Core-Shell Semiconductor-Graphene Nanoarchitectures for Efficient Photocatalysis:State of the Art and Perspectives

Semiconductor photocatalysis holds great promise for renewable energy generation and environment remediation,but generally suffers from the serious drawbacks on light absorption,charge generation and transport,and structural stability that limit the performance.The core-shell semiconductorgraphene(CSSG)nanoarchitectures may address these issues due to their unique structures with exceptional physical and chemical properties.This review explores recent advances of the CSSG nanoarchitectures in the photocatalytic performance.It starts with the classification of the CSSG nanoarchitectures by the dimensionality.Then,the construction methods under internal and external driving forces were introduced and compared with each other.Afterward,the physicochemical properties and photocatalytic applications of these nanoarchitectures were discussed,with a focus on their role in photocatalysis.It ends with a summary and some perspectives on future development of the CSSG nanoarchitectures toward highly efficient photocatalysts with extensive application.By harnessing the synergistic capabilities of the CSSG architectures,we aim to address pressing environmental and energy challenges and drive scientific progress in these fields.

Advances in magnetic-assisted triboelectric nanogenerators:structures,materials and self-sensing systems

Triboelectric nanogenerators(TENG),renowned for their remarkable capability to harness weak mechanical energy from the environment,have gained considerable attention owing to their cost-effectiveness,high output,and adaptability.This review provides a unique perspective by conducting a comprehensive and in-depth analysis of magnetically assisted TENGs that encompass structures,materials,and self-powered sensing systems.We systematically summarize the diverse functions of the magnetic assistance for TENGs,including system stiffness,components of the hybrid electromagnetic-triboelectric generator,transmission,and interaction forces.In the material domain,we review the incorporation of magnetic nano-composites materials,along with ferrofluid-based TENG and microstructure verification,which have also been summarized based on existing research.Furthermore,we delve into the research progress on physical quantity sensing and human-machine interface in magnetic-assisted TENGs.Our analysis highlights that magnetic assistance extends beyond the repulsive and suction forces under a magnetic field,thereby playing multifaceted roles in improving the output performance and environmental adaptability of the TENGs.Finally,we present the prevailing challenges and offer insights into the future trajectory of the magnetic-assisted TENGs development.

Multimodality imaging in nanomedicine and nanotheranostics

Accurate diagnosis of tumors needs much detailed information. However, available single imaging modality cannot provide complete or comprehensive data. Nanomedicine is the application of nanotechnology to medicine, and multimodality imaging based on nanoparticles has been receiving extensive attention. This new hybrid imaging technology could provide complementary information from different imaging modalities using only a single injection of contrast agent. In this review, we introduce recent developments in multifunctional nanoparticles and their biomedical applications to multimodal imaging and theragnosis as nanomedicine. Most of the reviewed studies are based on the intrinsic properties of nanoparticles and their application in clinical imaging technology. The imaging techniques include positron emission tomography, single-photon emission computed tomography, computerized tomography, magnetic resonance imaging, optical imaging, and ultrasound imaging.

Light-Responsive Nanomaterials for Cancer Therapy

Due to its unique advantages,which include minimal invasiveness and relative clinical safety,photother-apy is considered to be a promising approach for cancer treatment.However,the treatment efficacy of phototherapy is often restricted by the limited depth of light penetration and the low targeting effect of phototherapeutic agents.The emergence of light-responsive nanomaterials offers a possible approach to achieve enhanced phototherapy potency.This review summarizes the progress in biomedical applica-tions of light-responsive nanomaterials for cancer therapy,which include photothermal therapy(PTT),photodynamic therapy(PDT),light-responsive molecule delivery,and light-controlled combination ther-apy.Future prospects are also discussed.This review aims to demonstrate the significance of light-responsive nanomaterials in cancer therapy and to provide strategies to expand the applications of phototherapy.

