Výsledky vyhledávání - "Hashemi, Nicole N."

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Accelerating Hydrodynamic Fabrication of Microstructures using Deep Neural Networks

Autor: Clinkinbeard, Nicholus R., Montazami, Reza, Hashemi, Nicole N.

Manufacturing of microstructures using a microfluidic device is a largely empirical effort due to the multi-physical nature of the fabrication process. As such, models are desired that will predict microstructure performance characteristics (e.g., si

Externí odkaz: http://arxiv.org/abs/2403.01089

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Supplementation of deep neural networks with simplified physics-based features to increase model prediction accuracy

Autor: Clinkinbeard, Nicholus R., Hashemi, Nicole N.

To improve predictive models for STEM applications, supplemental physics-based features computed from input parameters are introduced into single and multiple layers of a deep neural network (DNN). While many studies focus on informing DNNs with phys

Externí odkaz: http://arxiv.org/abs/2204.06764

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Akademický článek

Moving toward autonomous manufacturing by accelerating hydrodynamic fabrication of microstructures using deep neural networks

Autor: Clinkinbeard, Nicholus R., Hashemi, Nicole N.

Publikováno v: In Micro and Nano Engineering September 2024 24

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Machine Learning-Assisted E-jet Printing of Organic Flexible Biosensors

Autor: Shirsavar, Mehran Abbasi, Taghavimehr, Mehrnoosh, Ouedraogo, Lionel J., Javaheripi, Mojan, Hashemi, Nicole N., Koushanfar, Farinaz, Montazami, Reza

Electrohydrodynamic-jet (e-jet) printing technique enables the high-resolution printing of complex soft electronic devices. As such, it has an unmatched potential for becoming the conventional technique for printing soft electronic devices. In this s

Externí odkaz: http://arxiv.org/abs/2111.03985

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