Insights into capacitance variance mechanisms via a machine learning-biased evolutionary approach

Insights into capacitance variance mechanisms via a machine learning-biased evolutionary approach

Dielectric particles are often added to ink formulations to tailor the macro level permittivity of printed dielectric substrates and coatings. In these inks, the combined role of particle morphology, discrete spatial arrangement and material properties on variance is difficult to distinguish experim...

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Bibliographic Details
Main Authors: Venkatesh Meenakshisundaram, David Yoo, Andrew Gillman, Clare Mahoney, James Deneault, Nicholas Glavin, Philip Buskohl
Format: Article
Language:English
Published: Elsevier 2021-02-01
Series:Materials & Design
Subjects:
Heterogeneous dielectric particles
Interdigitated capacitors
Finite element model
Genetic algorithms
Neural networks
Unsupervised classification
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127520309308

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http://www.sciencedirect.com/science/article/pii/S0264127520309308

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