Extreme Gradient Boosting to Predict Atomic Layer Deposition for Platinum Nano-Film Coating.

Extreme gradient boosting (XGBoost) is an artificial intelligence algorithm capable of high accuracy and low inference time. The current study applies this XGBoost to the production of platinum nano-film coating through atomic layer deposition (ALD). In order to generate a database for model development, platinum is coated on α-Al2O3 using a rotary-type ALD equipment. The process is controlled by four parameters: process temperature, stop valve time, precursor pulse time, and reactant pulse time. A total of 625 samples according to different process conditions are obtained. The ALD coating index is used as the Al/Pt component ratio through ICP-AES analysis during postprocessing. The four process parameters serve as the input data and produces the Al/Pt component ratio as the output data. The postprocessed data set is randomly divided into 500 training samples and 125 test samples. XGBoost demonstrates 99.9% accuracy and a coefficient of determination of 0.99. The inference time is lower than that of random forest regression, in addition to a higher prediction safety than that of the light gradient boosting machine.

Determination of material constants of vertically aligned carbon nanotube structures in compressions.

Different chemical vapour deposition (CVD) fabrication conditions lead to a wide range of variation in the microstructure and morphologies of carbon nanotubes (CNTs), which actually determine the compressive mechanical properties of CNTs. However, the underlying relationship between the structure/morphology and mechanical properties of CNTs is not fully understood. In this study, we characterized and compared the structural and morphological properties of three kinds of vertically aligned carbon nanotube (VACNT) arrays from different CVD fabrication methods and performed monotonic compressive tests for each VACNT array. The compressive stress-strain responses and plastic deformation were first compared and analyzed with nanotube buckling behaviours. To quantify the compressive properties of the VACNT arrays, a strain density energy function was used to determine their intrinsic material constants. Then, the structural and morphological effects on the quantified material constants of the VACNTs were statistically investigated and analogized to cellular materials with an open-cell model. The statistical analysis shows that density, defect degree, and the moment of inertia of the CNTs are key factors in the improvement of the compressive mechanical properties of VACNT arrays. This approach could allow a model-driven CNT synthesis for engineering their mechanical behaviours.

Vibrational characteristics of graphene sheets elucidated using an elastic network model.

Recent studies of graphene have demonstrated its great potential for highly sensitive resonators. In order to capture the intrinsic vibrational characteristics of graphene, we propose an atomistic modeling method called the elastic network model (ENM), in which a graphene sheet is modeled as a mass-spring network of adjacent atoms connected by various linear springs with specific bond ratios. Normal mode analysis (NMA) reveals the various vibrational features of bi-layer graphene sheets (BLGSs) clamped at two edges. We also propose a coarse-graining (CG) method to extend our graphene study into the meso- and macroscales, at which experimental measurements and synthesis of graphene become practical. The simulation results show good agreement with experimental observations. Therefore, the proposed ENM approach will not only shed light on the theoretical study of graphene mechanics, but also play an important role in the design of highly-sensitive graphene-based resonators.

A transparent and stretchable graphene-based actuator for tactile display.

A tactile display is an important tool to help humans interact with machines by using touch. In this paper, we present a transparent and stretchable graphene-based actuator for advanced tactile displays. The proposed actuator is composed of transparent and compliant graphene electrodes and a dielectric elastomer substrate. Since the electrode is coated onto the appointed region of the substrate layer by layer, only the area of the dielectric elastomer substrate with electrodes bumps up in response to the input voltage, which consequently produces actuation. The actuator is proven to be operable while preserving its electrical and mechanical properties even under 25% stretching. Also, the simple fabrication of the proposed actuator is cost-effective and can easily be extended to multiple arrays. The actuator is expected to be applicable to various applications including tactile displays, vari-focal lenses etc.

Evaluation of multi-layered graphene surface plasmon resonance-based transmission type fiber optic sensor.

