Advanced Functional Electromagnetic Shielding Materials:A Review Based on Micro‑Nano Structure Interface Control of Biomass Cell Walls

Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.

Designing Electronic Structures of Multiscale Helical Converters for Tailored Ultrabroad Electromagnetic Absorption

Atomic-scale doping strategies and structure design play pivotal roles in tailoring the electronic structure and physicochemical property of electromagnetic wave absorption(EMWA)materials.However,the relationship between configuration and electromagnetic(EM)loss mechanism has remained elusive.Herein,drawing inspiration from the DNA transcription process,we report the successful synthesis of novel in situ Mn/N co-doped helical carbon nanotubes with ultrabroad EMWA capability.Theoretical calculation and EM simulation confirm that the orbital coupling and spin polarization of the Mn–N4–C configuration,along with cross polarization generated by the helical structure,endow the helical converters with enhanced EM loss.As a result,HMC-8 demonstrates outstanding EMWA performance,achieving a minimum reflection loss of−63.13 dB at an ultralow thickness of 1.29 mm.Through precise tuning of the graphite domain size,HMC-7 achieves an effective absorption bandwidth(EAB)of 6.08 GHz at 2.02 mm thickness.Furthermore,constructing macroscale gradient metamaterials enables an ultrabroadband EAB of 12.16 GHz at a thickness of only 5.00 mm,with the maximum radar cross section reduction value reaching 36.4 dB m2.This innovative approach not only advances the understanding of metal–nonmetal co-doping but also realizes broadband EMWA,thus contributing to the development of EMWA mechanisms and applications.

From VIB‑to VB‑Group Transition Metal Disulfides:Structure Engineering Modulation for Superior Electromagnetic Wave Absorption

The laminated transition metal disulfides(TMDs),which are well known as typical two-dimensional(2D)semiconductive materials,possess a unique layered structure,leading to their wide-spread applications in various fields,such as catalysis,energy storage,sensing,etc.In recent years,a lot of research work on TMDs based functional materials in the fields of electromagnetic wave absorption(EMA)has been carried out.Therefore,it is of great significance to elaborate the influence of TMDs on EMA in time to speed up the application.In this review,recent advances in the development of electromagnetic wave(EMW)absorbers based on TMDs,ranging from the VIB group to the VB group are summarized.Their compositions,microstructures,electronic properties,and synthesis methods are presented in detail.Particularly,the modulation of structure engineering from the aspects of heterostructures,defects,morphologies and phases are systematically summarized,focusing on optimizing impedance matching and increasing dielectric and magnetic losses in the EMA materials with tunable EMW absorption performance.Milestones as well as the challenges are also identified to guide the design of new TMDs based dielectric EMA materials with high performance.

Enhancing electromagnetic wave absorption with core‐shell structured SiO_(2)@MXene@MoS_(2) nanospheres

Material composition and structural design are important factors influencing the electromagnetic wave(EMW)absorption performance of materials.To alleviate the impedance mismatch attributed to the high dielectric constant of Ti_(3)C_(2)T_(x)MXene,we have successfully synthesized core‐shell structured SiO_(2)@MXene@MoS_(2)nanospheres.This architecture,comprising SiO_(2) as the core,MXene as the intermediate layer,and MoS_(2) as the outer shell,is achieved through an electrostatic self‐assembly method combined with a hydrothermal process.This complex core‐shell structure not only provides a variety of loss mechanisms that effectively dissipate electromagnetic energy but also prevents self‐aggregation of MXene and MoS_(2) nanosheets.Notably,the synergistic combination of SiO_(2) and MoS_(2) with highly conductive MXene enables the suitable dielectric constant of the composites,ensuring optimal impedance matching.Therefore,the core‐shell structured SiO_(2)@MXene@MoS_(2) nanospheres exhibit excellent EMW absorption performance,featuring a remarkable minimum reflection loss(RL_(min))of−52.11 dB(2.4 mm).It is noteworthy that these nanospheres achieve an ultra‐wide effective absorption bandwidth(EAB)of 6.72 GHz.This work provides a novel approach for designing and synthesizing high‐performance EMW absorbers characterized by“wide bandwidth and strong reflection loss.”

