Emerging topological thermal physics has revolutionized thermal management with topological thermal metamaterials, but most of them only consider passive/static thermal diffusion. Inspired by ecological dynamics, we investigate the topological thermal physics in an active/dynamic three-body heat-transfer system connected with Peltier modules, in which the cyclic interaction is exemplified by the rock-paper-scissors (RPS) chain. Numerical simulations demonstrate a robust temperature localization phenomenon against parametric disturbance and structural perturbations, and topological phase transition in a thermal RPS chain is discussed via a topological band-theory analysis of the corresponding Hamiltonian. Our findings establish a framework for exploring dynamic topological phenomena in non-equilibrium thermal transport, offering new pathways for active thermal management.

Rapid and accurate temperature field prediction is critical for the thermal management of high-power lightemitting diodes (LEDs), as heat accumulation severely decreases device reliability and lifespan. Reduced-order modeling combining proper orthogonal decomposition (POD) and machine learning has been proven effective for fast temperature filed simulation. However, conventional algorithms struggle to capture the complex nonlinear fluctuations inherent in high-order POD mode coefficients. To address this, we propose a time-delay LSTM-Transformer (TDLformer) integrating with POD to establish a robust reduced-order framework for high-power LEDs thermal modeling. Within this architecture, POD facilitates efficient dimensionality reduction and the TDLformer predicts the temporal evolution of mode coefficients. To validate this framework, a spray cooling experimental platform for high-power LEDs is constructed and evaluated across 24 distinct operating conditions. The results demonstrate the superior predictive performance of the TDLformer over traditional models. The maximum temperature field prediction error is less than 1 degrees C, yielding reductions in the MAPE, MAE and RMSE of 45%, 42% and 54%, respectively. Furthermore, the average measured temperature error is 0.82 degrees C, with a maximum deviation of 2.63 degrees C (6.2%), and the maximum junction temperature error is 2.67 degrees C (3.2%). The TDLformer enables efficient and accurate predictions, offering a computational tool for managing complex, high-heat-flux electronics.

Thermoelastic stability is a critical requirement for inertial sensors (ISs) in the space-based gravitational wave detection, with the relative distance stability between the IS and the optical bench being a key performance driver. In existing studies, systematic optimization strategy for the thermoelastic compensation support of the IS has yet to be developed. In this study, a unified design framework integrating parametric geometric modeling, thermoelastic simulation, and the optimization algorithms is established and applied to the optimization of a typical IS support structure. A set of practical design strategy is proposed: (i) steady temperature and heat sources have negligible coupling effects into the frequency-domain thermoelastic analysis; (ii) the level of the thermal noise should be treated as a constraint in the optimization design; (iii) the lowest frequency within the target frequency band may be selected as the representative for the full band. Following these strategy, the gain for the thermoelastic displacement reduces from 3.28 & times; 10-8 m/W@ 0.1 mHz to 5.81 & times; 10-9 m/W@ 0.1 mHz for an improved configuration. The gain for the temperature fluctuation reaches 0.94 & times; 10-4 K/W@ 0.1 mHz, which remains within the acceptable limits. This work provides systematic optimization methodology and design criteria for the future space ISs.

Herein, we elucidate the determining role of aluminum (Al) in regulating the precipitation behavior and mechanical properties of Ni-Cr-Mo-V low-alloy steel subjected to quenching-lamellarizing-tempering (QLT) heat treatment. A novel high-strength steel with a superior combination of yield strength (1097 MPa), total elongation (19.5%), and impact toughness at -40 degrees C (96 J) was successfully developed. The matrix microstructural characteristics and precipitation nanostructural features of the experimental steels were systematically characterized using scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), and atom probe tomography (APT). A high Al content in the alloy composition effectively promoted the precipitation of Ni(Al, Mn) nanoparticles. Furthermore, these Ni(Al, Mn) nanoparticles served as heterogeneous nucleation sites for (Mo,Cr,V)2C carbides, thereby significantly increasing the nucleation rate of the carbides. Beyond the precipitation effect, an increase in Al content also elevated the Ac1 temperature from 604 degrees C to 615 degrees C, which resulted in a reduction in the reversed austenite (RA) content while enhancing its stability. Ultimately, the enhanced stability of reversed austenite and the strengthening effect of nano-scale precipitates synergistically enabled the test steel to achieve an excellent balance of high strength, excellent ductility, and superior toughness.

