain, demonstrating high adaptability and robustness to better handle uncertainty and complex environments. Importantly, this paper innovatively explores six potential applications of brain-inspired navigation technology in the agricultural field, highlighting its significant potential to enhance the intelligence of agricultural machinery. The review concludes by discussing current limitations and future research directions. The findings of this study aim to guide the development of more intelligent, adaptive, and resilient navigation systems, accelerating the transformation toward fully autonomous agricultural operations.</div></div>","PeriodicalId":52814,"journal":{"name":"Artificial Intelligence in Agriculture","volume":"16 1","pages":"Pages 94-123"},"PeriodicalIF":12.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145264764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-19DOI: 10.1016/S1872-5813(26)60646-9
Lin YANG , Yanfang YANG , Kuan LU
As a key component of shale oil, petroleum fractions, and chemical products, the oxidative pyrolysis behavior of paraffin directly influences energy conversion efficiency and the direction of process optimization. A deep understanding of its oxidative pyrolysis mechanism is crucial for addressing wax deposition in oil and gas extraction, enhancing product selectivity in cracking processes, and advancing novel clean fuel technologies. Traditional experimental methods face challenges in capturing transient free-radical reaction pathways at high temperatures, whereas molecular dynamics simulations offer a powerful approach to bridge the research gap in elucidating atomic-scale dynamic mechanisms. This database is constructed based on high-precision molecular dynamics simulations, comprising oxidative pyrolysis trajectory data for three paraffin models featuring different straight-chain hydrocarbon distributions within the temperature range of 2100–2500 K. The COMPASS force field was employed to optimize the initial structures, and the ReaxFF reactive force field was used to simulate the oxidative pyrolysis process. The database includes atomic trajectories, species evolution information, and reaction network analysis results for both heating and isothermal cracking processes, with a total data volume of approximately 141 GB (including 150000 atomic configuration frames). The data is stored in a hierarchical directory structure, supporting multi-scale oxidative pyrolysis mechanism studies and providing atomic-scale dynamic evidence for revealing carbon chain length effects and temperature sensitivity.
{"title":"Molecular dataset based on paraffin oxidative pyrolysis","authors":"Lin YANG , Yanfang YANG , Kuan LU","doi":"10.1016/S1872-5813(26)60646-9","DOIUrl":"10.1016/S1872-5813(26)60646-9","url":null,"abstract":"<div><div>As a key component of shale oil, petroleum fractions, and chemical products, the oxidative pyrolysis behavior of paraffin directly influences energy conversion efficiency and the direction of process optimization. A deep understanding of its oxidative pyrolysis mechanism is crucial for addressing wax deposition in oil and gas extraction, enhancing product selectivity in cracking processes, and advancing novel clean fuel technologies. Traditional experimental methods face challenges in capturing transient free-radical reaction pathways at high temperatures, whereas molecular dynamics simulations offer a powerful approach to bridge the research gap in elucidating atomic-scale dynamic mechanisms. This database is constructed based on high-precision molecular dynamics simulations, comprising oxidative pyrolysis trajectory data for three paraffin models featuring different straight-chain hydrocarbon distributions within the temperature range of 2100–2500 K. The COMPASS force field was employed to optimize the initial structures, and the ReaxFF reactive force field was used to simulate the oxidative pyrolysis process. The database includes atomic trajectories, species evolution information, and reaction network analysis results for both heating and isothermal cracking processes, with a total data volume of approximately 141 GB (including 150000 atomic configuration frames). The data is stored in a hierarchical directory structure, supporting multi-scale oxidative pyrolysis mechanism studies and providing atomic-scale dynamic evidence for revealing carbon chain length effects and temperature sensitivity.</div><div><span><figure><span><img><ol><li><span><span>Download: <span>Download high-res image (281KB)</span></span></span></li><li><span><span>Download: <span>Download full-size image</span></span></span></li></ol></span></figure></span></div></div>","PeriodicalId":15956,"journal":{"name":"燃料化学学报","volume":"54 3","pages":"Article 20250365"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147409569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-22DOI: 10.1016/j.wse.2025.12.005
Mustafa Alkayed , Behzad Lak , S. Samuel Li
An open-channel transition is needed in most water conveyance channels to connect channel sections with different cross-sectional shapes, areas, bottom slopes, or their combinations. However, these transitions inherently create adverse pressure gradients, flow separation, turbulent eddies, and energy losses, presenting a long-standing hydraulic issue. This study investigated a warped transition (WT), a transition type favored for its smooth linking geometry, which connected a small rectangular upstream channel section to a large downstream trapezoidal section, and evaluated the effectiveness of installing a honeycomb in the WT in reducing turbulence and improving flow characteristics and hydraulic efficiency. The three-dimensional velocity field of turbulent flow was measured using an acoustic Doppler velocimeter. The results showed that the honeycomb effectively improved mean flow properties by enhancing the uniformity of primary flow and reducing the strength of secondary currents and reversed flow. The cell size of the honeycomb limited the formation of larger energy-bearing turbulent eddies. Compared to a conventional WT without a honeycomb, the modified transition exhibited less severe flow separation and lower turbulence intensities. Implementing a honeycomb is a practical and inexpensive intervention for both existing and new transitions. The findings of this study provide valuable insights for improving the design of water conveyance channels.
{"title":"Enhancing mean flow characteristics and reducing turbulence in channel transition using honeycomb","authors":"Mustafa Alkayed , Behzad Lak , S. Samuel Li","doi":"10.1016/j.wse.2025.12.005","DOIUrl":"10.1016/j.wse.2025.12.005","url":null,"abstract":"<div><div>An open-channel transition is needed in most water conveyance channels to connect channel sections with different cross-sectional shapes, areas, bottom slopes, or their combinations. However, these transitions inherently create adverse pressure gradients, flow separation, turbulent eddies, and energy losses, presenting a long-standing hydraulic issue. This study investigated a warped transition (WT), a transition type favored for its smooth linking geometry, which connected a small rectangular upstream channel section to a large downstream trapezoidal section, and evaluated the effectiveness of installing a honeycomb in the WT in reducing turbulence and improving flow characteristics and hydraulic efficiency. The three-dimensional velocity field of turbulent flow was measured using an acoustic Doppler velocimeter. The results showed that the honeycomb effectively improved mean flow properties by enhancing the uniformity of primary flow and reducing the strength of secondary currents and reversed flow. The cell size of the honeycomb limited the formation of larger energy-bearing turbulent eddies. Compared to a conventional WT without a honeycomb, the modified transition exhibited less severe flow separation and lower turbulence intensities. Implementing a honeycomb is a practical and inexpensive intervention for both existing and new transitions. The findings of this study provide valuable insights for improving the design of water conveyance channels.</div></div>","PeriodicalId":23628,"journal":{"name":"Water science and engineering","volume":"19 1","pages":"Pages 132-143"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147409681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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