Topological optimization of ballistic protective structures through genetic algorithms in a vulnerability-driven environment

Reducing the vulnerability of a platform,i.e.,the risk of being affected by hostile objects,is of paramount importance in the design process of vehicles,especially aircraft.A simple and effective way to decrease vulnerability is to introduce protective structures to intercept and possibly stop threats.However,this type of solution can lead to a significant increase in weight,affecting the performance of the aircraft.For this reason,it is crucial to study possible solutions that allow reducing the vulnerability of the aircraft while containing the increase in structural weight.One possible strategy is to optimize the topology of protective solutions to find the optimal balance between vulnerability and the weight of the added structures.Among the many optimization techniques available in the literature for this purpose,multiobjective genetic algorithms stand out as promising tools.In this context,this work proposes the use of a in-house software for vulnerability calculation to guide the process of topology optimization through multi-objective genetic algorithms,aiming to simultaneously minimize the weight of protective structures and vulnerability.In addition to the use of the in-house software,which itself represents a novelty in the field of topology optimization of structures,the method incorporates a custom mutation function within the genetic algorithm,specifically developed using a graph-based approach to ensure the continuity of the generated structures.The tool developed for this work is capable of generating protections with optimized layouts considering two different types of impacting objects,namely bullets and fragments from detonating objects.The software outputs a set of non-dominated solutions describing different topologies that the user can choose from.

In-phase and out-of-phase spin pumping effects in Py/Ru/Pysynthetic antiferromagnetic structures

The spin pumping effect in magnetic heterostructures and multilayers is a highly effective method for the generationand transmission of spin currents. In the increasingly prominent synthetic antiferromagnetic structures, the two ferromagneticlayers demonstrate in-phase and out-of-phase states, corresponding to acoustic and optical precession modes. Withinthis context, our study explores the spin pumping effect in Py/Ru/Py synthetic antiferromagnetic structures across differentmodes. The heightened magnetic damping resulting from the spin pumping effect in the in-phase state initially decreaseswith increasing Py thickness before stabilizing. Conversely, in the out-of-phase state, the amplified damping exceeds thatof the in-phase state, suggesting a greater spin relaxation within this configuration, which demonstrates sensitivity to alterationsin static exchange interactions. These findings contribute to advancing the application of synthetic antiferromagneticstructures in magnonic devices.

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.

First‑principles study on electronic structure,optical and magnetic properties of rare earth elements X(X=Sc,Y,La,Ce,Eu)doped with two‑dimensional GaSe

The electronic structure,magnetic,and optical properties of two-dimensional(2D)GaSe doped with rare earth elements X(X=Sc,Y,La,Ce,Eu)were calculated using the first-principles plane wave method based on den-sity functional theory.The results show that intrinsic 2D GaSe is a p-type nonmagnetic semiconductor with an indi-rect bandgap of 2.6611 eV.The spin-up and spin-down channels of Sc-,Y-,and La-doped 2D GaSe are symmetric,they are non-magnetic semiconductors.The magnetic moments of Ce-and Eu-doped 2D GaSe are 0.908μ_(B)and 7.163μ_(B),which are magnetic semiconductors.Impurity energy levels appear in both spin-up and spin-down chan-nels of Eu-doped 2D GaSe,which enhances the probability of electron transition.Compared with intrinsic 2D GaSe,the static dielectric constant of the doped 2D GaSe increases,and the polarization ability is strengthened.The ab-sorption spectrum of the doped 2D GaSe shifts in the low-energy direction,and the red-shift phenomenon occurs,which extends the absorption spectral range.The optical reflection coefficient of the doped 2D GaSe is improved in the low energy region,and the improvement of Eu-doped 2D GaSe is the most obvious.

