Building energy consumption prediction has a significant effect on energy control, design optimization, retrofit evaluation, energy price guidance, and prevention and control of COVID-19 in buildings, providing a guarantee for energy efficiency and carbon neutrality. This study reviews 116 research papers on data-driven building energy prediction from the perspective of data and machine learning algorithms and discusses feasible techniques for prediction across time scales, building levels, and energy consumption types in the context of the factors affecting data-driven building energy prediction. The review results revealed that the outdoor dry-bulb temperature is a vital factor affecting building energy consumption. In data-driven building energy consumption prediction, data preprocessing enables prediction across time scales, energy consumption feature extraction enables prediction across energy consumption types, and hyperparameter optimization enables prediction across time scales and building layers.

Flexible silica aerogel composites in intact monolith of 12 cm were successfully fabricated by reinforcing SiO₂ aerogel with electrospun polyvinylidene fluoride (PVDF) webs via electrospinning and sol‐gel processing. Three electrospun PVDF webs with different microstructures (e.g., nanofibers, microparticles, and combined nanofibers and microparticles) were fabricated by regulating electrospinning parameters. The as‐electrospun PVDF webs with various microstructures were impregnated into the silica sol to synthesize the PVDF/SiO₂ composites followed by solvent exchange, surface modification, and drying at ambient atmosphere. The morphologies of the PVDF/SiO₂ aerogel composites were characterized and the thermal and mechanical properties were measured. The effects of electrospun PVDF on the thermal and mechanical properties of the aerogel composites were evaluated. The aerogel composites reinforced with electrospun PVDF nanofibers showed intact monolith, improved strength, and perfect flexibility and hydrophobicity. Moreover, the aerogel composites reinforced with the electrospun PVDF nanofibers had the lowest thermal conductivity (0.028 W·m⁻¹·K⁻¹). It indicates that the electrospun PVDF nanofibers could greatly improve the mechanical strength and flexibility of the SiO₂ aerogels while maintaining a lower thermal conductivity, which provides increasing potential for thermal insulation applications.