The advancement of high-power-density electronic devices imposes increasing demands on liquid cooling technology, in which the performance and size of the micropump are of paramount importance. For plate-level integrated applications, micropumps are required to possess both high performance and ultra-thin characteristics, a requirement that exceeds the capabilities of traditional decoupled hydraulic-electromagnetic designs. However, the transition to a co-design paradigm introduces new challenges. To address this, this paper proposes hydraulic-electromagnetic co-design methodology. The core of this method involves managing the dual bidirectional constraints-pertaining to both performance and geometric dimensions-between the hydraulic and electromagnetic components. The design process commences with the determination of preliminary hydraulic parameters based on the empirical coefficient method, followed by systematic characteristic matching and multi-round iterative optimization. Through this process, a high-performance, feasible design that balances hydraulic efficiency, electromagnetic performance, mechanical constraints, and manufacturability is efficiently identified, rather than pursuing a computationally prohibitive global optimum. An ultra-thin plate-level micropump prototype (34 & times; 34 & times; 4.9 mm-3) fabricated based on this approach demonstrates a stable output of 100 ml min-1 flow rate at 13.05 kPa with merely 1 W power consumption.

Humanoid robot joint actuators, particularly those employing high power-density motors, face significant thermal challenges due to their compact structural configuration and intermittent peak load operation, which impose stringent requirements on heat dissipation performance. To address this issue, an innovative integrated liquid cooling ring (LCR) is proposed, featuring axially layered and circumferentially closed annular flow channels. Systematic simulation was conducted to evaluate the cooling performance under peak power loads of 250 W, corresponding to high heat flux of 115.04 W/cm2.The results demonstrate that the implementation of the LCR provides a reduction in operating temperatures, maintaining the motor below 85 °C at a significant improvement over the 380 °C reached in the absence of active cooling. Analysis of heat transfer by convection characteristics indicates that the cooling efficiency is highly dependent on the volumetric flow rate, with the heat transfer coefficient h reaching approximately 1340 W/m2K at a flow rate of 0.6 L/min. Furthermore, the temperature gradient between the surface wall and the coolant exhibited a robust linear correlation with the heat flux, confirming a stable, single-phase heat dissipation regime. A general Nusselt number and Reynolds number correlation was developed to characterize the heat transfer performance. The results are consistent with the experimental data, falling within an ±6% error band. These findings demonstrate that the proposed LCR design offers a lightweight and highly efficient solution for maintaining thermal stability in high-density robotic actuators, providing a framework for future humanoid robotic thermal management systems.

Non-Hermitian skin effect (NHSE) has been identified as the unique properties of non-Hermitian thermal systems under open boundary condition (OBC) and has been extended from wave system to thermal diffusion system. Here, we explore the dynamic properties of diffusive NHSE based on a nonreciprocal thermal lattice. The corresponding Hamiltonian of the thermal lattice is established, and the corresponding spectra are analyzed. Temperature evolutions of the thermal lattice are characterized, and dynamic NHSE and topological winding number can be clearly observed, which are further analyzed in the generalized Brillouin zone with Z transformation and OBC eigenmode decomposition. Capacity-induced NHSE is realized with passive thermal system in simulations and experiments. Our work enriches the understanding of diffusive NHSE from the dynamic perspective and triggers the further studies of non-Hermitian thermal diffusion processes.

Synthetic jet pumps hold great promise for heat dissipation, particularly due to their potential for miniaturization. Existing studies have shown that the geometric configuration significantly affects performance. However, the flow rate mechanism remains unclear, and there is a gap between vortex-related research and practical synthetic jet pumps. This study investigates the outlet configuration effects of synthetic jet pumps. A 2D axisymmetric model is established, and the simulation results are validated by PIV experiments. It is found that the flow rate first increases and then decreases with outlet orifice size under small and medium jet-to-outlet distances, while under a large distance it increases monotonically and then nearly levels off, with the maximum flow rate occurring at a medium outlet orifice and jet-to-outlet distance. The underlying vortex dynamics are revealed via Lagrangian coherent structures and particle trajectories. It is found that under a small jet-to-outlet distance, the outlet is strongly affected by the suction process. At a medium distance and an appropriate aperture, a vortex deformation-reorganization phenomenon occurs, leading to strong entrainment. When the distance is larger, due to circulation decay, the vortex is blocked by the orifice edge and no deformation-reorganization is observed.

The increasing size of high-strength bulb-flat steel has posed significant challenges for maintaining the uniformity of mechanical properties across the section. In the present study, the effects of tempering temperature and overall induction quenching on the microstructure and cross-sectional mechanical uniformity of extra-large bulbflat steel (430 mm in width) were systematically investigated. The results reveal that the as-quenched bulb region contains a mixture of martensite(M) and bainite(B), whereas the flat region is fully martensitic. It leads to variations in the tempering response across the cross-section. Increasing the tempering temperature effectively improves the sectional strength uniformity of bulb-flat steel and enhances its low-temperature toughness. After tempering at 660 degrees C, the bulb's yield strength reached 812 MPa, while that of the flat was 818 MPa. The results of strengthening calculation show that the mechanical homogeneity of the section of bulb-flat steel tempered at 660 degrees C is controlled by dislocation strengthening and precipitation strengthening. Grain refinement is the primary factor contributing to the enhanced low-temperature toughness of the tested steel as the tempering temperature increases. The enhanced low-temperature impact toughness of the bulb section is mainly associated with the formation of a tempered martensite-bainite mixed microstructure, compared with the flat section. These results provide a theoretical basis for optimizing the heat-treatment process and improving the through-thickness uniformity of mechanical properties in super-large bulb-flat steel.