Graphene is a zero band-gap semi-metal with remarkable electromagnetic and mechanical characteristics. This study is the first ever attempt to use graphene in the surface plasmon resonance (SPR) sensor as replacement material for gold/silver. Graphene, comprised of a single atomic layer of carbon, is a purely two-dimensional material and it is an ideal candidate for use as a biosensor because of its high surface-to-volume ratio. This sensor is based on the resonance occasion of the surface plasmon wave (SPW) according to the dielectric constants of each metal film and detected material in gas or aqueous phase. Graphene in the SPR sensor is expected to enlarge the range of analyte to bio-aerosols based on the superior electromagnetic properties of graphene. In this study, a SPR-based fiber optic sensor coated with multi-layered graphene is described. The multi-layered graphene film synthesized by chemical vapor deposition (CVD) on Ni substrate was transferred on the sensing region of an optical fiber. The graphene coated SPR sensor is used to analyze the interaction between structured DNA biotin and Streptavidin is analyzed. Transmitted light after passing through the sensing region is measured by a spectrometer and multimeter. As the light source, blue light which of 450 to 460 nm in wavelength was used. We observed the SPR phenomena in the sensor and show the contrary trends between bare fiber and graphene coated fiber. The fabricated graphene based fiber optic sensor shows excellent detection sensitivity of the interaction between structured DNA and Streptavidin.

High-performance graphene-based transparent flexible heaters.

We demonstrate high-performance, flexible, transparent heaters based on large-scale graphene films synthesized by chemical vapor deposition on Cu foils. After multiple transfers and chemical doping processes, the graphene films show sheet resistance as low as ∼43 Ohm/sq with ∼89% optical transmittance, which are ideal as low-voltage transparent heaters. Time-dependent temperature profiles and heat distribution analyses show that the performance of graphene-based heaters is superior to that of conventional transparent heaters based on indium tin oxide. In addition, we confirmed that mechanical strain as high as ∼4% did not substantially affect heater performance. Therefore, graphene-based, flexible, transparent heaters are expected to find uses in a broad range of applications, including automobile defogging/deicing systems and heatable smart windows.

Flow-dependent directional growth of carbon nanotube forests by chemical vapor deposition.

We demonstrated that the structural formation of vertically aligned carbon nanotube (CNT) forests is primarily affected by the geometry-related gas flow, leading to the change of growth directions during the chemical vapor deposition (CVD) process. By varying the growing time, flow rate, and direction of the carrier gas, the structures and the formation mechanisms of the vertically aligned CNT forests were carefully investigated. The growth directions of CNTs are found to be highly dependent on the nonlinear local gas flows induced by microchannels. The angle of growth significantly changes with increasing gas flows perpendicular to the microchannel, while the parallel gas flow shows almost no effect. A computational fluid dynamics (CFD) model was employed to explain the flow-dependent growth of CNT forests, revealing that the variation of the local pressure induced by microchannels is an important parameter determining the directionality of the CNT growth. We expect that the present method and analyses would provide useful information to control the micro- and macrostructures of vertically aligned CNTs for various structural/electrical applications.

A statistical study on nanoparticle movements in a microfluidic channel.

Microfluidic channels have received much attention because they can be used to control and transport nanoscale objects such as nanoparticles, nanowires, carbon nanotubes, DNA and cells. However, so far, practical channels have not been easy to design because they require very expensive fabrication and sensitive experiments. Numerical approaches can be alternatives or supplementary measures to predict the performance of new channels because they efficiently explain nanoscale multi-physics phenomena and successfully solve nanowire alignment and cell adhesion problems. In this paper, a newly updated immersed finite element method that accounts for collision force and Brownian motion as well as fluid-solid interaction is proposed, and is applied to simulate nanoparticle movements in a microfluidic channel. As part of the simulation, Brownian motion effects in a single nanoparticle focusing lens system are examined under different temperature conditions, and the resulting transport efficiencies are discussed. Furthermore, nanoparticle movements in a double focusing lens system are predicted to show the enhancement of focusing efficiency.

Detection of acetone vapor using graphene on polymer optical fiber.

