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Flame-Retardant and Form-Stable Phase-Change Composites Based on Phytic Acid/ZnO-Decorated Surface-Carbonized Delignified Wood with Superior Solar-Thermal Conversion Efficiency and Improved Thermal Conductivity.

Hao YueJiuao WangHaibo WangZongliang DuXu ChengXiaosheng Du
Published in: ACS applied materials & interfaces (2023)
In order to efficiently exploit solar-thermal energy, it is essential to develop form-stable phase-change material (PCM) composites simultaneously with superior solar-thermal storage efficiency, excellent flame retardancy, and improved thermal conductivity. Herein, phytic acid (PA)-modified, zinc oxide-deposited, and surface-carbonized delignified woods (PZCDWs) were constructed by alkaline boiling, PA modification, ZnO deposition, and surface carbonization. Then, novel form-stable PCMs (PZPCMs) with superior solar-thermal storage efficiency, excellent flame retardancy, and improved thermal conductivity were fabricated by impregnating n -docosane into PZCDWs under vacuum. The PZCDW aerogels can well support the n -docosane and overcome liquid leakage owing to their superior surface tension and strong capillary force. Differential scanning calorimetry results showed that PZPCMs possessed superior n -docosane encapsulation yield and high phase-change enthalpy (185.2-213.1 J/g). Decorating delignified wood by surface carbonization and ZnO deposition significantly improved the solar-thermal conversion efficiency (up to 86.2%) and thermal conductivity (193.3% increased) of PCM composites. Furthermore, with the introduction of PA into PZPCMs, the peak heat release rate and total heat release of the PCM composites decreased considerably, indicating the enhanced flame retardancy of PZPCMs. In conclusion, the novel renewable wood-based PCM composites demonstrate promising potential in solar energy harnessing and thermal modulation technologies.
Keyphrases
  • reduced graphene oxide
  • quantum dots
  • visible light
  • risk assessment
  • machine learning
  • wastewater treatment
  • big data
  • artificial intelligence
  • heavy metals
  • sewage sludge