Marangoni Flow Driven via Hole Structure of Soluble Acene–Polymer Blends for Selective Nitrogen Dioxide Sensing

The correlations between semiconductor type and gas sensing properties in soluble acene/polymer blends have not yet been examined. Here, the phase separation mechanism in pseudo-liquid phase blend film is investigated and an unusual solid-state morphology that is effective for amperometric gas sensing performance is demonstrated. In 6,13-bis(triisopropylsilylethynyl) pentacene (TIPS–pentacene)/poly(fluorine-co-triarylamine) (PTAA) blend, two phases are uniformly mixed, without being completely phase-separated due to the similar solubility and surface tension. On the other hand, in 2,8-difluoro-5,11-bis(triethylsilylethynyl) anthradithiophene (diF–TES ADT)/PTAA blend, the diF−TES ADT molecules are segregated both at the air–film, and film–substrate interfaces, and subsequently crystallized with a high degree of crystal perfection. In the meanwhile, Marangoni-flow induces crater-like via hole structure of PTAA at the middle layer. In situ measurement of (ultraviolet–visible) UV–vis absorption spectra and computational calculation reveal kinetics of liquid–solid–crystal transition in relation to the functional groups of soluble acene. Interestingly, flow driven hole structure of PTAA in diF–TES ADT/PTAA blend film allows the target NO₂ gas to selectively penetrate the channel region, thereby enhancing sensitivity toward NO₂, while decreasing affinity with other gases. The results provide protocols for fabricating highlperformance field-effect transistors and gas sensors in a blending system.     

Continuous point projection to planar freeform curves using spiral curves

We present an efficient algorithm for projecting a continuously moving query point to a family of planar freeform curves. The algorithm is based on the one-sided Hausdorff distance from the trajectory curve (of the query point) to the planar curves. Using a bounding volume hierarchy (BVH) of the planar curves, we estimate an upper bound [`(h)]\overline{h} of the one-sided Hausdorff distance and eliminate redundant curve segments when they are more than distance [`(h)]\overline{h} away from the trajectory curve. Recursively subdividing the trajectory curve and repeating the same elimination procedure to the BVH of the remaining curves, we can efficiently determine where to project the moving query point. The explicit continuous point projection is then interpreted as a curve reparameterization problem, for which we propose a few simple approximation techniques. Using several experimental results, we demonstrate the effectiveness of the proposed approach.     

The roles of intrinsic motivators and extrinsic motivators in promoting e-learning in the workplace: A case from South Korea

Acceptance of e-learning by employees is critical to the successful implementation of e-learning in the workplace. To explain why employees might accept the e-learning technology, motivational factors must be considered. Although the Unified Theory of Acceptance and Use of Technology (UTAUT) has identified many variables to understand employees’ motivation to use e-learning, current literature cannot conclude the roles of extrinsic and intrinsic motivators in the technology adoption process. Consequently, organizations often overestimate the effects of extrinsic motivators in promoting e-learning while ignoring employees’ intrinsic motivation. To examine the effect difference between the two motivational factors, this study surveyed 261 employees in a food service company in South Korea with the UTAUT instrument. Upon analyzing 226 valid cases with LISREL, the findings revealed that intrinsic motivators (effort expectancy, attitudes, and anxiety) affected employees’ intention to use e-learning in the workplace more strongly than did the extrinsic motivators (performance expectancy, social influence, and facilitating conditions). Furthermore, the effects of intrinsic motivators mediated the effect of extrinsic motivators. Implications of this study are important for both researchers and practitioners.     

Dynamic fuzzy neural networks-a novel approach to functionapproximation

In this paper, an architecture of dynamic fuzzy neural networks (D-FNN) implementing Takagi-Sugeno-Kang (TSK) fuzzy systems based on extended radial basis function (RBF) neural networks is proposed. A novel learning algorithm based on D-FNN is also presented. The salient characteristics of the algorithm are: 1) hierarchical on-line self-organizing learning is used; 2) neurons can be recruited or deleted dynamically according to their significance to the system's performance; and 3) fast learning speed can be achieved. Simulation studies and comprehensive comparisons with some other learning algorithms demonstrate that a more compact structure with higher performance can be achieved by the proposed approach.     

Electrical Conductivity Gradient Based on Heterofibrous Scaffolds for Stable Lithium‐Metal Batteries

The inability to guide the nucleation locations of electrochemically deposited Li has long been considered the main factor limiting the utilization of high‐energy‐density Li‐metal batteries. In this study, an electrical conductivity gradient interfacial host comprising 1D high conductivity copper nanowires and nanocellulose insulating layers is used in stable Li‐metal anodes. The conductivity gradient system guides the nucleation sites of Li‐metal to be directed during electrochemical plating. Additionally, the controlled parameter of the intermediate layer affects the highly stable Li‐metal plating. The electrochemical behavior is confirmed through experiments associated with the COMSOL Multiphysics simulation data. The distributed Li‐ion reaction flux resulting from the controlled electrical conductivity enables stable cycling for more than 250 cycles at 1 mA cm^?2. The gradient system effectively suppresses dendrite growth even at a high current density of 5 mA cm^?2 and ensures Li plating and stripping with ultra‐long‐term stability. To demonstrate the high‐energy‐density full‐cell application of the developed anode, it is paired with the LiNi_0.8Co_0.1Mn_0.1O₂ cathode. The cells demonstrate a high capacity retention of 90% with an extremely high Coulombic efficiency of 99.8% over 100 cycles. These results shed light on the formidable challenges involved in exploiting the engineering aspects of high‐energy‐density Li‐metal batteries.     

