Properties of nanoporous organosilicate hybrid thin films with a bimodal pore size distribution

Low dielectric poly[methylsilsesquioxane‐ran‐trifluoropropylsilsesquioxane‐ran‐(2,4,6,8‐tetramethyl‐2,4,6,8‐tetraethylenecyclotetrasiloxane)silsesquioxane]s {P[M‐ran‐TFP‐ran‐(TCS)]SSQs} having various compositions were synthesized using trifluoropropyl trimethoxysilane, methyl trimethoxysilane and 2,4,6,8‐tetramethyl‐2,4,6,8‐tetra(trimethoxysilylethyl)cyclotetrasiloxane. The chemical composition of the polymers and the content of SiOH end‐groups were controlled by adjusting the reaction conditions, and they were characterized by ¹H‐NMR. The thermally decomposable trifluoropropyl groups on the P[M‐ran‐TFP‐ran‐(TCS)]SSQ backbone and heptakis(2,3,6‐tri‐O‐methyl)‐β‐cyclodextrin (CD) were employed as pore generators. The dielectric constants of the porous CD/P[M‐ran‐TFP‐ran‐(TCS)]SSQ films were in the range 2.0–2.7 (at 100 kHz) depending on the concentration of the porogens, and showed no change over 4 days under aqueous conditions. The pore size of the films showed a bimodal distribution, with diameters of ca 0.5–1.0 nm for those originating from the trifluoropropyl groups and 1.7 nm from the CD. The elastic modulus and hardness of the 30 vol% CD‐blended film with a dielectric constant of 2.26 were 2.40 and 0.38 GPa, respectively, as determined by a nanoindenter. Copyright © 2005 Society of Chemical Industry     

A positive‐working photosensitive polyimide based on thermal cross‐linking and acidolytic cleavage

A novel positive‐working photosensitive polyimide (PSPI) based on a poly(hydroxyimide) (PHI), a crosslinking agent having vinyl ether groups, and a photoacid generator (PAG) was prepared. The PHI as a base resin of the three‐component PSPI was synthesized from 4,4′‐oxydiphthalic anhydride and 2,2′‐bis(3‐amino‐4‐hydroxyphenyl)hexafluoropropane through ring‐opening polymerization and subsequent thermal cyclization. 2,2′‐bis(4‐(2‐(vinyloxy)ethoxy)phenyl)propane (BPA‐DEVE) was used as a vinylether compound and diphenyliodonium 5‐hydroxynaphthalene‐1‐sulfonate was used as a PAG. The phenolic hydroxyl groups of the PHI and the vinyl ether groups of BPA‐DEVE are thermally crosslinked with acetal structures during prebake step, and the crosslinked PHI becomes completely insoluble in an aqueous basic solution. Upon exposure to UV light (365 nm) and subsequent postexposure bake (PEB), a strong acid generated from the PAG cleaves the crosslinked structures, and the exposed area is effectively solubilized in the alkaline developer. The dissolution behavior of the PSPI containing each 11.5 wt % of BPA‐DEVE and of the PAG was studied after UV exposure (365 nm) and PEB. It was found that the difference in dissolution rates between exposed and unexposed areas was enough to get high resolution. A fine positive pattern with a resolution of 5 μm in a 3.7‐μm‐thick film was obtained from the three‐component PSPI. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Time-slide window join over data streams

The join is an important operator in processing data streams. To produce outputs continuously over unbounded data streams, sliding windows are generally used to limit the scope of the join at a certain time. In the existing join algorithms, only a simple type of windows have been considered, which are updated whenever a new data item arrives on any input stream. On the other hand, a more common type of windows have not been addressed yet, whose intervals are updated periodically, i.e., slid by a predefined time interval. In this paper, we consider the time-slide windows in joining multiple data streams. The algorithm for the time-slide window join can vary according to (i) how frequently the join is evaluated and (ii) which structure is used for windowing. Regarding this, possible algorithms are discussed, and experimental results that compare their performances are provided in this paper.     

Performance Comparisons Between Thumb-Based and Finger-Based Input on a Small Touch-Screen Under Realistic Variability

The potential benefits of thumb-based touch interaction have not been fully exploited due to its usability problems and performance deterioration. Despite the well-known problems, mobile phone users often prefer thumb-based input method in their daily context of use. Without understanding input performance under realistic variability, design solutions may not address the problems adequately. This research aims to evaluate performance of one-handed thumb-based input compared to cradled finger-based input for the large number of users and varying task conditions. By investigating performance under a range of user- and task-variability, common patterns can be identified to help infer realistic performance in context of use. For this experiment, 259 participants were recruited balanced on gender and age. They performed user testing of moving an icon on a mobile touch-screen. Overall, the one-handed thumb input showed a 30% reduction in throughput compared to the cradled finger-based input, with significant reduction in speed and accuracy. Reduced throughput is attributed to inaccuracy rather than speed. In addition, the partial effects of touch position, dragging direction, and target size were investigated and quantified. In conclusion, performance could maintain constant throughput only for the finger-based input of limited task conditions, when realistic variability was introduced. Also, high variance of throughput for the thumb-based input led to poor conformity to Fitts’s law. The findings have implications for design of thumb-based touch interface to offset performance reduction and characterizing performance measure for thumb-based input method.     

