Memristors Empowering Next‐Generation Human‐Computer Interaction

ABSTRACT With the continuous advancement of artificial intelligence, human‐computer interaction (HCI) is evolving toward intelligent perception, collaborative decision‐making, and natural integration. However, the physical separation of memory and computing units in traditional von Neumann architecture poses critical bottlenecks in terms of power consumption and latency, which limits its ability to meet the requirements of next‐generation HCI systems. Memristors, with their unique advantages of in‐memory computing, synaptic plasticity emulation, and multi‐physical responsiveness, have emerged as a key enabling technology for brain‐inspired perception and interaction systems. This article systematically reviews the latest research progress of memristors in intelligent perception and neuromorphic systems for next‐generation HCI. First, starting from the material system, performance regulation, and application adaptation are analyzed. Second, the strategy of memristors in device design and integration architecture is discussed. Furthermore, the biomimetic perception system based on memristors is emphasized, demonstrating its integration capability at the hardware level of brain‐inspired perception information processing. Finally, it systematically summarizes the research achievements of memristors in the field of HCI applications and discusses the key challenges currently faced. Looking forward, this review suggests that memristors are expected to provide a solid foundation for building high‐performance, low‐power, and biocompatible next‐generation HCI systems.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2026-09-12
DOI
https://doi.org/10.1002/adfm.78446
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Memristors Empowering Next‐Generation Human‐Computer Interaction

Zelin Cao, Mengna Wang, Chuncai Kong, Bai Sun et al.
Advanced Functional Materials
Advanced Memory and Neural Computing
article

Memristors Empowering Next‐Generation Human‐Computer Interaction

Zelin Cao, Mengna Wang, Chuncai Kong, Bai Sun, Jinlong He, Song Ling Wang, Longhui Fu, Kaikai Gao, Bo Yang, Jinyou Shao, Teng Wu, Ye Tang, Kun Wang, Qi Chen
article en

Abstract

ABSTRACT With the continuous advancement of artificial intelligence, human‐computer interaction (HCI) is evolving toward intelligent perception, collaborative decision‐making, and natural integration. However, the physical separation of memory and computing units in traditional von Neumann architecture poses critical bottlenecks in terms of power consumption and latency, which limits its ability to meet the requirements of next‐generation HCI systems. Memristors, with their unique advantages of in‐memory computing, synaptic plasticity emulation, and multi‐physical responsiveness, have emerged as a key enabling technology for brain‐inspired perception and interaction systems. This article systematically reviews the latest research progress of memristors in intelligent perception and neuromorphic systems for next‐generation HCI. First, starting from the material system, performance regulation, and application adaptation are analyzed. Second, the strategy of memristors in device design and integration architecture is discussed. Furthermore, the biomimetic perception system based on memristors is emphasized, demonstrating its integration capability at the hardware level of brain‐inspired perception information processing. Finally, it systematically summarizes the research achievements of memristors in the field of HCI applications and discusses the key challenges currently faced. Looking forward, this review suggests that memristors are expected to provide a solid foundation for building high‐performance, low‐power, and biocompatible next‐generation HCI systems.

Advanced Functional Materials
Fujian Institute of Research on the Structure of Matter (CN), Second Affiliated Hospital of Xi'an Jiaotong University (CN), State Key Laboratory of Remote Sensing Science (CN), Xi'an Jiaotong University (CN)
Xi'an Jiaotong University, National Natural Science Foundation of China, Natural Science Basic Research Program of Shaanxi Province
Openalex Percentile: Top 20%
Advanced Memory and Neural Computing
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.