Results 81 to 90 of about 5,289 (241)

Hydrogen‐Stabilized Self‐Rectifying Memristor Arrays for Reliable Multilevel Synapses in Transformer‐Based Keyword Spotting

Advanced Science, EarlyView.
A non‐filamentary self‐rectifying HfO2/TiOx resistive random‐access memory integrates H2 annealing with an incremental step pulse with verify algorithm to achieve stable and linear analog conductance modulation. The device enables low‐current 6‐bit multilevel operation while suppressing sneak current in crossbar arrays. Implemented in Transformer‐based
Seonjeong Lee, Seohyeon Ju, Won Joo Lee, Myounggon Kang, Sungjun Kim, Yoon Kim   +5 more
wiley   +1 more source

RRAM Variability Harvesting for CIM‐Integrated TRNG

Advanced Electronic Materials, EarlyView.
This work demonstrates a compute‐in‐memory‐compatible true random number generator that harvests intrinsic cycle‐to‐cycle variability from a 1T1R RRAM array. Parallel entropy extraction enables high‐throughput bit generation without dedicated circuits. This approach achieves NIST‐compliant randomness and low per‐bit energy, offering a scalable hardware
Ankit Bende, Gokulnath Rajendran, Regina Dittmann, Anupam Chattopadhyay, Vikas Rana   +4 more
wiley   +1 more source

Resistance Non-volatile Memory – RRAM [PDF]

, 2007
Electric-pulse induced resistance (EPIR) change effect encompasses the reversible change of resistance of a thin oxide film under the application of short, low voltage pulses.
Yibo Nian, Christina Papagianni, John Strozier, Shangqing Liu, Alex Ignatiev, Xin Chen, Naijuan Wu   +6 more
core   +1 more source

Design of an FPGA-based RRAM parameter measurement platform [PDF]

, 2018
Flash memory has been the dominant technology in non-volatile memory market for the last couple of decades. Along with down-scaling in the CMOS manufacturing process, industry and academia started to evaluate the use of alternative memory cell ...
Tekin, Serdar B.
core   +3 more sources

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Overcoming the Trade‐off in Oscillatory TRNGs With a Hybrid NbO2 and Atomic Fluctuation Entropy Source Architecture

Advanced Electronic Materials, EarlyView.
A hybrid oscillator combining an atomic swith and an insulator‐to metal transition device converts stochastic filament resistance into random oscillation periods. The interaction between highly variable atomic switching and stable high‐frequency oscillation amplifies entropy, enabling fast energy‐efficient, and reliable true random number generation ...
Sunhyeong Lee, Seongjae Heo, Dongmin Kim, Ohhyuk Kwon, Hyunsang Hwang   +4 more
wiley   +1 more source

Resistive random access memory: introduction to device mechanism, materials and application to neuromorphic computing

Nanoscale Research Letters, 2023
The modern-day computing technologies are continuously undergoing a rapid changing landscape; thus, the demands of new memory types are growing that will be fast, energy efficient and durable.
Furqan Zahoor, Fawnizu Azmadi Hussin, Usman Bature Isyaku, Shagun Gupta, Farooq Ahmad Khanday, Anupam Chattopadhyay, Haider Abbas   +6 more
doaj   +1 more source

Model‐Based Time‐Modulated Write Algorithm for 1R Analog Memristive Crossbar Arrays

Advanced Electronic Materials, EarlyView.
A novel model‐based time‐modulated write algorithm efficiently programs analog 1R memristive crossbar arrays by varying pulse duration at a fixed voltage. By leveraging a physics‐based compact model and a dynamic gain mechanism, this approach overcomes device nonlinearities and parasitic effects.
Richard Schroedter, Ahmet Samil Demirkol, Ioannis Messaris, Christian Bruchatz, Eter Mgeladze, Stefan Slesazeck, Thomas Mikolajick, Ronald Tetzlaff   +7 more
wiley   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range

Advanced Electronic Materials, EarlyView.
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel, Aleix Barrera, Lluís Balcells, Narcís Mestres, Enrique Miranda, Anna Palau, Jordi Suñé   +6 more
wiley   +1 more source