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Appl. Sci., Volume 9, Issue 14 (July-2 2019) – 173 articles

Cover Story (view full-size image): The real-time estimation of ocean wave spectrum and elevation are essential for feed-forward DP (dynamic positioning) and route optimization. This manuscript uses the Kalman filter to estimate wave spectrum and elevation in real-time from the vessel's motion. If the ship is less responsive for high-frequency waves, amplified noise may occur and cause overestimation problems. Therefore, a new Kalman filter configuration by applying the principle of Wiener filter is proposed to suppress these overestimations. View this paper.
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15 pages, 2027 KiB  
Article
A Method Validation for Simultaneous Determination of Phthalates and Bisphenol A Released from Plastic Water Containers
by Ivan Notardonato, Carmela Protano, Matteo Vitali, Badal Bhattacharya and Pasquale Avino
Appl. Sci. 2019, 9(14), 2945; https://doi.org/10.3390/app9142945 - 23 Jul 2019
Cited by 44 | Viewed by 6728
Abstract
Phthalates (or phthalate esters, PAEs) and bisphenol A (BPA) are widely used in various industries, particularly in the fields of cosmetics and packaging, and they increase the malleability and workability of materials. As a result of their use, some international health organizations have [...] Read more.
Phthalates (or phthalate esters, PAEs) and bisphenol A (BPA) are widely used in various industries, particularly in the fields of cosmetics and packaging, and they increase the malleability and workability of materials. As a result of their use, some international health organizations have begun to study them. In this study, the authors developed a methodology for the simultaneous determination of dimethyl phthalate (DMP), diethyl phthalate (DEP), diisobutyl phthalate (DiBP); dibutyl phthalate (DBP), bis(2-ethylhexyl) phthalate (DEHP); di-n-octyl-phthalate (DnOP) and bisphenol A (BPA) from drinking and non-potable waters. The extraction of PAEs and BPA was performed using a solvent-based dispersive liquid–liquid microextraction (SB-DLLME) method. The analytical determination was performed using a gas chromatography–ion trap mass spectrometry (GC-IT/MS) analysis. The entire procedure was validated as recoveries were studied according to the volume and the extraction solvent used, pH, and ionic strength. Dynamic linearity ranges and linear equations of all the compounds were experimentally determined as well as the limit of detection (LOD) (1–8 ng mL−1) and the limit of quantification (LOQ) (5–14 ng mL−1), reproducibility, and sensitivity. The method was applied to 15 water samples (mineral water and tap water) for determining PAEs and BPA released from the plastic container. After the release simulation, four PAEs (i.e., DiBP, DBP, DHEP, and DnOP) were determined at very low concentrations (below 1.2 ng mL−1) in two water samples from (sport) bottles. Full article
(This article belongs to the Section Chemical and Molecular Sciences)
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26 pages, 6583 KiB  
Article
A Multi-Objective Evolutionary Algorithm Model for Product Form Design Based on Improved SPEA2
by Zeng Wang, Weidong Liu, Minglang Yang and Dongji Han
Appl. Sci. 2019, 9(14), 2944; https://doi.org/10.3390/app9142944 - 23 Jul 2019
Cited by 13 | Viewed by 3741
Abstract
As a Kansei engineering design expert system, the product form design multi-objective evolutionary algorithm model (PFDMOEAM) contains various methods. Among them, the multi-objective evolutionary algorithm (MOEA) is the key to determine the performance of the model. Due to the deficiency of MOEA, the [...] Read more.
As a Kansei engineering design expert system, the product form design multi-objective evolutionary algorithm model (PFDMOEAM) contains various methods. Among them, the multi-objective evolutionary algorithm (MOEA) is the key to determine the performance of the model. Due to the deficiency of MOEA, the traditional PFDMOEAM has limited innovation and application value for designers. In this paper, we propose a novel PFDMOEAM with an improved strength Pareto evolutionary algorithm 2 (ISPEA2) as the core and combining the elliptic Fourier analysis (EFA) and the entropy weight and technique for order preference by similarity to ideal solution (entropy-TOPSIS) methods. Based on the improvement of the original operators in SPEA2 and the introduction of a new operator, ISPEA2 outperforms SPEA2 in convergence and diversity simultaneously. The proposed model takes full advantage of this superiority, and further combines the EFA method’s high accuracy and degree of multi-method integration, as well as the entropy-TOPSIS method’s good objectivity and operability, so it has excellent comprehensive performance and innovative application value. The feasibility and effectiveness of the model are verified by a case study of a car form design. The simulation system of the model is developed, and the simulation results demonstrate that the model can provide a universal and effective tool for designers to carry out multi-objective evolutionary design of product form. Full article
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20 pages, 31742 KiB  
Article
An Experimental Study on Mechanical and Thermal Insulation Properties of Rubberized Concrete Including Its Microstructure
by Jiaqi Guo, Meng Huang, Shanxiu Huang and Sheng Wang
Appl. Sci. 2019, 9(14), 2943; https://doi.org/10.3390/app9142943 - 23 Jul 2019
Cited by 29 | Viewed by 4287
Abstract
This study aimed to investigate the effects of the size and weight content of waste rubber particles on the relevant performances of rubberized concrete. First, the fine aggregates were partially replaced by rubber particles of different sizes to produce rubberized concrete. Secondly, the [...] Read more.