Recently, many studies have been focused on the development of fiber optic sensor systems for various gases and vapors. In the present study, an intrinsic polymer optical fiber (POF) sensor using graphene is described for the purpose of acetone vapor sensing for the first time. Observations on the continuous measurement of acetone vapor in dehydrated air are presented. The principle of operation of sensor transduction relies on the dependence of the reflectance on the optical and geometric properties of the sensitive over layered when the vapor molecules are adsorbed on the graphene film. For the same purpose the CVD synthesized graphene film was transferred on the POF end. The synthesized graphene film thickness was evaluated using atomic force microscopy (AFM), Raman spectroscopy and transmission electron microscopy (TEM). For the preliminary evaluation using volatile organic compounds, we evaluated the sensor performance for acetone. Upon the interaction of the sensor with acetone vapor, the variation in the reflected light was monitored as a function of the acetone concentration. The sensor response shows a significant change in sensitivity as compared with the POF probe without a graphene coating. The present sensor shows a satisfactory response upon exposure to various concentrations of acetone vapor from 44 ppm to 352 ppm. To the best of our knowledge, the use of graphene film along with POF for the sensing of volatile organic compounds has not previously been reported.

Prediction of anisotropic behavior of nano/micro composite based on damage mechanics with cell modeling.

New advanced composite materials have recently been of great interest. Especially, many researchers have studied on nano/micro composites based on matrix filled with nano-particles, nano-tubes, nano-wires and so forth, which have outstanding characteristics on thermal, electrical, optical, chemical and mechanical properties. Therefore, the need of numerical approach for design and development of the advanced materials has been recognized. In this paper, finite element analysis based on multi-resolution continuum theory is carried out to predict the anisotropic behavior of nano/micro composites based on damage mechanics with a cell modeling. The cell modeling systematically evaluates constitutive relationships from microstructure of the composite material. Effects of plastic anisotropy on deformation behavior and damage evolution of nano/micro composite are investigated by using Hill's 48 yield function and also compared with those obtained from Gurson-Tvergaard-Needleman isotropic damage model based on von Mises yield function.

Development and calibration of differential mobility analyzer for 20 to 80 nm particles under low pressure conditions.

The vienna-type differential mobility analyzer (DMA) was developed for the measurement of wide-range nm-sized particles under low-pressure conditions (2.9-8 kPa) with the faraday cup electrometer (FCE). The length, inner and outer diameter of DMA are calculated as a function of flow rate, applied voltage, pressure, and particle diameter to avoide breakdown in DMA. The algorithm for the diffusion transfer function of the DMA was successfully developed and verified by comparing the numerical and experimental results. The DMA was calibrated via the tandem DMA (TDMA) method which using two DMA in parallel. The inversion algorithm was applied to the size distribution obtained from the current of the FCE. The calibration experiment was performed with 1% NaCl particles under atmospheric and low-pressure conditions. The calibration result showed that the development of the DMA was successful as it was able to measure 20- to 80-nm paricles under low-pressure conditions with various flow rates (0.1-0.5 l/min).

Numerical simulation of a nanoparticle focusing lens in a microfluidic channel by using immersed finite element method.

Lap-on-a-chip system is one of challenging parts in nano and bio engineering fields, for instance, microfluidic channels on the chip are useful for selecting a target particle and mass transferring of boiomolecules in fluid. However, since experimental approach is highly expensive both in time and cost, alternative reliable methods are required to conceive optimized channels. The purpose of this research is to simulate a nanoparticle focusing lens in a microfluidic channel from nanoparticle control point of view. A promising immersed finite element method is expanded to estimate the path of randomly moving nanoparticles through a focusing lens. The channel flow is assumed as incompressible viscous fluid and Brownian motion effects as well as initial position of particle are quantitatively examined. As a representative result, while the nanoparticles with/without Brownian motion were focused along the center of the channel, the concentration factor representing focusing efficiency was calculated. Therefore, it is expected that the newly proposed numerical method considering Brownian motion will be efficiently applicable to design the microfluidic channel containing various particles, molecules and so forth in the near future.

