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• Effect of Y element on phase structure and electrochemical performance is studied. • Y improves volume match [A 2 B 4 ]/[AB 5 ] subunits and strengthens anti-pulverization. • Y increases long-term stability from 74.2 % to 78.5 % after cycling 300 times. La-Mg-Ni-based hydrogen storage alloys with superlattice structures are the new generation anode material for nickel metal hydride (Ni-MH) batteries owing to the advantages of high capacity and exceptional activation properties. However, the cycling stability is not currently satisfactory enough which plagues its application. Herein, a strategy of partially substituting La with the Y element is proposed to boost the capacity durability of La-Mg-Ni-based alloys. Furthermore, phase structure regulation is implemented simultaneously to obtain the A 5 B 19 -type alloy with good crystal stability specifically. It is found that Y promotes the phase formation of the Pr 5 Co 19 -type phase after annealing at 985 °C. The alloy containing Y contributes to the superior rate capability resulting from the promoted hydrogen diffusion rate. Notably, Y substitution enables strengthening the anti-pulverization ability of the alloy in terms of increasing the volume match between [A 2 B 4 ] and [AB 5 ] subunits, and effectively enhances the anti-corrosion ability of the alloy due to high electronegativity, realizing improved long-term cycling stability of the alloy from 74.2 % to 78.5 % after cycling 300 times. The work is expected to shed light on the composition and structure design of the La-Mg-Ni-based hydrogen storage alloy for Ni-MH batteries. [Display omitted] [ABSTRACT FROM AUTHOR]

The integration of phase change materials (PCMs) with planar multilayer structures, metasurfaces, waveguides, and photonic integrated circuits has triggered a technological revolution in nonvolatile tunable nanophotonic devices. The performance of devices is largely determined by PCMs, which is highly desired to have a high optical contrast and switchable capability. Here, we present a novel material platform based on Ge0.9 Sb0.1 Te suitable for nanophotonics applications across the entire visible spectral region. Ge0.9 Sb0.1 Te exhibits an optical contrast of up to 66%, significantly higher than that of the most widely reported Ge2Sb2Te5 (30%~35%) and GeTe (45%~50%). Through experiments and first-principles calculations, we reveal that this excellent performance originates from the unique solid-solution structure of crystalline Ge0.9 Sb0.1 Te, which combines high structural order with a narrow optical band gap. Using ultrafast laser induction technology, we demonstrate that the crystalline state of Ge0.9 Sb0.1 Te can be arbitrarily written and erased, achieving 16 distinct optical levels, which exceeds the 7 levels of Ge2Sb2Te5. In addition, we demonstrated grayscale lithography based on Ge0.9 Sb0.1 Te, proving that Ge0.9 Sb0.1 Te has a broad range of application potential as a visible reconfigurable nanophotonic platform.

Fiber-reinforced composites offer innovative solutions for architectural applications with high strength and low weight. Coreless filament winding extends industrial processes, reduces formwork, and allows for tailoring of fiber layups to specific requirements. A previously developed computational co-design framework for coreless filament winding is extended toward the integration of reciprocal design feedback to maximize design flexibility and inform design decisions throughout the process. A multi-scalar design representation is introduced, representing fiber structures at different levels of detail to generate feedback between computational design, engineering, and fabrication. Design methods for global, component, and material systems are outlined and feedback generation is explained. Structural and fabrication feedback are classified, and their integration is described in detail. This paper demonstrates how reciprocal feedback allows for co-evolution of domains of expertise and extends the existing co-design framework toward design problems. The developed methods are shown in two case studies at a global and component scale.Graphical Abstract

High-resolution and high-squint spaceborne synthetic aperture radar (SAR) system has excellent earth observation performance. However, high-squint spaceborne SAR data is more challenging to process than the general broadside counterpart because of the severe range-azimuth coupling (RAC). Whereas the classic linear range walk correction (LRWC) method can handle this problem, it is performed in azimuth time-domain and seriously constrains azimuth swath width. In this article, a decoupled hybrid correlation Algorithm (DHCA), combining the range-azimuth decoupling (RAD) in 2-D frequency domain with the modified hybrid correlation (MHC), is proposed to handle sliding spotlight spaceborne SAR data of high-squint angle case. The decoupled hybrid correlation (DHC) is the main body of the proposed algorithm, and it starts with RAD filtering in 2-D frequency domain, which is designed to eliminate the majority of the range cell migration (RCM) and RAC caused by high-squint angles. A nonlinear chirp scaling (NLCS) in range direction is subsequently performed to equalize the variant range chirp rate caused by residual RCM and RAC. Coarse range compression can then be realized uniformly by the range-matched filtering. The NLCS operation and range coarse compression ensure that the range-Doppler (RD) signals of all targets within the whole scene occupy very narrow range cell scopes. By making full use of the principle of stationary point (POSP) to signals, the range compression position and range frequency mapping relationship after NLCS can be derived. The MHC can therefore be fulfilled by extracting the RD signals along the residual RCM and constructing the reference correlation function after the range NLCS. Thus, both the efficiency and the accuracy of focusing processing are guaranteed. Simulations are carried out to validate the proposed algorithm.

