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  1. Research Outputs

Integrating physics-based simulations, machine learning, and Bayesian inference for accurate detection and metrology of elongated nanoscale analytes using high-frequency capacitance spectroscopy

Academic Article
Publication Date:
2025
Short description:
Integrating physics-based simulations, machine learning, and Bayesian inference for accurate detection and metrology of elongated nanoscale analytes using high-frequency capacitance spectroscopy / Khodadadian, Ehsan; Goldoni, Daniele; Nicolini, Jacopo; Khodadadian, Amirreza; Heitzinger, Clemens; Selmi, Luca. - In: ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE. - ISSN 0952-1976. - 159:C(2025), pp. N/A-N/A. [10.1016/j.engappai.2025.111679]
Iris type:
Articolo su rivista
Keywords:
Bayesian inversion; Data augmentation; High-frequency impedance spectroscopy; Machine learning; Nanoscale metrology; Physics-based simulation;
List of contributors:
Khodadadian, Ehsan; Goldoni, Daniele; Nicolini, Jacopo; Khodadadian, Amirreza; Heitzinger, Clemens; Selmi, Luca
Authors of the University:
NICOLINI JACOPO
SELMI LUCA
Handle:
https://iris.unimore.it/handle/11380/1384448
Published in:
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Journal
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