Two‐Dimensional Materials for Flexible Neuromorphic Devices: Materials, Engineering Strategies, Architectures, and Emerging Applications

ABSTRACT Two‐dimensional (2D) materials offer a distinctive foundation for flexible neuromorphic electronics by combining atomically thin structures, mechanical compliance, and tunable electronic, ionic, and interfacial properties. These features are essential for artificial synapses, memristors, synaptic transistors, and bio‐inspired devices that require low operating voltage, reduced energy consumption, stable conductance modulation, and reliable operation under mechanical deformation. This review provides a materials‐centered analysis of recent progress in 2D‐material‐based flexible neuromorphic devices. Primary 2D material platforms, including graphene‐derived sheets, MXenes, transition‐metal dichalcogenides, black phosphorus, and other layered or nanosheet systems, are distinguished from 2D‐like CNT‐network films and hybrid functional layers and are compared according to their dimensionality, structural form, and device role. Defect engineering, van der Waals heterostructure design, and surface functionalization are then examined as key routes for regulating charge transport, ion migration, synaptic linearity, mechanical robustness, and environmental stability. Flexible memristive devices, synaptic transistors, and bio‐integrated neuromorphic systems are further discussed within this material‐to‐device framework. By clarifying the links among material properties, engineering strategies, device architectures, neuromorphic metrics, and deformation‐stable functionality, this review provides mechanism‐guided design principles for scalable, energy‐efficient, and application‐oriented 2D neuromorphic platforms.

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Publication Details

Journal
Advanced Electronic Materials
Published
2026-08-24
DOI
https://doi.org/10.1002/aelm.70543
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Two‐Dimensional Materials for Flexible Neuromorphic Devices: Materials, Engineering Strategies, Architectures, and Emerging Applications

Letian Dai, Junzhe Tang
Advanced Electronic Materials
Advanced Memory and Neural Computing
article

Two‐Dimensional Materials for Flexible Neuromorphic Devices: Materials, Engineering Strategies, Architectures, and Emerging Applications

Letian Dai, Junzhe Tang
article en

Abstract

ABSTRACT Two‐dimensional (2D) materials offer a distinctive foundation for flexible neuromorphic electronics by combining atomically thin structures, mechanical compliance, and tunable electronic, ionic, and interfacial properties. These features are essential for artificial synapses, memristors, synaptic transistors, and bio‐inspired devices that require low operating voltage, reduced energy consumption, stable conductance modulation, and reliable operation under mechanical deformation. This review provides a materials‐centered analysis of recent progress in 2D‐material‐based flexible neuromorphic devices. Primary 2D material platforms, including graphene‐derived sheets, MXenes, transition‐metal dichalcogenides, black phosphorus, and other layered or nanosheet systems, are distinguished from 2D‐like CNT‐network films and hybrid functional layers and are compared according to their dimensionality, structural form, and device role. Defect engineering, van der Waals heterostructure design, and surface functionalization are then examined as key routes for regulating charge transport, ion migration, synaptic linearity, mechanical robustness, and environmental stability. Flexible memristive devices, synaptic transistors, and bio‐integrated neuromorphic systems are further discussed within this material‐to‐device framework. By clarifying the links among material properties, engineering strategies, device architectures, neuromorphic metrics, and deformation‐stable functionality, this review provides mechanism‐guided design principles for scalable, energy‐efficient, and application‐oriented 2D neuromorphic platforms.

Advanced Electronic Materials
Lanzhou University of Technology (CN), Wuhan National Laboratory for Optoelectronics (CN), Lanzhou City University (CN), Hubei University of Technology (CN), Lanzhou University (CN)
Natural Science Foundation of Hubei Province
Affordable and clean energy
Openalex Percentile: Top 19%
Advanced Memory and Neural Computing
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