Graph Convolutional Networks Embedding Textual Structure Information for Relation Extraction

Deep neural network-based relational extraction research has made significant progress in recent years,andit provides data support for many natural language processing downstream tasks such as building knowledgegraph,sentiment analysis and question-answering systems.However,previous studies ignored much unusedstructural information in sentences that could enhance the performance of the relation extraction task.Moreover,most existing dependency-based models utilize self-attention to distinguish the importance of context,whichhardly deals withmultiple-structure information.To efficiently leverage multiple structure information,this paperproposes a dynamic structure attention mechanism model based on textual structure information,which deeplyintegrates word embedding,named entity recognition labels,part of speech,dependency tree and dependency typeinto a graph convolutional network.Specifically,our model extracts text features of different structures from theinput sentence.Textual Structure information Graph Convolutional Networks employs the dynamic structureattention mechanism to learn multi-structure attention,effectively distinguishing important contextual features invarious structural information.In addition,multi-structure weights are carefully designed as amergingmechanismin the different structure attention to dynamically adjust the final attention.This paper combines these featuresand trains a graph convolutional network for relation extraction.We experiment on supervised relation extractiondatasets including SemEval 2010 Task 8,TACRED,TACREV,and Re-TACED,the result significantly outperformsthe previous.

Comparative Study of Genetic Structure and Genetic Diversity betweenWild and Cultivated Populations of Taxus cuspidata,Northeast China

Taxus cuspidata is a rare plant with important medicinal and ornamental value.Aiming at the obvious differences between wild and cultivated populations of T.cuspidata from Northeast China,a total of 61 samples,that is,33 wild yews and 28 cultivated yews were used to analyze the differences and correlations of the kinship,genetic diversity,and genetic structure between them by specific length amplified fragment sequencing(SLAF-seq).Finally,470725 polymorphic SLAF tags and 58622 valid SNP markers were obtained.Phylogenetic analysis showed that 61 samples were classified into 2 clusters:wild populations and cultivated populations,and some wild yews were categorized into the cultivated populations;the genetic diversity analysis showed that the Nei diversity index of wild populations(0.4068)was smaller than that of cultivated populations(0.4414),and the polymorphic information content(PIC)of wild populations(0.2861)was smaller than that of cultivated populations(0.3309).The genetic differentiation analysis showed that the total populations of gene diversity(H_(t))of cultivated and wild populations were respectively 0.8159 and 0.5685,the coefficient of gene differentiation(G_(st))of cultivated and wild populations was respectively 0.3021 and 0.1068,and the gene flow(N_(m))(2.4967)of wild populations was larger than cultivated populations(0.8199).The molecular variance(AMOVA)revealed that inter-population variation accounted for 29.57%of the total genetic variation,while intra-population variation accounted for 70.42% of the total genetic variation(p<0.001),this suggested that the genetic variation in the T.cuspidata is mainly attributed to within-population factors.In conclusion,the genetic distance between geographical ecological groups of wild populations was generally smaller than that of cultivated populations,and the degree of genetic diversity and genetic differentiation was smaller than that of cultivated populations.As evident,the utilization of SLAF-seq technology enables efficient and accurate development of SNP markers suitable for genetic analysis of T.cuspidata species.These developed SNP markers can provide a molecular foundation for T.cuspidata breeding,construction of genetic maps,variety identification,and association analysis of agronomic traits.

3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.

Interpenetrated Structures for Enhancing Ion Diffusion Kinetics in Electrochemical Energy Storage Devices

The architectural design of electrodes offers new opportunities for next-generation electrochemical energy storage devices(EESDs)by increasing surface area,thickness,and active materials mass loading while maintaining good ion diffusion through optimized electrode tortuosity.However,conventional thick electrodes increase ion diffusion length and cause larger ion concentration gradients,limiting reaction kinetics.We demonstrate a strategy for building interpenetrated structures that shortens ion diffusion length and reduces ion concentration inhomogeneity.This free-standing device structure also avoids short-circuiting without needing a separator.The feature size and number of interpenetrated units can be adjusted during printing to balance surface area and ion diffusion.Starting with a 3D-printed interpenetrated polymer substrate,we metallize it to make it conductive.This substrate has two individually addressable electrodes,allowing selective electrodeposition of energy storage materials.Using a Zn//MnO_(2) battery as a model system,the interpenetrated device outperforms conventional separate electrode configurations,improving volumetric energy density by 221%and exhibiting a higher capacity retention rate of 49%compared to 35%at temperatures from 20 to 0℃.Our study introduces a new EESD architecture applicable to Li-ion,Na-ion batteries,supercapacitors,etc.

