Hybrid Self-Assembled Multilayer Films Formed by Alternating Layers of Keggin Polyoxometalates and 1,10DAD

Hybrid self-assembled multilayer films were prepared by alternate adsorption of 1,10-diaminodecane (1,10-DAD) and Keggin polyoxometalates of SiW12O404-, SiW11VO405-, and PMo12O403-, respectively. The films were reproducibly grown at each adsorption cycle as monitored by UV spectroscopy.

Chitosan/Sodium Alginate Multilayer pH-Sensitive Films Based on Layer-by-Layer Self-Assembly for Intelligent Packaging

The abuse of plastic food packaging has brought about severe white pollution issues around the world.Developing green and sustainable biomass packaging is an effective way to solve this problem.Hence,a chitosan/sodium alginate-based multilayer film is fabricated via a layer-by-layer(LBL)self-assembly method.With the help of superior interaction between the layers,the multilayer film possesses excellent mechanical properties(with a tensile strength of 50 MPa).Besides,the film displays outstanding water retention property(blocking moisture of 97.56%)and ultraviolet blocking property.Anthocyanin is introduced into the film to detect the food quality since it is one natural plant polyphenol that is sensitive to the pH changes ranging from 1 to 13 in food when spoilage occurs.It is noted that the film is also bacteriostatic which is desired for food packaging.This study describes a simple technique for the development of advanced multifunctional and fully biodegradable food packaging film and it is a sustainable alternative to plastic packaging.

Self-similarity of multilayer networks

Research on the self-similarity of multilayer networks is scarce, when compared to the extensive research conducted on the dynamics of these networks. In this paper, we use entropy to determine the edge weights in each sub-network,and apply the degree–degree distance to unify the weight values of connecting edges between different sub-networks, and unify the edges with different meanings in the multilayer network numerically. At this time, the multilayer network is compressed into a single-layer network, also known as the aggregated network. Furthermore, the self-similarity of the multilayer network is represented by analyzing the self-similarity of the aggregate network. The study of self-similarity was conducted on two classical fractal networks and a real-world multilayer network. The results show that multilayer networks exhibit more pronounced self-similarity, and the intensity of self-similarity in multilayer networks can vary with the connection mode of sub-networks.

The Electrochemical Characteristics of Multilayer Assembly of Hemoglobin and Polystyrene Sulfonate at Self-assembled MonolayerSurface

A multilayer film of hemoglobin (Hb) molecules and polyelectrolyte sulfonate were fabricated on a thiol self-assembled monolayers (SAMs) by electrostatic force. The Hb maintains electroactive property in the multilayer film, methylene blue (MB) incorporated into the multilayer can enhance the electron transfer rate between the Hb and the electrode surface.

Fiber Optic Humidity Sensor Based on Self-Assembled Polyelectrolyte Multilayers

Polyelectrolyte multilayers were self-assembled onto planar glass substrates and multimode optic fibers. The multilayer thin films deposited on glass substrates were characterized by using UV-vis spectroscopy and X-ray photoelectron spectroscope. The multilayer thin films containing hydrophilic side-groups possessed are affinity for uwer molecules. The adsorption and desorption of free water vapor gave rise to the changes in the refractive index and in the reflectance of the thin films. A multilayer thin film based fiber optic humidity sensor with an LED light source of 0.85 mum was designed. Under certain conditions, the rejected light intensity of the thin film sensor was a function of the humidity of air. About 30 bilayers was optimal for the multilayer thin film sensor working at wavelength of 0.85 mum. This sensor can work over almost the whole relative humidity range with very good sensitivity.

