22 research outputs found
Performance Evaluation of a Two-Stage Compression Heat Pump System With Refrigerant Charge and EEV Opening
Healthcare and Welfare Policy Efficiency in 34 Developing Countries in Asia
The healthcare and welfare policies of nations, as well as the amount of investments put into these areas, vary across countries. Investments in healthcare and welfare have been increasing worldwide which brings the question of assessing the efficiency of these investments. There are, however, difficulties in evaluating the effectiveness of such investments due to differences in countries’ economic development levels and due to the differences in data definition issues. There are only a limited number of studies in the literature that employ consistent and comparable indicators across countries. This study evaluates the healthcare investment efficiency and health competitiveness efficiency of 34 developing countries in Asia using a two-stage dynamic data envelopment analysis approach. Furthermore, we employ a broader measure of indicators on national healthcare and welfare policies and outcomes, in addition to the investment data on healthcare and welfare expenditures. Our findings indicate that the establishment of an investment environment with a consolidated approach and management is an important factor that increases the efficiency of investments in healthcare and welfare sectors. A consistent delivery of the national policy strategy is also crucial for reaching the medium-and long-term targets for each country. For example, if a country establishes healthcare and welfare policies that focus on improving its indicators with low efficiencies, the output will be improved and a better return on investment will be ensured in a long-term perspective
Atomic-Scale Observations of the Manganese Porphyrin/Au Catalyst Interface Under the Electrocatalytic Process Revealed with Electrochemical Scanning Tunneling Microscopy
© 2021 Wiley-VCH GmbH.As a promising molecular catalyst for oxygen evolution reaction (OER), metalloporphyrin is a good model system that is extensively studied. The catalytic efficiency of metalloporphyrin can be improved with deeper insight into its complex issues, such as structural stability and catalytic activity. Using in situ electrochemical scanning tunneling microscopy (EC-STM) and X-ray photoelectron spectroscopy, the morphological evolution of the manganese porphyrin/Au(111) interface affected by the electrocatalytic reaction is revealed. In alkaline solution, the catalytic performance is dramatically enhanced after the first potential sweep, directly related to the formation of the MnOx-porphyrin complexes, driven by an irreversible oxidation–reduction process. These newly formed catalytically active materials exhibit synergistic effects with the Au interface. In situ EC-STM imaging provides the molecular evidence for the formation of the real active metalloporphyrin-based catalyst, showing the complicated interrelation of the morphology, structure, catalytic activity, and electrolyte in OER catalysts.11Nsciescopu
A Deep Learning-Based Fragment Detection Approach for the Arena Fragmentation Test
The arena fragmentation test (AFT) is one of the tests used to design an effective warhead. Conventionally, complex and expensive measuring equipment is used for testing a warhead and measuring important factors such as the size, velocity, and the spatial distribution of fragments where the fragments penetrate steel target plates. In this paper, instead of using specific sensors and equipment, we proposed the use of a deep learning-based object detection algorithm to detect fragments in the AFT. To this end, we acquired many high-speed videos and built an AFT image dataset with bounding boxes of warhead fragments. Our method fine-tuned an existing object detection network named the Faster R-convolutional neural network (CNN) on this dataset with modification of the network’s anchor boxes. We also employed a novel temporal filtering method, which was demonstrated as an effective non-fragment filtering scheme in our recent previous image processing-based fragment detection approach, to capture only the first penetrating fragments from all detected fragments. We showed that the performance of the proposed method was comparable to that of a sensor-based system under the same experimental conditions. We also demonstrated that the use of deep learning technologies in the task of AFT significantly enhanced the performance via a quantitative comparison between our proposed method and our recent previous image processing-based method. In other words, our proposed method outperformed the previous image processing-based method. The proposed method produced outstanding results in terms of finding the exact fragment positions
Design Optimization of a Refrigerant-Cooling Thermal Management System for the Battery in Electric Vehicles
Extended Abstract As Li-ion cells are widely used for power source of electric vehicles, thermal management of batteries become an important issue. The large energy capacity and compactness of the cells cause heat accumulation in the battery pack. Excessively high temperature and uneven temperature distribution in the battery degrade the performance and reduce the cycle life of the cells. Many kinds of thermal management system are developed and used to cool down the battery during the operation process. The conventional air-cooling system is low cost and easy to fabricate, but it shows insufficient cooling performance in abuse conditions with high discharge rate and high ambient temperature, which is due to low heat transfer coefficient and small thermal capacity of the air. As an alternative system of air-cooling, two-phase cooling systems are considered because latent heat cooling has very large thermal capacity at a constant temperature. As a solid-toliquid phase change, PCMs are used for thermal management of batteries in many studies In this paper, a two-phase cooling system using R-134a as a coolant is modelled. A rectangular type Li-ion cell with