Controlled Twill Surface Structure Endowing Nanofiber Composite Membrane Excellent Electromagnetic Interference Shielding

Inspired by the Chinese Knotting weave structure,an electromagnetic interference(EMI)nanofiber composite membrane with a twill surface was prepared.Poly(vinyl alcohol-co-ethylene)(Pva-co-PE)nanofibers and twill nylon fabric were used as the matrix and filter templates,respectively.A Pva-co-PEMXene/silver nanowire(Pva-co-PE-MXene/AgNW,PM_(x)Ag)membrane was successfully prepared using a template method.When the MXene/AgNW content was only 7.4 wt%(PM_(7.4)Ag),the EMI shielding efficiency(SE)of the composite membrane with the oblique twill structure on the surface was 103.9 dB and the surface twill structure improved the EMI by 38.5%.This result was attributed to the pre-interference of the oblique twill structure in the direction of the incident EM wave,which enhanced the probability of the electromagnetic waves randomly colliding with the MXene nanosheets.Simultaneously,the internal reflection and ohmic and resonance losses were enhanced.The PM_(7.4)Ag membrane with the twill structure exhibited both an outstanding tensile strength of 22.8 MPa and EMI SE/t of 3925.2 dB cm^(-1).Moreover,the PM_(x)Ag nanocomposite membranes demonstrated an excellent thermal management performance,hydrophobicity,non-flammability,and performance stability,which was demonstrated by an EMI SE of 97.3%in a high-temperature environment of 140℃.The successful preparation of surface-twill composite membranes makes it difficult to achieve both a low filler content and a high EMI SE in electromagnetic shielding materials.This strategy provides a new approach for preparing thin membranes with excellent EMI properties.

A three-dimensional co-continuous network structure polymer electrolyte with efficient ion transport channels enabling ultralong-life all solid-state lithium metal batteries

Solid polymer electrolytes(SPEs)have emerged as one of the most promising candidates for the construction of solid-state lithium batteries due to their excellent flexibility,scalability,and interface compatibility with electrodes.Herein,a novel all-solid polymer electrolyte(PPLCE)was fabricated by the copolymer network of liquid crystalline monomers and poly(ethylene glycol)dimethacrylate(PEGDMA)acts as a structural frame,combined with poly(ethylene glycol)diglycidyl ether short chain interspersed serving as mobile ion transport entities.The preparaed PPLCEs exhibit excellent mechanical property and out-standing electrochemical performances,which is attributed to their unique three-dimensional cocontinuous structure,characterized by a cross-linked semi-interpenetrating network and an ionic liquid phase,resulting in a distinctive nanostructure with short-range order and long-range disorder.Remarkably,the addition of PEGDMA is proved to be critical to the comprehensive performance of the PPLCEs,which effectively modulates the microscopic morphology of polymer networks and improves the mechanical properties as well as cycling stability of the solid electrolyte.When used in a lithiumion symmetrical battery configuration,the 6 wt%-PPLCE exhibites super stability,sustaining operation for over 2000 h at 30 C,with minimal and consistent overpotential of 50 mV.The resulting Li|PPLCE|LFP solid-state battery demonstrates high discharge specific capacities of 160.9 and 120.1 mA h g^(-1)at current densities of 0.2 and 1 C,respectively.Even after more than 300 cycles at a current density of 0.2 C,it retaines an impressive 73.5%capacity.Moreover,it displayes stable cycling for over 180 cycles at a high current density of 0.5C.The super cycle stability may promote the application for ultralong-life all solid-state lithium metal batteries.

Electrical structure identification of deep shale gas reservoir in complex structural area using wide field electromagnetic method