Highly Exposed ?NH2 Edge on Fragmented g-C3N4 Framework with Integrated Molybdenum Atoms for Catalytic CO2 Cycloaddition: DFT and Techno-Economic Assessment

This study focuses on the applicability of single-atom Mo-doped graphitic carbon nitride (GCN) nanosheets which are specifically engineered with high surface area (exfoliated GCN),  NH₂ rich edges, and maximum utilization of isolated atomic Mo for propylene carbonate (PC) production through CO₂ cycloaddition of propylene oxide (PO). Various operational parameters are optimized, for example, temperature (130 °C), pressure (20 bar), catalyst (Mo₂GCN), and catalyst mass (0.1 g). Under optimal conditions, 2% Mo-doped GCN (Mo₂GCN) has the highest catalytic performance, especially the turnover frequency (TOF) obtained, 36.4 h⁻¹ is higher than most reported studies. DFT simulations prove the catalytic performance of Mo₂GCN significantly decreases the activation energy barrier for PO ring-opening from 50–60 to 4.903 kcal mol⁻¹. Coexistence of Lewis acid/base group improves the CO₂ cycloaddition performance by the formation of coordination bond between electron-deficient Mo atom with O atom of PO, while  NH₂ surface group disrupts the stability of CO₂ bond by donating electrons into its low-level empty orbital. Steady-state process simulation of the industrial-scale consumes 4.4 ton h⁻¹ of CO₂ with PC production of 10.2 ton h⁻¹. Techno-economic assessment profit from Mo₂GCN is estimated to be 60.39 million USD year⁻¹ at a catalyst loss rate of 0.01 wt% h⁻¹.     

Memory effects of all‐solution‐processed oxide thin‐film transistors using ZnO nanoparticles

Abstract— Non‐volatile memory effects of an all‐solution‐processed oxide thin‐film transistor (TFT) with ZnO nanoparticles (NPs) as the charge‐trapping layer are reported. The device was fabricated by using a soluble MgInZnO active channel on a ZrHfO^x gate dielectric. ZnO NPs were used as the charge‐trapping site at the gate‐insulator—channel interface, and Al was used for source and drain electrodes. Transfer characteristics of the device showed a large clockwise hysteresis, which can be used to demonstrate its memory function due to electron trapping in the ZnO NP charge‐trapping layer. This memory effect has the potential to be utilized as a memory application on displays and disposable electronics.     

Optimization of silicon solar cell fabrication based on neural network and genetic programming modeling

This study describes techniques for the cascade modeling and the optimization that are required to conduct the simulator-based process optimization of solar cell fabrication. Two modeling approaches, neural networks and genetic programming, are employed to model the crucial relation for the consecutively connected two processes in solar cell fabrication. One model (Model 1) is used to map the five inputs (time, amount of nitrogen and DI water in surface texturing and temperature and time in emitter diffusion) to the two outputs (reflectance and sheet resistance) of the first process. The other model (Model 2) is used to connect the two inputs (reflectance and sheet resistance) to the one output (efficiency) of the second process. After modeling of the two processes, genetic algorithms and particle swarm optimization were applied to search for the optimal recipe. In the first optimization stage, we searched for the optimal reflectance and sheet resistance that can provide the best efficiency in the fabrication process. The optimized reflectance and sheet resistance found by the particle swarm optimization were better than those found by the genetic algorithm. In the second optimization stage, the five input parameters were searched by using the reflectance and sheet resistance values obtained in the first stage. The found five variables such as the texturing time, amount of nitrogen, DI water, diffusion time, and temperature are used as a recipe for the solar cell fabrication. The amount of nitrogen, DI water, and diffusion time in the optimized recipes showed considerable differences according to the modeling approaches. More importantly, repeated applications of particle swarm optimization yielded process conditions with smaller variations, implying greater consistency in recipe generation.     

A method of stepwise benchmarking for inefficient DMUs based on the proximity-based target selection

DEA is a useful nonparametric method of measuring the relative efficiency of a DMU and yielding a reference target for an inefficient DMU. However, it is very difficult for inefficient DMUs to be efficient by benchmarking a target DMU which has different input use. Identifying appropriate benchmarks based on the similarity of input endowment makes it easier for an inefficient DMU to imitate its target DMUs. But it is rare to find out a target DMU, which is both the most efficient and similar in input endowments, in real situation. Therefore, it is necessary to provide an optimal path to the most efficient DMU on the frontier through several times of a proximity-based target selection process. We propose a dynamic method of stepwise benchmarking for inefficient DMUs to improve their efficiency gradually.The empirical study is conducted to compare the performance between the proposed method and the prior methods with a dataset collected from Canadian Bank branches. The comparison result shows that the proposed method is very practical to obtain a gradual improvement for inefficient DMUs while it assures to reach frontier eventually.