Explicit electrothermal LLP VO2 model reproducing Preisach like hysteresis for memristive and neuromorphic devices

Vanadium dioxide (VO$$_2$$) devices exploit a thermally driven metal–insulator transition accompanied by strong hysteresis, making them promising candidates for compact memristive elements and neuromorphic functionalities. Here we present a fully explicit electrothermal LLP–VO$$_2$$ model aimed at enabling practical implementation of LLP hysteresis operators in VO$$_2$$ and related materials. The formulation couples a single thermal balance equation to a discrete LLP operator that governs the metallic fraction while capturing key Preisach-like features, including nested hysteresis loops and return-point memory. The resulting resistance expression combines an Arrhenius-type conduction term with a metallic offset. A systematic comparison between explicit Euler and fourth-order Runge–Kutta (RK4) time integration schemes examines numerical accuracy and solver-dependent stiffness effects across the transition region. The results indicate that LLP-based hysteresis can be simulated efficiently without introducing additional differential states, while maintaining numerical reproducibility. The proposed model may serve as a lightweight and implementation-ready framework for applications requiring controlled VO$$_2$$ hysteresis behavior, and is designed to be compatible with SPICE-class solvers for future integration and benchmarking against HP- and Chua-type compact models.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-04-24
DOI
https://doi.org/10.1038/s41598-026-49919-9
Primary Topic
Transition Metal Oxide Nanomaterials
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Explicit electrothermal LLP VO2 model reproducing Preisach like hysteresis for memristive and neuromorphic devices

Bruno Aparecido Sousa Figueiredo Sena, L. A. L. Almeida
Scientific Reports
Transition Metal Oxide Nanomaterials
article

Explicit electrothermal LLP VO2 model reproducing Preisach like hysteresis for memristive and neuromorphic devices

Bruno Aparecido Sousa Figueiredo Sena, L. A. L. Almeida
article en

Abstract

Vanadium dioxide (VO$$_2$$) devices exploit a thermally driven metal–insulator transition accompanied by strong hysteresis, making them promising candidates for compact memristive elements and neuromorphic functionalities. Here we present a fully explicit electrothermal LLP–VO$$_2$$ model aimed at enabling practical implementation of LLP hysteresis operators in VO$$_2$$ and related materials. The formulation couples a single thermal balance equation to a discrete LLP operator that governs the metallic fraction while capturing key Preisach-like features, including nested hysteresis loops and return-point memory. The resulting resistance expression combines an Arrhenius-type conduction term with a metallic offset. A systematic comparison between explicit Euler and fourth-order Runge–Kutta (RK4) time integration schemes examines numerical accuracy and solver-dependent stiffness effects across the transition region. The results indicate that LLP-based hysteresis can be simulated efficiently without introducing additional differential states, while maintaining numerical reproducibility. The proposed model may serve as a lightweight and implementation-ready framework for applications requiring controlled VO$$_2$$ hysteresis behavior, and is designed to be compatible with SPICE-class solvers for future integration and benchmarking against HP- and Chua-type compact models.

Scientific Reports
Federal Institute of São Paulo (BR), Universidade Federal do ABC (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Openalex Percentile: Top 10%
Transition Metal Oxide Nanomaterials
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.