Piezocatalytic technology demonstrates significant potential for effectively degrading pollutants and facilitating green chemical reactions,indicating promising development prospects.In this study,multi-flaw MoS_(2) n...Piezocatalytic technology demonstrates significant potential for effectively degrading pollutants and facilitating green chemical reactions,indicating promising development prospects.In this study,multi-flaw MoS_(2) nanosheets were synthesized via a hydrothermal method,and CuS nanoparticles were loaded onto their surface to form CuS/MoS_(2) piezocatalysts.The 40%CuS/MoS_(2) nanocomposite achieved an 86%degradation rate of TC under low-power(100 W,40 kHz)ultrasonic irradiation,which are 1.53 and 1.75 times higher than that of pure MoS_(2) and CuS,respectively.Furthermore,piezoresponse force microscopy(PFM)confirmed the excellent piezocatalytic performance of the composite material.The piezocurrent images revealed a significant enhancement in the piezoelectric properties of 40%CuS/MoS_(2),which is attributed to the construction of the CuS/MoS_(2) heterojunction promoting the separation of electrons and holes.This research provides a novel conceptual framework for enhancing the performance of piezocatalytic degradation.展开更多
为改善单一预警算法出现的误警率高、漏警率高、预警不及时等问题,避免车道偏离预警系统出现频繁报警、干扰驾驶员操作等情况,提高系统的抗干扰性和适应性,论文提出了一种基于多因素模糊模式识别的驾驶员意图分析方法。结合横向车辆偏...为改善单一预警算法出现的误警率高、漏警率高、预警不及时等问题,避免车道偏离预警系统出现频繁报警、干扰驾驶员操作等情况,提高系统的抗干扰性和适应性,论文提出了一种基于多因素模糊模式识别的驾驶员意图分析方法。结合横向车辆偏离时间TLC(Time to Lane Crossing)和车辆目前位置CCP(Car Current Position)的车道偏离预警算法,同时考虑到驾驶员的驾驶特性,将驾驶员类型、车辆轮胎与车道边界线的距离、跨道时间作为影响车道偏离的因素并进行模糊化处理,设置合理的模糊规则,输出车道偏离程度的模糊评价指数。最后在Matlab中搭建控制模型,并与CARSIM做联合仿真来验证算法。仿真结果表明算法具有较好的实效性。展开更多
基金Funding Projects for Young Backbone Teachers of Higher Education Institutions in Henan Province(2023GGJS020)National Natural Science Foundation of China(21901061,22171071)。
文摘Piezocatalytic technology demonstrates significant potential for effectively degrading pollutants and facilitating green chemical reactions,indicating promising development prospects.In this study,multi-flaw MoS_(2) nanosheets were synthesized via a hydrothermal method,and CuS nanoparticles were loaded onto their surface to form CuS/MoS_(2) piezocatalysts.The 40%CuS/MoS_(2) nanocomposite achieved an 86%degradation rate of TC under low-power(100 W,40 kHz)ultrasonic irradiation,which are 1.53 and 1.75 times higher than that of pure MoS_(2) and CuS,respectively.Furthermore,piezoresponse force microscopy(PFM)confirmed the excellent piezocatalytic performance of the composite material.The piezocurrent images revealed a significant enhancement in the piezoelectric properties of 40%CuS/MoS_(2),which is attributed to the construction of the CuS/MoS_(2) heterojunction promoting the separation of electrons and holes.This research provides a novel conceptual framework for enhancing the performance of piezocatalytic degradation.
文摘为改善单一预警算法出现的误警率高、漏警率高、预警不及时等问题,避免车道偏离预警系统出现频繁报警、干扰驾驶员操作等情况,提高系统的抗干扰性和适应性,论文提出了一种基于多因素模糊模式识别的驾驶员意图分析方法。结合横向车辆偏离时间TLC(Time to Lane Crossing)和车辆目前位置CCP(Car Current Position)的车道偏离预警算法,同时考虑到驾驶员的驾驶特性,将驾驶员类型、车辆轮胎与车道边界线的距离、跨道时间作为影响车道偏离的因素并进行模糊化处理,设置合理的模糊规则,输出车道偏离程度的模糊评价指数。最后在Matlab中搭建控制模型,并与CARSIM做联合仿真来验证算法。仿真结果表明算法具有较好的实效性。