Optical characterization of DNA-wrapped single walled carbon nanotubes irradiated with ultraviolet light.

We have investigated the effect of ultraviolet irradiation exposure time on single walled carbon nanotubes (SWNTs) wrapped with single-strand DNA (ssDNA) using absorption spectroscopy and Raman spectroscopy. The absorbance value of ssDNA-wrapped SWNTs in aqueous media was found to be decreased, where as SWNTs wrapped with ssDNA with polyd(T) were aggregated under UV irradiation.

Effect of slip boundary condition on the design of nanoparticle focusing lenses.

The importance of nanoparticles as a building block for novel application has been emphasized in various fields. Especially, nanoparticle beam has been widely used to measure particle size distribution, synthesize materials, and generate micro-patterns, as it can enhance the measurement resolution and transport efficiency. The aerodynamic lens system has been developed to focus particles in a certain size range. The manufacturing of nanoparticles in gas phase is typically performed at the low pressure conditions and the design and simulation of lens at low pressure have been steadily reported. The computational fluid dynamics (CFD) has been utilized to analyze the flow field and obtain particle trajectories. However, previous work has used no-slip boundary condition at low pressure. This paper describes the lens design and simulation with slip boundary condition at low pressure (approximately 1 Torr). The design of lens is discussed on the basis of the Wang et al.'s guidelines and the commercial code FLUENT is used for simulation. The results of this study show that the difference of particle beam radius between no-slip and slip boundary conditions is 0.03 approximately 0.9 mm for particle size ranging from 3 to 200 nm with Brownian diffusion and that the transport efficiency is slightly higher with slip boundary condition.

Development of user customized smart keyboard using Smart Product Design-Finite Element Analysis Process in the Internet of Things.

In a hyper-connected society, IoT environment, markets are rapidly changing as smartphones penetrate global market. As smartphones are applied to various digital media, development of a novel smart product is required. In this paper, a Smart Product Design-Finite Element Analysis Process (SPD-FEAP) is developed to adopt fast-changing tends and user requirements that can be visually verified. The user requirements are derived and quantitatively evaluated from Smart Quality Function Deployment (SQFD) using WebData. Then the usage scenarios are created according to the priority of the functions derived from SQFD. 3D shape analysis by Finite Element Analysis (FEA) was conducted and printed out through Rapid Prototyping (RP) technology to identify any possible errors. Thus, a User Customized Smart Keyboard has been developed using SPD-FEAP.

Normal mode analysis of Zika virus.

In recent years, Zika virus (ZIKV) caused a new pandemic due to its rapid spread and close relationship with microcephaly. As a result, ZIKV has become an obvious global health concern. Information about the fundamental viral features or the biological process of infection remains limited, despite considerable efforts. Meanwhile, the icosahedral shell structure of the mature ZIKV was recently revealed by cryo-electron microscopy. This structural information enabled us to simulate ZIKV. In this study, we analyzed the dynamic properties of ZIKV through simulation from the mechanical viewpoint. We performed normal mode analysis (NMA) for a dimeric structure of ZIKV consisting of the envelope proteins and the membrane proteins as a unit structure. By analyzing low-frequency normal modes, we captured intrinsic vibrational motions and defined basic vibrational properties of the unit structure. Moreover, we also simulated the entire shell structure of ZIKV at the reduced computational cost, similar to the case of the unit structure, by utilizing its icosahedral symmetry. From the NMA results, we can not only comprehend the putative dynamic fluctuations of ZIKV but also verify previous inference such that highly mobile glycosylation sites would play an important role in ZIKV. Consequently, this theoretical study is expected to give us an insight on the underlying biological functions and infection mechanism of ZIKV.

The evaluation of individual dispersion of single-walled carbon nanotubes using absorption and fluorescence spectroscopic techniques.