Au@Ag Core-shell Nanorods Self-assembled on Polyelectrolyte Multilayers for Ultra-High Sensitivity SERS Fiber Probes

We demonstrated a chemical process in the fabrication of a SERS fiber probe with an ultrahigh sensitivity.The synthesis was carried out by preparing Au@Ag core-shell nanorods (Au@Ag-NRs) selfassembled on polyelectrolyte (PE) multilayers,for which Au@Ag-NRs were controlled by adjusting the silver layer thickness.The effect of silver layer thickness of Au@Ag-NRs on the SERS performance of the fiber probe was investigated.The SERS fiber probe shows the best performance when the silver layer thickness is controlled at 8.57 nm.Under the condition of optimizing silver layer thickness,the fiber probe exhibits ultra-high sensitivity (i e,10^(-10) M crystalline violet,CV),good reproducibility (i e,RSD of 3.5%) and stability.Besides,electromagnetic field distribution of the SERS fiber probe was also investigated.The strongest enhancement is found within the core of fiber,whereas a weakened electromagnetic field exists in the fiber cladding layer.The SERS fiber probe can be a good candidate in ultra-trace detection for biomedical and environmental areas.

OptoGPT: A foundation model for inverse design in optical multilayer thin film structures

Optical multilayer thin film structures have been widely used in numerous photonic applications.However,existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets,or are difficult to suit for different types of structures,e.g.,designing for different materials at each layer.These methods also cannot accommodate versatile design situations under different angles and polarizations.In addition,how to benefit practical fabrications and manufacturing has not been extensively considered yet.In this work,we introduce OptoGPT(Opto Generative Pretrained Transformer),a decoder-only transformer,to solve all these drawbacks and issues simultaneously.

Interfacial Modification of NiO_(x)by Self-assembled Monolayer for Efficient and Stable Inverted Perovskite Solar Cells

NiO_(x)as a hole transport material for inverted perovskite solar cells has received great attention owing to its high transparency,low fabrication temperature,and superior stability.However,the mismatched energy levels and possible redox reactions at the NiO_(x)/perovskite interface severely limit the performance of NiO_(x) based inverted perovskite solar cells.Herein,we introduce a p-type self-assembled monolayer between NiO_(x)and perovskite layers to modify the interface and block the undesirable redox reaction between perovskite and NiO_(x)The selfassembled monolayer molecules all contain phosphoric acid function groups,which can be anchored onto the NiOr surface and passivate the surface defect.Moreover,the introduction of self-assembled monolayers can regulate the energy level structure of NiO_(x),reduce the interfacial band energy offset,and hence promote the hole transport from perovskite to NiO_(x)layer.Consequently,the device performance is significantly enhanced in terms of both power conversion efficiency and stability.

Analysis of electrochemical impedance and XRD spectroscopy for complex self-assembled film on silver

Self-assembled monolayers （SAMs） of （3-mercaptopropy） trimethoxysilane （3-MtrF） chemisorbed on silver surfaces were chemically ＂modified by 1-octadecanethiol to form self-assembled mixed-monolayers （SAMM） and the co-polymer of N-vinylcarbazole and methyl methacrylate ester （to form complex selfassembled film （CSAF））. The oxidation resistance of these barriers on silver surfaces and some influential factors concerned processes were analyzed by electrochemical impedance spectroscopy （EIS） in a 10% NaOH aqueous solution at oxidation potential. X-ray diffraction （XRD） spectroscopy shows that the oxidation occurring on the silver surface may be restrained effectively due to the coating barrier, and CSAF（Ⅱ） is the best one. Studies also reveal that oxide processes of bare silver and a series of modified silver electrodes in a 10% NaOH aqueous solution are of more than two relaxation time constants.

Mass-spring model for elastic wave propagation in multilayered van der Waals metamaterials

Multilayered van der Waals(vdW)materials have attracted increasing interest because of the manipulability of their superior optical,electrical,thermal,and mechanical properties.A mass-spring model(MSM)for elastic wave propagation in multilayered vdW metamaterials is reported in this paper.Molecular dynamics(MD)simulations are adopted to simulate the propagation of elastic waves in multilayered vdW metamaterials.The results show that the graphene/MoS_(2)metamaterials have an elastic wave bandgap in the terahertz range.The MSM for the multilayered vdW metamaterials is proposed,and the numerical simulation results show that this model can well describe the dispersion and transmission characteristics of the multilayered vdW metamaterials.The MSM can predict elastic wave transmission characteristics in multilayered vdW metamaterials stacked with different two-dimensional(2D)materials.The results presented in this paper offer theoretical help for the vibration reduction of multilayered vdW semiconductors.