Direct-Ink-Writing Printed Strain Rosette Sensor Array with Optimized Circuit Layout

The full-field multiaxial strain measurement is highly desired for application of structural monitoring but still challenging,especially when the manufacturing and assembling for largearea sensing devices is quite difficult.Compared with the traditional procedure of gluing commercial strain gauges on the structure surfaces for strain monitoring,the recently developed Direct-Ink-Writing(DIW)technology provides a feasible way to directly print sensors on the structure.However,there are still crucial issues in the design and printing strategies to be probed and improved.Therefore,in this work,we propose an integrated strategy from layered circuit scheme to rapid manufacturing of strain rosette sensor array based on the DIW technology.Benefit from the innovative design with simplified circuit layout and the advantages of DIW for printing multilayer structures,here we achieve optimization design principle for strain rosette sensor array with scalable circuit layout,which enable a hierarchical printing strategy for multiaxial strain monitoring in large scale or multiple domains.The strategy is highly expected to adapt for the emerging requirement in various applications such as integrated soft electronics,nondestructive testing and small-batch medical devices.

Deep-ultraviolet photonics for the disinfection of SARS-CoV-2 and its variants(Delta and Omicron)in the cryogenic environment

Deep-ultraviolet(DUV)disinfection technology provides an expeditious and efficient way to suppress the transmission of coronavirus disease 2019(COVID-19).However,the influences of viral variants(Delta and Omicron)and low temperatures on the DUV virucidal efficacy are still unknown.Here,we developed a reliable and uniform planar light source comprised of 275-nm light-emitting diodes(LEDs)to investigate the effects of these two unknown factors and delineated the principle behind different disinfection performances.We found the lethal effect of DUV at the same radiation dose was reduced by the cryogenic environment,and a negative-U large-relaxation model was used to explain the difference in view of the photoelectronic nature.The chances were higher in the cryogenic environment for the capture of excited electrons within active genetic molecules back to the initial photo-ionised positions.Additionally,the variant of Omicron required a significantly higher DUV dose to achieve the same virucidal efficacy,and this was thanks to the genetic and proteinic characteristics of the Omicron.The findings in this study are important for human society using DUV disinfection in cold conditions(e.g.,the food cold chain logistics and the open air in winter),and the relevant DUV disinfection suggestion against COVID-19 is provided.

Electronic and thermal properties of Ag-doped single crystal zinc oxide via laser-induced technique

The doping of ZnO has attracted lots of attention because it is an important way to tune the properties of ZnO.Postdoping after growth is one of the efficient strategies.Here,we report a unique approach to successfully dope the single crystalline ZnO with Ag by the laser-induced method,which can effectively further post-treat grown samples.Magnetron sputtering was used to coat the Ag film with a thickness of about 50 nm on the single crystalline ZnO.Neodymium-doped yttrium aluminum garnet(Nd:YAG)laser was chosen to irradiate the Ag-capped ZnO samples,followed by annealing at700℃for two hours to form ZnO:Ag.The three-dimensional(3D)information of the elemental distribution of Ag in ZnO was obtained through time-of-flight secondary ion mass spectrometry(TOF-SIMS).TOF-SIMS and core-level x-ray photoelectron spectroscopy(XPS)demonstrated that the Ag impurities could be effectively doped into single crystalline ZnO samples as deep as several hundred nanometers.Obvious broadening of core level XPS profiles of Ag from the surface to depths of hundred nms was observed,indicating the variance of chemical state changes in laser-induced Ag-doped ZnO.Interesting features of electronic mixing states were detected in the valence band XPS of ZnO:Ag,suggesting the strong coupling or interaction of Ag and ZnO in the sample rather than their simple mixture.The Ag-doped ZnO also showed a narrower bandgap and a decrease in thermal diffusion coefficient compared to the pure ZnO,which would be beneficial to thermoelectric performance.

