Electrochemical ion insertion from the atomic to the device scale

A Sood, AD Poletayev, DA Cogswell… - Nature Reviews …, 2021 - nature.com
Electrochemical ion insertion involves coupled ion–electron transfer reactions, transport of
guest species and redox of the host. The hosts are typically anisotropic solids with 2D …

Materials strategies for organic neuromorphic devices

A Gumyusenge, A Melianas, ST Keene… - Annual Review of …, 2021 - annualreviews.org
Neuromorphic computing is becoming increasingly prominent as artificial intelligence (AI)
facilitates progressively seamless interaction between humans and machines. The …

[HTML][HTML] Analog architectures for neural network acceleration based on non-volatile memory

TP Xiao, CH Bennett, B Feinberg, S Agarwal… - Applied Physics …, 2020 - pubs.aip.org
Analog hardware accelerators, which perform computation within a dense memory array,
have the potential to overcome the major bottlenecks faced by digital hardware for data …

CMOS-compatible electrochemical synaptic transistor arrays for deep learning accelerators

J Cui, F An, J Qian, Y Wu, LL Sloan, S Pidaparthy… - Nature …, 2023 - nature.com
In-memory computing architectures based on memristive crossbar arrays could offer higher
computing efficiency than traditional hardware in deep learning applications. However, the …

Oxide‐based electrolyte‐gated transistors for spatiotemporal information processing

Y Li, J Lu, D Shang, Q Liu, S Wu, Z Wu… - Advanced …, 2020 - Wiley Online Library
Spiking neural networks (SNNs) sharing large similarity with biological nervous systems are
promising to process spatiotemporal information and can provide highly time‐and energy …

[HTML][HTML] Intrinsically stretchable neuromorphic devices for on-body processing of health data with artificial intelligence

S Dai, Y Dai, Z Zhao, F Xia, Y Li, Y Liu, P Cheng… - Matter, 2022 - cell.com
For leveraging wearable technologies to advance precision medicine, personalized and
learning-based analysis of continuously acquired health data is indispensable, for which …

Filament‐free bulk resistive memory enables deterministic analogue switching

Y Li, EJ Fuller, JD Sugar, S Yoo, DS Ashby… - Advanced …, 2020 - Wiley Online Library
Digital computing is nearing its physical limits as computing needs and energy consumption
rapidly increase. Analogue‐memory‐based neuromorphic computing can be orders of …

One transistor one electrolyte‐gated transistor based spiking neural network for power‐efficient neuromorphic computing system

Y Li, Z Xuan, J Lu, Z Wang, X Zhang… - Advanced Functional …, 2021 - Wiley Online Library
Neuromorphic computing powered by spiking neural networks (SNN) provides a powerful
and efficient information processing paradigm. To harvest the advantage of SNNs, compact …

Multilevel memory and artificial synaptic plasticity in P (VDF-TrFE)-based ferroelectric field effect transistors

Y Sun, N He, Y Wang, Q Yuan, D Wen - Nano Energy, 2022 - Elsevier
Multilevel data memory and artificial synaptic plasticity in poly (vinylidene fluoride-co-
trifluoroethylene)[P (VDF-TrFE)] ferroelectric field effect transistors were demonstrated. The …

Thin-film transistors for emerging neuromorphic electronics: Fundamentals, materials, and pattern recognition

C Wang, Y Li, Y Wang, X Xu, M Fu, Y Liu… - Journal of Materials …, 2021 - pubs.rsc.org
The main goal of the field of neuromorphic electronics is to develop novel microelectronic
components that emulate the memory and computing functionalities of the biological …