IONIC SELF-ASSEMBLY AND HUMIDITY SENSITIVITY OF POLYELECTROLYTE MULTILAYERS

Multilayer thin films of alternately adsorbed layers of polyelectrolytes PDDA and PS-119 were formed on both planar silica substrates and optical fibers through the ionic self-assembly technique. Intrinsic Fabry-Perot cavities were fabricated by stepwise assembling the polyelectrolytes onto the ends of optical fibers for the purposes of fiber optical device and sensor development. Ionically assembled polyelectrolyte multilayer thin films, in which. there are hydrophilic side groups with strong affinity towards water molecules, are a category of humidity-sensitive functional materials. The polyelectrolyte multilayer thin film Fabry-Perot cavity-type fiber optical humidity sensor can work over a wide range from about 0% RH to about 100% RH with a response time less than 1 s.

Thick Electrodes of a Self-Assembled MXene Hydrogel Composite for High-Rate Energy Storage

Supercapacitors based on two-dimensional MXene(Ti_(3)C_(2)T_(z))have shown extraordinary performance in ultrathin electrodes with low mass loading,but usually there is a significant reduction in high-rate performance as the thickness increases,caused by increasing ion diffusion limitation.Further limitations include restacking of the nanosheets,which makes it challenging to realize the full potential of these electrode materials.Herein,we demonstrate the design of a vertically aligned MXene hydrogel composite,achieved by thermal-assisted self-assembled gelation,for high-rate energy storage.The highly interconnected MXene network in the hydrogel architecture provides very good electron transport properties,and its vertical ion channel structure facilitates rapid ion transport.The resulting hydrogel electrode show excellent performance in both aqueous and organic electrolytes with respect to high capacitance,stability,and high-rate capability for up to 300μm thick electrodes,which represents a significant step toward practical applications.

A multilayer network diffusion-based model for reviewer recommendation

With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to deal with this problem.However,most existing approaches resort to text mining techniques to match manuscripts with potential reviewers,which require high-quality textual information to perform well.In this paper,we propose a reviewer recommendation algorithm based on a network diffusion process on a scholar-paper multilayer network,with no requirement for textual information.The network incorporates the relationship of scholar-paper pairs,the collaboration among scholars,and the bibliographic coupling among papers.Experimental results show that our proposed algorithm outperforms other state-of-the-art recommendation methods that use graph random walk and matrix factorization and methods that use machine learning and natural language processing,with improvements of over 7.62%in recall,5.66%in hit rate,and 47.53%in ranking score.Our work sheds light on the effectiveness of multilayer network diffusion-based methods in the reviewer recommendation problem,which will help to facilitate the peer-review process and promote information retrieval research in other practical scenes.

Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems

The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for patients.Consequently,Machine Learning methods are widely utilized in Smart Healthcare Systems(SHS)to extract valuable features fromheterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient activities.These methods are employed across different domains that are susceptible to adversarial attacks,necessitating careful consideration.Hence,this paper proposes a crossover-based Multilayer Perceptron(CMLP)model.The collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on themedical records of patients.Once an attack is detected,healthcare professionals are promptly alerted to prevent data leakage.The paper utilizes two datasets,namely the synthetic dataset and the University of Queensland Vital Signs(UQVS)dataset,from which numerous samples are collected.Experimental results are conducted to evaluate the performance of the proposed CMLP model,utilizing various performancemeasures such as Recall,Precision,Accuracy,and F1-score to predict patient activities.Comparing the proposed method with existing approaches,it achieves the highest accuracy,precision,recall,and F1-score.Specifically,the proposedmethod achieves a precision of 93%,an accuracy of 97%,an F1-score of 92%,and a recall of 92%.

