Near-field thermophotonic (TPX) systems that replace the high-temperature emitter in the thermophotovoltaic systems with a light-emitting diode (LED) have been reported to achieve low-grade heat harvesting and electroluminescent cooling, respectively. Nevertheless, the requirements for the two functionalities are different, leading to challenges to coordinate them. In our work, we propose a near-field TPX system composed of the CdTe LED and InP photovoltaic (PV) cell to realize two such functionalities with high performance. With wide-bandgap and high-quality semiconductors, the proposed system achieves a bandgap alignment at various temperatures and has low nonradiative recombination rates, thus enabling the functionality integration. Without changing the structures and materials, the system can switch functionality from power generation to electroluminescent refrigeration by tuning the LED temperature from 800 to 260 K while the PV temperature is maintained at 300 K. In addition, we suggest an additional layer of a thin Pt film on the PV cell to suppress phonon-polaritons parasitic heat transfer and further improve the system efficiency of both functionalities. This work theoretically demonstrates the possible integration of multiple functionalities and triggers further explorations of practical TPX systems.

Electrically heating garment (EHG) is an effective protection for human in cold environment. In this study, we analysed the principal agents of heat transfer in EHG, and established a theoretical model including heat conduction, natural convection and radiation. To verify the model, the numerical simulations and experiments were compared, and showed a temperature discrepancy smaller than 0.3°C, which was acceptable in engineering design. Using numerical simulation, it is convenient to optimize the design parameters of EHG in different thermal conditions. For instance, to maintain the average temperature of skin within 32-34°C when people are in low metabolic activities, the power of heating elements should range from 73.1-110.7 W/m2 under high heating gear or 10.8-48.5 W/m2 under low heating gear. The more importance is that the calculation allows easy predesign of EHG. The effect of the arrangements of heating elements was studied, herein, the results of six arrangement patterns were presented. It is found that the most effective arrangement can raise the average temperature of skin under heating elements about 0.4-1.2°C than other cases.

Thermophotovoltaic (TPV) devices, which can break the Shockley–Queisser limit (33.7%) and enhance the thermal energy utilization efficiency, have garnered increasing attention in recent decades. Structuring the emitter surface has been demonstrated to be powerful for tailoring thermal emission to enhance the power density and system efficiency of a TPV system. However, the design and optimization of the broad parameters of the surface nanostructures manually remain to be thorny issues. In this paper, the Bayesian algorithm under the framework of material informatics was coupled with a rigorous coupled wave analysis to optimize the geometry of the infrared grating nanostructure to achieve wavelength-selective emission to boost the TPV performance. It is demonstrated that only less than 0.173% of the total candidate structures were calculated to find out the optimal structure with high spectral emittance in the range of 0.3–1.708  μm, and the power density and system efficiency of the TPV system were enhanced to 4.20 W/cm2 and 35.37%, respectively. The present machine-learning-based optimization of a multi-parameter nanostructure can improve the performance of the TPV system significantly and can be extended to other physical fields in a feasible manner.

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