To fully exploit the technical advantages of the large-depth and high-precision artificial source electromagnetic method in the complex structure area of southern Sichuan and compensate for the shortcomings of the conventional electromagnetic method in exploration depth,precision,and accuracy,the large-depth and high-precision wide field electromagnetic method is applied to the complex structure test area of the Luochang syncline and Yuhe nose anticline in the southern Sichuan.The advantages of the wide field electromagnetic method in detecting deep,low-resistivity thin layers are demonstrated.First,on the basis of the analysis of physical property data,a geological–geoelectric model is established in the test area,and the wide field electromagnetic method is numerically simulated to analyze and evaluate the response characteristics of deep thin shale gas layers on wide field electromagnetic curves.Second,a wide field electromagnetic test is conducted in the complex structure area of southern Sichuan.After data processing and inversion imaging,apparent resistivity logging data are used for calibration to develop an apparent resistivity interpretation model suitable for the test area.On the basis of the results,the characteristics of the electrical structure change in the shallow longitudinal formation of 6 km are implemented,and the transverse electrical distribution characteristics of the deep shale gas layer are delineated.In the prediction area near the well,the subsequent data verification shows that the apparent resistivity obtained using the inversion of the wide field electromagnetic method is consistent with the trend of apparent resistivity revealed by logging,which proves that this method can effectively identify the weak response characteristics of deep shale gas formations in complex structural areas.This experiment,it is shown shows that the wide field electromagnetic method with a large depth and high precision can effectively characterize the electrical characteristics of deep,low-resistivity thin layers in complex structural areas,and a new set of low-cost evaluation technologies for shale gas target layers based on the wide field electromagnetic method is explored.

Viscosity and structure relationship with equimolar substitution of CaO with MgO in the CaO–MgO–Al_(2)O_(3)–SiO_(2)slag melts

Currently,the Al_(2)O_(3)content in the high-alumina slag systems within blast furnaces is generally limited to 16wt%–18.5wt%,making it challenging to overcome this limitation.Unlike most studies that concentrated on managing the MgO/Al_(2)O_(3)ratio or basicity,this paper explored the effect of equimolar substitution of MgO for CaO on the viscosity and structure of a high-alumina CaO-MgO-Al_(2)O_(3)-SiO_(2)slag system,providing theoretical guidance and data to facilitate the application of high-alumina ores.The results revealed that the viscosity first decreased and then increased with higher MgO substitution,reaching a minimum at 15mol%MgO concentration.Fourier transform infrared spectroscopy(FTIR)results found that the depths of the troughs representing[SiO_(4)]tetrahedra,[AlO_(4)]tetrahedra,and Si-O-Al bending became progressively deeper with increased MgO substitution.Deconvolution of the Raman spectra showed that the average number of bridging oxygens per Si atom and the X_(Q^(3))/X_(Q^(2))(X_(Q^(i))is the molar fraction of Q^(i) unit,and i is the number of bridging oxygens in a[SiO_(4)]tetrahedral unit)ratio increased from 2.30 and 1.02 to 2.52 and 2.14,respectively,indicating a progressive polymerization of the silicate structure.X-ray photoelectron spectroscopy(XPS)results highlighted that non-bridging oxygen content decreased from 77.97mol% to 63.41mol% with increasing MgO concentration,whereas bridging oxygen and free oxygen contents increased.Structural analysis demonstrated a gradual increase in the polymerization degree of the tetrahedral structure with the increase in MgO substitution.However,bond strength is another important factor affecting the slag viscosity.The occurrence of a viscosity minimum can be attributed to the complex evolution of bond strengths of non-bridging oxygens generated during depolymerization of the[SiO_(4)]and[AlO_(4)]tetrahedral structures by CaO and MgO.

Analysis of Urban Agglomeration Network Structure Based on Baidu Migration Data: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Urban Agglomeration

The inter-city linkage heat data provided by Baidu Migration is employed as a characterization of inter-city linkages in order to facilitate the study of the network linkage characteristics and hierarchical structure of urban agglomeration in the Greater Bay Area through the use of social network analysis method.This is the inaugural application of big data based on location services in the study of urban agglomeration network structure,which represents a novel research perspective on this topic.The study reveals that the density of network linkages in the Greater Bay Area urban agglomeration has reached 100%,indicating a mature network-like spatial structure.This structure has given rise to three distinct communities:Shenzhen-Dongguan-Huizhou,Guangzhou-Foshan-Zhaoqing,and Zhuhai-Zhongshan-Jiangmen.Additionally,cities within the Greater Bay Area urban agglomeration play different roles,suggesting that varying development strategies may be necessary to achieve staggered development.The study demonstrates that large datasets represented by LBS can offer novel insights and methodologies for the examination of urban agglomeration network structures,contingent on the appropriate mining and processing of the data.