Sketch face recognition has recently gained significant attention in the field of computer vision due to its ability to quickly identify matched pairs of optical and sketch images. This technology has the potential to greatly improve the efficiency of law enforcement agencies in criminal investigations. However, there are still challenges that need to be addressed in sketch face recognition algorithms, such as modal differences and limited sample sizes. To overcome these issues, this study proposes a Residual Serialized Cross Grouping Transformer (RSCGT), which contains a residual serialized module to reduce the computation complexity, a two-layer Cross Grouping Transformer module that is capable of extracting modality-invariant context features, a domain adaptive module to mitigate the impact of modal differences. Additionally, we introduce a meta-learning training strategy to augment the generalization ability of this model. Experimental results demonstrate that the RSCGT achieves high accuracy in sketch face recognition tasks, even with small-scale datasets.

Sketch face recognition has a wide range of applications in criminal investigation, but it remains a challenging task due to the small‐scale sample and the semantic deficiencies caused by cross‐modality differences. The authors propose a light semantic Transformer network to extract and model the semantic information of cross‐modality images. First, the authors employ a meta‐learning training strategy to obtain task‐related training samples to solve the small sample problem. Then to solve the contradiction between the high complexity of the Transformer and the small sample problem of sketch face recognition, the authors build the light semantic transformer network by proposing a hierarchical group linear transformation and introducing parameter sharing, which can extract highly discriminative semantic features on small–scale datasets. Finally, the authors propose a domain‐adaptive focal loss to reduce the cross‐modality differences between sketches and photos and improve the training effect of the light semantic Transformer network. Extensive experiments have shown that the features extracted by the proposed method have significant discriminative effects. The authors’ method improves the recognition rate by 7.6% on the UoM‐SGFSv2 dataset, and the recognition rate reaches 92.59% on the CUFSF dataset. First, the authors employ the meta‐learning training strategy to obtain task‐related training samples to solve the small sample problem. To solve the contradiction between the high complexity of the Transformer and the small sample problem of sketch face recognition, the authors then build the light semantic Transformer network by introducing hierarchical group linear transformation and parameter sharing, which can extract highly discriminative semantic features on small datasets. Finally, the authors propose domain‐adaptive focal loss to reduce cross‐modality differences between sketches and photos and improve the training effect of the light semantic Transformer network.

Soft nanoporous crystals with structural dynamics are among the most exciting recently discovered materials. However, designing or controlling a porous system with delicate softness that can recognize similar gas pairs, particularly for the promoted ability at increased temperature, remains a challenge. Here, we report a soft crystal (NTU-68) with a one-dimensional (1D) channel that expands and contracts delicately around 4 Å at elevated temperature. The completely different adsorption processes of propane (C3H8: kinetic dominance) and propylene (C3H6: thermodynamic preference) allow the crystal to show a sieving separation of this mixtures (9.9 min·g–1) at 273 K, and the performance increases more than 2-fold (20.4 min·g–1) at 298 K. This phenomenon is contrary to the general observation for adsorption separation: the higher the temperature, the lower the efficiency. Gas-loaded in situ powder X-ray analysis and modeling calculations reveal that slight pore expansion caused by the increased temperature provides plausible nanochannel for adsorption of the relatively smaller C3H6while maintaining constriction on the larger C3H8. In addition, the separation process remains unaffected by the general impurities, demonstrating its true potential as an alternative sorbent for practical applications. Moving forward, the delicate crystal dynamics and promoted capability for molecular recognition provide a new route for the design of next-generation sieve materials.

