Xiaokun Gu

Materials with exceptionally low thermal conductivity are desirable for thermal insulation and waste heat recovery. While foams and aerogels boast ultralow thermal conductivities akin to air, lack of mechanical stiffness in these soft materials necessitates a paradigm shift in materials design that can offer thermal insulation and mechanical rigidity simultaneously. Here, we show that spun-cast layered hybrid organic-inorganic perovskite thin films, azobenzene ethyl ammonium lead iodides, exhibit a record-low thermal conductivity, down to ∼0.04 watts per meter per kelvin at room temperature, while maintaining mechanical rigidity with an elastic modulus of 7.7 gigapascals that surpasses that of most plastics, foams, and aerogels. This unusual combination of ultralow thermal conductivity and high mechanical rigidity is attributed to the specially engineered organic cations in the layered structure. Our finding highlights the potential of molecular engineering in hybrid layered structures to push the extreme of thermal insulation in dense, rigid solids.

We investigate thermal transport in nanowire composites with anisotropic fillers. Using Monte Carlo and finite element methods, we show that anisotropy strongly suppresses effective thermal conductivity, independent of anisotropy ratio definition, thermal boundary conductance, or filler orientation. Within a three-channel framework, the extended network governs heat conduction, but thermal transport is constrained by the intrinsic randomness of heat flux and by anisotropy-induced axial and radial conductivity bottlenecks. These results highlight the role of nanowire isotropy and the connectivity of the extended network in overall heat conduction, guiding the design of high-performance thermal interface materials.

This study establishes an explicit photoresponse theory for polycrystalline nanowire photoconductors, addressing the gap in understanding gain mechanisms in scalable polycrystalline systems. Traditional photoconductive gain models assume uniform carrier distribution and equal electron–hole contributions, which fail to account for grain boundary effects in polycrystalline materials. The proposed theory introduces the photogating effect as the origin of high gain, where light-induced photovoltage modulates conduction barriers at grain boundaries. Experimental validation utilized silicon nanowires with multiple transparent ITO gates to mimic grain boundary potential barriers. Photoresponse measurements under varying gate voltages and light intensities (532 nm LED) demonstrated excellent agreement with derived analytical equations, enabling the extraction of critical parameters such as minority carrier recombination lifetime (τ0) and critical light intensity. Silvaco TCAD simulations further corroborated the theory, showing barrier height and number-dependent photocurrent trends consistent with experiments. Additionally, polycrystalline ZnO thin-film devices and literature data from other polycrystalline systems were successfully fitted to the model, confirming its universality. This work provides a unified framework for optimizing responsivity and bandwidth in low-dimensional photodetectors, bridging theoretical insights with practical applications in next-generation optoelectronics.

In recent years, the localized solar thermal evaporation technology for solar seawater desalination systems has gained widespread attention, primarily due to its ability to achieve over 80% evaporation efficiency under a single sun intensity. As research progresses, solar seawater desalination systems based on this technology have continually made breakthroughs in freshwater production. This chapter introduces the application of interfacial evaporation technology in solar seawater desalination systems, including the development and improvement of interfacial evaporation solar stills. First, the theoretical analysis methods and mathematical models of interfacial evaporation solar stills are discussed. Secondly, based on the interfacial evaporation structure, the performance optimization methods of solar stills are explored. Finally, the application of multistage waste heat recovery technology in interfacial evaporation solar stills is discussed. This chapter provides a broader scope for the application of localized solar evaporation in seawater desalination systems.

Graphite is a cornerstone material in heat dissipation due to its exceptionally high in-plane thermal conductivity (~ 2000 W m^− 1 K^− 1). However, its low through-plane thermal conductivity remains a bottleneck for heat dissipation, typically limited to 5–9 W m^− 1 K^− 1. Here we reveal that graphite, when structure is optimized, delivers a record high through-plane thermal conductivity of up to 13.4 W m^− 1 K^− 1 at room temperature. This enhancement is achieved by reducing the helical twist within the graphite crystal structure. We demonstrate that while having minimal impact on in-plane conductivity, these twists significantly hinder heat-carrying phonons traveling through-plane. This work establishes a new benchmark for graphite's thermal properties and paves the way for unlocking its full potential in thermal management applications.

High-throughput screening of thermoelectric materials from databases requires efficient and accurate computational methods. Machine-learning interatomic potentials (MLIPs) provide a promising avenue, facilitating the development of database-driven thermal transport applications through high-throughput simulations. However, the present challenge is the lack of standardized databases and openly available models for precise large-scale simulations. Here, we introduce HH130, a standardized database for 130 Half-Heusler (HH) compounds in MatHub-3d (http://www.mathub3d.net), containing both MLIP models and datasets for the thermal transport of HH thermoelectrics. HH130 contains 31,891 total configurations (~ 245 configurations per HH) and 390 MLIP models (three models per HH), generated using the dual adaptive sampling method to cover a wide range of thermodynamic conditions, and will be open-access on MatHub-3d. Comprehensive validation against first-principles calculations demonstrates that the MLIP models accurately predict energies, forces, and interatomic force constants (IFCs). The MLIP models in HH130, enabled us to efficiently performed four-phonon interactions for 80 HHs with phonon frequencies closely matching ab initio results. It is found that HHs with 8 valence electron count (VEC) per unit cell generally exhibit lower lattice thermal conductivities (κ_Ls) compared to those with 18 VEC, due to a combination of low 2^nd-order IFCs and large scattering phase spaces in the former group. Additionally, we identified several HHs that demonstrate significant reductions in κ_L due to four-phonon interactions. HH130 provides a robust platform for high-throughput computation of κ_L and aids in the discovery of next-generation thermoelectrics through machine learning.