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Updated: Jan 29, 2026

Atomic Layer Deposition of Vanadium Dioxide and a Temperature-dependent Optical Model
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AI-Optimized Vanadium Oxide Multilayers for More Than 20-fold Enhancement in Bolometric Performance.

Jin-Hyun Choi1, Hyoung-Taek Lee1,2, Jeonghoon Kim1

  • 1Department of Physics, Ulsan National Institute of Science & Technology, Ulsan, Republic of Korea.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|January 28, 2026
PubMed
Summary

Researchers developed advanced WxV1-xOy thin films using machine learning to create linear, non-hysteretic infrared bolometers. This breakthrough overcomes limitations of vanadium dioxide, significantly enhancing bolometric performance for infrared sensors.

Keywords:
machine learningmetal‐insulator transitionmicrobolometersphase‐transition materialsvanadium oxides

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Sensor Technology

Background:

  • Phase-transition materials like vanadium dioxide (VO2) show non-linear, hysteretic behavior, limiting their use in infrared bolometric sensors.
  • Nonstoichiometric VOx is used in bolometers but has degraded transitions and lower temperature coefficient of resistance (TCR).
  • Achieving high TCR and linear, non-hysteretic response is a key challenge for microbolometer technology.

Purpose of the Study:

  • To develop a multilayer approach using machine-learning-optimized WxV1-xOy thin films to achieve linear, non-hysteretic responses with high TCR.
  • To overcome the limitations of traditional vanadium dioxide-based infrared sensors.
  • To enhance the performance of microbolometers for advanced infrared detection.

Main Methods:

  • Utilized a multilayer thin-film deposition strategy with varying tungsten (W) doping ratios in VxOy.
  • Employed genetic algorithm optimization to tailor film properties for desired TCR profiles and reduced hysteresis.
  • Grew WxV1-xOy thin films under complementary metal-oxide semiconductor (CMOS)-compatible conditions.

Main Results:

  • Achieved tailored linear/flat TCR profiles and significantly reduced hysteresis in multilayer WxV1-xOy systems.
  • Demonstrated simultaneous high TCR and low electrical noise.
  • Reported a 23.6-fold improvement in universal bolometric performance compared to commercial materials.

Conclusions:

  • The developed multilayer WxV1-xOy films offer a viable solution for linear, high-performance infrared bolometers.
  • The machine-learning-guided approach provides a general methodology for optimizing materials with large, linear responses.
  • This work has broad implications for microbolometer technology and other stimulus-responsive devices.