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Background Numerous studies have evaluated the rupture risk of intracranial aneurysms using morphological parameters because of their good predictive capacity. However, the limitation of current morphological parameters is that they do not always allow evaluation of irregularities of intracranial aneurysms. The purpose of this study is to propose a new morphological parameter that can quantitatively describe irregularities of intracranial aneurysms and to evaluate its performance regarding rupture risk prediction. Methods In a retrospective study, conventional morphological parameters (aspect ratio, bottleneck ratio, height-to-width ratio, volume to ostium ratio, and size ratio) and a newly proposed morphological parameter (mass moment of inertia) were calculated for 125 intracranial aneurysms (80 unruptured and 45 ruptured aneurysms). Additionally, hemodynamic parameters (wall shear stress and strain) were calculated using computational fluid dynamics and fluid--structure interaction. Artificial neural networks trained with each parameter were used for rupture risk prediction. Results All components of the mass moment of inertia (Ixx, Iyy, and Izz) were significantly higher in ruptured cases than in unruptured cases (p values for Ixx, Iyy, and Izz were 0.032, 0.047, and 0.039, respectively). When the conventional morphological and hemodynamic parameters as well as the mass moment of inertia were considered together, the highest performance for rupture risk prediction was obtained (sensitivity 96.3%; specificity 85.7%; area under the receiver operating characteristic curve 0.921). Conclusions The mass moment of inertia would be a useful parameter for evaluating aneurysm irregularity and hence its risk of rupture. The new approach described here may help clinicians to predict the risk of aneurysm rupture more effectively. [ABSTRACT FROM AUTHOR]

Background Cerebral aneurysms should be treated before rupture because ruptured aneurysms result in serious disability. Therefore, accurate prediction of rupture risk is important and has been estimated using various hemodynamic factors. Objective To suggest a new way to predict rupture risk in cerebral aneurysms using a novel deep learning model based on hemodynamic parameters for better decision-making about treatment. Methods A novel convolutional neural network (CNN) model was used for rupture risk prediction retrospectively of 123 aneurysm cases. To include the effect of hemodynamic parameters into the CNN, the hemodynamic parameters were first calculated using computational fluid dynamics and fluid--structure interaction. Then, they were converted into images for training the CNN using a novel approach. In addition, new data augmentation methods were devised to obtain sufficient training data. A total of 53,136 images generated by data augmentation were used to train and test the CNN. Results The CNNs trained with wall shear stress (WSS), strain, and combination images had area under the receiver operating characteristics curve values of 0.716, 0.741, and 0.883, respectively. Based on the cut-off values, the CNN trained with WSS (sensitivity: 0.5, specificity: 0.79) or strain (sensitivity: 0.74, specificity: 0.71) images alone was not highly predictive. However, the CNN trained with combination images of WSS and strain showed a sensitivity and specificity of 0.81 and 0.82, respectively. Conclusion CNN-based deep learning algorithm using hemodynamic factors, including WSS and strain, could be an effective tool for predicting rupture risk in cerebral aneurysms with good predictive accuracy. [ABSTRACT FROM AUTHOR]

Highly sensitive capacitive pressure sensors with poly(vinylidenefluoride-co-trifluoroethylene) (P(VDF-TrFE)) dielectric layers were prepared. The dielectric layers were directly produced by electrospinning P(VDF-TrFE) nanofibers for various spinning times. A longer spinning time enhanced the deformability of the electrospun P(VDF-TrFE) layers, resulting in higher sensitivity owing to larger changes in the deformation of the dielectric layer. One of the capacitive pressure sensors showed a high sensitivity of 2.81 kPa-1 at a pressure ≤0.12 kPa, a good response time of 42 ms, and small hysteresis. The sensitivity of the sensor was five times higher than that of a typical capacitive pressure sensor. The fabricated pressure sensor could detect a tiny water droplet as light as 7mg. It is expected that the electrospun P(VDF-TrFE) nanofibers can be used as sensing materials for highly sensitive pressure sensors in wearable electronics applications. [ABSTRACT FROM AUTHOR]

