Reinforcement Learning-Enabled Environmentally Friendly and Multi-functional Chrome-looking Plating
Keywords: chrome replacement, inverse design, structural color, optical coating, reinforcement learning algorithm
TL;DR: Using reinforcement learning, we designed and fabricated two multilayer thin film structures that can mimic the visual appearance of decorative chrome plating, serving as a environmentally friendly and multi-functional replacement
Abstract: Although decorative chrome plating (DCP) is ubiquitous in metal finishings and coatings, the industrial process of chromium deposition is fraught with adverse health effects for the workers involved and causes environmental pollution. In this work, we seek to find an environmentally friendly replacement to DCP by mimicking the chrome color used for decoration. To discover a suitable replacement efficiently, we employ a reinforcement learning (RL) algorithm to perform an automatic inverse design in optical multilayer thin film structures. The RL algorithm successfully figures out two different structures with environmentally friendly materials while still showing a chrome color. One structure is further designed to have high transmission in the radio frequency regime, a property that general metals cannot have, which can broaden the decorative chrome applications to include microwave operating devices. We also experimentally fabricate these structures and validate their performance.
Submission Track: Original Research
Submission Number: 61
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