Development of a novel micro-spray-assembly process for multilayer ultra-thin film formation

A novel micro-spray-assembly process and an automatic device to fabricate multilayer ultra-thin film are introduced. Employing self-assembly monolayer (SAM) technique, ultra-thin film can be assembled by utilizing the micro-spray-assembly device. The thickness and roughness of each monolayer can be controlled by varying various materials attributes, i.e., deposition time, ionic strength, pH value, molecular concentration and by selecting different manufacturing parameters of the automatic device such as spraying rate, size of micro-drop, N₂ flow rate, temperature of N₂ flow.

Effects of deformation-induced heating on bond strength of rolled metal multilayer

The bond strength of various metal multilayers produced by cold rolling of metal foils with different thermal conductivity was investigated. Results indicated that under the same conditions of deformation and surface preparation, the metallic multilayer system with low thermal conductivity exhibited relative high bond strength while high thermal conductivity metal system may fail to be roll-bonded together. The relationship between the deformation-induced localized heating and the bond strength were discussed. The deformation-induced localized heating in the low thermal conductivity metal multilayer systems may provide opportunities for achieving a successful accumulative roll bonding or a “cold roll/heat treatment/cold roll” process to synthesize metallic multilayer materials.

Synthesis, characterization, and multilayer assembly of pH sensitive graphene−polymer nanocomposites

pH sensitive graphene−polymer composites have been prepared by the modification of graphene basal planes with pyrene-terminated poly(2-N,N′-(dimethyl amino ethyl acrylate) (PDMAEA) and poly(acrylic acid) (PAA) via π−π stacking. The pyrene-terminal PDMAEA and PAA were synthesized using reversible addition−fragmentation chain transfer (RAFT) polymerization with a pyrene-functional RAFT agent. The graphene−polymer composites were found to demonstrate phase transfer behavior between aqueous and organic media at different pH values. Atomic force microscopy (AFM) analysis revealed that the thicknesses of the graphene−polymer sheets were approximately 3.0 nm when prepared using PDMAEA (M_n: 6800 and PDI: 1.12). The surface coverage of polymer chains on the graphene basal plane was calculated to be 5.3 × 10⁻¹¹ mol cm⁻² for PDMAEA and 1.3 × 10⁻¹⁰ mol cm⁻² for PAA. The graphene−polymer composites were successfully characterized using X-ray photoelectron spectroscopy (XPS), attenuated total reflection infrared (ATR-IR) spectroscopy, and thermogravimetric analysis (TGA). Self-assembly of the two oppositely charged graphene−polymer composites afforded layer-by-layer (LbL) structures as evidenced by high-resolution scanning electron microscopy (SEM) and quartz crystal microbalance (QCM) measurements.

Design and analysis of a multilayer localized surface plasmon resonance graphene biosensor

This paper describes a multilayer localized surface plasmon resonance (LSPR) graphene biosensor that includes a layer of graphene sheet on top of the gold layer, and the use of different coupled configuration of a laser beam. The study also investigates the enhancement of the sensitivity and detection accuracy of the biosensor through monitoring biomolecular interactions of biotin-streptavidin with the graphene layer on the gold thin film. Additionally, the role of thin films of gold, silver, copper and aluminum in the performance of the biosensor is separately investigated for monitoring the binding of streptavidin to the biotin groups. The performance of the LSPR graphene biosensor is theoretically and numerically assessed in terms of sensitivity, adsorption efficiency, and detection accuracy under varying conditions, including the thickness of biomolecule layer, number of graphene layers and operating wavelength. Enhanced sensitivity and improved adsorption efficiency are obtained for the LSPR graphene biosensor in comparison with its conventional counterpart; however, detection accuracy under the same resonance condition is reduced by 5.2% with a single graphene sheet. This reduction in detection accuracy (signal to noise ratio) can be compensated for by introducing an additional layer of silica doped B2O3 (sdB2O3) placed under the graphene layer. The role of prism configuration, prism angle and the interface medium (air and water) is also analyzed and it is found that the LSPR graphene biosensor has better sensitivity with triangular prism, higher prism angle, lower operating wavelength and larger number of graphene layers. The approach involves a plot of a reflectivity curve as a function of the incidence angle. The outcomes of this investigation highlight the ideal functioning condition corresponding to the best design parameters.