Studying the co-evolution of information diffusion,vaccination behavior and disease transmission in multilayer networks with local and global effects

Today,with the rapid development of the internet,a large amount of information often accompanies the rapid transmission of disease outbreaks,and increasing numbers of scholars are studying the relationship between information and the disease transmission process using complex networks.In fact,the disease transmission process is very complex.Besides this information,there will often be individual behavioral measures and other factors to consider.Most of the previous research has aimed to establish a two-layer network model to consider the impact of information on the transmission process of disease,rarely divided into information and behavior,respectively.To carry out a more in-depth analysis of the disease transmission process and the intrinsic influencing mechanism,this paper divides information and behavior into two layers and proposes the establishment of a complex network to study the dynamic co-evolution of information diffusion,vaccination behavior,and disease transmission.This is achieved by considering four influential relationships between adjacent layers in multilayer networks.In the information layer,the diffusion process of negative information is described,and the feedback effects of local and global vaccination are considered.In the behavioral layer,an individual's vaccination behavior is described,and the probability of an individual receiving a vaccination is influenced by two factors:the influence of negative information,and the influence of local and global disease severity.In the disease layer,individual susceptibility is considered to be influenced by vaccination behavior.The state transition equations are derived using the micro Markov chain approach(MMCA),and disease prevalence thresholds are obtained.It is demonstrated through simulation experiments that the negative information diffusion is less influenced by local vaccination behavior,and is mainly influenced by global vaccination behavior;vaccination behavior is mainly influenced by local disease conditions,and is less influenced by global disease conditions;the disease transmission threshold increases with the increasing vaccination rate;and the scale of disease transmission increases with the increasing negative information diffusion rate and decreases with the increasing vaccination rate.Finally,it is found that when individual vaccination behavior considers both the influence of negative information and disease,it can increase the disease transmission threshold and reduce the scale of disease transmission.Therefore,we should resist the diffusion of negative information,increase vaccination proportions,and take appropriate protective measures in time.

Love wave propagation in one-dimensional piezoelectric quasicrystal multilayered nanoplates with surface effects

The exact solutions for the propagation of Love waves in one-dimensional(1D)hexagonal piezoelectric quasicrystal(PQC)nanoplates with surface effects are derived.An electro-elastic model is developed to investigate the anti-plane strain problem of Love wave propagation.By introducing three shape functions,the wave equations and electric balance equations are decoupled into three uncorrelated problems.Satisfying the boundary conditions of the top surface on the covering layer,the interlayer interface,and the matrix,a dispersive equation with the influence of multi-physical field coupling is provided.A surface PQC model is developed to investigate the surface effects on the propagation behaviors of Love waves in quasicrystal(QC)multilayered structures with nanoscale thicknesses.A novel dispersion relation for the PQC structure is derived in an explicit closed form according to the non-classical mechanical and electric boundary conditions.Numerical examples are given to reveal the effects of the boundary conditions,stacking sequence,characteristic scale,and phason fluctuation characteristics on the dispersion curves of Love waves propagating in PQC nanoplates with surface effects.

Improving the spaceborne GNSS-R altimetric precision based on the novel multilayer feedforward neural network weighted joint prediction model

Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater navigation.At present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically assessed.Therefore,GNSS-R satellite constellations that meet the global altimetry needs to be designed.Meanwhile,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability.Firstly,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is established.Secondly,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is excellent.Finally,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.