Half-metals are promising candidates for spintronic applications due to the complete spin polarization at the Fermi level. Recently, ferromagnetic half-metallic NiMnSb has regained considerable research attention owing to its nontrivial topological properties. For example, Singh et al. found that the Weyl node in NiMnSb produces anomalous Hall conductivity [Adv. Sci. 11, no.31 (2024): 2 404 495]. In this work, we design an AlAs/NiMnSb heterostructure and a magnetic tunnel junction (MTJ) NiMnSb/AlAs/NiMnSb to explore the potential spintronic applications of half-metallic NiMnSb. Density functional theory combined with non-equilibrium Green's function method reveals that the heterostructure exhibits an ideal thermal spin filtering effect and a spin diode effect. In addition, the MTJ has a large tunnel magnetoresistance ratio up to 3.7 & times; 105% at room temperature. These phenomena can be understood from the spin-dependent band structure and transmission spectrum. These results highlight the promising potential of NiMnSb for spintronic devices.

Quantum dots (QDs) face significant challenges in high-temperature and high-humidity environments, where both thermal and humidity-induced degradation as well as humidity-induced enhancement can occur simultaneously. This dual stress coupling effect can lead to complex intensity evolution in QDs. Given the critical importance of performance and lifetime prediction in optoelectronic devices, a systematic study and predictive modeling of the aging performance of QDs under temperature-humidity conditions are essential. In this work, we experimentally investigated the light intensity evolution of QDs composites under various temperature-humidity conditions. The results showed both increases and decreases in intensity within a single aging curve. By analyzing the underlying mechanisms of these intensity changes, we developed a predictive model by modifying the Kohlrausch-Williams-Watts equation with an asymmetric Gaussian pulse function (AsG-KWW), which demonstrated excellent agreement with the experimental data under each aging condition. According to this model, three distinct stages were identified: a sharp initial intensity drop, a recovery, and a stable attenuation. Additionally, the mean time to failure (MTTF) of the samples was derived and analyzed using the AsG-KWW model. Analysis of the fitting parameters revealed that intensity recovery only occurred under relatively mild aging conditions.

The research on near-infrared (NIR) luminescent materials faces core challenges of expanding the spectrum to longer wavelengths, especially in the full-range NIR-I region (700-1100 nm). To this end, this study proposed a co-doping strategy of Cr3+ and Yb3+ via constructing a high-efficiency energy transfer bridge. The dual activators were successfully introduced into the garnet structure matrix Ca2GdGa3Ge2O12 (CGGGO). Interestingly, compared with the sample doped with Cr3+ only, the sample co-doped with Cr3+ and Yb3+ not only makes the emission spectrum cover the entire NIR-I region, but also significantly enhances the thermal stability. The phosphor was integrated with a commercial 450 nm blue light chip to prepare a broadband NIR phosphorescent conversion light-emitting diode (pc-LED), and its application potential in biological imaging, nondestructive testing, and other fields was systematically explored. This study provides a new idea for solving the contradiction between wavelength tuning and thermal stability of NIR-I luminescent materials, and lays a material foundation for the practical development of NIR optoelectronic devices.

We investigate the control of the parity-time (PT-)symmetry-breaking threshold in a periodically driven onedimensional dimerized lattice with spatially symmetric gain and loss defects. We elucidate the contrasting roles played by Floquet topological edge states in determining the PT-symmetry-breaking threshold within the highand low-frequency driving regimes. In the high-frequency regime, the participation of topological edge states in PT-symmetry breaking is contingent upon the position of the PT-symmetric defect pairs, whereas in the lowfrequency regime, their participation is unconditional and independent of the defect pairs placement, resulting in a universal zero threshold. We establish a direct link between the symmetry-breaking threshold and how the spatial profile of the Floquet topological edge states evolves over one driving period. We further demonstrate that lattices with an odd number of sites exhibit unique threshold patterns, in contrast to even-sized systems. Moreover, applying cofrequency periodic driving to the defect pairs, which preserves time-reversal symmetry, can significantly enhance the PT-symmetry-breaking threshold.

