Designing Practical LiDAR-Detectable Pigments via Sustainable Recycling of Semiconductor Waste

초록

In this study, LiDAR-detectable black titania hollow nanoparticles (BT-HNPs) are synthesized by utilizing silicon sludge, a byproduct of semiconductor manufacturing, as a template. The BT-HNPs are prepared via a sequential sol-gel process, followed by etching and chemical reduction. The resulting BT-HNPs are then mixed with hydrophilic transparent varnish and spray-coated onto 2D substrates. Notably, the BT-HNP-based paint manifests a high near-infrared (NIR) reflectance of 26.9R% at the LiDAR detection wavelength of 905 nm. Practical LiDAR recognition of the BT-HNP-coated substrate is confirmed using a commercial MEMS mirror and rotating LiDAR sensors. This study suggests a viable strategy for recycling silicon sludge as a template for synthesizing NIR-reflective black materials, expanding the range of LiDAR-detectable dark-tone coatings for autonomous driving. 본 연구는 2025년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(RS-2022-NR070869) Keywords : Semiconductor waste, LiDAR recognition, pigment, autonomous vehicle. †Corresponding Author: cmyoon4321@inha.ac.kr