High-entropy alloys (HEAs), with multi-principal-element composition, are gaining attention for their structural stability and mechanical properties. Extensive research has focused on using HEAs as electrocatalysts in the conversion of single-component reactions, such as hydrogen evolution reaction (HER), oxygen evolution reaction (OER), carbon dioxide reduction reaction (CO$_2$RR), etc. However, their potential in the application of synergistic conversion of pollutants (e.g., carbon dioxide (CO$_2$) and nitrogen oxides (NO$_x$)) has been largely overlooked. This review overviews HEAs' fundamental concepts and characteristics, and delves into their advantages in transition metals and optimization strategies for the synergistic conversion process. It offers a novel approach for sustainable environmental remediation and resource utilization.

Designing novel two-dimensional structures and precisely modulating their second harmonic generation (SHG) attributes are key to advancing nonlinear photonic technologies. In this work, through first-principles calculations, we propose a novel tetrahedral phase of transition metal dichalcogenides (TMDs) and validate its structural feasibility in a family of compounds, i.e., $ZX_2$ ($Z = {\rm Ti}$, Zr, Hf; $X ={\rm S}$, Se, Te). Cohesive energy and phonon dispersion calculations further demonstrate that eight of nine possible $ZX_2$ monolayers are dynamically stable. All the $ZX_2$ monolayers exhibit pronounced out-of-plane SHG with nonlinear susceptibility components reaching the order of 10$^2$ pm/V. Strain engineering imposes a profound influence on the SHG response of $ZX_2$ monolayers by reducing symmetry and modifying nonlinear susceptibility components. The redshift and significant enhancement of the prominent peak in SHG spectra are also revealed due to strain-induced charge redistribution and band gap reduction. Intriguingly, strain-driven nonlinear optical switching effects are realized in the $ZX_2$ monolayers, with a reversible switching of SHG component ordering under tensile and compressive strain. In such a case, the anisotropic SHG pattern transforms from fourfold to twofold symmetry under the strain. Our work demonstrates the efficacy of strain engineering in precisely enhancing SHG, paving the way for the integration of novel TMD structures into tunable and flexible nonlinear optical devices.

As a representative of wide-bandgap semiconductors, wurtzite gallium nitride (GaN) has been widely utilized in high-power devices due to its high breakdown voltage and low specific on-resistance. Accurate prediction of wurtzite GaN's thermal conductivity is a prerequisite for designing effective thermal management systems for electronic applications. Machine learning-driven molecular dynamics simulation offers a promising approach to predicting the thermal conductivity of large-scale systems without requiring predefined parameters. However, these methods often underestimate the thermal conductivity of materials with inherently high thermal conductivity due to the large predicted force error compared with first-principles calculations, posing a critical challenge for their broader application. In this study, we successfully developed a neuroevolution potential for wurtzite GaN and accurately predicted its thermal conductivity, 259$\pm$6 W/(m$\cdot$K) at room temperature, achieving excellent agreement with reported experimental measurements. The hyperparameters of the neuroevolution potential (NEP) were optimized based on a systematic analysis of reproduced energy and force, structural features, and computational efficiency. Furthermore, a force error correction method was implemented, effectively reducing the error caused by the additional force noise in the Langevin thermostat by extrapolating to the zero-force error limit. This study provides valuable insights and holds significant implications for advancing efficient thermal management technologies in wide-bandgap semiconductor devices.

The photothermal properties of dielectric materials at the nanoscale have garnered significant attention, especially in fields such as optical heating, photothermal therapy, and solar utilization. However, although dielectric materials can concentrate and manipulate light at the nanoscale, they cannot provide sufficient photothermal efficiency in a direct absorption solar collector. Combining plasmonic metal nanoparticles with dielectric nanostructures enables the fabrication of hybrid nanomaterials with excellent photothermal performance. This study presents a novel approach involving uniformly adhering plasmonic gold nanoparticles onto dielectric silicon nanoparticles to enhance the absorption peak, leading to a substantial enhancement of photothermal conversion efficiency. The results demonstrate that the absorption peak of silicon-gold hybrid nanoparticles exceeds that of pure silicon nanoparticles, achieving a 38% increase in photothermal conversion efficiency within a 10 ppm aqueous solution under a 20 mm optical path. The coupling of localized surface plasmon resonance and quadrupole resonance effects enhances the electric field, causing a temperature rise in both the hybrid nanoparticles and the surrounding aqueous solution. Nanostructural modulation studies reveal that the photothermal efficiency of silicon-gold hybrid nanoparticles is positively correlated with gold nanoparticle size but negatively correlated with silicon nanoparticle size. Combining multiple plasmonic nanoparticles with dielectric materials can effectively enhance photothermal performance and hold great application potential in direct absorption solar collectors and solar thermal utilization.

In order to meet the growing global energy demand and fulfill energy conservation and emission reduction goals, the efficient utilization of solar energy is becoming increasingly critical. However, the effects of high temperatures on solar absorption are rarely considered in practical research. Therefore, this study presents a porous zinc and silver sulfide solar absorber with high-temperature radiative cooling capabilities. The solar absorption rate and radiative cooling efficiency in the high-temperature range (636 K-1060 K) are computed using the finite-difference time-domain method. Furthermore, the impact of parameters such as characteristic length, porosity, incident angle, and pore shape factor on both the absorption rate and efficiency of the solar absorber is analyzed. The mechanism is further examined from the perspective of microscopic thermal radiation. The results show that, in the high-temperature range, the solar absorption rate increases with higher porosity and incident angles, reaching its peak when the characteristic length is 1 μm. These findings highlight the significant potential of the solar absorber for efficient solar energy harvesting in photo-thermal conversion applications within a specific high-temperature range.