Carbon-Based Electrode Materials for Supercapacitor： Progress, Challenges and Prospective Solutions

Carbon-based materials are typical and commercially active electrode for supercapacitors due to their advantages such as low cost, good stability and easy availability. In the light of energy storage, supercapacitors mechanism is classified into EDLCs （electrochemical double layer capacitors） and pseudocapacitors. Multidimensional carbon nanomaterials （active carbon, carbon nanotube, graphene, etc.）, carbon-based composite and corresponding electrolyte are the critical and important factor in the eyes of researcher. In this minireview, we will discuss the storage mechanism and summarize recent developed novel carbon and carbon-based materials in supercapacitors. The techniques to design the novel nanostructure and high performance electrodematerials that facilitate charge transfer to achieve high energy and power densities will also be discussed.

Nano-scale Interfacial Friction Behavior between Two Kinds of Materials in MEMS Based on Molecular Dynamics Simulations

The aim of this article was to provide a systematic method to perform molecular dynamics simulotion or evaluation for nano-scale interfacial friction behavior between two kinds of materials in MEMS design. Friction is an important factor affecting the performance and reliability of MEMS. The model of the nano-scale interracial friction behavior between two kinds of materials was presented based on the Newton＇ s equations of motion. The Morse potential function was selected for the model. The improved Verlet algorithm was employed to resolve the model, the atom trajectories and the law of the interfacial friction behavior. Comparisons with experimental data in other paper confirm the validity of the model. Using the model it is possible to simulate or evaluate the importance of different factors for designing of the nano-scale interfacial friction behavior between two kinds of materials in MEMS.

Accurate capacitance-voltage characterization of organic thin films with current injection

To deal with the invalidation of commonly employed series model and parallel model in capacitance-voltage(C-V)characterization of organic thin films when current injection is significant,a three-element equivalent circuit model is proposed.On this basis,the expression of real capacitance in consideration of current injection is theoretically derived by small-signal analysis method.The validity of the proposed equivalent circuit and theoretical expression are verified by a simulating circuit consisting of a capacitor,a diode,and a resistor.Moreover,the accurate C-V characteristic of an organic thin film device is obtained via theoretical correction of the experimental measuring result,and the real capacitance is 35.7%higher than the directly measured capacitance at 5-V bias in the parallel mode.This work strongly demonstrates the necessity to consider current injection in C-V measurement and provides a strategy for accurate C-V characterization experimentally.

Topological Expression Model of Satellite Gear Mechanism

By investigation of the topological characteristics of the kinematic structure of Satellite Gear Mechanism (SGM) with graph theory, the graph model of SGM is analyzed, and a topological expression model between input and output of SGM is established based on systematic design point. Meanwhile, the mathematical expression for SGM is deduced by integrating matrix theory and graph theory; thus, the topological characteristics of the kinematic structure of SGM can be converted into a matrix model, and the topological design problem of SGM into a matrix operation problem. In addition, a brief discussion about the measures for identification of isomorphism of the graph mode is made.

PARAMETRIC MATCHING SELECTION OF MULTI-MEDIUM COUPLING SHOCK ABSORBER

To achieve the dual demand of resisting violent impact and attenuating vibration in vibration-impact-safety of protection for precision equipment such as MEMS packaging system, a theo- retical mathematical model of multi-medium coupling shock absorber is presented. The coupling of quadratic damping, linear damping, Coulomb damping and nonlinear spring are considered in the model. The approximate theoretical calculating formulae are deduced by introducing transformation-tactics. The contrasts between the analytical results and numerical integration results are developed. The resisting impact characteristics of the model are also analyzed in progress. In the meantime, the optimum model of the parameters matching selection for design of the shock absorber is built. The example design is illustrated to confirm the validity of the modeling method and the theoretical solution.

