Multiscale modelling of nanoscaled FETs based on 2D ferroelectric materials
Abstract
Ferroelectric materials are highly attractive for low-power, high-speed electronics and emerging neuromorphic computing architectures. However, the severe physical scaling limits of conventional bulk (3D) ferroelectrics at the nanoscale have shifted attention towards two-dimensional (2D) ferroelectric monolayers. Accurate device-level performance predictions are essential to accelerate the experimental testing and screening of these novel materials. In this work, we present a multiscale simulation framework that bridges first-principles density functional theory with Non-Equilibrium Green's Function (NEGF) transport calculations. Using a 2D Indium Phosphide monolayer as a case study, our approach leverages a continuously interpolated, polarization-dependent Hamiltonian embedded within a self-consistent Poisson-NEGF solver. The model captures the dynamic interplay between ion movement and electronic transport, naturally reproducing macroscopic hysteresis loops and memory windows without empirical parameters. This predictive pipeline provides a computationally efficient tool to evaluate and optimize next-generation 2D ferroelectric field-effect transistors.
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BibTeX
@misc{torallopez2026multiscale,
title = {{Multiscale modelling of nanoscaled FETs based on 2D ferroelectric materials}},
author = {Alejandro Toral-Lopez and Michele Virgilio and Gianluca Fiori and Damiano Marian},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.37823},
eprint = {2609.37823},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.37823},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Multiscale modelling of nanoscaled FETs based on 2D ferroelectric materials
AU - Alejandro Toral-Lopez
AU - Michele Virgilio
AU - Gianluca Fiori
AU - Damiano Marian
PY - 2026
DA - 2026/09/29
PB - arXiv
DO - 10.48550/arxiv.2609.37823
UR - https://arxiv.org/abs/2609.37823
AB - Ferroelectric materials are highly attractive for low-power, high-speed electronics and emerging neuromorphic computing architectures. However, the severe physical scaling limits of conventional bulk (3D) ferroelectrics at the nanoscale have shifted attention towards two-dimensional (2D) ferroelectric monolayers. Accurate device-level performance predictions are essential to accelerate the experimental testing and screening of these novel materials. In this work, we present a multiscale simulation framework that bridges first-principles density functional theory with Non-Equilibrium Green's Function (NEGF) transport calculations. Using a 2D Indium Phosphide monolayer as a case study, our approach leverages a continuously interpolated, polarization-dependent Hamiltonian embedded within a self-consistent Poisson-NEGF solver. The model captures the dynamic interplay between ion movement and electronic transport, naturally reproducing macroscopic hysteresis loops and memory windows without empirical parameters. This predictive pipeline provides a computationally efficient tool to evaluate and optimize next-generation 2D ferroelectric field-effect transistors.
ER -