High-strength, tough bulb flat steel is critical for hull stiffness regulation and lightweight design. Conventional furnace quenching of bulb flat steel suffers from inherent limitations including significant deformation, challenging straightening, and considerable fluctuations in mechanical properties. This study introduces a multistage induction heating technique that effectively addresses these issues, enabling successful induction quenching of large-scale bulb flat steel while incorporating embedded thermocouples for real-time monitoring of the temperature field. Experimental results demonstrate that three-stage high-temperature quenching (3IH) reduces the peak temperature variation across the bulb section by 55 % and decreases the yield strength differential between the bulb and flat by 73 %. The superior performance of 3IH is attributed to enhanced microstructural homogeneity under elevated temperatures, which improves strength uniformity through dislocation-mediated mechanisms. In contrast, two-stage low-temperature quenching (2IH) exhibits marginally lower strength but achieves exceptional ultra-low temperature toughness (-100 degrees C, KV2 >= 190 J) via synergistic effects of multiphase microstructure and grain refinement. The formation of multiphase microstructure in 2IH is governed by carbon diffusion coefficient, diffusion duration, and undissolved ferrite content. Furthermore, the flat region in 2IH undergoes a distinctive two-stage austenitization process that introduces high-density dislocations, resulting in greater dislocation strengthening contributions compared to 3IH.

Temperature fluctuation is a major disturbance for the space-based gravitational wave detectors, especially for the strain sensitivity of the TianQin inertial sensor. Comprehensive low-frequency thermal stability of the inertial sensor are essential inputs to the thermal design and the thermal diagnostics. However, the relative contributions of the different heat transfer effects within the vacuum chamber, as well as the effect of rarefied gas, remain undefined. In this work, the various heat transfer processes are decoupled and analyzed, particularly the rarefied gas heat transfer based on the frequency domain thermal framework. The results indicate that the thermal radiation accounts for only 4.55 % of the total heat transfer within the inertial sensor, and the rarefied gas heat transfer contributes even less. In order to meet the error budget, the temperature fluctuations along the x-axis direction of the vacuum chamber in the inertial sensor should be limited to 1 mK/Hz1/2. Moreover, the thermocouples on the vacuum chamber should be arranged in pairs.

Thermal field prediction has garnered ever-increasing attention as an urgent and vital issue in broad applications ranging from thermal management, performance prognosis, lifetime evaluation, and safety assessment, to energy conversion and carbon neutrality. Suffering from the huge amounts of data and iterative iterations, traditional full-order prediction methods are overstretched for rapid predictions and analysis of complex physical fields. In contrast, reduced-order methods, like proper orthogonal decomposition, can tackle such issues with accelerated computational efficiency but predictions and design may be physically inconsistent or implausible. Here we develop a physics-informed proper orthogonal decomposition for the acceleration of thermal field prediction. By introducing a unified index matrix to reduce the amount of processed data and to uniform the physical equations with the reduced-order equations, we achieve accurate and superfast predictions of thermal fields for unstructured grid, validated by typical complicated spray cooling experiments. The amount of data to be processed achieved a reduction of ten million times, with a maximum computational speedup of 101 times. The physics-informed proper orthogonal decomposition framework is demonstrated to be highly efficient and accurate and can be extended to address a wide range of scientific and technological applications beyond thermal field predictions.

The ability to actively control local states in thermal lattice provides critical insights into nonequilibrium thermodynamics and enables novel approaches to energy management across nano to macroscopic scales. The process of thermalization in thermal lattice is a kind of neighboring interactions due to the media- and path-dependent characteristic of Fourier's diffusion, rendering the significant challenge for remote control of local thermal state. Here we construct the time-independent Hamiltonian of a thermal lattice system with consideration of conduction and convection simultaneously and derive the optimal external command for active control of local thermal states. We implement three thermal targeting control—insulation, synchronization, and fluctuation—by modulating power inputs and precisely monitoring temperature evolution to demonstrate the validity and powerfulness of remote spatiotemporal control of local thermal states. Our work paves the way for remote spatiotemporal control of thermal states and provides efficient alternatives for advanced active thermal management in complex architectures.

Because of the significance role of nozzles in a Pelton turbine, various experimental and numerical studies have been performed to investigate their flow characteristics. However, there is still a research gap to develop a theoretical model for rapid prediction of flow performance. To this end, the classical theoretical model for a confined jet is employed and extended to nozzle jets in a Pelton turbine. The velocity profiles along radial direction are divided into three regions, i.e., potential jet zone, self-preserving jet shear layer zone, secondary potential flow zone. The velocity profiles in each region with unknow parameters are further determined by integrating continuity equation and momentum equation along radial direction. The theoretical prediction results of velocity profiles are validated by numerical results of large eddy simulations with good consistency.