Thermally activated flux motion in optimally electron-doped (Ca0.85La0.15)(10)(Pt3As8)(Fe2As2)(5) and Ca-10(Pt3As8)((Fe0.92Pt0.08)(2)As-2)(5) single crystals

The temperature dependence of the electric resistivity measured in various magnetic fields was analyzed by the vortex glass theory and the thermally activated flux motion (TAFM) theory. The vortex glass-to-vortex liquid (GTL) transition Tg obtained from the analysis shows a temperature dependence of BgT=B01-T/Tcm. The vortex liquid region is divided into the critical region existing in a finite temperature region just above Tg and the TAFM region present in the finite temperature region above it. In the critical region, the activation energy is expressed as Ueff=kBTTc-T/(Tc-Tg), whereas in the TAFM region, the activity energy is expressed as temperature-nonlinear UT,B=U0B1-tq. In the GTL transition, (Ca0.85La0.15)10(Pt3As8)(Fe2As2)5 maintains the 3D vortex structure without exhibiting dimension crossover of the vortex, but Ca10(Pt3As8)((Fe0.92Pt0.08)2As2)5 exhibits the dimension crossover from the 3D vortex glass to the 2D vortex liquid. © 2020 The Author(s)1

Effect of the proton irradiation on the thermally activated flux flow in superconducting SmBCO coated conductors

We investigate changes in the vortex pinning mechanism caused by proton irradiation through the measurement of the in-plane electrical resistivity for H//c in a pristine and two proton-irradiated (total doses of 1 × 1015 and 1 × 1016 cm−2) SmBa2Cu3O7-δ (SmBCO) superconducting tapes. Even though proton irradiation has no effect on the critical temperature (Tc), the resulting artificial point defect causes an increase in normal state electrical resistivity. The electrical resistivity data around Tc shows no evidence of a phase transition to the vortex glass state but only broadens with increasing magnetic field due to the vortex depinning in the vortex liquid state. The vortex depinning is well interpreted by a thermally activated flux flow model in which the activation energy shows a nonlinear temperature change U(T,H)=U0(H)(1−T/Tc)q (q = 2). The field dependence of activation energy shows a U0~H−α with larger exponents above 4 T. This field dependence is mainly due to correlated disorders in pristine sample and artificially created point defects in irradiated samples. Compared with the vortex pinning due to correlated disorders, the vortex pinning due to the appropriate amount of point defects reduces the magnitude of Uo(H) in the low magnetic field region and slowly reduces Uo(H) in high magnetic fields. © 2020, The Author(s).1

Satellite-based monitoring of an open-pit mining site using Sentinel-1 advanced radar interferometry: A case study of the December 21, 2020, landslide in Toledo City, Philippines

Understanding the causal factors and mechanisms behind catastrophic landslides and debris flows is crucial for accurate forecasting and disaster risk reduction. Synthetic aperture radar (SAR) data and interferometric SAR (InSAR) technologies provide valuable information for early warning systems’ landslide and debris flow detection and monitoring strategies. This paper applied the Sentinel-1 Persistent Scatterer InSAR (PSInSAR) technique to detect and monitor precursory slope movements over the open-pit mining site in Toledo City, Cebu Island, in the Philippines. The results show that the slope showed instabilities between December 30, 2019, to December 12, 2020, before the actual failure on December 21, 2020. The landslide initiation zone moved with velocities exceeding –10 mm/yr and reaching –90 mm/yr. The topography and morphology of the mining site contributed to the cut slope instabilities. The mining operations and hydrometeorological conditions during the analysis period aggravated the situation, leading to the cut slope failure. Overall, with favorable slope geometry, surface characteristics, and SAR data availability, the Sentinel-1 PSInSAR technique can serve as a landslide early warning system tool and aid decision-making in an actively operating open-pit mine and other landscapes

Effect of multiple debris flow countermeasures on flow characteristics and topographic changes through real-scale experiment

In this study, to investigate the effect of multiple countermeasure on the flow characteristics of debris flows, a real-scale experiment was conducted in a natural gully by reproducing a debris flow with a installation of multiple countermeasures. In addition, the topographic changes before and after experiment by debris flow were investigated using UAV-LiDAR. Based on the experiment results, the effect of multiple countermeasures and the topographic changes against the gully erosion and deposition caused by debris flow were also analyzed. The installation of multiple countermeasures significantly decreased the frontal velocity of debris flow. Furthermore, the countermeasure induced the deposition of debris material on the back of the countermeasure

Effect of the sample work function on alkali metal dosing induced electronic structure change

Alkali metal dosing (AMD) has been widely used as a way to control doping without chemical substitution. This technique, in combination with angle resolved photoemission spectroscopy (ARPES), often provides an opportunity to observe unexpected phenomena. However, the amount of transferred charge and the corresponding change in the electronic structure vary significantly depending on the material. Here, we report study on the correlation between the sample work function and alkali metal induced electronic structure change for three iron-based superconductors: FeSe, Ba(Fe$_{0.94}$Co$_{0.06}$)$_{2}$As$_{2}$ and NaFeAs which share a similar Fermi surface topology. Electronic structure change upon monolayer of alkali metal dosing and the sample work function were measured by ARPES. Our results show that the degree of electronic structure change is proportional to the difference between the work function of the sample and Mulliken's absolute electronegativity of the dosed alkali metal. This finding provides a possible way to estimate the AMD induced electronic structure change.Comment: 4 page

전자와 정공이 도핑 된 초전도 Ca10(Pt3As8)(Fe2As2)5의 광학적 특성

NContents Abstract i Chapter 1. Introduction 1 Chapter 2. Iron-based superconductors Ca10(Pt3As8)(Fe2As2)5 2.1 Crystals structure of Ca10(Pt3As8)(Fe2As2)5 and Ca10(Pt4As8)(Fe2As2)5 7 2.2 Crystal structure of La doped Ca10(Pt3As8)(Fe2As2)5 single crystal 9 2.3 Transport properties of Ca10(Pt3As8)(Fe2As2)5 2.3.1. Parent Ca10(Pt3As8)(Fe2As2)5 compound 14 2.3.2. Doping dependence of Ca10(Pt3As8)(Fe2As2)5 compound 15 2.4 Electronic structure of Ca10(Pt3As8)(Fe2As2)5 and Ca10(Pt4As8)(Fe2As2)5 17 2.5 Optical properties of iron-based superconductors 2.5.1. Optical properties of Pt doped Ca10(Pt3As8)(Fe2As2)5 compound 20 2.5.2. Psuedogap and electronic correlations in iron-based superconductor 23 References 28 Chapter 3. Experimental and Theoretical Methods 3.1. Synthesis methods of single crystal 3.1.1. Single crystals grown by vertical Bridgman method 32 3.1.2. Single crystal growth of La & Na doped Ca 10-3-8 compound 35 3.2. Transport measurement 3.2.1. Electrical resistivity measurement and measurement systems 37 3.2.2. Magnetoresistivity and Hall resistivity 39 3.3. Optical Spectroscopy 3.3.1. The principle of Fourier-transform spectroscopy 42 3.3.2. Fourier-transform infrared spectroscopy 45 3.3.3. Kramers-Kronig (K-K) relations for reflectivity analysis 50 3.3.4. Sum rules 52 3.3.5. Drude-Lorentz model 53 3.3.6. Superconducting gaps 55 References 57 Chapter 4. Results and Discussion 4.1 Superconducting-induced transfer of spectral weight due to microscopic coexistence of superconducting and magnetic correlation 58 References. 82 4.2 Optical properties in the hole-doped Ca8.5Na1.5(Pt3As8)(Fe2As2)5 single crystal with strong electron correlations 83 Referencee 111DoctordCollectio

Source Type Classification and Localization of Inter-Floor Noise with a Single Sensor and Knowledge Transfer between Reinforced Concrete Buildings

A convolutional neural network (CNN)-based inter-floor noise source type classifier and locator with input from a single microphone was proposed in [Appl. Sci. 9, 3735 (2019)] and validated in a campus building experiment. In this study, the following extensions are presented: (1) data collections of nearly 4700 inter-floor noise events that contain the same noise types as those in the previous work at source positions on the floors above/below in two actual apartment buildings with spatial diversity, (2) the CNN-based method for source type classification and localization of inter-floor noise samples in apartment buildings, (3) the limitations of the method as verified through several tasks considering actual application scenarios, and (4) source type and localization knowledge transfer between the two apartment buildings. These results reveal the generalizability of the CNN-based method to inter-floor noise classification and the feasibility of classification knowledge transfer between residential buildings. The use of a short and early part of event signal is shown as an important factor for localization knowledge transfer

Fluctuation magnetoconductivity in superconducting Ca10(Pt4As8)(Fe2As2)5 single crystal

Fluctuation-induced conductivity up to μ0 H = 14 T for superconducting Ca10(Pt4As8)(Fe2As2)5 single crystal was evaluated from the measured in-plane electrical resistivity, and it was analyzed by Aslamazov-Larkin (AL) theory for zero magnetic field and Ullah and Dorsey (UD) scaling method for magnetic field. A dimensional crossover of superconducting fluctuations from low-temperature three-dimension to high-temperature two-dimension was observed. When the dimensional crossover occurs, a temperature region in which two-dimensional and three-dimensional fluctuations occur simultaneously was found in the intermediate temperature region. © 2022 The Author(s)TRU

Classification of Inter-Floor Noise Type/Position Via Convolutional Neural Network-Based Supervised Learning

Inter-floor noise, i.e., noise transmitted from one floor to another floor through walls or ceilings in an apartment building or an office of a multi-layered structure, causes serious social problems in South Korea. Notably, inaccurate identification of the noise type and position by human hearing intensifies the conflicts between residents of apartment buildings. In this study, we propose a robust approach using deep convolutional neural networks (CNNs) to learn and identify the type and position of inter-floor noise. Using a single mobile device, we collected nearly 2000 inter-floor noise events that contain 5 types of inter-floor noises generated at 9 different positions on three floors in a Seoul National University campus building. Based on pre-trained CNN models designed and evaluated separately for type and position classification, we achieved type and position classification accuracy of 99.5% and 95.3%, respectively in validation datasets. In addition, the robustness of noise type classification with the model was checked against a new test dataset. This new dataset was generated in the building and contains 2 types of inter-floor noises at 10 new positions. The approximate positions of inter-floor noises in the new dataset with respect to the learned positions are presented