Recent advances and future prospects for memristive materials, devices, and systems
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
Memory devices and applications for in-memory computing
Traditional von Neumann computing systems involve separate processing and memory
units. However, data movement is costly in terms of time and energy and this problem is …
units. However, data movement is costly in terms of time and energy and this problem is …
Equivalent-accuracy accelerated neural-network training using analogue memory
Neural-network training can be slow and energy intensive, owing to the need to transfer the
weight data for the network between conventional digital memory chips and processor chips …
weight data for the network between conventional digital memory chips and processor chips …
Organic electronics for neuromorphic computing
Neuromorphic computing could address the inherent limitations of conventional silicon
technology in dedicated machine learning applications. Recent work on silicon-based …
technology in dedicated machine learning applications. Recent work on silicon-based …
Low-dimensional nanostructures for monolithic 3D-integrated flexible and stretchable electronics
Flexible/stretchable electronics, which are characterized by their ultrathin design, lightweight
structure, and excellent mechanical robustness and conformability, have garnered …
structure, and excellent mechanical robustness and conformability, have garnered …
A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing
The brain is capable of massively parallel information processing while consuming only∼ 1–
100 fJ per synaptic event,. Inspired by the efficiency of the brain, CMOS-based neural …
100 fJ per synaptic event,. Inspired by the efficiency of the brain, CMOS-based neural …
A review of resistive switching devices: performance improvement, characterization, and applications
As human society enters the big data era, huge data storage and energy‐efficient data
processing are in great demand. The resistive switching device is an emerging device with …
processing are in great demand. The resistive switching device is an emerging device with …
Neuromorphic computing using non-volatile memory
Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …
for implementing massively-parallel and highly energy-efficient neuromorphic computing …
Memristive crossbar arrays for storage and computing applications
The emergence of memristors with potential applications in data storage and artificial
intelligence has attracted wide attentions. Memristors are assembled in crossbar arrays with …
intelligence has attracted wide attentions. Memristors are assembled in crossbar arrays with …
Challenges and applications of emerging nonvolatile memory devices
W Banerjee - Electronics, 2020 - mdpi.com
Emerging nonvolatile memory (eNVM) devices are pushing the limits of emerging
applications beyond the scope of silicon-based complementary metal oxide semiconductors …
applications beyond the scope of silicon-based complementary metal oxide semiconductors …