Role of iron ore in enhancing gasification of iron coke:Structural evolution,influence mechanism and kinetic analysis

The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the microstructure of iron coke was investigated.Furthermore,a comparative study of the gasification reactions between iron coke and coke was conducted through non-isothermal thermogravimetric method.The findings indicate that compared to coke,iron coke exhibits an augmentation in micropores and specific surface area,and the micropores further extend and interconnect.This provides more adsorption sites for CO_(2) molecules during the gasification process,resulting in a reduction in the initial gasification temperature of iron coke.Accelerating the heating rate in non-isothermal gasification can enhance the reactivity of iron coke.The metallic iron reduced from iron ore is embedded in the carbon matrix,reducing the orderliness of the carbon structure,which is primarily responsible for the heightened reactivity of the carbon atoms.The kinetic study indicates that the random pore model can effectively represent the gasification process of iron coke due to its rich pore structure.Moreover,as the proportion of iron ore increases,the activation energy for the carbon gasification gradually decreases,from 246.2 kJ/mol for coke to 192.5 kJ/mol for iron coke 15wt%.

First-Principle Study on the Electronic Structure and Optical Property of New Diluted Magnetic Semiconductor(Y_(0.75)Ca_(0.25))(Cu_(0.75)Mn_(0.25))SO

The band structure,DOSs,and optical properties of(Y_(0.75)Ca_(0.25))(Cu_(0.75)Mn_(0.25))SO,including dielectric function,absorption function,reflection function,and energy loss spectrum were studied by using the first-principles calculation.The calculation results indicate that(Y_(0.75)Ca_(0.25))(Cu_(0.75)Mn_(0.25))SO is a direct bandgap semiconductor with a bandgap of 1.1 eV.The Fermi surface is asymmetric and exhibits spin splitting phenomenon.The new type of dilute magnetic semiconductor(Y_(0.75)Ca_(0.25))(Cu_(0.75)Mn_(0.25))SO exhibits significant light loss around 70 eV,with light reflection gradually increasing after 30 eV,and light absorption mainly occurring around 8-30 eV.These results also provide a basis for the discovery of more types of 1111 phase new dilute magnetic semiconductors in the future.

Emerging structures and dynamic mechanisms ofγ-secretase for Alzheimer’s disease

γ-Secretase,called“the proteasome of the membrane,”is a membrane-embedded protease complex that cleaves 150+peptide substrates with central roles in biology and medicine,including amyloid precursor protein and the Notch family of cell-surface receptors.Mutations inγ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer’s disease.γ-Secretase has thus served as a critical drug target for treating familial Alzheimer’s disease and the more common late-onset Alzheimer’s disease as well.However,critical gaps remain in understanding the mechanisms of processive proteolysis of substrates,the effects of familial Alzheimer’s disease mutations,and allosteric modulation of substrate cleavage byγ-secretase.In this review,we focus on recent studies of structural dynamic mechanisms ofγ-secretase.Different mechanisms,including the“Fit-Stay-Trim,”“Sliding-Unwinding,”and“Tilting-Unwinding,”have been proposed for substrate proteolysis of amyloid precursor protein byγ-secretase based on all-atom molecular dynamics simulations.While an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-boundγ-secretase,molecular dynamics simulations on a resolved model of Notch1-boundγ-secretase that was reconstructed using the amyloid precursor protein-boundγ-secretase as a template successfully capturedγ-secretase activation for proper cleavages of both wildtype and mutant Notch,being consistent with biochemical experimental findings.The approach could be potentially applied to decipher the processing mechanisms of various substrates byγ-secretase.In addition,controversy over the effects of familial Alzheimer’s disease mutations,particularly the issue of whether they stabilize or destabilizeγ-secretase-substrate complexes,is discussed.Finally,an outlook is provided for future studies ofγ-secretase,including pathways of substrate binding and product release,effects of modulators on familial Alzheimer’s disease mutations of theγ-secretase-substrate complexes.Comprehensive understanding of the functional mechanisms ofγ-secretase will greatly facilitate the rational design of effective drug molecules for treating familial Alzheimer’s disease and perhaps Alzheimer’s disease in general.