Hybrid 3D printed three-axis force sensor aided by machine learning decoupling

Identification of magnitude and orientation for spatially applied loading is highly desired in the fields of not only the machinery components but also human-machine interaction.Despite the fact that the 3-axis force sensor with different structures has been proposed to measure the spatial force,there are still some common limitations including the multi-step manufacturing-assembly processes and complicated testing of decoupling calibration.Here,we propose a rapid fabrication strategy with low-cost to achieve high-precision 3-axis force sensors.The sensor is designed to compose of structural Maltese cross base and sensing units.It is directly fabricated within one step by a hybrid 3D printing technology combining deposition modeling(FDM)with direct-ink-writing(DIW).In particular,a machine learning(ML)model is used to convert the strain signal to the force components.Instead of a mount of calibration tests,this ML model is trained by sufficient simulation data based on programmed batch finite element modeling.This sensor is capable of continuously identifying a spatial force with varying magnitude and orientation,which successfully quantify the applied force of traditional Chinese medicine physiotherapy including Gua Sha and massage.This work provides insight for design and rapid fabrication of multi-axis force sensors,as well as potential applications.

Advances of machine learning in materials science: Ideas and techniques

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution, with large database and repositories appearing everywhere. Traditionally, materials science is a trial-and-error field, in both the computational and experimental departments. With the advent of machine learning-based techniques, there has been a paradigm shift: materials can now be screened quickly using ML models and even generated based on materials with similar properties;ML has also quietly infiltrated many sub-disciplinary under materials science. However, ML remains relatively new to the field and is expanding its wing quickly. There are a plethora of readily-available big data architectures and abundance of ML models and software;The call to integrate all these elements in a comprehensive research procedure is becoming an important direction of material science research. In this review, we attempt to provide an introduction and reference of ML to materials scientists, covering as much as possible the commonly used methods and applications, and discussing the future possibilities.

Non-destructive and deep learning-enhanced characterization of 4H-SiC material

The silicon carbide(SiC)crystal growth is a multiple-phase aggregation process of Si and C atoms.With the development of the clean energy industry,the 4H-SiC has gained increasing attention as it is an ideal material for new energy automobiles and optoelectronic devices.The aggregation process is normally complex and dynamic due to its distinctive formation energy,and it is hard to study and trace back in a non-destructive and comprehensive way.Here,this work developed a non-destructive and deep learning-enhanced characterization method of 4H-SiC material,which was based on micro-CT scanning,the verification of various optical measurements,and the convolutional neural network(ResNet-50 architecture).Harmful defects at the micro-level,polytypes,micropipes,and carbon inclusions could be identified and orientated with more than 96%high performance on both accuracy and precision.The three-dimensional visual reconstruction with quantitative analyses provided a vivid tracing back of the SiC aggregation process.This work demonstrated a use-ful tool to understand and optimize the SiC growth technology and further enhance productivity.

Circulation patterns and molecular characteristics of respiratory syncytial virus among hospitalized children in Tianjin,China,before and during the COVID-19 pandemic(2017–2022)

Respiratory syncytial virus(RSV)is the main pathogen that causes hospitalization for acute lower respiratory tract infections(ALRIs)in children.With the reopening of communities and schools,the resurgence of RSV in the COVID-19 post-pandemic era has become a major concern.To understand the circulation patterns and genotype variability of RSV in Tianjin before and during the COVID-19 pandemic,a total of 19,531 nasopharyngeal aspirate samples from hospitalized children in Tianjin from July 2017 to June 2022 were evaluated.Direct immunofluorescence and polymerase chain reaction(PCR)were used for screening RSV-positive samples and subtyping,respectively.Further analysis of mutations in the second hypervariable region(HVR2)of the G gene was performed through Sanger sequencing.Our results showed that 16.46%(3215/19,531)samples were RSV positive and a delayed increase in the RSV infection rates occurred in the winter season from December 2020 to February 2021,with the average RSV-positive rate of 35.77%(519/1451).The ON1,with H258Q and H266L substitutions,and the BA9,with T290I and T312I substitutions,are dominant strains that alternately circulate every 1–2 years in Tianjin,China,from July 2017 to June 2022.In addition,novel substitutions,such as N296Y,K221T,N230K,V251A in the BA9 genotype,and L226I in the ON1 genotype,emerged during the COVID-19 pandemic.Analysis of clinical characteristics indicated no significant differences between RSV-A and RSV-B groups.This study provides a theoretical basis for clinical prevention and treatment.However,further studies are needed to explore the regulatory mechanism of host immune responses to different lineages of ON1 and BA9 in the future.

