Phase change energy storage materials have been recognized as potential energy-saving materials for balancing cooling and heating demands in buildings. However, individual phase change materials (PCM) with single phase change temperature cannot be adapted to different temperature requirements. To this end, the concept of fabricating different kinds of microencapsulated PCM (MEPCM) and combing them to form a multiphase change material (MPCM) for multi-seasonal applications in buildings has been proposed. To prove the feasibility of this idea, three kinds of MEPCMs were fabricated and used for the development of three different composite MPCMs, classified as MPCM-1, MPCM-2, and MPCM-3. Analysis of the results shows that each MPCM sample was able to release latent heat at two different temperatures thus making them suitable for multi-temperature thermal energy storage applications. The phase change temperatures of the MPCMs were however found to be slightly reduced by 0.09–0.31 °C as compared with the MEPCMs samples. The measured energy storage capacities for the MPCMs were also reduced in the range of 6.3–11.4% as compared with the theoretical values but they displayed relatively good thermal stability behaviour of up to 197.8–218.8 °C. It was further identified that the phase change temperatures and latent heat of the MPCM was attributed to the weight percentages of individual components, as the theoretical values for the three MPCM samples were all in good accordance with the measured values. Therefore, optimizing the weight ratios of the MEPCM in MPCM samples and their corresponding thermophysical properties based on specific climatic conditions would be a necessary step to take in future investigations. Thermal performance enhancement of the MPCM is also being recommended as an essential part of further research.

Monodisperse droplets, characterized by their uniform size distribution and well-controlled physicochemical properties, have found extensive applications in drug delivery, bioengineering, and food science. However, experimentally tuning droplet size typically requires multiple rounds of photomask design and microfluidic chip fabrication, which is costly and inefficient. To address this, we developed a numerical model for droplet generation in microfluidics based on the Volume of Fluid method in Fluent. The model was experimentally validated, achieving a maximum relative error below 5.43%. We systematically investigated the droplet formation mechanism, with a particular focus on the influence of structural and operational parameters on the control of droplet size. Three flow-focusing chips with dispersed phase inlet widths of 20, 40, and 70 μm enabled controlled modulation of droplet diameters ranging from 13.6 to 108.55 μm. Pressure variations at the geometric center of the flow-focusing structure inlet region revealed four distinct stages of droplet formation: lagging, filling, necking, and detachment. The associated pressure curves exhibited periodic oscillations, serving as a reliable indicator of monodispersity and generation stability. Structural parameters significantly affected both droplet size and frequency. The chip with a 20 μm inlet generated droplets at frequencies ranging from 625 to 7695 Hz, markedly higher than those of the 70 μm inlet (66.67–715 Hz). This study demonstrates the capability of high-precision, low-cost control of droplet size via numerical simulation. The findings provide theoretical insights for the design of microfluidic chips and practical guidance for applications in drug formulation, cell encapsulation, and microcapsule synthesis.

Building energy flexibility is essential for integrating renewables, optimizing energy use, and ensuring grid stability. While renewable and storage systems are increasingly used in buildings, poorly designed storage strategies often cause supply-demand mismatches, and a comprehensive, indicator-based assessment approach for quantifying flexibility remains lacking. Therefore, this study designs customized energy storage regulation strategies and constructs a comprehensive energy flexibility assessment scheme to address key issues in supply-demand coordination and energy flexibility evaluation. LSTM and Rolling-XGB methods are used to predict building energy consumption and PV generation, respectively. Based on battery safety constraints, a data-driven battery energy storage system (BESS) model simulates battery behavior to evaluate and compare building energy flexibility under two scenarios: (1) uncoordinated PV-BESS, and (2) coordinated PV-BESS with load forecasting. A practical validation was conducted using a net-zero-carbon building as the case study. Simulation results show that the data-driven BESS model improves building energy flexibility and reduces electricity costs through optimized battery sizing, tailored storage strategies, and consideration of local time-of-use tariffs. In the case study, local energy coverage reached 62.75%, surplus time increased to 34.77%, and costs were cut by nearly 40% compared to the PV-only scenario, demonstrating the significant benefits brought by the proposed BESS model that integrates load forecasting and PV generation prediction features.

Radiative sky cooling (RC) offers a passive route for reducing building cooling demand by releasing heat through the atmospheric window, but its practical performance depends on both local meteorological conditions and building energy demand. A key challenge is that high theoretical cooling potential does not necessarily indicate high building-level energy savings, and the climatic constraints that should guide material design remain insufficiently linked with regional deployment decisions. To address this issue, this study develops a climate-adaptive assessment framework for RC application across China. Radiative cooling power is theoretically calculated for 270 representative cities to characterize the spatial distribution of its theoretical potential, while interpretable machine learning is used to identify the dominant climatic drivers and connect them with material design priorities. Simulated building energy analyses are then used to examine how this cooling potential is translated into practical energy-saving performance under different regional conditions. The analysis shows that cloud fraction is the primary constraint on RC potential, while precipitable water vapor, wind speed, and air temperature impose region-specific secondary limitations. At the building scale, RC roofs show high applicability in arid northern and northwestern regions with favorable atmospheric-window conditions and in warm southern and southwestern regions with strong cooling demand. By contrast, cold high-altitude regions may exhibit weak or negative savings because increased heating demand can offset the cooling benefit. These findings indicate that RC deployment should be guided by both climatic suitability and building energy response, providing a basis for climate-adaptive material design and region-specific application strategies.