As a two-dimensional carbon based semiconductor,C_(3)N acts as a promising material in many application areas.However,the basic physical properties such as Raman spectrum properties of C_(3)N is still not clear.In thi...As a two-dimensional carbon based semiconductor,C_(3)N acts as a promising material in many application areas.However,the basic physical properties such as Raman spectrum properties of C_(3)N is still not clear.In this paper,we clarify the Raman spectrum properties of multilayer C_(3)N.Moreover,the stacking driven Raman spectra change of multilayer C_(3)N is also discussed.展开更多
Nonlinear physical systems hold great promise for energy-efficient and lowhardware-cost information processing.However,their computational capabilities remain constrained by the complexity and tunability of system non...Nonlinear physical systems hold great promise for energy-efficient and lowhardware-cost information processing.However,their computational capabilities remain constrained by the complexity and tunability of system nonlinearity.Here we report a dual-ferroelectric gate-tunable memristor with a dipole coupling effect,achieving enlarged hysteresis,rich temporal dynamics,and nonvolatile heterosynaptic plasticity.By harnessing the dynamic nonlinearity of the dual-ferroelectric memristor,multimodal reservoir computing with an in-material fusion strategy has been achieved,which is demonstrated with a multimodal object recognition task.By exploring the static nonlinearity of the dual-ferroelectric memristor,nonlinear in-memory computing is realized with gate-tunable nonlinear functions,which successfully accelerates the Euclidean distance computation in the K-means clustering task.This work achieves strong coupling between the intrinsic physical dynamics and computational functionalities,offering new opportunities for more efficient hardware-accelerated systems.展开更多
基金supported by The National Natural Science Foundation of China (Nos. 11804353 and 11774368)Shanghai Science and Technology Committee (No. 18511110600)
文摘As a two-dimensional carbon based semiconductor,C_(3)N acts as a promising material in many application areas.However,the basic physical properties such as Raman spectrum properties of C_(3)N is still not clear.In this paper,we clarify the Raman spectrum properties of multilayer C_(3)N.Moreover,the stacking driven Raman spectra change of multilayer C_(3)N is also discussed.
基金National Natural Science Foundation of China,Grant/Award Numbers:92164302,8206100486,62404007Guangdong Provincial Key Laboratory of In-Memory Computing Chips,Grant/Award Number:2024B1212020002+5 种基金Shenzhen Science and Technology Program,Grant/Award Number:JCYJ20241202125907011Beijing Natural Science Foundation,Grant/Award Numbers:L234026,L257010,25D40029,25FY3314111 Project,Grant/Award Number:B18001Fok Ying-Tong Education FoundationTencent FoundationChina Postdoctoral Science Foundation,Grant/Award Number:2023M740051。
文摘Nonlinear physical systems hold great promise for energy-efficient and lowhardware-cost information processing.However,their computational capabilities remain constrained by the complexity and tunability of system nonlinearity.Here we report a dual-ferroelectric gate-tunable memristor with a dipole coupling effect,achieving enlarged hysteresis,rich temporal dynamics,and nonvolatile heterosynaptic plasticity.By harnessing the dynamic nonlinearity of the dual-ferroelectric memristor,multimodal reservoir computing with an in-material fusion strategy has been achieved,which is demonstrated with a multimodal object recognition task.By exploring the static nonlinearity of the dual-ferroelectric memristor,nonlinear in-memory computing is realized with gate-tunable nonlinear functions,which successfully accelerates the Euclidean distance computation in the K-means clustering task.This work achieves strong coupling between the intrinsic physical dynamics and computational functionalities,offering new opportunities for more efficient hardware-accelerated systems.
