• Journal of Adhesion and Interface
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• v.25 no.2
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• pp.56-62
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• 2024

In this study, LiDAR-detectable black hollow-structured materials are synthesized using different reducing agents to evaluate their applicability to LiDAR sensor. Initially, white SiO₂/TiO₂ core/shell (WST) materials are fabricated via a sol-gel method, followed by a reduction using ascorbic acid (AA) and sodium borohydride (SB). After the reduction, subsequent etching of the SiO₂ core leads to the formation of two different black hollow-structured materials (AA-BHT and SB-BHT). The lightness (L^*) and near-infrared (NIR) reflectance (R%) of AA-BHT are measured as ca. 19.1 and 34.5 R%, and SB-BHT shows values of ca. 11.5 and 31.8 R%, respectively. While AA-BHT exhibits higher NIR reflectance compared to SB-BHT, it displays slightly lower blackness. Compared with core/shell structured materials, improved NIR reflectance of both AA-BHT and SB-BHT is attributed to the morphology of hollow- structured materials, which increase light reflection at the interface between air and black TiO₂ according to the Fresnel's reflection principle. Consequently, both AA-BHT and SB-BHT are effectively detected by the commercially available LiDAR sensors, validating their suitability as black materials for autonomous vehicle and environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• Journal of the Korea Organic Resources Recycling Association
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• v.32 no.1
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• pp.39-47
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• 2024

In this study, LiDAR-detective black material is synthesized by recycling silicon sludge (SS) that is generated from semiconductor manufacturing process, and its recognition is confirmed using two types of LiDAR sensors (MEMS and Rotating LiDAR). In detail, metal impurities on the surface of SS is removed, followed by coating of titanium dioxide (TiO₂) and subsequent chemical reduction to obtain SS-derived black TiO₂ (SS/bTiO₂) material. As-prepared SS/bTiO₂ is mixed with transparent paint to prepare hydrophilic black paints and applied to a glass substrate using a spray gun. SS/bTiO₂-based paint shows similar blackness (L^*=15.7) compared to commercial carbon black-based paint, and remarkable NIR reflectance (26.5R%, 905nm). Furthermore, MEMS and Rotating LiDAR have successfully detected the SS/bTiO₂-based paint. This is attributed to the occurrence of high reflection of light at the interface between the black TiO₂ and the silicon sludge according to the Fresnel's reflection principle. Hence, the new application field to effectively recycle silicon sludge generated in the semiconductor manufacturing process has been presented.