Maize (Zea maysL.) is an important food crop in the world. Reasonably increasing planting density is an important way to increase maize yield. Test weight (TW) determines the classification and affects market price. In order to clarify the influence and mechanism of planting density on TW, in this study, a 2‐year field experiment was carried out in Tongliao, Inner Mongolia Autonomous Region in 2019 and 2020. Four widely planted maize hybrids and six planting densities (6.0, 7.5, 9.0, 10.5, 12.0, and 13.5 × 104plants ha−1) were tested, using drip irrigation water and fertilizer integration. The output parameters measured were grain yield, TW, thousand‐kernel weight (TKW), kernel volume, kernel density (KD), kernels per unit volume (KPV), and kernel packing efficiency. The result showed that yields ranged from 12.04 to 16.58 ton ha−1and TW ranged from 751 to 807 kg m−3, which exceeded the requirements for classification as first‐grade maize (720 kg m−3). Both yield and TW have a quadratic curve relationship with planting density, but the planting density corresponding to the two indicators is different when they reach the maximum value. With the increase in planting density, the TKW decreased and KPV increased, which made the relationship between TW(y) and planting density (x) and expressed as y= ax2+ bx+ c. Planting density had a significant influence on TW and the relationship between TW and planting density was consistent under growth years and maize varieties. Considering the economic benefits, the planting density corresponding to the maximum yield is strongly recommended for future maize production. Both yield and test weight of maize have a quadratic curve relationship with planting density.Decreased thousand‐kernel weight (TKW) and increased kernels per unit volume (KPV) cause test weight (TW) to vary with increasing planting density.Growing maize at the planting density corresponding to the highest yield can achieve the greatest benefits.

Analog in-memory computing (AiMC) reduces the cost of data transfer by processing data inside memory. Compared with other emerging nonvolatile memories, AiMC with magnetic random access memory (MRAM) shows potential with logic-compatible supply voltage, small variability issues, and high endurance. However, the analog output of the array must be converted to digital using an analog-to-digital converter (ADC), which significantly offsets the benefits of AiMC. This article presents power-aware quantization circuits in AiMC with spin transfer torque MRAM (STT-MRAM) macro, in which a successive approximation register (SAR) ADC with reconfigurable 3/4 bit resolution and 250 MS/s sampling rate addresses the need for high speed and low power for AiMC. By using a 28 nm CMOS process, simulation results show that the proposed ADC consumes only $31.6 ~\mu \text{W}$ at a 900 mV supply and 250 MS/s. A 10.4–25.7 TOPS/W is realized with 2 bit input, 1 bit weight, and 4 bit output convolution neural network (CNN).

The linear design workflow for structural systems, involving a multitude of iterative loops and specialists, obstructs disruptive innovations. During design iterations, vast amounts of data in different reference systems, origins, and significance are generated. This data is often not directly comparable or is not collected at all, which implies a great unused potential for advancements in the process. In this paper, a novel workflow to process and analyse the data sets in a unified reference frame is proposed. From this, differently sophisticated iteration loops can be derived. The developed methods are presented within a case study using coreless filament winding as an exemplary fabrication process within an architectural context. This additive manufacturing process, using fiber-reinforced plastics, exhibits great potential for efficient structures when its intrinsic parameter variations can be minimized. The presented method aims to make data sets comparable by identifying the steps each data set needs to undergo (acquisition, pre-processing, mapping, post-processing, analysis, and evaluation). These processes are imperative to provide the means to find domain interrelations, which in the future can provide quantitative results that will help to inform the design process, making it more reliable, and allowing for the reduction of safety factors. The results of the case study demonstrate the data set processes, proving the necessity of these methods for the comprehensive inter-domain data comparison.Graphical Abstract

The precise regulation of the electron-withdrawing/electron-donating strength in a probe is of great significance for the design of reaction-based fluorescent probes with specific functionalities. Here, a family of excited-state intramolecular proton transfer (ESIPT)-based probes with fluorescence turn-on sensing properties toward KMnO4was designed by precisely modulating the electron-withdrawing strength of the substituents located at the para-position of the recognition group. It is found that −F, −CHO, and −H as the electron-withdrawing groups bound at the probe can specifically recognize KMnO4, which ensures a blue emission displayed by the reaction products. Especially with −CHO as the electron-withdrawing group, the reaction product shows the most stable fluorescence. The probe 2-(benzo[d]oxazol-2-yl)-4-formylphenyl acrylate (BOPA-CHO) demonstrated a more superior sensing performance toward KMnO4, including a low limit of detection (LOD, 0.96 nM), a rapid response (<3 s), and a rather good selectivity even in the presence of 21 interferents. Moreover, the practicality of the probe was further verified by a test pen comprising a BOPA-CHO-embedded sponge, which is capable of detecting KMnO4solid with a naked-eye LOD of 11.62 ng. The present probe design and modulation strategy would open up a new path for the design of high-performance fluorescent probes.