Multiple fields manipulation on nitride material structures in ultraviolet light-emitting diodes

As demonstrated during the COVID-19 pandemic,advanced deep ultraviolet(DUV)light sources(200–280 nm),such as AlGaN-based light-emitting diodes(LEDs)show excellence in preventing virus transmission,which further reveals their wide applications from biological,environmental,industrial to medical.However,the relatively low external quantum efficiencies(mostly lower than 10%)strongly restrict their wider or even potential applications,which have been known related to the intrinsic properties of high Al-content AlGaN semiconductor materials and especially their quantum structures.Here,we review recent progress in the development of novel concepts and techniques in AlGaNbased LEDs and summarize the multiple physical fields as a toolkit for effectively controlling and tailoring the crucial properties of nitride quantum structures.In addition,we describe the key challenges for further increasing the efficiency of DUV LEDs and provide an outlook for future developments.

Reversing abnormal hole localization in high-Alcontent AlGaN quantum well to enhance deep ultraviolet emission by regulating the orbital state coupling

AlGaN has attracted considerable interest for ultraviolet(UV)applications.With the development of UV optoelectronic devices,abnormal carrier confinement behaviour has been observed for c-plane-oriented AlGaN quantum wells(QWs)with high Al content.Because of the dispersive crystal field split-off hole band(CH band)composed of pz orbitals,the abnormal confinement becomes the limiting factor for efficient UV light emission.This observation differs from the widely accepted concept that confinement of carriers at the lowest quantum level is more pronounced than that at higher quantum levels,which has been an established conclusion for conventional continuous potential wells.In particular,orientational pz orbitals are sensitive to the confinement direction in line with the conducting direction,which affects the orbital intercoupling.In this work,models of Al_(0.75)Ga_(0.25)N/AlN QWs constructed with variable lattice orientations were used to investigate the orbital intercoupling among atoms between the well and barrier regions.Orbital engineering of QWs was implemented by changing the orbital state confinement,with the well plane inclined from 0°to 90°at a step of 30°(referred to the c plane).The barrier potential and transition rate at the band edge were enhanced through this orbital engineering.The concept of orbital engineering was also demonstrated through the construction of inclined QW planes on semi-and nonpolar planes implemented in microrods with pyramid-shaped tops.The higher emission intensity from the QWs on the nonpolar plane compared with those on the polar plane was confirmed via localized cathodoluminescence(CL)maps.

Dynamic Transmissibility of a Complex Nonlinear Coupling Isolator

A mathematical model was developed for a complex nonlinear coupling isolator for attenuating vibration which coupled quadratic damping, viscous damping, Coulomb damping, and nonlinear spring forces. The approximate analytical solution for the dynamic transmissibility of the isolator was deduced by combining Fourier transforms and the harmonic balance method with deterministic excitation. The mathematical characteristics of the dynamic transmissibility were analyzed to illustrate the dynamic performance of the isolator. The analytical results show multiple solutions, especially the low-frequency attenuation characteristics below the resonance frequency. The results provide a theoretical basis for the design of nonlinear isolators.

Mechanical Characteristics of Oil-Damping Shock Absorber for Protection of Electronic-Packaging Components

A microstructure oil-damping shock absorber was designed for the protection of electronic- packaging components in vibration-impact environments. The nonlinearity of the oil viscosity, the oil flow characteristics, and the coupling between the oil and the physical structure were included in a mathematical model of the oil-damping shock absorber to attenuate vibrations. The results of multi-parameter-coupled dy- namic tests show that the mathematical model accurately simulates the actual physical system of the oil- damping shock absorber. The model could be used for engineering designs of vibration-impact isolation of electronic-packaging components.