large capacity is applied, and 10 to 20 numbers of cells form a module. Micro-channel heat sink is attached on the bottom surface of the module and absorbs the heat from the module. The effects of the refrigerant temperature and mass flow rate on the cooling performance are investigated using a 3-D transient numerical model. The discharge rate and the ambient temperature vary according to operating conditions, and the maximum temperature of the battery module and the maximum temperature difference in the module are calculated to evaluate thermal performance. In mild operating condition when the discharge rate is 1C and the ambient temperature is 20-25°C, the maximum temperature during the discharge process is below 30°C and the maximum temperature difference in the module is within the allowable range of 5°C. However, in abuse condition of a discharge rate of 2C and an ambient temperature of 30°C, the temperature difference exceeds the range of 5°C at the end of discharge. The decrease of the refrigerant temperature and increase of the mass flow rate drop the maximum temperature of the module, but increase the temperature difference in the module. By analysing this trade-off characteristic of the maximum temperature and temperature difference, the temperature and mass flow rate of the refrigerant are optimized in each specific operating condition. Finally, an improved cooling system which combines the refrigerant-cooling and forced air-cooling is suggested and the enhancement of the cooling performance is also investigated. In the newly designed system, the refrigerant-cooling plays a role in dropping the maximum temperature of the module while the forced air-cooling enhances the heat transfer on the module surface and reduces the temperature difference significantly. References [1] S. Al-Hallaj and J. R. Selman, "Thermal modelling of secondary lithium batteries for electric vehicle/hybrid electric vehicl
In Situ Probing of CO2 Reduction on Cu‐Phthalocyanine‐Derived CuxO Complex
Abstract An in situ measurement of a CO2 reduction reaction (CO2RR) in Cu‐phthalocyanine (CuPC) molecules adsorbed on an Au(111) surface is performed using electrochemical scanning tunneling microscopy. One intriguing phenomenon monitored in situ during CO2RR is that a well‐ordered CuPC adlayer is formed into an unsuspected nanocluster via molecular restructuring. At an electrode potential of −0.7 V versus Ag/AgCl, the Au surface is covered mainly with the clusters, showing restructuring‐induced CO2RR catalytic activity. Using a measurement of X‐ray photoelectron spectroscopy, it is revealed that the nanocluster represents a Cu complex with its formation mechanism. This work provides an in situ observation of the restructuring of the electrocatalyst to understand the surface‐reactive correlations and suggests the CO2RR catalyst works at a relatively low potential using the CuPC‐derived Cu nanoclusters as active species
In-situ imaging of the electrode surface during electrochemical reactions with a beetle-type electrochemical scanning tunneling microscope
In this paper, we present the design and performances of a beetle-type electrochemical scanning tunneling microscope (EC-STM) which allows horizontal tip motion at millimeter range (5 mm × 5 mm). With its symmetrical scanner design inducing a relatively low thermal drift, the beetle-type EC-STM has the desirable ability to operate in a variety of chemical reactions. Atom-resolved high-resolution STM images of highly oriented pyrolytic graphite (HOPG) and Au(111) surfaces in the liquid phase are presented to confirm the scan performance of the beetle-type EC-STM, which also provides in situ information on the electrode surface during electrochemical reactions, including adsorbed– and desorbed– electrolyte and metal electrodeposition. These systemically obtained STM images on the electrode surface clearly demonstrate the high stability of the newly developed EC‐STM under reaction conditions. © 2023 Korean Physical Society11Nsciescopuskc
Effect of Water Vapor on Oxidation Processes of the Cu(111) Surface and Sublayer
Copper-based catalysts have different catalytic properties depending on the oxidation states of Cu. We report operando observations of the Cu(111) oxidation processes using near-ambient pressure scanning tunneling microscopy (NAP-STM) and near-ambient pressure X-ray photoelectron spectroscopy (NAP-XPS). The Cu(111) surface was chemically inactive to water vapor, but only physisorption of water molecules was observed by NAP-STM. Under O2 environments, dry oxidation started at the step edges and proceeded to the terraces as a Cu2O phase. Humid oxidation of the H2O/O2 gas mixture was also promoted at the step edges to the terraces. After the Cu2O covered the surface under humid conditions, hydroxides and adsorbed water layers formed. NAP-STM observations showed that Cu2O was generated at lower steps in dry oxidation with independent terrace oxidations, whereas Cu2O was generated at upper steps in humid oxidation. The difference in the oxidation mechanisms was caused by water molecules. When the surface was entirely oxidized, the diffusion of Cu and O atoms with a reconstruction of the Cu2O structures induced additional subsurface oxidation. NAP-XPS measurements showed that the Cu2O thickness in dry oxidation was greater than that in humid oxidation under all pressure conditions
Yu-Shiba-Rusinov bound states studied by tuning the electron density at the Fermi energy
We studied the nature of Yu-Shiba-Rusinov (YSR) bound states in response to the potential scattering U by tuning the electron density at the Fermi energy. By comparing two systems, Mn-phthalocyanine molecules on Pb(111) and Co atoms on PbSe/Pb(111), we demonstrate that the sign of U can be unambiguously determined by varying the electron density at the Fermi energy. We further show that U competes with the exchange interaction JS in the formation of YSR bound states. Our work provides insights into the interactions between magnetic atoms and superconductors at a fundamental level.11Nsciescopu