Metal–organic framework (MOF) membranes are energy-efficient candidates for molecular separations, but it remains a considerable challenge to eliminate defects at the atomic scale. The enlargement of pores due to defects reduces the molecular-sieving performance in separations and hampers the wider application of MOF membranes, especially for liquid separations, owing to insufficient stability. Here we report the elimination of lattice defects in MOF membranes based on a high-probability theoretical coordination strategy that creates sufficient chemical potential to overcome the steric hindrance that occurs when completely connecting ligands to metal clusters. Lattice defect elimination is observed by real-space high-resolution transmission electron microscopy and studied with a mathematical model and density functional theory calculations. This leads to a family of high-connectivity MOF membranes that possess ångström-sized lattice apertures that realize high and stable separation performance for gases, water desalination and an organic solvent azeotrope. Our strategy could enable a platform for the regulation of nanoconfined molecular transport in MOF pores.

In recent years, sketch face recognition has a wide application in law enforcement agencies and criminals. Deep learning plays a crucial role in the recent developments of face recognition, however, it is challenging to employ deep learning methods for sketch face recognition due to insufficient face photo–sketch data. Moreover, compared to photos, sketches lack detailed texture, and there exists a domain gap between photos and sketches, hence, traditional homogeneous face recognition methods perform poorly in sketch face recognition. In this paper, a novel deep learning method termed Domain Adaptation Scaled Entropy Meta-Network (DASEMN) is proposed to tackle sketch face recognition tasks. Specifically, a meta-learning training strategy is designed to tackle the few-shot problem and improve the generalization ability of the network. Then, a generalized entropy loss termed scaled mean entropy loss is proposed to guide the network to extract discriminate features. Finally, a domain adaptation module is introduced in the training set to reduce the domain gap between the sketch domain and the photo domain. Experiments on UoM-SGFS and CUFSF sketch face databases show that the proposed method is superior to other sketch face recognition methods.

Rowhammer Attack, a new DRAM-based attack, was developed exploiting weak cells to alter their content. Such attacks can be launched at the user level without requiring access permission to the victim memory cells. Leveraging such attacks, a new bit-flip-based adversarial weights attack (BFA) was developed targeting deep neural network models. When BFA attackers acquire a DNN model, they manipulate the existing DNN adversarial attack into locating vulnerable bits in the target DNN model. By flipping a subset of them using Rowhammer, they can crash that model within 30 trails. In this paper, we propose a lightweight and easy-to-deploy defense mechanism in the bit-level, Randomized Rotated and Nonlinear Encoding (RREC), which generates both robustness and fault-tolerant against BFA. Since flipping the most significant bit (MSB) in quantized data is too dangerous, we introduce randomized Rotation to obfuscate the bit order of model data and efficiently hide truly vulnerable bits with less vulnerable ones. Further, RREC reduces the average bit-flipped distance by more than 3x from the nonlinear encoding. It decreases the bit-flip distance among the majority of bits (including those vulnerable bits). Theoretically, RREC minimized the impact of a single bit BFA to 1/24 compared with baseline. Experimentally, RREC tolerates more than 17x flipped bits versus baseline model and 4.8x and 5.7x more bits compared with the existing BFA defenses (4B QAT and WR) with 0.01x to 0.08x of runtime latency. Moreover, we evaluate RREC against a newly emerged attack, Targeted-BFA, and it improves the defense rate from $5\%$5% to $95\%$95%.

