Revolutionizing neuromorphic computing: brain-like functions emerge from standard silicon transistors.

Sci Bull (Beijing)

School of Physics and Technology, Wuhan University, Wuhan 430072, China. Electronic address:

Published: August 2025


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scib.2025.08.043DOI Listing

Publication Analysis

Top Keywords

revolutionizing neuromorphic
4
neuromorphic computing
4
computing brain-like
4
brain-like functions
4
functions emerge
4
emerge standard
4
standard silicon
4
silicon transistors
4
revolutionizing
1
computing
1

Similar Publications

Temperature-dependent resistive switching statistics and mechanisms in nanoscale graphene-SiO-graphene memristors.

Nanoscale

July 2025

Beijing National Center for Condensed Matter Physics, Beijing Key Laboratory for Nanomaterials and Nanodevices, Institute of Physics, Chinese Academy of Sciences (CAS), Beijing 100190, China.

The development of memristors presents a transformative opportunity to revolutionize electronic devices and computing systems by enabling non-volatile memory and neuromorphic computing. Silicon oxide memristors are particularly promising due to their potential for low cost, high integration and compatibility with existing manufacturing processes. In this study, we statistically investigate the switching mechanisms of a nanoscale (sub-2 nm) silicon oxide memristor at different temperatures.

View Article and Find Full Text PDF

2D van der Waals (vdW) ferroelectric materials are emerging as transformative components in modern electronics and neuromorphic computing. The atomic-scale thickness, coupled with robust ferroelectric properties and seamless integration into vdW engineering, offers unprecedented opportunities for the development of high-performance and low-power devices. Notably, 2D ferroelectric devices excel in enabling multistate storage and neuromorphic functionalities in emulating synapses or retinas, positioning them as prime candidates for next-generation in-sensor-and-memory units.

View Article and Find Full Text PDF

Novel non-volatile memory devices are under intense investigation to revolutionize information processing for ultra-energy-efficient implementation of artificial intelligence and machine learning tasks. Ferroelectric memory devices with ultra-low power and fast operation, non-volatile data retention and reliable switching to multiple polarization states promise one such option for memory and synaptic weight elements in neuromorphic hardware. For quick adaptation by industry, complementary metal oxide semiconductor process compatibility is a key criterion that led to huge attention to hafnia-based FE materials.

View Article and Find Full Text PDF

Organic Mixed Conductors for Neural Biomimicry and Biointerfacing.

Annu Rev Chem Biomol Eng

June 2025

Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, Norrköping, Sweden; email:

Organic mixed ionic-electronic conductors (OMIECs) could revolutionize bioelectronics by enabling seamless integration with biological systems. This review explores their role in neural biomimicry and biointerfacing, with a focus on how backbone design, sidechain optimization, and antiambipolarity impact performance. Recent advances highlight OMIECs' biocompatibility and mechanical compliance, making them ideal for bioelectronic applications.

View Article and Find Full Text PDF