Going through decades of development, great progress in both theory and experiment has been achieved in thermoelectric materials. With the growing enhancement in thermoelectric performance, it is also companied with the complexation of defects induced in the materials. 0D point defects, 1D linear defects, 2D planar defects, and 3D bulk defects have all been induced in thermoelectric materials for the optimization of thermoelectric performance. Considering the distinct characteristics of each type of defects, in-depth understanding of their roles in the thermoelectric transport process is of vital importance. In this paper, we classify and summarize the defect-related physical effects on both band structure and transport behavior of carriers and phonons when inducing different types of defects. Recent achievements in experimental characterization and theoretical simulation of defects are also summarized for accurately determining the type of defects serving for the design of thermoelectric materials. Finally, based on the current theoretical and experimental achievements, strategies engaged with multiple dimensional defects are reviewed for thermoelectric performance optimization.

Active matter, comprising many active agents interacting and moving in fluids or more complex environments, is a commonly occurring state of matter in biological and physical systems. By its very nature, active matter systems exist in nonequilibrium states. In this paper, the active agents are small Janus colloidal particles that use chemical energy provided by chemical reactions occurring on their surfaces for propulsion through a diffusiophoretic mechanism. As a result of interactions among these colloids, either directly or through fluid velocity and concentration fields, they may act collectively to form structures such as dynamic clusters. A general nonequilibrium thermodynamics framework for the description of such systems is presented that accounts for both self-diffusiophoresis and diffusiophoresis due to external concentration gradients, and is consistent with microreversibility. It predicts the existence of a reciprocal effect of diffusiophoresis back onto the reaction rate for the entire collection of colloids in the system, as well as the existence of a clustering instability that leads to nonequilibrium inhomogeneous system states.

The steel bridge deck system, directly subjected to the vehicle load, is an important component to be considered in the optimization design of the bridges. Due to its complex structure, the design parameters are coupled with each other, and many fatigue details in the system result in time-consuming calculation during structure optimization. In view of this, a nonlinear optimization method based on the response surface methodology (RSM) is proposed in this study to simplify the design process and to reduce the amount of calculations during optimization. The optimization design of the steel bridge deck system with two-layer pavement on the top of the steel deck plate is taken as an example, the influence of eight structural parameters is considered. The Box-Behnken design is used to construct a sample space in which the eight structural parameters can be distributed evenly to reduce the calculation workload. The finite element method is used to model the mechanical responses of the steel bridge deck system. From the regression analysis by the RSM, the explicit relationships between the fatigue details and the design parameters can be obtained, based on which the nonlinear optimization design of the bridge deck system is conducted. The influence of constraint functions, objective functions, and optimization algorithms is also analyzed. The method proposed in this study is capable of considering the influence of different structural parameters and different optimization objectives according to the actual needs, which will effectively simplify the optimization design of the steel bridge deck system.

Origami has recently emerged as a promising building block of mechanical metamaterials because it offers a purely geometric design approach independent of scale and constituent material. The folding mechanics of origami-inspired metamaterials, i.e., whether the deformation involves only rotation of crease lines (rigid origami) or both crease rotation and facet distortion (nonrigid origami), is critical for fine-tuning their mechanical properties yet very difficult to determine for origami patterns with complex behaviors. Here, we characterize the folding of tubular waterbomb using a combined kinematic and structural analysis. We for the first time uncover that a waterbomb tube can undergo a mixed mode involving both rigid origami motion and nonrigid structural deformation, and the transition between them can lead to a substantial change in the stiffness. Furthermore, we derive theoretically the range of geometric parameters for the transition to occur, which paves the road to program the mechanical properties of the waterbomb pattern. We expect that such analysis and design approach will be applicable to more general origami patterns to create innovative programmable metamaterials, serving for a wide range of applications including aerospace systems, soft robotics, morphing structures, and medical devices.

Vanadium oxides have recently attracted widespread attention due to their unique advantages and have demonstrated promising chemical and physical properties for energy storage. This work develops a mild and efficient method to stereoassemble hollow V₂O₅@FeOOH heterostructured nanoflowers with thin nanosheets. These dual-phased architectures possess multiple lithiation voltage plateau and well-defined heterointerfaces facilitating efficient charge transfer, mass diffusion, and self-reconstruction with volumetric strain. As a proof of concept, the resulting V₂O₅@FeOOH hollow nanoflowers as an anode material for lithium-ion batteries (LIBs) realize high-specific capacities, long lifespans, and superior rate capabilities, e.g., maintaining a specific capacity as high as 985 mAh g⁻¹ at 200 mA g⁻¹ with good cyclability.