A S-parameters-based detection method for a multilayer SPR biosensor

In this paper, S-parameters investigation of a variable incidence angle multilayer SPR biosensor is presented. Both magnitude and phase of the S-parameters are taken into account in the investigation. The work presented in this paper is the first attempt to apply S-parameters analysis to a multilayer SPR biosensor. The goal is to improve sensitivity through involving S-parameters including their phase values. In addition, further investigation is carried out to understand the relationship between the S-parameters and thickness of biomolecular layer and also the design parameters including the number of graphene layers.

A theoretical analysis for fiber contacts in multilayer nanofibrous assemblies

A theoretical analysis is presented for the estimation of the number of contacts between fibers in random multilayer nanofibrous assemblies with arbitrary fiber diameter and orientation. The statistics of fiber contacts for single-layer nanofiber mats were considered first, and the equations were developed for three-dimensional multilayer nanofibrous assemblies by considering the superposition of the single-layer assemblies. Based on the theoretical approach presented here for multilayer nanofibrous networks, the network porosity, mean fiber diameter and a function of fiber aspect ratio contribute to a model to determine the average number of fiber contacts per unit fiber length in multilayer nanofibrous mats. The theory is studied parametrically and results compared with the work of a model presented by Samson. It is shown that the presented model compared to the existing models is more sensitive with the fiber diameter in the nano-scale. It is also believed that the presented theory for fiber-to-fiber contacts is more realistic and useful for further studies of multilayer nanofibrous assemblies.

Design and analysis of a multilayer surface plasmon resonance biosensor

Designed a multilayer SPR biosensor to improve the detection sensitivity and accuracy simultaneously. Developed a design procedure to identify optimum design parameters for SPR biosensing. Devised a new detection measurement technique based on S-parameters for SPR biosensing.

Experimental verification of theoretical prediction of fiber to fiber contacts in electrospun multilayer nano-microfibrous assemblies: effect of fiber diameter and network porosity

Average number of fiber-to-fiber contacts in a fibrous structure is a prerequisite to investigate the mechanical, optical and transport properties of stochastic nanomicrofibrous networks. In this research work, based on theoretical analysis presented for the estimation of the number of contacts between fibers in electrospun random multilayer nanofibrous assembles, experimental verification for theoretical dependence of fiber diameter and network porosity on the fiber to fiber contacts has been provided. The analytical model formulated is compared with the existing theories to predict the average number of fiber contacts of nanofiber structures. The effect of fiber diameters and network porosities on average number of fiber contacts of nano-microfiber mats has been investigated. A comparison is also made between the experimental and theoretical number of inter-fiber contacts of multilayer electrospun random nanomicrofibrous networks. It has been found that both the fiber diameter and the network porosity have significant effects on the properties of fiber-to-fiber contacts.

Simulation and analysis of a sub-wavelength grating based multilayer surface plasmon resonance biosensor

This paper presents a subwavelength grating based multilayer surface plasmon resonance biosensor (SPRB) which includes a periodic array of subwavelength grating on top of a layer of graphene sheet in the biosensor. The proposed biosensor is named grating-graphene SPRB (GG-SPRB). The aim of the proposed multilayer structure is to improve the sensitivity of the SPRB through monitoring of the biomolecular interactions of DNA hybridization. Significant sensitivity improvement is obtained for the GG-SPRB compared with the conventional SPRB. The result of the numerical investigation of the GG-SPRB is presented and compared with a theoretically developed multilayer matrix formalism, and a good agreement has been observed. In addition, an optimization of the grating dimensions including volume factor, grating depth, grating angle, grating period, and grating geometry (e.g., rectangular, sinusoidal and triangular) is presented. The outcome of the investigation presented in this paper identifies desired functioning conditions corresponding to the best design parameters for the GG-SPRB.

