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A Perspective on Tellurium/Selenium-Based Nanomaterials for Neuromorphic Computing

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The long-standing von Neumann architecture, while foundational to modern computing, intrinsically suffers from data-transfer inefficiency, which imposes severe limits on speed and energy efficiency in artificial intelligence, machine learning, and real-time data processing. Inspired by the remarkable energy efficiency of the human brain, neuromorphic computing seeks to emulate neural architectures through hardware capable of adaptive learning. Although early complementary metal-oxide-semiconductor (CMOS)-based neuromorphic systems captured basic synaptic behaviors, their narrow dynamic ranges and high operating voltages impede their application prospects. Van der Waals (vdW) materials, particularly tellurium (Te) and Selenium (Se), have recently emerged as promising platforms for next-generation neuromorphic devices due to their intriguing electronic and optoelectronic properties including considerable carrier mobilities, broadband photoresponse, and strong coupling between electrical, optical, and mechanical stimuli. These unique properties offer a direct physical analogy to biological synapses, thereby enabling neuromorphic computing. This Perspective introduces the fundamentals of synaptic behavior and neuromorphic computing and highlights the distinctive properties of Te/Se nanomaterials for synaptic devices. Then we discuss critical advances in Te/Se-based memristors, heterostructures, and electronic/optoelectronic synaptic transistors. In the end, we conclude this perspective with a discussion on the remaining challenges and future opportunities in this evolving field. © 2025 American Chemical Society.
Original languageEnglish
Pages (from-to)67401–67414
Number of pages14
JournalACS Applied Materials & Interfaces
Volume17
Issue number50
Online published2 Dec 2025
DOIs
Publication statusPublished - 17 Dec 2025

Funding

C.T. thanks the funding support from the Start-Up Grant (Project No. 9610710) from City University of Hong Kong, General Research Fund (GRF: CityU 11200122 and CityU 17301525) and the Collaborative Research Fund (RGC; no. C2001-23Y and C5001-24Y) from the Research Grant Council of Hong Kong and ITC via Hong Kong Branch of National Precious Metals Material Engineering Research Center (NPMM). P.Y. thanks the funding support from the National Natural Science Foundation of China (Grant No. 62404138), Shenzhen Science and Technology Program (Grant No. 20231128102926002), Natural Science Foundation of Top Talent of SZTU (Grant no. GDRC202420).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Research Keywords

  • tellurium
  • selenium
  • van der Waals heterostructures
  • synaptic devices
  • neuromorphic computing

RGC Funding Information

  • RGC-funded

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