Quantum interference effect serves as a critical strategy for addressing incorrect energy level alignment between frontier molecular orbitals and electrodes in molecular junctions. Weak-coupling structures offer an effective approach to suppress phonon thermal conductance. The thermoelectric properties of pure C$_{3}$N$_{4}$ nanoribbon devices and C$_{3}$N$_{4}$-C$_{20}$ molecular junctions are systematically investigated based on density functional theory (DFT) combined with non-equilibrium Green's function (NEGF) formalism. The results show that pure C$_{3}$N$_{4}$ nanoribbon devices have superior charge transport capabilities and excellent Seebeck coefficients. A remarkable thermoelectric figure of merit ($ZT=0.98$) is achieved near 0.09 eV. The pronounced scattering effect induced by embedding a C$_{20}$ molecule in the center of the C$_{3}$N$_{4}$ nanoribbon significantly suppresses phonon transport. A maximum ZT value of 1.68 is observed at 0.987 eV. The electron mobility of C$_{3}$N$_{4}$-C$_{20}$-par is effectively increased due to quantum interference effect which greatly improves the alignment between the C$_{20}$ molecule's frontier orbital energy level and C$_{3}$N$_{4}$ electrodes. The C$_{3}$N$_{4}$-C$_{20}$-van der Waals (vdW) molecular junction allows very few phonons to pass through the C$_{20}$ molecule from the left electrode to the right electrode. As a result, the C$_{3}$N$_{4}$-C$_{20}$-vdW junction achieves an excellent ZT value of 3.82 near the Femi level.

Direct absorption solar collectors use nanofluids to absorb and convert solar radiation. Despite the limitations of the photothermal properties of these nanofluids within the absorption spectra range, modifying the surface structure of the nanoparticles can broaden their absorption spectrum, thereby significantly improving the solar thermal conversion efficiency. This paper utilizes the finite element method to investigate the influence of surface pits on the photothermal properties of plasmonic nanoparticles, considering both material composition and surface micro-nano structures. Based on the findings, a novel TiN nanoparticle is proposed to enhance photothermal performance. This nanoparticle exhibits the lowest average reflectance (0.0145) in the 300-1100 nm wavelength range and the highest light absorption intensity across the solar spectrum, enabling highly efficient solar energy conversion. It not only reduces material costs but also effectively broadens the light absorption spectrum of spherical plasmonic nanoparticles. The distributions of the electric field, magnetic field, and energy field of the nanoparticles indicate that the combination of the ``lightning rod'' effect and surface plasmon resonance (SPR) significantly enhances both the electric and magnetic fields, thereby increasing the localized heating effect and improving the photothermal performance. Additionally, the number and size of the pits have a significant impact on the absorption efficiency ($\eta_{\rm abs}$) of TiN nanoparticles. When the surface of the nanoparticles has 38 pits, $\eta _{\rm abs}$ can reach 90%, with the minimum optical penetration depth ($h$) of the nanofluid being 7 mm and the minimum volume fraction ($f_{\rm v}$) being 6.95$\times10^{-6}$. This study demonstrates that nanoparticles with micro-nano structures have immense potential in solar thermal applications, particularly in the field of direct absorption solar collectors.

This study presents a systematic investigation of thermal transport properties in a novel class of carbon-based graphene-like materials (AKCs). Through first-principles calculations combined with the phonon Boltzmann transport equation and machine-learning potential, we analyzed the lattice thermal conductivity and its microscopic mechanisms in three structures: AKC60, AKC33, and AKC41. The research reveals that these materials exhibit significant in-plane thermal conductivity at room temperature (191.0 W/m$\cdot$K, 122.6 W/m$\cdot$K, and 248.3 W/m$\cdot$K, respectively), though an order of magnitude lower than that of graphene. Through detailed analysis of phonon dispersion relations, group velocities, three-phonon scattering phase space, and Grüneisen parameters, we uncovered the physical origins of AKCs' relatively lower thermal conductivity. The findings indicate that despite AKC60's larger primitive cell, its better preservation of graphene's honeycomb structure leads to superior harmonic properties, resulting in higher thermal conductivity than that of AKC33 with its smaller primitive cell. These discoveries provide valuable guidance for AKCs' applications in future electronic devices.

Liquid metals demonstrate significant potential for applications in thermal management and flexible electronic circuits, necessitating a comprehensive understanding of their transport properties for technological advancements. Experimental measurement of these properties presents challenges due to factors like cost, corrosion and impurity control. Consequently, accurate computational simulations become essential for predicting the physical properties of these materials. In this research, molecular dynamics (MD) simulations were employed to model several properties of gallium (Ga), indium (In) and Ga-In alloys, including lattice structural parameters, radial distribution functions (RDF), structure factors, self-diffusion coefficients and viscosity. Due to the difficulty of traditional interatomic potentials in capturing the short-range interactions directly related to the mechanical behavior of liquid atoms, machine-learning interatomic potentials (MLIPs) have been constructed to precisely describe the liquid metals Ga, In, and Ga-In alloys. This was achieved by utilizing the moment tensor potential (MTP) framework in combination with an active learning strategy. MTP was trained using a comprehensive database generated from DFT and MD simulations, which include a variety of crystal structures, point defects and liquid structures. The calculations of physical properties in this research have shown strong consistency with experimental data, demonstrating that the MTP can accurately describe the interatomic interactions between Ga-Ga, In-In and Ga-In. Our work has established a novel paradigm for investigating the physical properties of various liquid metal systems, offering valuable insights and references for future research.