ABSTRACT
As a technique in artificial intelligence, a convolution neural network model has been utilized to extract average surface roughness from the geometric characteristics of a membrane image featuring micro- and nanostructures. For surface roughness measurement, e.g. atomic force microscopy and optical profiler, the previous methods have been performed to analyze a porous membrane surface on an interest of region with a few micrometers of the restricted area according to the depth resolution. However, an image from the scanning electron microscope, combined with the feature extraction process, provides clarity on surface roughness for multiple areas with various depth resolutions. Through image preprocessing, the geometric pattern is elucidated by amplifying the disparity in pixel intensity values between the bright and dark regions of the image. The geometric pattern of the binary image and magnitude spectrum confirmed the classification of the surface roughness of images in a categorical scatter plot. A group of cropped images from an original image is used to predict the logarithmic average surface roughness values. The model predicted 4.80 % MAPE for the test dataset. The method of extracting geometric patterns through a feature map-based CNN, combined with a statistical approach, suggests an indirect surface measurement. The process is achieved through a bundle of predicted output data, which helps reduce the randomness error of the structural characteristics. A novel feature extraction approach of CNN with statistical analysis is a valuable method for revealing hidden physical characteristics in surface geometries from irregular pixel patterns in an array of images.
ABSTRACT
The potential applications of epoxy-based solid polymer electrolytes are continually expanding because of their versatile characteristics. These characteristics include mechanical rigidity, nonvolatility, nonflammability, and electrochemical stability. However, it is worth noting that pure epoxy-based solid polymer electrolytes inherently exhibit lower ion transport capabilities when compared to traditional liquid electrolytes. Striking a balance between high mechanical integrity and superior ionic conductivity at room temperature poses a significant challenge. In light of this challenge, this review is dedicated to elucidating the fundamental concepts of epoxy-based solid polymer electrolytes. It will explore various preparation techniques, the incorporation of different nanomaterials into epoxy-based solid polymer electrolytes, and an evaluation of their multifunctional properties. This comprehensive evaluation will cover both mechanical and electrical properties with a specific focus on their potential applications in batteries and structural supercapacitors.
ABSTRACT
A microfluidic circuit on a disk platform, also known as lab-on-a-disk, is an integrated system for automated high-throughput screening for biochemical analysis. The microfluidic circuit on a disk performs biochemical analysis through sequential processes such as filtration, separation, detection, and synthesis of reagents. Sequential processes in microfluidic circuits operate through the systematically linked components, which include channels, valves, and chambers. The microchannels should have micrometer-scale for precise micro-volume liquid control in the microfluidic circuit on a disk. However, it is difficult to also consider productivity in the traditional technology. In addition, as the channel length increases, much effort is required to construct the components of the microfluidic circuit in the limited space of the disk. 3D printing is drawing attention as a microfluidic channel fabrication technique in order to overcome the physical limitations of the traditional methods. A new concept of a 3D slope valve has been developed, which performs precise and sequential micro-volume liquid control through centrifugal and gravitational forces. Micro-volumes of liquids in a slope valve-equipped circuit are controlled over a wide range of angular velocities through the control of the valve geometry, types of liquid and volume. For sequential micro-volume of liquid control, three lines of assembled modules are connected to a microfluidic circuit. In the microfluidic circuit with slope valves, the detection of fluorescent dye tagged-VEGF is possible through sequential mixing and reaction processes. As a result, micro-volume liquid is successfully controlled with high accuracy using the 3D microfluidic circuit with a slope valve.
ABSTRACT
A fast-cure carbon fiber/epoxy prepreg was thermoformed against a replicated automotive roof panel mold (square-cup) to investigate the effect of the stacking sequence of prepreg layers with unidirectional and plane woven fabrics and mold geometry with different drawing angles and depths on the fiber deformation and formability of the prepreg. The optimum forming condition was determined via analysis of the material properties of epoxy resin. The non-linear mechanical properties of prepreg at the deformation modes of inter- and intra-ply shear, tensile and bending were measured to be used as input data for the commercial virtual forming simulation software. The prepreg with a stacking sequence containing the plain-woven carbon prepreg on the outer layer of the laminate was successfully thermoformed against a mold with a depth of 20 mm and a tilting angle of 110°. Experimental results for the shear deformations at each corner of the thermoformed square-cup product were compared with the simulation and a similarity in the overall tendency of the shear angle in the path at each corner was observed. The results are expected to contribute to the optimization of parameters on materials, mold design and processing in the thermoforming mass-production process for manufacturing high quality automotive parts with a square-cup geometry.
ABSTRACT
Nickel oxide has been widely used in chemical sensing applications, because it has an excellent p-type semiconducting property with high chemical stability. Here, we present a novel technique of fabricating three-dimensional porous nitrogen-doped nickel oxide nanosheets as a highly sensitive NO2 sensor. The elaborate nanostructure was prepared by a simple and effective hydrothermal synthesis method. Subsequently, nitrogen doping was achieved by thermal treatment with ammonia gas. When the p-type dopant, i.e., nitrogen atoms, was introduced in the three-dimensional nanostructures, the nickel-oxide-nanosheet-based sensor showed considerable NO2 sensing ability with two-fold higher responsivity and sensitivity compared to non-doped nickel-oxide-based sensors.