The capability to work on the high-squint mode brings great advantages to the synthetic aperture radar (SAR) system. However, the efficient imaging of the high-squint SAR data has not been well settled. Due to the severe range-azimuth coupling (RAC), the conventional imaging algorithms fail to work properly in high-squint cases. In this article, a decoupled chirp scaling algorithm (DCSA) is proposed for high-squint SAR data imaging, whose key step is a range-azimuth decoupling (RAD) preprocessing in the 2-D frequency domain. After RAD, the majority of the RAC is eliminated, where the high-squint SAR data are simplified into the quasi-broadside mode. The data can be then processed via the chirp-scaling-typed scheme, which is summarized as follows. The data after RAD are first transformed into the range-Doppler (RD) domain, in which a nonlinear chirp scaling (NLCS) is performed in the range direction to eliminate the chirp rate variations caused by the residual RAC. The chirp scaling processing is simultaneously performed to equalize the range cell migrations (RCMs) for the full scene data. The range compression, bulk RCM correction, and compensation for the cubic and quartic phases introduced by the NLCS are then accomplished in the 2-D frequency domain. Finally, the azimuth compensation is accomplished in the RD domain to obtain the final focused SAR image. Different from the linear range walk correction (LRWC) accomplished in the azimuth time domain, the RAD method proposed here does not destroy the azimuth-invariant property of the SAR echoes. Therefore, the DCSA can adapt to the wide swath SAR data imaging. Simulation shows that, for the airborne SAR with 1-m resolution in both range and azimuth directions, and a squint angle of 45°, the DCSA can achieve the bulk focusing of the full-scene data with a range swath of 10 km, whereas the azimuth swath is not limited. Compared with the classical CSA, the DCSA requires only one more range fast Fourier transform (FFT)/inverse FFT (IFFT) and one more complex matrix multiplication, which is, therefore, timely and very efficient.

Landfilling is the main method used for garbage disposal, but landfill leachate can affect groundwater quality. To study the influence of landfill leachate on groundwater, 6 monitoring wells and 14 domestic wells in and around the Jiangcungou landfill site in northwest China were sampled. Groundwater chemistry characteristics were analyzed, and water quality and health risks were assessed. Saturation index and correlation analysis were used to identify the sources of major ions, and the hydrogeochemical mechanism controlling characteristic contaminants was analyzed. The result of single-factor water quality evaluation showed that 35% of groundwater samples had at least one indicator exceeding the drinking water standards. It was confirmed that the landfill had an impact on groundwater, as the average pollution index of the monitoring wells (0.72) was significantly higher than that of the domestic wells (0.31). The major characteristic pollutants were iron (Fe), manganese (Mn), arsenic (As) and fluoride (F−), and their average pollution indices were 12.91, 1.78, 1.1, and 2.47, respectively. The average non-carcinogenic health risks of F−, NO3−and As were 0.96, 0.58, and 0.42, respectively, while the average carcinogenic risk for arsenic was 1.90E−04. The landfill is in the methane production stage, resulting in a reducing redox environment. Among the four characteristic pollutants, Fe and Mn resulted mainly from the landfill, while As and F−were affected by the landfill as well as slow groundwater flow and other human activities. Necessary measures were also proposed to prevent groundwater pollution in and around the landfill.

The artificial ammonia synthesis via electrochemical nitrate reduction has met increasing research interest, but it is still necessary to develop advanced catalysts with high nitrate-to-ammonia capability. Herein, we propose and demonstrate a one-step method to construct binder-free Cu foam-supported oxygen vacancy-rich Cu/CuOxin-plane heterostructured nanosheet arrays (Cu/CuOx/CF). In addition to exposing ample active sites, the two-dimensional nanosheet morphology greatly facilitates the mass/charge-transfer process during electrocatalysis. Besides, the in-plane heterojunctions and rich oxygen vacancies induced synergistic effect can modulate the electronic structure of active sites and thus tune the adsorption properties of the reactant intermediates and inhibit the formation of undesirable byproducts, which is conducive to the further improvement of nitrate reduction activity. As a result, these advantages endow the Cu/CuOx/CF with superior performance for ammonia synthesis via nitrate electroreduction, achieving high ammonia selectivity (95.00%) and Faradaic efficiency (93.58%).

In this study, 419 water samples were collected from 47 river sections during January to September in 2019 for the assessment of the surface water quality in Taizhou City. Hierarchical cluster analysis was used to group water samples for further water quality analysis. Water quality was evaluated based on the water quality identification index. Seven water quality indicators including copper, fluoride, arsenic, cyanide, mercury, hexavalent chromium and zinc were selected to evaluate the potential non-carcinogenic risk and carcinogenic risk to the people who use the surface water for domestic purpose in Taizhou City. The results indicate that nitrogen pollution is serious in some locations. According to the water quality assessment results, 74.46% of the surface water samples have excellent and good quality, and 23.87% of the samples are rated as poor or extremely poor water. Surface water in the districts of Wenling, Jiaojiang and Luqiao poses an unacceptable non-carcinogenic risk to humans through drinking water intake and skin contact, while in other districts of the city the non-carcinogenic risk is acceptable. In addition, people in Taizhou City face a potential carcinogenic risk. Arsenic is the major chemical carcinogen in the area responsible for the potential carcinogenic health risk, and it should be treated before used for domestic purpose.

