Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been c...Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.展开更多
Seagoing vessels are responsible for more than 90%of global freight traffic,but meanwhile,emission pollutants(NO_(x)and SO_(x))of seagoing vessels also cause serious air pollution.Nonthermal plasma(NTP)combined with w...Seagoing vessels are responsible for more than 90%of global freight traffic,but meanwhile,emission pollutants(NO_(x)and SO_(x))of seagoing vessels also cause serious air pollution.Nonthermal plasma(NTP)combined with wet scrubbing technology is considered to be a promising technology.In order to improve the oxidation efficiency and energy efficiency of the NTP reactor,the screw and rod inner electrodes of dielectric barrier discharge(DBD)reactor were investigated.To analyze the mechanism,the optical emission spectra(OES)of NTP were measured and numerical calculation was applied.The experiment results show that the NO oxidation removal efficiency of screw electrode is lower than that of rod electrode.However,the SO_(2)removal efficiency of screw electrode is higher.According to the OES experiment and numerical calculation,the electric field intensity of the screw electrode surface is much higher than that of the rod electrode surface,and it is easier to generate N radicals to form NO.For the same energy density condition,the OH radical generation efficiency of the screw electrode reactor is similar to that of the rod electrode,but the gas temperature in the discharge gap is higher.Therefore,the SO2 oxidation efficiency of the thread electrode is higher.This study provides guidance for the optimization of oxidation efficiency and energy consumption of DBD reactor.展开更多
基金The authors acknowledge the funding provided by the National Key R&D Program of China(2021YFA1401200)Beijing Outstanding Young Scientist Program(BJJWZYJH01201910007022)+2 种基金National Natural Science Foundation of China(No.U21A20140,No.92050117,No.62005017)programBeijing Municipal Science&Technology Commission,Administrative Commission of Zhongguancun Science Park(No.Z211100004821009)This work was supported by the Synergetic Extreme Condition User Facility(SECUF).
文摘Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.
基金supported by National Natural Science Foundation of China(No.52301382)the Natural Science Foundation of Hubei Province(No.2022CFB730)Automotive Components Technology of Hubei Collaborative Innovation Project(No.2015XTZX0406)。
文摘Seagoing vessels are responsible for more than 90%of global freight traffic,but meanwhile,emission pollutants(NO_(x)and SO_(x))of seagoing vessels also cause serious air pollution.Nonthermal plasma(NTP)combined with wet scrubbing technology is considered to be a promising technology.In order to improve the oxidation efficiency and energy efficiency of the NTP reactor,the screw and rod inner electrodes of dielectric barrier discharge(DBD)reactor were investigated.To analyze the mechanism,the optical emission spectra(OES)of NTP were measured and numerical calculation was applied.The experiment results show that the NO oxidation removal efficiency of screw electrode is lower than that of rod electrode.However,the SO_(2)removal efficiency of screw electrode is higher.According to the OES experiment and numerical calculation,the electric field intensity of the screw electrode surface is much higher than that of the rod electrode surface,and it is easier to generate N radicals to form NO.For the same energy density condition,the OH radical generation efficiency of the screw electrode reactor is similar to that of the rod electrode,but the gas temperature in the discharge gap is higher.Therefore,the SO2 oxidation efficiency of the thread electrode is higher.This study provides guidance for the optimization of oxidation efficiency and energy consumption of DBD reactor.
