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Related Concept Videos

Semiconductors01:22

Semiconductors

1.4K
There is variation in the electrical conductivity of materials - metals, semiconductors, and insulators that are showcased with the help of the energy band diagrams.
Metals such as copper (Cu), zinc (Zn), or lead (Pb) have low resistivity and feature conduction bands that are either not fully occupied or overlap with the valence band, making a bandgap non-existent. This allows electrons in the highest energy levels of the valence band to easily transition to the conduction band upon gaining...
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Types of Semiconductors01:20

Types of Semiconductors

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Intrinsic semiconductors are highly pure materials with no impurities. At absolute zero, these semiconductors behave as perfect insulators because all the valence electrons are bound, and the conduction band is empty, disallowing electrical conduction. The Fermi level is a concept used to describe the probability of occupancy of energy levels by electrons at thermal equilibrium. In intrinsic semiconductors, the Fermi level is positioned at the midpoint of the energy gap at absolute zero. When...
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A Perspective on Tellurium/Selenium-Based Nanomaterials for Neuromorphic Computing.

Yuxi Chen1,2, Jiajia Zha3, Haoxin Huang3

  • 1College of Integrated Circuits and Optoelectronic Chips, Shenzhen Technology University, Shenzhen 518118, China.

ACS Applied Materials & Interfaces
|December 2, 2025
PubMed
Summary
This summary is machine-generated.

Van der Waals materials like tellurium and selenium offer new possibilities for energy-efficient neuromorphic computing. Their unique properties mimic biological synapses, overcoming limitations of current technologies for AI and machine learning.

Keywords:
neuromorphic computingseleniumsynaptic devicestelluriumvan der Waals heterostructures

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Area of Science:

  • Materials Science
  • Computer Engineering
  • Neuroscience

Background:

  • The von Neumann architecture faces data-transfer inefficiencies, limiting AI, machine learning, and real-time processing.
  • Neuromorphic computing, inspired by the brain, aims for adaptive learning hardware but faces challenges with CMOS-based systems.
  • Existing systems have limited dynamic ranges and high operating voltages, hindering practical applications.

Purpose of the Study:

  • To introduce the fundamentals of synaptic behavior and neuromorphic computing.
  • To highlight the distinctive properties of tellurium (Te) and selenium (Se) nanomaterials for synaptic devices.
  • To discuss advances and future opportunities in Te/Se-based neuromorphic computing.

Main Methods:

  • Review of synaptic behavior principles and neuromorphic computing concepts.
  • Analysis of the electronic and optoelectronic properties of Te/Se nanomaterials.
  • Discussion of recent developments in Te/Se-based memristors, heterostructures, and synaptic transistors.

Main Results:

  • Te/Se nanomaterials exhibit unique properties like high carrier mobility, broadband photoresponse, and multi-stimuli coupling.
  • These properties provide a physical analogy to biological synapses, enabling efficient neuromorphic functions.
  • Advances in Te/Se-based devices demonstrate potential for overcoming limitations of conventional computing architectures.

Conclusions:

  • Te/Se van der Waals materials are highly promising for next-generation neuromorphic devices.
  • These materials offer a pathway to overcome the speed and energy efficiency bottlenecks in AI and computing.
  • Further research into Te/Se-based devices holds significant potential for the future of neuromorphic engineering.