Document Type

Article

Publication Date

4-3-2025

Keywords

surface texture design, integer linear program, non-linear optimization

Abstract

Motivated by the potential of surface texturing to enhance the tribological performance of micro- and nano-electromechanical systems (MEMS/NEMS), this study proposes a novel non-linear optimization approach for designing textured surfaces. This model minimizes the contact area between interacting surfaces and deformation during sliding under dry conditions by controlling key design parameters, such as the size and shape of the designed surface. We test the performance of the proposed model using the lotus leaf surface with dimensions of 248 x 136 micrometers. Due to the large size of the model, we propose a solution approach which consists of a data aggregation step, an optimization step, and a data disaggregation step. The optimization step decomposes the model into smaller models that are easier to solve. Via the sensitivity analysis, we highlight the trade-offs between data aggregation and model decomposition and their effect on the quality of the solutions found. In conclusion, our approach bridges the gap between fabrication capabilities and design requirements, paving the way for significant advances in tribological performance and surface engineering.

Comments

Web of Science

MDPI

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Included in

Engineering Commons

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