Supplemental Digital Content is available in the text.

We study the self-frequency shift of continuously pumped Kerr solitons in AlN-on-sapphire microcavities with Raman gain bandwidths narrower than the cavity free-spectral range. Solitons are generated in ∼230GHz microcavities via high-order mode dispersion engineering. The dependence of the self-frequency shift on soliton pulse width is measured and differs from amorphous material microcavities. Our measurement and simulation reveal the impact of frequency detuning between the cavity resonances and Raman gain peaks, as well as the importance of all three Raman gain peaks. The interplay between the Raman effect and dispersive wave recoil and a potential quiet point are also observed.

How is social etiquette performed when offline interpersonal interactions are mediated online? Sixty semi‐structured interviews with WeChat users, China's most popular social media platform, show that the app's technical designs facilitated a set of online etiquette rules which reproduced those of acquaintance communities. Three dimensions of social etiquette rules were considered and observed: respect, elegance, and tidiness. Users honored the face of others and avoided causing others to lose face, often presented a positive but restrained self‐image, and strived to preserve the tidiness of the online public space by avoiding the sharing of and exposing others to “negative energy.” A video abstract is available at https://youtu.be/2tG40y8J11E.

Monocyte chemoattractant protein-1 induced protein 1 (MCPIP1), one of the MCPIP family members, is characterized by the presence of both C-x8-C-x5-C-x3-H (CCCH)- type zinc finger and PilT-N-terminal domains. As a potent regulator of innate immunity, MCPIP1 exerts anti-inflammatory effects through its ribonuclease (RNase) and deubiquitinating enzyme activities to degrade cytokine mRNAs and inhibit nuclear factor- kappa B (NF-ΚB), respectively. MCPIP1 is expressed not only in immune cells but also in many other cell types, including cardiomyocytes, vascular endothelial cells (ECs) and smooth muscle cells (SMCs). Increasing evidence indicates that MCPIP1 plays a role in the regulation of cardiac functions and is involved in the processes of vascular diseases, such as ischemia-reperfusion (I/R) and atherosclerosis. To better understand the emerging roles of MCPIP1 in the cardiovascular system, we reviewed the current literature with respect to MCPIP1 functions and discussed its association with the pathogenesis of cardiovascular diseases and the implication as a therapeutic target.

The formation of wurtzite (WZ) phase in III–V nanowires (NWs) such as GaAs and InP is a complication hindering the growth of pure-phase NWs, but it can also be exploited to form NW homostructures consisting of alternate zincblende (ZB) and WZ segments. This leads to different forms of nanostructures, such as crystal-phase superlattices and quantum dots. Here, we investigate the electronic properties of the simplest, yet challenging, of such homostructures: InP NWs with a single homojunction between pure ZB and WZ segments. Polarization-resolved microphotoluminescence (μ-PL) measurements on single NWs provide a tool to gain insights into the interplay between NW geometry and crystal phase. We also exploit this homostructure to simultaneously measure effective masses of charge carriers and excitons in ZB and WZ InP NWs, reliably. Magneto-μ-PL measurements carried out on individual NWs up to 29 T at 77 K allow us to determine the free exciton reduced masses of the ZB and WZ crystal phases, showing the heavier character of the WZ phase, and to deduce the effective mass of electrons in ZB InP NWs (me= 0.080 m0). Finally, we obtain the reduced mass of light-hole excitons in WZ InP by probing the second optically permitted transition Γ7C↔ Γ7uVwith magneto-μ-PL measurements carried out at room temperature. This information is used to extract the experimental light-hole effective mass in WZ InP, which is found to be mlh= 0.26 m0, a value much smaller than the one of the heavy hole mass. Besides being a valuable test for band structure calculations, the knowledge of carrier masses in WZ and ZB InP is important in view of the optimization of the efficiency of solar cells, which is one of the main applications of InP NWs.

