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  3. An Atom-precise Approach To Damp First-order Phase Transitions And Its Implications For Neuromorphic Signal Processing.
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  3. An Atom-precise Approach To Damp First-order Phase Transitions And Its Implications For Neuromorphic Signal Processing.

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An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal

George Agbeworvi1, Nitin Kumar2, John D Ponis1

  • 1Department of Chemistry, Texas A&M University, College Station, Texas 77843, United States.

Journal of the American Chemical Society
|May 13, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Researchers engineered neuromorphic computing devices by precisely controlling material structures. This work enables stable artificial neurons with tunable functionality for efficient, brain-inspired information processing.

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Area of Science:

  • Materials Science
  • Neuroscience
  • Computer Engineering

Background:

  • Neuromorphic computing mimics mammalian intelligence for efficient information processing.
  • Artificial neurons require materials with specific nonlinear dynamics, posing design challenges.
  • Controlling abrupt electronic transitions is crucial for device stability and preventing failure.

Purpose of the Study:

  • To establish structure-function correlations between atomistic composition and nonlinear dynamics in artificial neurons.
  • To investigate how modifying crystal structure impacts neuron-like functionality.
  • To bridge the gap between statistical mechanics and quantum chemistry in phase transition descriptions.

Main Methods:

  • Fabrication of oscillator circuits using millimeter-scale single crystals.
  • High-resolution atomic structure determination via X-ray diffraction.
  • Analysis of electronic transitions using temperature-variant X-ray spectroscopy.

    • Main Results:

    • Selective Pb cation positioning in CuxV2O5 frameworks was shown to modify charge ordering.
    • Atom-precise control was demonstrated to dampen abrupt first-order transitions.
    • Suppression of Cu-ion shuttling by Pb ions was identified as the mechanism for transition broadening.

    Conclusions:

    • Mechanistic understanding of phase transitions enables site-selective modification strategies.
    • Tuning the sharpness of first-order transitions is achievable through precise atomic manipulation.
    • This approach provides a pathway for developing advanced neuromorphic computing devices with enhanced neuronal signal processing.