Flexible and Semi‐Transparent Ultra‐Thin CIGSe Solar Cells Prepared on Ultra‐Thin Glass Substrate: A Key to Flexible Bifacial Photovoltaic Applications

For applications to semi‐transparent and/or bifacial solar cells in building‐integrated photovoltaics and building‐applied photovoltaics, studies are underway to reduce the processing cost and time by decreasing the thickness of Cu(In_1?x,Ga_x)Se₂ (CIGSe) absorber to the ultra‐thin scale (≤500 nm). To dynamically and affordably meet the growing demand for electric power, daylighting, and architectural aesthetics of buildings in urban area, flexible semi‐transparent ultra‐thin (F‐STUT) CIGSe solar cells are proposed on flexible ultra‐thin glass (UTG) and compared with rigid semi‐transparent ultra‐thin (STUT) CIGSe solar cells fabricated on soda‐lime glass (SLG). At all the tested deposition temperatures of CIGSe, the F‐STUT CIGSe solar cells exhibit superior performance compared to the rigid STUT CIGSe solar cells. Furthermore, through realistic measurement under ≈1.3‐sun illumination, maximum bifacial power conversion efficiency of 11.90% and 13.23% are obtained for SLG and UTG, respectively. The major advantages of using UTG instead of SLG are not only the intrinsic characteristics of UTG, such as flexibility and high transmittance, but also collateral benefits such as the larger CIGSe grain size at the deposition temperature, better CIGSe crystalline quality, more precise controllability of the alkali element, and reduced thickness of the interfacial GaO_x layer, which enhance the photovoltaic parameters.     

Multiarray Nanopattern Electronic Nose (E‐Nose) by High‐Resolution Top‐Down Nanolithography

An electronic nose (E‐nose) is an artificial sensing device that mimics the human olfactory system using a multiarray sensor system. However, since the design and fabrication of multiarray sensing channels are significantly limited because of the requirement of time‐consuming and nonuniversal processes, the development of commercializable and high‐throughput fabrication approaches are critically required. Herein, high‐resolution top‐down lithography is developed for E‐nose fabrication for the first time. Five different metal oxide semiconductor (MOS) nanopattern channels (NiO, CuO, Cr₂O₃, SnO₂, and WO₃) are fabricated into multiarray sensors with high‐throughput using a unique lithographic approach that utilizes the sputtering of grains of the metals via low‐energy ion plasma bombardment. The nanopattern channels show i) high‐resolutions (15 nm scale), ii) high‐aspect‐ratios (11; 14 nm width and 150 nm height), and iii) ultrasmall grains (5.1 nm) with uniformity on a cm² scale, resulting in high sensitivity toward the target analytes. The E‐nose system, which is composed of five MOS nanopattern channels, can successfully distinguish seven different hazardous analytes, including volatile organic compounds and nitrogen‐containing compounds. It is expected that this unique lithography approach can provide a simple and reliable method for commercializable channel fabrication, and the E‐noses can have further applications in real‐life situations.     

2D Perovskite Seeding Layer for Efficient Air‐Processable and Stable Planar Perovskite Solar Cells

Despite the record power conversion efficiencies, inverted perovskite solar cells (PSCs) are still looking to overcome the challenge of moisture instability. This is mitigated by introducing 2D perovskite at the base of a 3D perovskite via coating of ethylenediamine bications on top of the hole transport layer of p–i–n planar configured devices. The cations induce thin 2D perovskite growth beneath the 3D perovskite to create a 2D/3D hybrid active layer. This 2D layer in turn acts as a template for the growth of relatively large grains compared to that of pure 3D perovskite films. This stems from the merging of grain boundaries. The hydrophobicity of the 2D/3D perovskite film consequently improves, as evidenced by a large contact angle of 93.1°, compared to 68.9° for the 3D perovskite film. Because there are fewer defects sourced from grain boundaries, the air‐processed 2D/3D perovskite devices yield a high power conversion efficiency of 15.02%, compared to 13.10% from 3D perovskite devices. When stored in moderately humid environment of 55% relative humidity, the 2D/3D devices exhibit longer stabilities, with 75% of their power conversion efficiencies maintained after 150 h, compared to a total loss in efficiency for 3D device in the same time frame.     

Robust fuzzy controller for large-scale nonlinear systems using decentralized static output-feedback

This paper addresses a robust fuzzy control problem for an uncertain large-scale nonlinear system using decentralized static output-feedback scheme for both continuous-time and discrete-time cases. In both cases, sufficient design conditions are derived for robust asymptotic stabilization in terms of linear matrix inequalities (LMIs), and are therefore easily tractable by convex optimization. An illustrative example, a two-area power system with parametric uncertainties and the valve-position limit nonlinearity is provided to verify the effectiveness of the proposed technique.