We have investigated the degree of dispersion of single-walled carbon nanotubes (SWNTs) in solution using laser spectroscopic techniques. SWNTs were suspended in aqueous media using a sodium dodecyl sulfate (SDS) surfactant. SWNTs with different dispersion states were prepared by controlling the intensity and duration of sonication and centrifugation. The absorption and fluorescence spectroscopic techniques were employed to characterize the different dispersion state of the prepared samples. Nanotube suspensions with better dispersion showed higher fluorescence and sharper absorption peaks. The fluorescence data were characterized as a function of the nanotube chirality, and absorption peak shifts were analyzed depending on the first and second van Hove singularities (vHs) of semiconducting nanotubes.

Normal mode-guided transition pathway generation in proteins.

The biological function of proteins is closely related to its structural motion. For instance, structurally misfolded proteins do not function properly. Although we are able to experimentally obtain structural information on proteins, it is still challenging to capture their dynamics, such as transition processes. Therefore, we need a simulation method to predict the transition pathways of a protein in order to understand and study large functional deformations. Here, we present a new simulation method called normal mode-guided elastic network interpolation (NGENI) that performs normal modes analysis iteratively to predict transition pathways of proteins. To be more specific, NGENI obtains displacement vectors that determine intermediate structures by interpolating the distance between two end-point conformations, similar to a morphing method called elastic network interpolation. However, the displacement vector is regarded as a linear combination of the normal mode vectors of each intermediate structure, in order to enhance the physical sense of the proposed pathways. As a result, we can generate more reasonable transition pathways geometrically and thermodynamically. By using not only all normal modes, but also in part using only the lowest normal modes, NGENI can still generate reasonable pathways for large deformations in proteins. This study shows that global protein transitions are dominated by collective motion, which means that a few lowest normal modes play an important role in this process. NGENI has considerable merit in terms of computational cost because it is possible to generate transition pathways by partial degrees of freedom, while conventional methods are not capable of this.

Dynamic characteristics of a flagellar motor protein analyzed using an elastic network model.

At the base of a flagellar motor, its rotational direction and speed are regulated by the interaction between rotor and stator proteins. A switching event occurs when the cytoplasmic rotor protein, called C-ring, changes its conformation in response to binding of the CheY signal protein. The C-ring structure consists of FliG, FliM, and FliN proteins and its conformational changes in FliM and FliG including HelixMC play an important role in switching the motor direction. Therefore, clarifying their dynamic properties as well as conformational changes is a key to understanding the switching mechanism of the motor protein. In this study, to elucidate dynamic characteristics of the C-ring structure, both harmonic (intrinsic vibration) and anharmonic (transition pathway) analyses are conducted by using the symmetry-constrained elastic network model. As a result, the first three normal modes successfully capture the essence of transition pathway from wild type to CW-biased state. Their cumulative square overlap value reaches up to 0.842. Remarkably, it is also noted from the transition pathway that the cascade of interactions from the signal protein to FliM to FliG, highlighted by the major mode shapes from the first three normal modes, induces the reorientation (∼100° rotation of FliGC5) of FliG C-terminal that directly interacts with the stator protein. Presumably, the rotational direction of the motor protein is switched by this substantial change in the stator-rotor interaction.

The DNA hybridization assay using single-walled carbon nanotubes as ultrasensitive, long-term optical labels.

Single walled carbon nanotubes (SWNTs) exhibit strong Raman signals as well as fluorescence emissions in the near infrared region. Such signals do not blink or photobleach under prolonged excitation, which is an advantage in optical nano-biomarker applications. In this paper, we present single-stranded DNA conjugated SWNT probes to locate a particular sequence of DNA within a complex genome. Chromosomal DNAs of human fibroblasts and Escherichia coli are used as a target and a control, respectively. Southern blotting, which uses photostable Raman signals of nanotubes instead of fluorescent dyes, demonstrates excellent sensitivity and specificity of the probes. The results show that SWNTs may be used as generic nano-biomarkers for the precise detection of specific kinds of genes.