MyJournals Home  

RSS FeedsEnergies, Vol. 16, Pages 6068: Thermophysical Properties of POLWAX LTP ST Paraffin Doped with or without Carbon Nanotubes or Silver Nanowires and Passive Cooling of a High-Power LED Panel (Energies)

 
 

19 august 2023 11:10:03

 
Energies, Vol. 16, Pages 6068: Thermophysical Properties of POLWAX LTP ST Paraffin Doped with or without Carbon Nanotubes or Silver Nanowires and Passive Cooling of a High-Power LED Panel (Energies)
 


Commercially available paraffin wax LTP ST, manufactured in Poland by POLWAX, was used as a phase change material (PCM) for passive cooling of an LED panel containing 28 high power light emitting diodes (LEDs). Paraffin wax LTP ST of density ρ = 930 kg·m−3 at room temperature (RT) was chosen over other POLWAX waxes (LUXOLINA, LUXOLINA-ST, and LTP 56-20) because of its melting point range (44.5–55.4 °C), relatively high latent heat of fusion ΔH = 218.8 J·g−1, high specific heat Cp = 2.11 J·g−1K−1 and thermal conductivity k = 0.233 Wm−1K−1 at 0 °C. The thermophysical properties were studied in samples of pure LTP ST paraffin and doped with multi-walled carbon nanotubes (1.99, 3.49, 5.35, and 10.49 wt%, MWCNTs) or silver nanowires (0.26, 0.32, 1.06, 2.10, and 7.35 wt%, SNWs). Analysis of the thermal effects of doped samples showed a relative increase in the degree of subcooling, averaging 100% for MWCNT and 46% for SNW, a relative 15÷25% decrease in enthalpy of melting for MWCNT and 14÷16% for SNW. A 44% increase in thermal conductivity was found for the sample containing 5.35 wt% MWCNTs and a 91% increase for 1.06 wt% SNW. The results of cooling efficiency tests for three types of developed heat sinks fabricated of AW-2017A aluminum alloy are presented, i.e., (a) full system without PCM filling, (b) system with PCM chamber without intracellular ribs, (c) and system with PCM chamber with intracellular fins.


 
340 viewsCategory: Biophysics, Biotechnology, Physics
 
Energies, Vol. 16, Pages 6069: The Use of Real Energy Consumption Data in Characterising Residential Energy Demand with an Inventory of UK Datasets (Energies)
Energies, Vol. 16, Pages 6070: Research on Load Forecasting of Novel Power System Based on Efficient Federated Transfer Learning (Energies)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten