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Abelian modular symbols over real quadratic fields
No full textAbelian modular symbol (over Q) is first introduced by Hida in his blue book to reformulate the construction of the Kubota-Leopoldt p-adic L-function. I have shown a certain homological distribution result for the symbols to reprove residual non-vanishing result for special Dirichlet L-values with cyclotomic twists, namely Washington's Theorem. In the talk, I will discuss how to construct the symbols over real quadratic fields and present a possible approach to study the residual non-vanishing problem for special Hecke L-values of real quadratic fields with cyclotomic twists, which is a generalization of my previous argument for
Q. This is ongoing research and is joint work with Jungyun Lee and Jaesung Kwon
Electronic dispersion, correlations and stacking in the photoexcited state of 1T-TaS2
No full textHere we perform angle and time-resolved photoelectron spectroscopy on the commensurate charge density wave (CDW) phase of 1T-TaS2. Data with different probe pulse polarization are employed to map the dispersion of electronic states below and above the chemical potential. Upon photoexcitation, the fluctuations of CDW order erase the band dispersion and squeeze the electronic states near to the chemical potential. This transient phase sets within half a period of the coherent lattice motion and is favored by strong electronic correlations. The experimental results are compared to density-functional theory calculations with a self-consistent evaluation of the Coulomb repulsion. Our simulations indicate that the screening of Coulomb repulsion depends on the stacking order of the TaS2 layers. The entanglement of such degrees of freedom suggest that both the structural order and electronic repulsion are locally modified by the photoinduced CDW fluctuations
Pavement Monitoring Using Unmanned Aerial Vehicles: An Overview
No full textPavement monitoring involves periodic damage detection and condition assessment of pavements for efficient pavement management. Unmanned aerial vehicle (UAV)-based pavement monitoring requires multidisciplinary knowledge of pavement distress, drone type, payload, flight parameters, drone deployment, and image processing. Owing to the availability of various UAVs, data sensing devices, operating ecosystems, and post-processing tools, selecting an appropriate combination of these systems is crucial. Therefore, the primary objective of this study is to provide essential knowledge on the prevalent challenges of existing monitoring techniques and discuss the potential advantages of UAVs over conventional pavement monitoring practice. A state-of-the-art review emphasizing UAV technicalities in the context of image-based pavement monitoring is presented. A detailed workflow and checklist for drone deployment is drafted for novice users to ensure safe and high-quality data acquisition. Finally, the present challenges and future scope of UAV-based pavement monitoring is discussed. Overall, this study aims to provide inclusive and comprehensive information on UAV-based pavement monitoring to beginner researchers
Future projection of extreme precipitation over the Korean Peninsula under global warming levels of 1.5 ??C and 2.0 ??C, using large ensemble of RCMs in CORDEX-East Asia Phase 2
No full textThis study investigated future projections of extreme precipitation (PR) over the Korean Peninsula (KP) under global warming levels of 1.5 ??C and 2.0 ??C (GWL 1.5 ??C and 2.0 ??C). The bias-corrected large ensemble of the Regional Climate Model (RCM) in the Coordinated Regional Climate Downscaling Experiment???East Asia Phase 2 was used. Under GWL 1.5 ??C, the RCM multi-model ensemble (MME) predicted the extreme PR intensity (RX1day) to increase by 10.14% more than the mean PR of 4.69%. A regional difference was observed in the projection, with a larger increase over the northern KP (NKP) and southern KP (SKP) than central KP. Accordingly, the distribution of extreme PR was expected to shift with the right, and extreme events occurring once every 20 years over the SKP and NKP were expected to change to a reoccurrence of 12.56 years and 10.04 years, respectively. The mechanism of extreme PR was examined for cases from June to September. The expected increase in extreme PR per warming over the SKP and NKP was 5.64% ??C???1 and 8.37% ??C???1, respectively, which was close to the Clausius-Clapeyron scale (7.7% ??C???1). This implies that increased moisture capability from the warming will affect the change in extreme PR. Other possible factors were investigated and the RCM MME predicted vertical instability over East Asia to continue, and moisture flux and convergence around the KP to be intensified. Meanwhile, under GWL 2.0 ??C, mean PR and extreme PR were projected to increase more than under GWL 1.5 ??C
Prospects of glove-box versus air-processed organic solar cells
No full textIn the search for alternate green energy sources to offset dependence on fossil fuels, solar energy can certainly meet two needs with one deed: fulfil growing global energy demands due to its non-depletable nature and lower greenhouse gas emissions. As such, third generation thin film photovoltaic technology based organic solar cells (OSCs) can certainly play their role in providing electricity at a competing or lower cost than 1st and 2nd generation solar technologies. As OSCs are still at an early stage of research and development, much focus has been placed on improving power conversion efficiencies (PCEs) inside a controlled environment i.e. a glove-box (GB) filled with an inert gas such as N-2. This was necessary until now, to control and study the local nanomorphology of the spin-coated blend films. For OSCs to compete with other solar energy technologies, OSCs should produce similar or even better morphologies in an open environment i.e. air, such that air-processed OSCs can result in similar PCEs in comparison to their GB-processed counterparts. In this review, we have compared GB- vs. air-processed OSCs from morphological and device physics aspects and underline the key features of efficient OSCs, processed in either GB or air