Observation of active sites for oxygen reduction reaction on nitrogen-doped multilayer graphene

Active sites and the catalytic mechanism of nitrogen-doped graphene in an oxygen reduction reaction (ORR) have been extensively studied but are still inconclusive, partly due to the lack of an experimental method that can detect the active sites. It is proposed in this report that the active sites on nitrogen-doped graphene can be determined via the examination of its chemical composition change before and after ORR. Synchrotron-based X-ray photoelectron spectroscopy analyses of three nitrogen-doped multilayer graphene samples reveal that oxygen reduction intermediate OH(ads), which should chemically attach to the active sites, remains on the carbon atoms neighboring pyridinic nitrogen after ORR. In addition, a high amount of the OH(ads) attachment after ORR corresponds to a high catalytic efficiency and vice versa. These pinpoint that the carbon atoms close to pyridinic nitrogen are the main active sites among the different nitrogen doping configurations.

Numerical investigation of a grating and graphene-based multilayer surface plasmon resonance biosensor

A multilayer surface plasmon resonance biosensor (SPRB) incorporating a grating-graphene configuration is investigated for enhanced sensitivity. The numerical analysis of the impact of integrating a periodic array of subwavelength grating on top of a layer of graphene sheet for improving sensitivity is presented. The result of monitoring the biomolecular interactions of DNA hybridization is compared against the outcome of the conventional SPRB, a graphene-based multilayer SPRB, and a multilayer layer grating SPRB, and is mathematically validated. It is demonstrated that the inclusion of a grating and graphene layer on top of the gold thin film is an excellent candidate for a highly sensitive SPRB. To achieve further enhancement of sensitivity, the subwavelength grating is numerically optimized against its geometry including grating configurations (rectangular, sinusoidal, and triangular), grating depth, volume factor, and grating period. © 2014 Taylor & Francis.

A multilayer non-repudiation system: a Suite-B approach

 Security provisioning is an essential part in the design of any communication systems, which becomes more critical for wireless systems. The consideration and comparisons of security algorithms in various Open Systems Interconnection layers is a difficult task, because there are many performance metrics involved. The aim of this novel research article is to present research results for the design of a wireless system revolving around the practical and low-cost implementation of Suite-B algorithms in different layers. Suite-B, promulgated by the National Security Agency, is a set of cryptographic algorithms, including non-repudiation. The end results include the deployment of Suite-B algorithms at the application, transport, and network layers and the protocol flow at each layer.

Multilayer hybrid strategy for phishing email zero-day filtering

The cyber security threats from phishing emails have been growing buoyed by the capacity of their distributors to fine-tune their trickery and defeat previously known filtering techniques. The detection of novel phishing emails that had not appeared previously, also known as zero-day phishing emails, remains a particular challenge. This paper proposes a multilayer hybrid strategy (MHS) for zero-day filtering of phishing emails that appear during a separate time span by using training data collected previously during another time span. This strategy creates a large ensemble of classifiers and then applies a novel method for pruning the ensemble. The majority of known pruning algorithms belong to the following three categories: ranking based, clustering based, and optimization-based pruning. This paper introduces and investigates a multilayer hybrid pruning. Its application in MHS combines all three approaches in one scheme: ranking, clustering, and optimization. Furthermore, we carry out thorough empirical study of the performance of the MHS for the filtering of phishing emails. Our empirical study compares the performance of MHS strategy with other machine learning classifiers. The results of our empirical study demonstrate that MHS achieved the best outcomes and multilayer hybrid pruning performed better than other pruning techniques.

Visual feedback control of a robot in an unknown environment (learning control using neural networks)

In this paper, a visual feedback control approach based on neural networks is presented for a robot with a camera installed on its end-effector to trace an object in an unknown environment. First, the one-to-one mapping relations between the image feature domain of the object to the joint angle domain of the robot are derived. Second, a method is proposed to generate a desired trajectory of the robot by measuring the image feature parameters of the object. Third, a multilayer neural network is used for off-line learning of the mapping relations so as to produce on-line the reference inputs for the robot. Fourth, a learning controller based on a multilayer neural network is designed for realizing the visual feedback control of the robot. Last, the effectiveness of the present approach is verified by tracing a curved line using a 6-degrees-of-freedom robot with a CCD camera installed on its end-effector. The present approach does not necessitate the tedious calibration of the CCD camera and the complicated coordinate transformations.