Machine-Learning Assisted Optimization Strategies for Phase Change Materials Embedded within Electronic Packages

04/21/2021
by   Meghavin Bhatasana, et al.
0

Leveraging the latent heat of phase change materials (PCMs) can reduce the peak temperatures and transient variations in temperature in electronic devices. But as the power levels increase, the thermal conduction pathway from the heat source to the heat sink limits the effectiveness of these systems. In this work, we evaluate embedding the PCM within the silicon device layer of an electronic device to minimize the thermal resistance between the source and the PCM to minimize this thermal resistance and enhance the thermal performance of the device. The geometry and material properties of the embedded PCM regions are optimized using a combination of parametric and machine learning algorithms. For a fixed geometry, considering commercially available materials, Solder 174 significantly outperforms other organic and metallic PCMs. Also with a fixed geometry, the optimal melting points to minimize the peak temperature is higher than the optimal melting point to minimize the amplitude of the transient temperature oscillation, and both optima increase with increasing heater power. Extending beyond conventional optimization strategies, genetic algorithms and particle swarm optimization with and without neural network surrogate models are used to enable optimization of many geometric and material properties. For the test case evaluated, the optimized geometries and properties are similar between all ML-assisted algorithms, but the computational time depends on the technique. Ultimately, the optimized design with embedded phase change materials reduces the maximum temperature rise by 19

READ FULL TEXT
research
08/25/2023

Multiscale modeling of thermal properties in Polyurethane incorporated with phase change materials composites: A case study

Polyurethane (PU) is an ideal thermal insulation material due to its exc...
research
11/09/2018

Design of pin-fin heat sink for the platform inertial navigation system by surrogate assisted techniques

In this study, in order to reduce the local high temperature of the plat...
research
09/21/2022

Approximating the full-field temperature evolution in 3D electronic systems from randomized "Minecraft" systems

Neural Networks as fast physics simulators have a large potential for ma...
research
05/18/2022

Design of metamaterial-based heat manipulators by isogeometric shape optimization

There has been a growing interest in controlled heat flux manipulation t...
research
11/25/2020

Reconstructing the thermal phonon transmission coefficient at solid interfaces in the phonon transport equation

The ab initio model for heat propagation is the phonon transport equatio...
research
06/01/2021

Robust design optimisation of continuous flow polymerase chain reaction thermal flow systems

This paper presents an efficient methodology for the robust optimisation...

Please sign up or login with your details

Forgot password? Click here to reset