The recent outbreak of COVID-19 has been rapidly spreading on a global scale. To date, there is no specific vaccine against the causative virus, SARS-CoV-2, nor is there an effective medicine for treating COVID-19, thus raising concerns with respect to the effect of risk factors such as clinical course and pathophysiological parameters on disease severity and outcome in patients with COVID-19. By extracting and analyzing all available published clinical data, we identified several major clinical characteristics associated with increased disease severity and mortality among patients with COVID-19. Specifically, preexisting chronic conditions such as hypertension, cardiovascular disease, chronic kidney disease, and diabetes are strongly associated with an increased risk of developing severe COVID-19; surprisingly, however, we found no correlation between chronic liver disease and increased disease severity. In addition, we found that both acute cardiac injury and acute kidney injury are highly correlated with an increased risk of COVID-19-related mortality. Given the high risk of comorbidity and the high mortality rate associated with tissue damage, organ function should be monitored closely in patients diagnosed with COVID-19, and this approach should be included when establishing new guidelines for managing these high-risk patients. Moreover, additional clinical data are needed in order to determine whether a supportive therapy can help mitigate the development of severe, potentially fatal complications, and further studies are needed to identify the pathophysiology and the mechanism underlying this novel coronavirus-associated infectious disease. Taken together, these findings provide new insights regarding clinical strategies for improving the management and outcome of patients with COVID-19.

Realizing a high luminescence dissymmetry factor (g_{\text{lum}}) is a paramount yet challenging issue in the research field of circularly polarized luminescence (CPL). Here, we reported a novel set of organic conjugated systems with twisted intramolecular charge transfer (TICT) characteristics based on conjugated o-carborane-binaphthyl dyads composing of binaphthyl units as chiral electron donors and o-carborane units as achiral electron acceptors, demonstrating intense CPL with large g_{\text{lum}} values. Interestingly, single-crystalline o-1 exhibited a high-level brightness and a large g_{\text{lum}} factor as high as +0.13, whereas single-crystalline o-2 processed a relatively low brightness with a decreased g_{\text{lum}} value to -0.04. The significant diversity of CPL-active properties was triggered by the selective introduction of o-carborane units onto the binaphthyl units. Benefiting from the large magnetic dipole transition moments in TICT states, the CPL activity of TICT o-carborane-based materials exhibited amplified circular polarization. This study provides an efficient molecular engineering strategy for the rational design and development of highly efficient CPL-active materials.

Highly conductive topological semimetals with exotic electronic structures offer fertile ground for the investigation of the electrical and thermal transport behavior of quasiparticles. Here, we find that the layer-structured Dirac semimetal PtSn₄ exhibits a largely suppressed thermal conductivity under a magnetic field. At low temperatures, a dramatic decrease in the thermal conductivity of PtSn₄ by more than two orders of magnitude is obtained at 9 T. Moreover, PtSn₄ shows both strong longitudinal and transverse thermoelectric responses under a magnetic field. Large power factor and Nernst power factor of approximately 80–100  μW·cm^-1·K^-2 are obtained around 15 K in various magnetic fields. As a result, the thermoelectric figure of merit zT is strongly enhanced by more than 30 times, compared to that without a magnetic field. This work provides a paradigm for the decoupling of the electron and hole transport behavior of highly conductive topological semimetals and is helpful for developing topological semimetals for thermoelectric energy conversion.

Half-Heusler materials are strong candidates for thermoelectric applications due to their high weighted mobilities and power factors, which is known to be correlated to valley degeneracy in the electronic band structure. However, there are over 50 known semiconducting half-Heusler phases, and it is not clear how the chemical composition affects the electronic structure. While all the n-type electronic structures have their conduction band minimum at either the \Gamma- or X-point, there is more diversity in the p-type electronic structures, and the valence band maximum can be at either the \Gamma-, L-, or W-point. Here, we use high throughput computation and machine learning to compare the valence bands of known half-Heusler compounds and discover new chemical guidelines for promoting the highly degenerate W-point to the valence band maximum. We do this by constructing an “orbital phase diagram” to cluster the variety of electronic structures expressed by these phases into groups, based on the atomic orbitals that contribute most to their valence bands. Then, with the aid of machine learning, we develop new chemical rules that predict the location of the valence band maximum in each of the phases. These rules can be used to engineer band structures with band convergence and high valley degeneracy.

Cavitation and crazing in thermosetting polymers can be sophisticatedly designed for valuable applications in optics, electronics, and biotechnology. It is a great challenge for numerical study to describe the formations of cavity and fibrils in polymer composite due to the complicated interfacial interaction. To explore this challenging task, we exploit a two-phase coarse-grained framework which serves as an efficient atomistic level-consistent approach to expose and predict the transition between cavitation and crazing in a polymeric system. The coarse-grained framework is utilized to transmit the information between single phase and interface in polymer composite, and the learning tasks of force field are fulfilled through parameterization of mechanical performances and structural characterizations. We elaborate on the intrinsic characteristics of the cavitation-crazing transition in diamond nanothread- (DNT-) reinforced polymethyl methacrylate composites, in which DNT plays a specific role of nanomodulator to tune the cavity volume ratio. The transition from cavitation to crazing can be induced through a novel dissipative mechanism of opening an interlocked network, in which case the DNT is stretched to the aligned fibrils and links crazing tightly by interfacial adhesion. The designed computational framework can broaden the scope of theoretical tools for providing better insights into the microstructure design of polymer composites.