scholarly journals Machine Learning (ML) based Thermal Management for Cooling of Electronics Chips by Utilizing Thermal Energy Storage (TES) in Packaging that Leverage Phase Change Materials (PCM)

2021 ◽  
Author(s):  
Aditya Jayakumar Chuttar ◽  
Debjyoti Banerjee
Keyword(s):  
Energy Storage ◽  
Surface Temperature ◽  
Phase Change ◽  
Real Time ◽  
Thermal Management ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Phase Change Materials ◽  
Temperature Data ◽  
Prior History

Miniaturization of electronics devices is often limited by the concomitant high heat fluxes (cooling load) and maldistribution of temperature profiles (hot spots). Thermal energy storage (TES) platforms providing supplemental cooling can be a cost-effective solution, that often leverages phase change materials (PCM). Although salt hydrates provide higher storage capacities and power ratings (as compared to that of the organic PCMs), they suffer from reliability issues (e.g., supercooling). ‘Cold Finger Technique (CFT)’ can obviate supercooling by maintaining a small mass fraction of the PCM in solid state for enabling spontaneous nucleation. Optimization of CFT necessitates real-time forecasting of the transient values of the melt-fraction. In this study artificial neural network (ANN) is explored for real-time prediction of the time remaining to reach a target value of melt-fraction based on the prior history of the spatial distribution of the surface temperature transients. Two different approaches were explored for training the ANN model, using: (1) transient PCM-temperature data; or (2) transient surface-temperature data. When deployed in a heat sink that leverages PCM based passive thermal management systems for cooling of electronic chips and packages, this maverick approach (using the second method) affords cheaper costs, better sustainability, higher reliability and resilience.

scholarly journals Machine Learning (ML) Based Thermal Management for Cooling of Electronics Chips by Utilizing Thermal Energy Storage (TES) in Packaging That Leverages Phase Change Materials (PCM)

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2785
Author(s):  
Aditya Chuttar ◽  
Debjyoti Banerjee
Keyword(s):  
Energy Storage ◽  
Surface Temperature ◽  
Phase Change ◽  
Real Time ◽  
Thermal Management ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Phase Change Materials ◽  
Temperature Data ◽  
Prior History

Miniaturization of electronics devices is often limited by the concomitant high heat fluxes (cooling load) and maldistribution of temperature profiles (hot spots). Thermal energy storage (TES) platforms providing supplemental cooling can be a cost-effective solution, that often leverages phase change materials (PCM). Although salt hydrates provide higher storage capacities and power ratings (as compared to that of the organic PCMs), they suffer from reliability issues (e.g., supercooling). “Cold Finger Technique (CFT)” can obviate supercooling by maintaining a small mass fraction of the PCM in a solid state for enabling spontaneous nucleation. Optimization of CFT necessitates real-time forecasting of the transient values of the melt-fraction. In this study, the artificial neural network (ANN) is explored for real-time prediction of the time remaining to reach a target value of melt-fraction based on the prior history of the spatial distribution of the surface temperature transients. Two different approaches were explored for training the ANN model, using: (1) transient PCM-temperature data; or (2) transient surface-temperature data. When deployed in a heat sink that leverages PCM-based passive thermal management systems for cooling electronic chips and packages, this maverick approach (using the second method) affords cheaper costs, better sustainability, higher reliability, and resilience. The error in prediction varies during the melting process. During the final stages of the melting cycle, the errors in the predicted values are ~5% of the total time-scale of the PCM melting experiments.

Characterization and real-time testing of phase-change materials for solar thermal energy storage

2015 ◽  
Vol 40 (1) ◽  
pp. 61-70 ◽  
Author(s):  
Alain Joseph ◽  
Moe Kabbara ◽  
Dominic Groulx ◽  
Paul Allred ◽  
Mary Anne White
Keyword(s):  
Energy Storage ◽  
Phase Change ◽  
Real Time ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Phase Change Materials ◽  
Solar Thermal ◽  
Solar Thermal Energy

Effect of Different Production Processes on Metallic Composite Phase Change Materials for Thermal Energy Storage

2021 ◽  
Vol 1016 ◽  
pp. 359-365
Author(s):  
Chiara Confalonieri ◽  
Elisabetta Gariboldi
Keyword(s):  
Energy Storage ◽  
Powder Metallurgy ◽  
Phase Change ◽  
Thermal Management ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Phase Change Materials ◽  
Active Phase ◽  
Production Processes ◽  
Solid Liquid

Phase Change Materials (PCMs) can be applied in Thermal Energy Storage and Thermal Management systems, exploiting the storage and release of latent heat associated to a phase transition. Among them, metallic PCMs can be used at medium and high temperatures (i.e. above 150°C), storing higher heat per unit volume at higher temperatures with respect to the most widely investigated polymeric and salt-based PCMs. Miscibility Gap Alloys (MGAs) can be used to obtain multiple-phase mixtures in which the active phase (the actual PCM) is mixed to a second, high-melting temperature phase, with negligible interaction between them. These can actually be considered as fully metallic composite materials specifically developed for thermal management. Suitable microstructures can prevent leakage of active phase when the solid-liquid transition occurs, resulting in a form-stable PCM (FS-PCM). However, obtaining these microstructures it is not trivial. The present study focuses on a solid-liquid FS-PCM consisting of a ‘classical’ fully metallic FS-PCM, an Al-Sn based MGAs produced by powder metallurgy. The goal was to evaluate the effect of different production processes on thermal and mechanical behaviour of the PCM. Particularly, powder metallurgy routes including both simple mixing and ball milling were compared and further combined. Moreover, several compression and sintering conditions were considered, also substituting Al powders with Al-alloy powders, in order to optimize the material microstructures in view of suitable thermal and mechanical properties. Finally, the casting route with a rapid solidification approach was investigated for the same alloy.

Thermodynamic insights into n-alkanes phase change materials for thermal energy storage

2021 ◽  
Author(s):  
Huimin Yan ◽  
Huning Yang ◽  
Jipeng Luo ◽  
Nan Yin ◽  
Zhicheng Tan ◽  
...  
Keyword(s):  
Energy Storage ◽  
Phase Change ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Phase Change Materials
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