Results 161 to 170 of about 76,792 (271)

Reversible and Controllable Transition Between Filamentary and Interfacial Resistive Switching in HfO2‐Based Memristors

Advanced Electronic Materials, EarlyView.
5 nm HfO2 memristors exhibit a fully reversible, voltage‐controlled transition between filamentary and interfacial switching within the same device. At high voltages, a filament forms and dominates the conduction, whereas at lower voltages the device reversibly returns to interfacial mode without defect accumulation, implying a new reversible ...
Cuo Wu, Hao Shen, Richard Schroedter, Chong Peng, Hampus Hoffman, Stefan Slesazeck, Ronald Tetzlaff, Thomas Mikolajick, Benjamin Max   +8 more
wiley   +1 more source

Versatile optoelectronic memristor based on wide-bandgap Ga₂O₃ for artificial synapses and neuromorphic computing. [PDF]

Light Sci Appl
Cui D, Pei M, Lin Z, Zhang H, Kang M, Wang Y, Gao X, Su J, Miao J, Li Y, Zhang J, Hao Y, Chang J.   +12 more
europepmc   +1 more source

Reconfigurable, Non‐Volatile Switching in WO3 Film for Resistive Memory and Multistate Programming Toward Energy‐Efficient Neuromorphic Computing Applications

Advanced Electronic Materials, EarlyView.
WO3${\rm WO}_3$ based resistive switching device was precisely controlled and shows the reconfigurable, non‐volatile switching which can be programmable to multi‐resistance states for memory applications. The memory device can also be utilised for low energy neuromorphic application.
Keval Hadiyal, Nagarajan Raghavan, Ramesh Mohan Thamankar   +2 more
wiley   +1 more source

Selective UV Sensing for Energy-Efficient UV-A Artificial Synapses Using a ZnO/ZnGa₂O₄ Heterojunction Diode. [PDF]

Small
Khan T, Kandar S, Ali S, Singh P, Horng RH, Singh R.   +5 more
europepmc   +1 more source

Electrode‐Engineered Dual‐Mode Multifunctional Lead‐Free Perovskite Optoelectronic Memristors for Neuromorphic Computing

Advanced Electronic Materials, EarlyView.
A lead‐free perovskite memristive solar cell structure that call emulate both synaptic and neuronal functions controlled by light and electric fields depending on top electrode type. ABSTRACT Memristive devices based on halide perovskites hold strong promise to provide energy‐efficient systems for the Internet of Things (IoT); however, lead (Pb ...
Michalis Loizos, Konstantinos Rogdakis, Konstantinos Chatzimanolis, Katerina Anagnostou, Emmanuel Kymakis   +4 more
wiley   +1 more source

Triboelectric Tactile Transducers for Neuromorphic Sensing and Synaptic Emulation: Materials, Architectures, and Interfaces

Advanced Energy and Sustainability Research, EarlyView.
Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar, Arunkumar Chandrasekhar, Poongundran Selvaprabhu   +2 more
wiley   +1 more source

Highly Promising 2D/1D BP-C/CNT Bionic Opto-Olfactory Co-Sensory Artificial Synapses for Multisensory Integration. [PDF]

Adv Sci (Weinh)
Dong L, Xue B, Wei G, Yuan S, Chen M, Liu Y, Su Y, Niu Y, Xu B, Wang P.   +9 more
europepmc   +1 more source

Designing Memristive Materials for Artificial Dynamic Intelligence

Advanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

Domain wall magnetic tunnel junction-based artificial synapses and neurons for all-spin neuromorphic hardware. [PDF]

Nat Commun
Liu L, Wang D, Wang D, Sun Y, Lin H, Gong X, Zhang Y, Tang R, Mai Z, Hou Z, Yang Y, Li P, Wang L, Luo Q, Li L, Xing G, Liu M.   +16 more
europepmc   +1 more source

Flexible Memory: Progress, Challenges, and Opportunities

Advanced Intelligent Discovery, EarlyView.
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan, Sen Chen, Minghui Guo, Ziliang Cui, Yujie Du, Jing Liu   +5 more
wiley   +1 more source