Computational design of isotropic and anisotropic ultralow thermal conductivity polymer foams

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Abstract

Current state-of-the-art commercial polymer thermal insulation foam exhibits a thermal conductivity of 24 mW⸳m−1⸳K−1 (equivalently thermal resistivity of R-6/in.), similar to that of static air. To further optimize building energy efficiency, achieving even lower thermal conductivity is needed, which is, however, highly challenging. This paper presents computational evidence that demonstrates the feasibility of achieving an ultra-low thermal conductivity of less than 14.4 mW⸳m−1⸳K−1 (equivalently R-10/in.) using isotropic and anisotropic foam cell designs. For the isotropic design, we have identified analytical effective medium approximation (EMA) models within the accuracy of ±5% as finite element analysis (FEA) in predicting the effective thermal conductivity of foams with various porosities and filler gases. For the anisotropic design, we have developed and validated new EMA models against FEA in predicting the effective thermal conductivity of general anisotropic cuboids and Voronoi foams. For both isotropic and anisotropic designs, the design spaces for 18, 16, and 14.4 mW⸳m−1⸳K−1 (equivalently R-8, R-9 and R-10/in.) using various filler gases are obtained. It is found that polymer foams can be improved to achieve ultralow thermal conductivity by reducing CO2 concentration, reducing radiation, increasing porosity, and using anisotropic pore geometry. These findings contribute to the development of highly efficient thermal insulation materials, enhancing building energy efficiency and promoting sustainable construction practices.

Original languageEnglish
Article number109717
JournalJournal of Building Engineering
Volume92
DOIs
StatePublished - Sep 1 2024

Funding

This research was supported by the US Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (BTO) under Contract No. DE-AC05-00OR22725 with UT-Battelle, LLC, and used resources at the Building Technologies and Research Integration Center, a DOE-EERE User Facility at Oak Ridge National Laboratory. This work is supported by the project “Multi-Scale Simulations and Machine Learning-Guided Design and Synthesis of High-Performance Thermal Insulation Materials” funded by the DOE’s BTO and EERE. Som S Shrestha, Tianli Feng reports financial support was provided by US Department of Energy.This research was supported by the US Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (BTO) under Contract No. DE-AC05-00OR22725 with UT-Battelle, LLC, and used resources at the Building Technologies and Research Integration Center, a DOE-EERE User Facility at Oak Ridge National Laboratory. This work is supported by the project “Multi-Scale Simulations and Machine Learning-Guided Design and Synthesis of High-Performance Thermal Insulation Materials” funded by the DOE's BTO and EERE.

Keywords

  • Building energy efficiency
  • Effective medium approximation
  • Finite element analysis
  • Foam blowing agents
  • Polymer foams
  • Porous materials
  • Thermal insulation

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