High-efficiency design of self-assembled monolayers for enhanced thermal conductance at solid-water interfaces via parallel screening with simple physical metrics
journal contribution
posted on 2025-10-30, 13:40authored byShengluo Ma, Dezhao Huang, Dengke Ma, Yunwen Wu, Yuriy A Kosevich, Tapio Ala-NissilaTapio Ala-Nissila, Shenghong Ju
<p dir="ltr">Solid-water interfacial thermal transport is crucial at the micro-nano scale and has important applications in thermal devices and nanofluids. Functionalizing material surfaces with self-assembled monolayers (SAMs) can bridge the solid-water interfaces, reduce vibrational mismatches, and thereby enhancing interfacial thermal conductance (ITC). However, existing research on SAM thermal transport regulation only involves simple structures with scarce data, and high-throughput (HTP) discovery for complex SAM end group structures have not been reported. This work proposes a high-efficiency design framework for SAM end groups through parallel screening using simple physical indicators associated with ITC. Compared to obtain ITC through full simulations of all the relevant materials, here we calculate the interfacial interaction energy and vibrational spectral coupling strength of 250 complex end group structures in SAMs at gold-water interface and integrate ML models to perform multi-objective screening on another 750 complex candidates. Ultimately, through complete nonequilibrium molecular dynamics (NEMD) simulations, 9 SAM end group structures with ITC higher than 150 MW/(m<sup>2</sup>K) and the synthetic accessibility scores below 3 were discovered, which the ML models screening success rate exceeding 85%. Through thermal transport decomposition analysis of Coulombic and van der Waals interactions, the SAM with extremely high ITC can be attributed to strong Coulombic interactions with water molecules due to highly polar end groups. This HTP framework fills the gap in research on HTP screening of SAM end groups for ITC regulation. Additionally, the related computational data will contribute to future data-driven research on SAMs.</p>
Funding
Shanghai International Science and Technology Collaboration Project (No. 24160712600)
Shanghai Municipal Education Commission Research Project (No. 2024AIZD012)
National Natural Science Foundation of China (No. 52206107)
Department of Science and Technology of Jiangsu Province Grant (No. BK20231279)
Academy of Finland Grant (No. 353298) under the European Union - NextGenerationEU instrument