In this study, a honeycomb-like nanofiber based triboelectric nanogenerator (HN-TENG) is presented. In order to fabricate the honeycomb-like nanofiber, we utilized self-assembly of electrospun poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) nanofibers. The honeycomb-like P(VDF-TrFE) nanofiber network was directly produced via electrospinning without any additional processing. The HN-TENG showed a maximum voltage, current, and power density of 160 V, 17 µA, and 1.6W/m2, respectively. The power density was enhanced more than twofold as compared with a typical flat nanofiber network based TENG due to the large surface area and high surface roughness of the honeycomb structure. Finally, we verified that HN-TENG has the potential to be used for practical applications by driving 100 light emitting diodes and charging capacitors. [ABSTRACT FROM AUTHOR]

The effect of the needle shape on electrohydrodynamic (EHD) printing was investigated by comparing flat outlet needles and hypodermic needles. Line fabrication was performed to confirm the tendency of jetting stability and the printed line width with various driving voltage and stage speed by using Ag nanoparticle ink as a jetting solution on a hydrophobic surface. We verified that the hypodermic needle greatly improves the resolution in EHD printing. The ink slips down the inner wall of the hypodermic needle, and a very small meniscus is generated at the tip of the needle. Due to this phenomenon, high-resolution printing can be accomplished. The narrowest line that was fabricated using a hypodermic needle has a line width of 0.7 im, and it is smaller than 1% of the needle inner diameter. [ABSTRACT FROM AUTHOR]

The effect of the needle shape on electrohydrodynamic (EHD) printing was investigated by comparing flat outlet needles and hypodermic needles. Line fabrication was performed to confirm the tendency of jetting stability and the printed line width with various driving voltage and stage speed by using Ag nanoparticle ink as a jetting solution on a hydrophobic surface. We verified that the hypodermic needle greatly improves the resolution in EHD printing. The ink slips down the inner wall of the hypodermic needle, and a very small meniscus is generated at the tip of the needle. Due to this phenomenon, high-resolution printing can be accomplished. The narrowest line that was fabricated using a hypodermic needle has a line width of 0.7 pm, and it is smaller than 1% of the needle inner diameter. [ABSTRACT FROM AUTHOR]

A three-dimensional finite element analysis is performed to investigate the effects of fiber arrangements on the residual thermal stresses in unidirectional composites of various fiber volume fractions (FVFs). The fiber arrangements include the regular fiber arrays (square and hexagonal arrays) and a random fiber array. Normal, tangential, and shear stresses at the fiber--matrix interface are first obtained using unit cells of the regular square and hexagonal fiber arrays. To simulate better real fiber arrangements, random fiber distribution is modeled and analyzed using a finite element analysis. Statistical distributions of residual thermal stresses are obtained for various FVFs and compared with the results from regular fiber arrays. The effects of constituent material properties of composites on thermal stresses are also taken into consideration. The results indicate that the random arrangement of fibers has a significant influence on residual thermal stresses especially at high FVFs. The mode stresses of the random fibers are well estimated using the square array whereas the mean stresses are better predicted from the hexagonal array. It is shown that predicted coefficients of thermal expansion are not influenced by the microstructure of composites. [ABSTRACT FROM AUTHOR]

The micromechanical approach was used to investigate the interfacial strain distributions of a unidirectional composite under transverse loading in which fibers were usually found to be randomly packed. Representative volume elements (RVEs) for the analysis were composed of both periodic fiber arrays, such as a square array and a hexagonal array, and a random fiber array. The finite element analysis was performed to analyze the normal, tangential, and shear strains at the interface. In order to verify the RVE for describing a random fiber array, the generated RVE was statistically compared with the one constructed from typical images of a transverse cross-section of a unidirectional composite. Since the strata distributions at the interface experienced periodic characteristics along with its circumference, the Fourier series approximation with proper coefficients was utilized to evaluate the strain distributions at the interface for the periodic and random fiber arrays with respect to fiber volume fractions. From the analysis, it was found that the random arrangement of fibers had a significant influence on the strain distribution tit the interface, and the strain distribution in the periodic arrays was one of special cases of that in the random array. [ABSTRACT FROM AUTHOR]