Effect of singlet oxygen on redox mediators in lithium-oxygen batteries
No full textThe use of a redox mediator (RM) to chemically decompose Li2O2 is an efficient approach to improve the efficiency and cyclability of lithium-oxygen batteries. It has been suggested that RMs can react with the singlet oxygen (O-1(2)) but no attempt has been made to categorize the reactivity of different RMs with O-1(2), or investigate the impact of this reaction on the electrochemical behavior of RMs. Here we show that the reactivity of RMs with O-1(2) depends on the unique chemistry of the RM, and that the Li2O2 decomposition kinetics of RMs are considerably affected by their reactivity towards O-1(2). We examine changes to the chemical and electrochemical properties of RMs after exposure to O-1(2). These results suggest that the activity and lifetime of RMs in Li-O-2 cells are affected by their reactivity towards O-1(2), and that RMs can be classified depending on how easily they react with, or physically quench O-1(2)
Deep active-learning based model-synchronization of digital manufacturing stations using human-in-the-loop simulation
No full textThe effective and accurate modeling of human performance is one of the key technologies in virtual/smart manufacturing systems. However, a significant challenge lies in acquiring sufficient data for such modeling. Virtual Reality (VR) emerges as a promising solution, making human manufacturing experiments more practical and accessible. In this paper, we present a novel framework that efficiently models human assembly duration by leveraging VR to prototype data-acquisition systems for assembly tasks. Central to the framework is an active learning model, which intelligently selects experimental conditions to yield the most informative results, effectively reducing the number of experiments required. As a result, the system demands fewer experimental trials and operates on an automated basis. In VR experiments involving throughput rate, the active model significantly reduces the data requirement, thereby expediting the experiment and modeling process. While this framework demonstrates remarkable efficiency, it does exhibit sensitivity to non-constant noise and may necessitate prior data from similar assembly tasks to identify high-noise. Notably, this proposed method extends beyond manufacturing, allowing the quick generation of human performance models in virtual systems and enhancing experiment scalability across various fields. With its potential to revolutionize human performance modeling, our framework represents a promising avenue for advancing virtual/smart manufacturing systems and other related applications
Deep metal-assisted chemical etching using a porous monolithic AgAu layer to develop neutral-colored transparent silicon photovoltaics
No full textHere, we report deep metal-assisted chemical etching (MACE) using a porous monolithic AgAu layer on crystalline silicon (c-Si) as an alternative to the expensive deep reactive ion etching (DRIE) for fabricating neutral-colored transparent crystalline silicon photovoltaics (c-Si TPV). To prevent the uneven etching of c-Si by Ag particles, a porous monolithic Ag layer is developed by introducing acetonitrile to enhance the interaction between the c-Si surface and Ag precursor. This results in cooperative motion during MACE, as confirmed by microscopic observation, surface area measurements, and computational simulations. The durability of this Ag catalyst can be further improved by passivation with Au via galvanic replacement (i.e., the porous monolithic AgAu layer), thereby preventing indiscriminate defect generation. Thus, the fabricated c-Si TPV using MACE and a porous monolithic AgAu layer exhibits a high performance of 13.0% with 20% neutral-colored transparency, representing results superior to those obtained with samples fabricated by DRIE (11.5%)
Experimental and simulation of PEM water electrolyser with Pd/PN-CNPs electrodes for hydrogen evolution reaction: Performance assessment and validation
No full textWater electrolysis using a proton exchange membrane (PEM) offers a sustainable solution for green hydrogen production from intermittent renewable energy sources. However, the utilization of costly electrode materials and cell components has resulted in expensive hydrogen production costs and limited its commercial applications. Furthermore, the management of gas-liquid flow and thermal distributions presents significant challenges in the operation of PEM water electrolysers. In this study, a COMSOL Multiphysics model was developed for a 25 cm2 single cell PEM water electrolyser with parallel flow field configurations to investigate its performance including operating principles, mechanisms, and ion transport properties. Subsequently, the model was validated with in-house experimental data at different operating conditions. Impressively, it effectively predicted the current-voltage polarization curves, demonstrating strong correlation with the experimental data. For a more rigorous comparison between experimental and numerical simulation, the normalized root mean square deviation was calculated for current-voltage polarization curves at various temperatures, ranging from 30 degrees C to 80 degrees C. The deviation was observed to be around 1.1% across all the temperatures, an acceptably low error value. In addition, the model was used to analyze the reactant flow and thermal distributions. This work can provide both experimental and simulation support for the selection and optimization of operating conditions, including flow fields in PEM water electrolysers