Recent Advances in Neuromorphic Devices Based on 2D Materials

Abstract The convergence of neuromorphic computing and 2D materials presents a transformative approach to overcoming the von Neumann bottleneck by unifying sensing, memory, and computation. Owing to their atomic thickness, diverse physical effects (e.g., ferroelectricity, quantum tunneling, and phase transitions), and van der Waals (vdWs) heterostructure compatibility, 2D materials have demonstrated remarkable potential in emulating synaptic plasticity and enabling multifunctional, low‐power neuromorphic systems. This review comprehensively summarizes the recent progress from 2010 to 2025 in 2D materials‐based neuromorphic devices, spanning memristors, electrolyte‐gated and ferroelectric transistors, and floating‐gate memory. Breakthroughs include sub‐100 mV switching voltages, femtojoule‐level energy consumption, and multimodal perception capabilities. Special attention is given to bioinspired interactive systems integrating tactile, visual, and auditory functions for real‐time processing. Furthermore, the key material innovations that address non‐idealities, such as device variability and instability, via interface engineering, defect control, and heterostructure design are analyzed. These developments underscore the critical role of 2D materials in enabling highly integrated, energy‐efficient, and intelligent neuromorphic hardware for next‐generation AI and edge computing applications.

Authors

Institutions

Publication Details

Journal
Advanced Materials Technologies
Published
2025-11-08
DOI
https://doi.org/10.1002/admt.202501408
Citations
2
Primary Topic
2D Materials and Applications
Type
article
Field-Weighted Citation Impact
1.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Recent Advances in Neuromorphic Devices Based on 2D Materials

Qiaoqiao Kang, Tian‐Ling Ren, Shukai Li, Pengwen Guo et al.
2 citations
Advanced Materials Technologies
2D Materials and Applications
1.04
article

Recent Advances in Neuromorphic Devices Based on 2D Materials

Qiaoqiao Kang, Tian‐Ling Ren, Shukai Li, Pengwen Guo, Jiong Pan, Yan Li, Mengmeng Jia, Haolin Yang, Yi Yang
article en
2 citations

Abstract

Abstract The convergence of neuromorphic computing and 2D materials presents a transformative approach to overcoming the von Neumann bottleneck by unifying sensing, memory, and computation. Owing to their atomic thickness, diverse physical effects (e.g., ferroelectricity, quantum tunneling, and phase transitions), and van der Waals (vdWs) heterostructure compatibility, 2D materials have demonstrated remarkable potential in emulating synaptic plasticity and enabling multifunctional, low‐power neuromorphic systems. This review comprehensively summarizes the recent progress from 2010 to 2025 in 2D materials‐based neuromorphic devices, spanning memristors, electrolyte‐gated and ferroelectric transistors, and floating‐gate memory. Breakthroughs include sub‐100 mV switching voltages, femtojoule‐level energy consumption, and multimodal perception capabilities. Special attention is given to bioinspired interactive systems integrating tactile, visual, and auditory functions for real‐time processing. Furthermore, the key material innovations that address non‐idealities, such as device variability and instability, via interface engineering, defect control, and heterostructure design are analyzed. These developments underscore the critical role of 2D materials in enabling highly integrated, energy‐efficient, and intelligent neuromorphic hardware for next‐generation AI and edge computing applications.

Advanced Materials TechnologiesVol. 11(4)
Taiyuan University of Technology (CN), Tsinghua University (CN)
Openalex Percentile: Top 21%
2D Materials and Applications
1.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Recent Advances in Neuromorphic Devices Based on 2D Materials — Qiaoqiao Kang, Tian‐Ling Ren, et al. · Advanced Materials Technologies (2025) | TGRS Research Map | TGRS