Percutaneous coronary intervention is a well-established technique used to treat coronary artery disease, but the risk of coronary artery in-stent restenosis following percutaneous coronary intervention is still high. Previous studies revealed that high mobility group protein B1 (HMGB1) plays a critical role in neointima formation. In this study, we aimed to investigate the role of glycyrrhizic acid (GA), an HMGB1 inhibitor, in the process of neointima formation and the potential mechanisms. We investigated the role of GA in neointima formation through an iliac artery balloon injury model in rabbits. Proliferation, migration, and phenotype transformation of human vascular smooth muscle cells (VSMCs) were observed. Besides, inflammation and receptor for advanced glycosylation end products (RAGE) signaling pathways were studied. The results indicate that GA attenuated neointima formation and downregulated HMGB1 expression in injured artery in rabbits. HMGB1 promoted proliferation, migration, and phenotype transformation through the activation of RAGE signaling pathways in VSMCs, and blockade of HMGB1 by GA (1, 10, and 100 μM) could attenuate those processes and reduce proliferation of human VSMCs. In conclusion, the HMGB1 inhibitor GA might be useful to treat proliferative vascular diseases by downregulating RAGE signaling pathways. Our results indicate a new and promising therapeutic agent for restenosis.

The efficient separation of photoexcited electrons and holes is crucial for improving the activity of photocatalytic hydrogen evolution. Herein, an efficient core–shell p–n heterojunction of ZnIn2S4@CuInS2microflowers has been devised and fabricated by two-step hydrothermal method. The results revealed that the marigold-like microspheres of ZnIn2S4@CuInS2heterojunction consisted of thin nanosheets, matched well in the lattice, and had a large interface contact area, which boosted charge separation and transfer for solar hydrogen production. Moreover, the intimate interfacial contact between n-type ZnIn2S4and p-type CuInS2resulted in the formation of unique p–n heterojunction, which further promoted charge separation due to the built-in electric field. As a consequence, the ZnIn2S4@CuInS2photocatalyst with 5 atom % CuInS2showed the highest production of H2evolution (about 1168 μmol·g–1) among all prepared photocatalysts, which was nearly 4-fold the amount of the hydrogen production for the pristine ZnIn2S4. Therefore, the core–shell p–n heterojunction is an efficient structure design for the utilization of solar energy to obtain clean energy.

High-quality pure acetylene (C2H2) is a kind of crucial starting material for various value-added products. However, selective capture of C2H2from the main impurity of CO2via porous absorbents is a great challenge, as they possess extremely similar kinetic diameters and boiling points, as well as the explosive and reactive properties of C2H2. Herein, we report a porous coordination polymer (PCP), (NTU-55), which assembled from the coordination between a Cu dimer and a newly designed ligand with a nonmetal selenium (Se) site. Static single-component adsorption and dynamic breakthrough experiments reveal that desolvated NTU-55can completely adsorb C2H2from the C2H2/CO2mixture (1/4, v/v) at 298 K, along with higher C2H2capacity and much lower binding energy. The origin of this separation, as comprehensively revealed by density functional theory (DFT) calculations, is derived from the interaction discriminatory of C2H2and CO2toward accessible Se and Cu adsorption sites. To the best of our knowledge, this is the first time to find the positive effect of nonmetal Se sites for selective C2H2capture.

The dependence of the performance of ultraviolet‐C (UV‐C) laser diodes on the strain relaxation of lower cladding layer (LCL) is numerically investigated. As the strain relaxation increases from 0% to 100%, the threshold current density decreases from 25 to 12.7 kA cm−2, and the slope efficiency increases from 0.039 to 0.087 W A−1, thanks to an increase in internal quantum efficiency (IQE). The improvement of IQE is mainly due to the enhanced hole injection resulting from the increased hole concentration in the distributed polarization doping layers and the reduced hole blocking barrier height of the upper waveguide layer with increasing the strain relaxation. Additionally, the effective screening of the polarization field within the quantum well ameliorates the quantum‐confined Stark effect, further improving the IQE. Our study reveals that strain relaxed LCL is imperative to achieve low‐threshold UV‐C laser diodes. Performance of ultraviolet‐C laser diodes improves remarkably by using the highly relaxed lower cladding layer. Higher in‐plane strain value improves hole concentration in the polarization‐doped cladding layer. Lower hole blocking barrier height of the waveguide layer enhances hole transport. The enhanced hole injection and the consequential weaken quantum‐confined Stark effect increase the internal quantum efficiency and reduce the threshold current.