ABSTRACT
Mechanically robust, flexible, and electrically conductive textiles are highly suitable for use in wearable electronic applications. In this study, highly conductive and flexible graphene/Ag hybrid fibers were prepared and used as electrodes for planar and fiber-type transistors. The graphene/Ag hybrid fibers were fabricated by the wet-spinning/drawing of giant graphene oxide and subsequent functionalization with Ag nanoparticles. The graphene/Ag hybrid fibers exhibited record-high electrical conductivity of up to 15,800 S cm(-1). As the graphene/Ag hybrid fibers can be easily cut and placed onto flexible substrates by simply gluing or stitching, ion gel-gated planar transistors were fabricated by using the hybrid fibers as source, drain, and gate electrodes. Finally, fiber-type transistors were constructed by embedding the graphene/Ag hybrid fiber electrodes onto conventional polyurethane monofilaments, which exhibited excellent flexibility (highly bendable and rollable properties), high electrical performance (µh = 15.6 cm(2) V(-1) s(-1), Ion/Ioff > 10(4)), and outstanding device performance stability (stable after 1,000 cycles of bending tests and being exposed for 30 days to ambient conditions). We believe that our simple methods for the fabrication of graphene/Ag hybrid fiber electrodes for use in fiber-type transistors can potentially be applied to the development all-organic wearable devices.
ABSTRACT
The performance of fiber-reinforced composites is governed not only by the nature of each individual component comprising the composite but also by the interfacial properties between the fiber and the matrix. We present a novel layer-by-layer (LbL) assembly for the surface modification of a glass fiber to enhance the interfacial properties between the glass fiber and the epoxy matrix. Solution-processable graphene oxide (GO) and an aramid nanofiber (ANF) were employed as active components for the LbL assembly onto the glass fiber, owing to their abundant functional groups and mechanical properties. We found that the interfacial properties of the glass fibers uniformly coated with GO and ANF multilayers, such as surface free energy and interfacial shear strength, were improved by 23.6% and 39.2%, respectively, compared with those of the bare glass fiber. In addition, the interfacial adhesion interactions between the glass fiber and the epoxy matrix were highly tunable simply by changing the composition and the architecture of layers, taking advantage of the versatility of the LbL assembly.
ABSTRACT
Development of simple and efficient method for the large-scale production of gaphene/metal nanoparticle hybrids is highly desirable for practical applications, such as catalyst, energy generation and storage, optoelectronics, and sensors. Here, we present a facile approach for the preparation of graphene/gold nanoparticle (AuNP) hybrids by simply mixing the functionalized graphene oxide and AuNPs in aqueous media. Among various functionalized graphene sheets, amine-functionalized graphene oxide (GO-NH2) is used as the hybrid platform due to its synthetic convenience, good dispersity, scalable production with low cost, and positive charge on the surfacce, which could immobilize the AuNPs on the graphene sheets via electrostatic interaction. The synthesized graphene/AgNP hybrids show high surface-enhanced Raman scattering (SERS) sensitivity due to the combined effects of the high contents of amine functional groups on the GO-NH2 surface to adsorb more AgNPs and the electromagnetic enhancement of AgNPs.
ABSTRACT
Carbon fiber reinforced composite has been a good candidate of lightweight structural component in the automotive industry. As fast production speed is essential to apply the composite materials for the mass production area such as automotive components, the high speed liquid composite molding processes have been developed. Fast resin injection through the fiber preform by high pressure is required to improve the production speed, but it often results in undesirable deformations of the fiber preform which causes defectives in size and properties of the final composite products. In order to prevent the undesirable deformation and improve the stability of preform shape, polymer type binder materials are used. More stable fiber preform can be obtained by increasing the amount of binder material, but it disturbs the resin impregnation through the fiber preform. In this study, carbon nanomaterials such as graphene oxide were embedded on the surface of carbon fiber by electrophoretic deposition method in order to improve the shape stability of fiber preform and interfacial bonding between polymer and the reinforcing fiber. Effects of the modified reinforcing fiber were investigated in two respects. One is to increase the binding energy between fiber tows, and the other is to increase the interfacial bonding between polymer matrix and fiber surface. The effects were analyzed by measuring the binding force of fiber preform and interlaminar shear strength of the composite. This study also investigated the high speed liquid molding process of the composite materials composed of polymer matrix and the carbon fiber preforms embedded by carbon nanomaterials. Process parameter such as permeability of fiber preform was measured to investigate the effect of nanoscale surface modification on the macroscale processing condition for composite manufacturing.
ABSTRACT
We report a facile green approach to the synthesis of silver nanoparticles (Ag NPs) on the surface of graphene oxide nanosheets functionalized with mussel-inspired dopamine (GO-Dopa) without additional reductants or stabilizers at room temperature. The resulting hybrid Ag/GO-Dopa exhibits good dispersity and excellent catalytic activity in the reduction of nitroarenes.