Acta Energiae Solaris Sinica•2026•DOI: 10.19912/j.0254-0096.tynxb.202608_9694
Accurate estimation of the cold- and hot-side temperature difference in thermoelectric generator (TEG) modules is critical for online performance assessment and reliability prediction in industrial waste heat recovery systems. Conventional equivalent thermal networks neglect the nonlinear effects of convective and radiative heat dissipation, which are particularly pronounced under natural convection, leading to substantial errors in temperature difference estimation. This study proposes an improved equivalent thermal network that incorporates nonlinear convective and radiative branches to capture the temperature-dependent heat dissipation characteristics of TEG modules. A multi-objective parameter identification framework is developed, employing the estimation errors of hot-side, cold-side, and heat sink temperatures as objective functions. The convexity properties of the objective functions are analyzed, and the non-dominated sorting genetic algorithm II (NSGA-II) is applied to extract the thermal parameters that are difficult to determine theoretically. Experimental validation under natural convection conditions, where nonlinear heat dissipation is most significant, demonstrates that the proposed method achieves high-precision extraction of TEG module thermal parameters and accurately estimates the dynamic variations of the cold- and hot-side temperature difference. The method exhibits strong adaptability and extensibility, as it can be readily adapted to forced convection environments by substituting the corresponding convective thermal resistance expression. This work provides a robust tool for enhancing the performance prediction and reliability evaluation of thermoelectric power generation systems.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4337-2
Silica aerogels are recognized as leading super-insulating materials due to their ultralow thermal conductivity, yet their intrinsic brittleness and poor processability restrict practical deployment in complex industrial and extreme environments. This study introduces a macro-scale 'stiff–soft' synergistic strategy, combining a macroscopically processable, soft-and-tough framework as the load-bearing component with hard-and-brittle polymethylsilsesquioxane (PMSQ) aerogels as the insulating component. A pressure-driven assembly process enables viscosity-tunable PMSQ gel inks to be controllably infused into various hollow frameworks, including honeycomb panels, wheat straws, and hollow fibers. Guided by a modified Hagen–Poiseuille model, ink viscosity is precisely matched to the geometric parameters of the hollow structures. The resulting composites achieve compressive strength of 2.5 MPa, flexural strength of 6.25 MPa, and tensile strength of 40 MPa, while maintaining excellent thermal insulation. This versatile and scalable approach offers a new design paradigm for mechanically adaptive silica aerogel composites in thermal management applications.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4049-0
Isotope separations, particularly the separation of water isotopologues (H2O, HDO, D2O), are critical yet challenging due to their nearly identical physicochemical properties. Conventional methods such as distillation and electrolysis are energy-intensive and inefficient. Here, we report a molecularly woven porous polymer (PWPN-1) that achieves efficient room-temperature separation of water isotopologues via adaptive framework dynamics. PWPN-1 is constructed from interlaced two-dimensional woven layers linked by B←N coordination nodes, forming a three-dimensional flexible framework. Upon activation, it undergoes reversible contraction along the crystallographic c-axis, exhibiting a breathing behavior that creates differentiated adsorption sites favoring D2O retention. Gas-phase breakthrough experiments demonstrate markedly different retention times for H2O (223 min g−1) and D2O (686 min g−1), with clearly resolved breakthrough curves for H2O/HDO/D2O mixtures under continuous flow. The material is synthesized on a 100-gram scale with ~95% yield and remains stable over multiple adsorption-desorption cycles. Single-crystal structure analyses, combined with path-integral molecular dynamics and DFT calculations, reveal that D2O exhibits slightly stronger binding energies (by 1–2 kJ mol−1) and higher diffusion barriers, arising from nuclear quantum effects. These small energetic differences are amplified by the flexible woven topology, enabling efficient isotope separation under ambient conditions. This work represents a conceptual advance in materials design, transposing macroscopic weaving to the molecular scale for practical isotope enrichment.