Study on theoretical model for electrical explosion resistivity of Al/Ni reactive multilayer foil

Al/Ni reactive multilayer foil(RMF)possesses excellent comprehensive properties as a promising substitute for traditional Cu bridge.A theoretical resistivity model of Al/Ni RMF was developed to guide the optimization of EFIs.Al/Ni RMF with different bilayer thicknesses and bridge dimensions were prepared by MEMS technology and electrical explosion tests were carried out.According to physical and chemical reactions in bridge,the electrical explosion process was divided into 5 stages:heating of condensed bridge,vaporization and diffusion of Al layers,intermetallic combination reaction,intrinsic explosion,ionization of metal gases,which are obviously shown in measured voltage curve.Effects of interface and grain boundary scattering on the resistivity of film metal were considered.Focusing on variations of substance and state,the resistivity was developed as a function of temperature at each stage.Electrical explosion curves were calculated by this model at different bilayer thicknesses,bridge dimensions and capacitor voltages,which showed an excellent agreement with experimental ones.

Role of self-assembled molecules’anchoring groups for surface defect passivation and dipole modulation in inverted perovskite solar cells

Inverted perovskite solar cells have gained prominence in industrial advancement due to their easy fabrication,low hysteresis effects,and high stability.Despite these advantages,their efficiency is currently limited by excessive defects and poor carrier transport at the perovskite-electrode interface,particularly at the buried interface between the perovskite and transparent conductive oxide(TCO).Recent efforts in the perovskite community have focused on designing novel self-assembled molecules(SAMs)to improve the quality of the buried interface.However,a notable gap remains in understanding the regulation of atomic-scale interfacial properties of SAMs between the perovskite and TCO interfaces.This understanding is crucial,particularly in terms of identifying chemically active anchoring groups.In this study,we used the star SAM([2-(9H-carbazol-9-yl)ethyl]phosphonic acid)as the base structure to investigate the defect passivation effects of eight common anchoring groups at the perovskite-TCO interface.Our findings indicate that the phosphonic and boric acid groups exhibit notable advantages.These groups fulfill three key criteria:they provide the greatest potential for defect passivation,exhibit stable adsorption with defects,and exert significant regulatory effects on interface dipoles.Ionized anchoring groups exhibit enhanced passivation capabilities for defect energy levels due to their superior Lewis base properties,which effectively neutralize local charges near defects.Among various defect types,iodine vacancies are the easiest to passivate,whereas iodine-substituted lead defects are the most challenging to passivate.Our study provides comprehensive theoretical insights and inspiration for the design of anchoring groups in SAMs,contributing to the ongoing development of more efficient inverted perovskite solar cells.

Factors resisting protein adsorption on hydrophilic/hydrophobic self-assembled monolayers terminated with hydrophilic hydroxyl groups

The hydroxyl-terminated self-assembled monolayer(OH-SAM),as a surface resistant to protein adsorption,exhibits substantial potential in applications such as ship navigation and medical implants,and the appropriate strategies for designing anti-fouling surfaces are crucial.Here,we employ molecular dynamics simulations and alchemical free energy calculations to systematically analyze the factors influencing resistance to protein adsorption on the SAMs terminated with single or double OH groups at three packing densities(∑=2.0 nm^(-2),4.5 nm^(-2),and 6.5 nm^(-2)),respectively.For the first time,we observed that the compactness and order of interfacial water enhance its physical barrier effect,subsequently enhancing the resistance of SAM to protein adsorption.Notably,the spatial hindrance effect of SAM leads to the embedding of protein into SAM,resulting in a lack of resistance of SAM towards protein.Furthermore,the number of hydroxyl groups per unit area of double OH-terminated SAM at ∑=6.5 nm^(-2) is approximately 2 to 3 times that of single OH-terminated SAM at ∑=6.5 nm^(-2) and 4.5 nm^(-2),consequently yielding a weaker resistance of double OH-terminated SAM towards protein.Meanwhile,due to the structure of SAM itself,i.e.,the formation of a nearly perfect ice-like hydrogen bond structure,the SAM exhibits the weakest resistance towards protein.This study will complement and improve the mechanism of OH-SAM resistance to protein adsorption,especially the traditional barrier effect of interfacial water.