Predicting the surface roughness of an electrodeposited copper film using a machine learning technique

Electrodeposition-based metal coating techniques are used to manufacture various industrial products and rely on the quantitative control of the physical properties of the coating layers, such as electrical conductivity, surface roughness, and hardness. To clarify the experimental conditions require...

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Published in:Science and technology of advanced materials. Methods 2024-12, Vol.4 (1)
Main Authors: Tamura, Ryo, Inaba, Ryuichi, Watanabe, Mami, Mori, Yutaro, Urushihara, Makoto, Yamaguchi, Kenji, Matsuda, Shoichi
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Language:English
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copper film
electrochemistry
Electrodeposition
machine learning
surface roughness
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Inaba, Ryuichi
Watanabe, Mami
Mori, Yutaro
Urushihara, Makoto
Yamaguchi, Kenji
Matsuda, Shoichi
description Electrodeposition-based metal coating techniques are used to manufacture various industrial products and rely on the quantitative control of the physical properties of the coating layers, such as electrical conductivity, surface roughness, and hardness. To clarify the experimental conditions required to realize the desired physical properties of metal coating layers and shed light on the complex mechanism of the involved reactions, we prepared a custom-built experimental dataset (60 conditions) on the surface roughness of electrodeposited thin copper films and submitted it to an open-access data repository. Data-driven analysis revealed that surface roughness is strongly affected by the deposition temperature, current, and interelectrode distance.
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subjects copper film
electrochemistry
Electrodeposition
machine learning
surface roughness
title Predicting the surface roughness of an electrodeposited copper film using a machine learning technique
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