AI-Assisted 3D Modeling Strategy for Microstructure-Based Functional Surfaces Using ChatGPT and Random Forest
Year: 2024
Type: article
Abstract: With the development of computer programming, product design is being carried out through computer programming such as 3D CAD/CAM when developing products, and the cost of developing new products can be greatly reduced by using 3D modeling tools in which various engineering theories are programmed. With the recent rapid development of artificial intelligence (AI), various AI applications have been actively proposed in various fields. In this study, we report a ChatGPT-based 3D modeling program (CMP) which can easily design microstructures, and the theory of wettability that was programmed into the CMP. Since the theory related to wettability is programmed into the CMP, once the user enters basic information about the desired functional surface, such as superhydrophobic surfaces, at the CMP prompt, 3D structures with the performance of superhydrophobicity are immediately provided. Through microstructure fabrication techniques, the microstructure designed by the CMP was actually fabricated, wettability experiments were conducted, and it was confirmed that a superhydrophobic surface was successfully designed. As such, the AI-based CMP can easily design microstructure-based functional surfaces, and we expect this method not only to decrease the fabrication costs of designing micro/nano structures but also to be useful in various fields.
Source: Machines
Authors: Younghun Noh, Sucheong Park, Sungho Lee
Institution: Dong-A University
Language: English
Subfield: Surfaces, Coatings and Films
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,728
Funder: Dong-A University
OpenAlex ID: W4405515447