Morphology Controlled Synthesis of γ-Al₂O₃ Nano-Crystallites in Al@Al₂O₃ Core–Shell Micro-Architectures by Interfacial Hydrothermal Reactions of Al Metal Substrates

Fine control of morphology and exposed crystal facets of porous γ-Al2O3 is of significant importance in many application areas such as functional nanomaterials and heterogeneous catalysts. Herein, a morphology controlled in situ synthesis of Al@Al2O3 core–shell architecture consisting of an Al metal core and a porous γ-Al2O3 shell is explored based on interfacial hydrothermal reactions of an Al metal substrate in aqueous solutions of inorganic anions. It was found that the morphology and structure of boehmite (γ-AlOOH) nano-crystallites grown at the Al-metal/solution interface exhibit significant dependence on temperature, type of inorganic anions (Cl−, NO3−, and SO42−), and acid–base environment of the synthesis solution. Different extents of the electrostatic interactions between the protonated hydroxyl groups on (010) and (001) facets of γ-AlOOH and the inorganic anions (Cl−, NO3−, SO42−) appear to result in the preferential growth of γ-AlOOH toward specific crystallographic directions due to the selective capping of the facets by adsorption of the anions. It is hypothesized that the unique Al@Al2O3 core–shell architecture with controlled morphology and exposed crystal-facets of the γ-Al2O3 shell can provide significant intrinsic catalytic properties with enhanced heat and mass transport to heterogeneous catalysts for applications in many thermochemical reaction processes. The direct fabrication of γ-Al2O3 nano-crystallites from Al metal substrate with in-situ modulation of their morphologies and structures into 1D, 2D, and 3D nano-architectures explored in this work is unique and can offer significant opportunities over the conventional methods

Morphology Controlled Synthesis of γ-Al2O3 Nano-Crystallites in Al@Al2O3 Core–Shell Micro-Architectures by Interfacial Hydrothermal Reactions of Al Metal Substrates

Fine control of morphology and exposed crystal facets of porous γ-Al2O3 is of significant importance in many application areas such as functional nanomaterials and heterogeneous catalysts. Herein, a morphology controlled in situ synthesis of Al@Al2O3 core–shell architecture consisting of an Al metal core and a porous γ-Al2O3 shell is explored based on interfacial hydrothermal reactions of an Al metal substrate in aqueous solutions of inorganic anions. It was found that the morphology and structure of boehmite (γ-AlOOH) nano-crystallites grown at the Al-metal/solution interface exhibit significant dependence on temperature, type of inorganic anions (Cl−, NO3−, and SO42−), and acid–base environment of the synthesis solution. Different extents of the electrostatic interactions between the protonated hydroxyl groups on (010) and (001) facets of γ-AlOOH and the inorganic anions (Cl−, NO3−, SO42−) appear to result in the preferential growth of γ-AlOOH toward specific crystallographic directions due to the selective capping of the facets by adsorption of the anions. It is hypothesized that the unique Al@Al2O3 core–shell architecture with controlled morphology and exposed crystal-facets of the γ-Al2O3 shell can provide significant intrinsic catalytic properties with enhanced heat and mass transport to heterogeneous catalysts for applications in many thermochemical reaction processes. The direct fabrication of γ-Al2O3 nano-crystallites from Al metal substrate with in-situ modulation of their morphologies and structures into 1D, 2D, and 3D nano-architectures explored in this work is unique and can offer significant opportunities over the conventional methods

Touch or Push?: Button Design for VR HMD using Hand Interaction

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Robustifying multi-hop question answering through pseudo-evidentiality training

© 2021 Association for Computational LinguisticsThis paper studies the bias problem of multihop question answering models, of answering correctly without correct reasoning. One way to robustify these models is by supervising to not only answer right, but also with right reasoning chains. An existing direction is to annotate reasoning chains to train models, requiring expensive additional annotations. In contrast, we propose a new approach to learn evidentiality, deciding whether the answer prediction is supported by correct evidences, without such annotations. Instead, we compare counterfactual changes in answer confidence with and without evidence sentences, to generate “pseudo-evidentiality” annotations. We validate our proposed model on an original set and challenge set in HotpotQA, showing that our method is accurate and robust in multi-hop reasoning.N

Modelling the Intrusive Feelings of Advanced Driver Assistance Systems Based on Vehicle Activity Log Data: Case Study for the Lane Keeping Assistance System

Although the automotive industry has been among the sectors that best-understands the importance of drivers' affect, the focus of design and research in the automotive field has long emphasized the visceral aspects of exterior and interior design. With the adoption of Advanced Driver Assistance Systems (ADAS), endowing semi-autonomy' to the vehicles, however, the scope of affective design should be expanded to include the behavioural aspects of the vehicle. In such a shared-control' system wherein the vehicle can intervene in the human driver's operations, a certain degree of intrusive feelings' are unavoidable. For example, when the Lane Keeping Assistance System (LKAS), one of the most popular examples of ADAS, operates the steering wheel in a dangerous situation, the driver may feel interrupted or surprised because of the abrupt torque generated by LKAS. This kind of unpleasant experience can lead to prolonged negative feelings such as irritation, anxiety, and distrust of the system. Therefore, there are increasing needs of investigating the driver's affective responses towards the vehicle's dynamic behaviour. In this study, four types of intrusive feelings caused by LKAS were identified to be proposed as a quantitative performance indicator in designing the affectively satisfactory behaviour of LKAS. A metric as well as a statistical data analysis method to quantitatively measure the intrusive feelings through the vehicle sensor log data.11Nsciescopuskc

Suggesting Design Method for Performance Evaluation System Based on IoT Data: Considering UX

The rapid development of Internet of Things (IoT) technology makes it possible to connect various objects among each other and to collect sensor data from the objects. Connected car, achieved by advanced driver assistance system (ADAS), is one of the representative example of IoT technology. Since massive amount of IoT data could be effectively analyzed with appropriate methods, it is helpful to introduce supportive systems for the analysis. This study proposes a method to design supportive system for the analysis of IoT data considering user experience (UX). The suggested method is applied to design the supportive system for lane keeping assistance system (LKAS), which is one of the ADAS.1

Investigating user needs for intelligence services in IoT environments

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