Bio-Based Phase Change Materials Incorporated in Lignocellulose Matrix for Energy Storage in Buildings—A Review

A comprehensive review of critical analysis of biodegradable waste PCM for thermal energy storage systems using machine learning and deep learning to predict dynamic behavior

This article explores the use of phase change materials (PCMs) derived from waste, in energy storage systems. It emphasizes the potential of these PCMs in addressing concerns related to fossil fuel usage and environmental impact. This article also highlights the aspects of these PCMs including reduced reliance on renewable resources minimized greenhouse gas emissions and waste reduction. The study also discusses approaches such as integrating nanotechnology to enhance thermal conductivity and utilizing machine learning and deep learning techniques for predicting dynamic behavior. The article provides an overall view of research on biodegradable waste-based PCMs and how they can play a promising role in achieving energy-efficient and sustainable thermal storage systems. However, specific conclusions drawn from the presented results are not explicitly outlined, leaving room, for investigation and exploration in this evolving field. Artificial neural network (ANN) predictive models for thermal energy storage devices perform differently. With a 4% adjusted mean absolute error, the Gaussian radial basis function kernel Support Vector Regression (SVR) model captured heat-related charging and discharging issues. The ANN model predicted finned tube heat and heat flux better than the numerical model. SVM models outperformed ANN and ANFIS in some datasets. Material property predictions favored gradient boosting, but Linear Regression and SVR models performed better, emphasizing application- and dataset-specific model selection. These predictive models provide insights into the complex thermal performance of building structures, aiding in the design and operation of energy-efficient systems. Biodegradable waste-based PCMs' sustainability includes carbon footprint, waste reduction, biodegradability, and circular economy alignment. Nanotechnology, machine learning, and deep learning improve thermal conductivity and prediction. Circular economy principles include waste reduction and carbon footprint reduction. Specific results-based conclusions are not stated. Presenting a comprehensive overview of current research highlights biodegradable waste-based PCMs' potential for energy-efficient and sustainable thermal storage systems.

Bio-Based Phase Change Materials for Wooden Building Applications

Solid wood can serve multifunctionality for energy savings in buildings. The study reveals the results of biodeterioration and degradation of solid Scots pine wood used to incorporate single or multicomponent fatty acid mixtures as bio-based phase change materials (BPCMs). The sapwood samples were impregnated with capric acid (CA), methyl palmitate (MP), lauryl alcohol (LA) and a mixture of coconut oil fatty acids and linoleic acid (CoFA-LA). The samples were tested against subterranean termites by an Italian species (Reticulitermes lucifugus), the wood boring beetle Hylotrupes bajulus and mold through a discoloration test. Tested against termites, the impregnated samples were significantly less susceptible to the attack than the controls, i.e., the tested BPCMs were resistant to R. lucifugus. The only test with MP terminated at the moment against H. bajulus showed positive results with no larvae surviving. The mold discoloration test revealed that the wood impregnated with CoFA-LA was identically susceptible to mold discoloration when compared to the control, nonimpregnated samples. This pioneer study verifies that solid wood employed for the encapsulation of BPCMs for building purposes can serve identically or somewhat better than similar wooden building elements regarding attacks of the above microorganisms and insects. Such multifunctional building elements will be tested further in a pilot scale building to characterize better the durability aspects of the new materials.