During the curing process of thick glass/epoxy composite laminates, substantial amounts of temperature lag and overshoot at the center of the laminates is usually experienced due to the large thickness and low thermal conductivity of the glass/epoxy composites, which require a long time for full and uniform consolidation. In this work, the temperature profiles of a 20 mm thick unidirectional glass/epoxy laminate during an autoclave vacuum bag process were measured and compared with the numerically calculated results. For the calculation of distributions of the temperature, degree of cure, resin pressure, exothermic heat and required time for full consideration by three-dimensional finite element analyses, the effects of convective heat transfer coefficient and geometry of mold and bagging assembly on the temperature profiles were taken into consideration. Based on the numerical results, an optimized cure cycle with the cooling and reheating steps was developed by minimizing the objective function to reduce the temperature overshoot in the composite. From the experimental and numerical results, it was found that the measured temperature profiles were in good agreement with the numerical ones, and conventional cure cycles recommended by prepreg manufacturers for thin laminates should be modified to prevent temperature overshoot and to obtain full consolidation. [ABSTRACT FROM AUTHOR]

We demonstrate the effects of overlap condition and surface wettability of dielectric layers on the drying process and crystalline structure of inkjet-printed semiconductor layers. 6,13-bis(triisopropylsilylethynyl) pentacene (TIPS pentacene) was utilized to inkjet-print the semiconductor layer. Using various overlap conditions, semiconductor layers were inkjet-printed on dielectric layers with different surface wettabilities. It is observed that crystal growth and the resulting crystalline structures in inkjet-printed semiconductor layers are primarily determined by evaporation behavior, particularly the contact line movement of the drying semiconductor layers, which can be controlled via the overlap condition. With inappropriate overlap conditions, randomly oriented TIPS pentacene crystalline structures are generated in the semiconductor layer through irregular contact line recession. One-dimensionally oriented TIPS pentacene crystal structures can be obtained using the optimized overlap condition of 50% as a result of the uniform contact line movement. Relatively hydrophobic dielectric layers help to generate good crystallinity in the semiconductor layer. All-inkjet-printed organic thin film transistors (OTFTs) with well-oriented TIPS pentacene crystalline structures in the semiconductor layer show a high field effect mobility of ~0.1 cm2 V−1s−1, suggesting that, when printing inkjet semiconductor layers, the overlap condition and surface wettability of the dielectric layer are important factors for generating a well-oriented crystalline structure and thereby fabricating high-performance all-inkjet-printed OTFTs. [ABSTRACT FROM AUTHOR]

The paper aims to investigate the influence of bottom electrode configurations in all-inkjet-printed organic thin film transistors (OTFTs) on crystalline structures of semiconductor layers as well as the electrical performance of OTFTs. Two different types of all-inkjet-printed OTFTs were fabricated: one type with a new bottom-top contact configuration and the other type with a conventional bottom-bottom contact configuration. The crystal growth of semiconductor layer and the electrical characteristics of OTFTs were evaluated and compared between two different bottom electrode configurations. The resulting crystalline structures of semiconductor layers are mostly affected by the evaporation process of semiconductor layer. Randomly-oriented crystalline structures are generated in the semiconductor layer with a conventional bottom-bottom contact configuration due to irregular evaporation. However, a new bottom-top contact configuration leads to well-oriented crystalline structures because of controlled contact line movement. The average mobility of OTFTs with well-oriented crystalline structures is about 11 times as high as that with randomly-oriented crystalline structures. [ABSTRACT FROM AUTHOR]