A data driven approach to model thermal boundary resistance from molecular dynamics simulations
Abhijith Anandakrishnan1, Sarith P Sathian1
1Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India. sarith@iitm.ac.in.
Physical Chemistry Chemical Physics : PCCP
|January 10, 2023
Summary
A new method models nanoscale thermal boundary resistance (TBR) using macroscopic data. This approach links TBR to system properties and material parameters, improving understanding of heat transfer at solid-liquid interfaces.
Area of Science:
- Materials Science
- Thermodynamics
- Nanotechnology
Background:
- Accurate modeling of thermal boundary resistance (TBR) at nanoscale solid-liquid interfaces is crucial for understanding heat transfer.
- Existing models often lack generality or require detailed nanoscale information.
Purpose of the Study:
- To develop a generalized method for modeling TBR at nanoscale solid-liquid interfaces.
- To correlate TBR with macroscopic observables, thermodynamic variables, material properties, and geometric parameters.
Main Methods:
- Utilized data-driven heuristic algorithms to establish relationships between TBR and system observables.
- Investigated descriptor variable independence and quantified their influence on TBR models.
- Analyzed the role of interfacial liquid layering, work of adhesion, and system geometry.
Main Results:
- Developed a generalized TBR model expressed through physical observables and material-specific parameters.
- Demonstrated that interfacial liquid layering strongly correlates with TBR.
- Identified that work of adhesion and geometry influence TBR under specific conditions like phonon size effects and extreme thermodynamics.
Conclusions:
- The data-driven approach provides significant insights into TBR mechanisms at nanoscale solid-liquid interfaces.
- This method enhances the understanding of interfacial thermal transport by linking macroscopic observables to nanoscale phenomena.
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