Piezocatalysis, an emerging green and advanced oxidation technology, has recently been widely researched in environmental treatment. However, the limited polarization efficiency of the piezocatalyst is a serious bottleneck for its practical application. The search for an excellent piezocatalyst with a high piezoelectric coefficient and abundant reactive sites remains an urgent task that needs to be developed. Herein, a piezocatalyst, CaZn2(BO3)2(CZBO), obtained by quenching has an excellent piezocatalysis, which exhibited superior activity for ibuprofen (IBP) and carbamazepine (CBZ) removal with 100% and 83.8% efficiency under ultrasonic cavitation (120 W, 40 kHz) within 36 min, respectively. The outstanding piezocatalytic degradation was attributed to the strong polarization of the material under the synergistic effect of oxygen vacancies (OVs) and lattice distortion, which effectively facilitated the generation of a high concentration of reactive oxygen species (ROS). The lattice distortion induced by O-deficient [BO3] plane units can promote the e–and h+pair separation and transportation, and the OVs with abundant electron-rich regions can significantly decrease O–O bond activation energy, thus collaboratively contributing to the high production of ROS for IBP and CBZ degradation. This work provides a simple avenue for enhancing piezoelectric polarization based on the OVs and lattice distortion and proposes insights into the reaction mechanisms for degrading nonantibiotic pharmaceuticals in wastewater.

•Spatial targeting methods of Payment for Ecosystem Services (PES) were reviewed.•Cost-benefit analysis is the most widely applied method at different spatial scales.•Multi-objective optimization and data envelope analysis are also commonly used.•Advantages, limitations, and application conditions of these methods were compared.•Combined application of different methods needs to be considered in future research.

The interaction between graphene oxide (GO) in solvent is a fundamental basis in its colloidal suspensible stabilization, which is important in the solution processing technique for the preparation of processable graphene sheets. In this work, the potential of mean force (PMF) between two GO nanosheets in solvents was simulated to quantify the interaction mechanism. It was observed that GO sheets in water with various oxidization levels demonstrate diverse interacting performances. The neutral GO sheets generally show weak attractive interaction with kinetic reversible aggregating/dispersing stability. However, the deprotonated GO sheets with negative charges have strong colloidal stability, which is due to the long-range electrostatic repulsion arising from the charged functional groups. The interaction of GO sheets is a delicate balance of the interacting force between GOs themselves and the corresponding solvation force. The detailed PMF analysis identifies the distinct roles of water in the contribution to GO interactions. For neutral GO sheets, the solvation force provides repulsive action, aiding the GO dispersion. However, for the negatively charged GO sheets, the solvation force contrarily exhibits attractive hydrophilic interaction due to the strong water affinity of deprotonated carboxyl groups. In the nonpolar benzene solvent, the PMF profile displays strong aggregation trend compared with the water solvent. The solvation force in benzene solvent could not afford sufficient repulsive interaction to overcome the attractive interaction between GO sheets. This behavior reflects the specific effect of benzene solvent on functional groups. Our simulation results present new a molecular-level understanding of GO interactions in solvents.

The ability to tune the polymorph and crystal orientation of semiconducting conjugated polymers provides a powerful platform for revealing processing–structure–property relationships. In contrast to the widely studied poly(3-alkylthiophene)s, their close poly(3-alkylselenophene) analogs have been much less studied. Herein, we report tailoring the polymorphs and crystal orientations in poly(3-hexylselenophene) (P3HS) of different molecular weights (MWs) via rubbing and elucidate the relationships between the crystalline structure and charge transfer characteristics for organic field-effect transistors (OFETs). In particular, the as-cast P3HS-3K film exhibits polymorph II with a dominant flat-on crystal orientation; however, it transforms into polymorph I with a face-on crystal orientation upon rubbing at elevated temperatures. Moreover, the as-cast P3HS-22K film transitions from edge-on to face-on with its polymorph I retained throughout the rubbing process. The polymorph and crystal orientation transitions in the P3HS-3K and 22K systems are accompanied by the formation of large-scale highly aligned crystalline films along the rubbing direction. The polymorph transformation kinetics during the rubbing process and associated alterations in the crystalline packing and photophysical properties are investigated. The various P3HS films exhibit OFET performance that shows a strong relationship with the attained crystalline structures. Such polymorph and crystal orientation transformations involving the rubbing technique are readily applied to other conjugated polymers in interest. This research emphasizes tailoring the crystalline structures and, thus, the charge transfer characteristics of conjugated polymers, which advances their use in optoelectronic-device applications.