This study aimed to investigate the effects of the size and weight content of waste rubber particles on the relevant performances of rubberized concrete. First, the fine aggregates were partially replaced by rubber particles of different sizes to produce rubberized concrete. Secondly, the mechanical and thermal insulation properties of rubberized concrete were investigated. Finally, microstructural analyses of rubberized concrete including scanning electronic microscope (SEM) and energy distribution spectroscopy (EDS) were examined. Experimental results indicated that uniaxial compressive strength of rubberized concrete was reduced, while the peak strain was gradually increased and thermal insulation properties were improved with the increase of rubber content or decrease of rubber particle size. In addition, rubber particles affected the failure modes, endowing concrete with weak brittleness and strong cracking resistance. Additionally, it was observed that the interfacial adhesion between the matrix rubber and the aggregates was weak under SEM, which seemed to be a key factor that reduced the strength of rubberized concrete. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings and Innovative Materials for Building Construction)
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9 pages, 1166 KiB  
Article
Potential Marker Genes for Predicting Adipogenic Differentiation of Mesenchymal Stromal Cells
by Masami Kanawa, Akira Igarashi, Katsumi Fujimoto, Veronica Sainik Ronald, Yukihito Higashi, Hidemi Kurihara, Yukio Kato and Takeshi Kawamoto
Appl. Sci. 2019, 9(14), 2942; https://doi.org/10.3390/app9142942 - 23 Jul 2019
Cited by 3 | Viewed by 4066
Abstract
Mesenchymal stromal cells (MSCs) are a promising source for tissue engineering of soft connective tissues. However, the differentiation capacity of MSCs varies among individual cell lines. Here, we show marker genes to predict the adipogenic potential of MSCs. To clarify the correlation between [...] Read more.
Mesenchymal stromal cells (MSCs) are a promising source for tissue engineering of soft connective tissues. However, the differentiation capacity of MSCs varies among individual cell lines. Here, we show marker genes to predict the adipogenic potential of MSCs. To clarify the correlation between gene expression patterns before adipogenic induction and the differentiation level of MSCs after differentiation, we compared mRNA levels of 95 genes and glycerol-3-phosphate dehydrogenase (GPDH) activities in 15 MSC lines (five jaw and 10 ilium MSCs) from 15 donors. Expression profiles of 22 genes before differentiation significantly correlated with GPDH activities after differentiation. Expression levels of 11 out of the 22 genes in highly potent ilium MSCs were at least three times higher compared with jaw MSCs, which have limited differentiation potential. Furthermore, three-dimensional scatter plot for mRNA expression of ITGA5, CDKN2D, and CD74 could completely distinguish highly potent MSCs from poorly potent MSCs for adipogenesis. The treatment of MSC cultures with the anti-ITGA5 antibody reduced adipogenic differentiation of MSCs. Collectively, these results suggest that the three genes play a role in adipogenesis before induction and can serve as predictors to select potent MSCs for adipogenic differentiation. Full article
(This article belongs to the Special Issue Biomaterials for Bone Tissue Engineering)
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20 pages, 8168 KiB  
Article
A Study on Development of the Camera-Based Blind Spot Detection System Using the Deep Learning Methodology
by Donghwoon Kwon, Ritesh Malaiya, Geumchae Yoon, Jeong-Tak Ryu and Su-Young Pi
Appl. Sci. 2019, 9(14), 2941; https://doi.org/10.3390/app9142941 - 23 Jul 2019
Cited by 11 | Viewed by 6729
Abstract
One of the recent news headlines is that a pedestrian was killed by an autonomous vehicle because safety features in this vehicle did not detect an object on a road correctly. Due to this accident, some global automobile companies announced plans to postpone [...] Read more.
One of the recent news headlines is that a pedestrian was killed by an autonomous vehicle because safety features in this vehicle did not detect an object on a road correctly. Due to this accident, some global automobile companies announced plans to postpone development of an autonomous vehicle. Furthermore, there is no doubt about the importance of safety features for autonomous vehicles. For this reason, our research goal is the development of a very safe and lightweight camera-based blind spot detection system, which can be applied to future autonomous vehicles. The blind spot detection system was implemented in open source software. Approximately 2000 vehicle images and 9000 non-vehicle images were adopted for training the Fully Connected Network (FCN) model. Other data processing concepts such as the Histogram of Oriented Gradients (HOG), heat map, and thresholding were also employed. We achieved 99.43% training accuracy and 98.99% testing accuracy of the FCN model, respectively. Source codes with respect to all the methodologies were then deployed to an off-the-shelf embedded board for actual testing on a road. Actual testing was conducted with consideration of various factors, and we confirmed 93.75% average detection accuracy with three false positives. Full article
(This article belongs to the Special Issue Multimodal Deep Learning Methods for Video Analytics)
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12 pages, 8831 KiB  
Article
A Study on the Deformation Behavior of a Microstructure Depending on Its Shape and the Cutting Section in the Precision Cutting of a Functional Part
by Ki-Hyeong Song, Young-Jae Choi and Yong-Shin Lee
Appl. Sci. 2019, 9(14), 2940; https://doi.org/10.3390/app9142940 - 23 Jul 2019
Cited by 3 | Viewed by 3188
Abstract
The shape accuracy of microstructures is an important factor that directly affects the quality and performance of products. Nevertheless, it is difficult to find a study for the shape accuracy of microstructures below several microns. This study aimed to reduce the shape error [...] Read more.
The shape accuracy of microstructures is an important factor that directly affects the quality and performance of products. Nevertheless, it is difficult to find a study for the shape accuracy of microstructures below several microns. This study aimed to reduce the shape error in the precision machining of microstructures with a repeated triangular cross-sectional shape with a width of 5 µm or less. Two important factors in this study were the morphological features of the microstructure to be fabricated and the cross-sectional shape of the chip. The tool path was modified in consideration of these two factors. Before the tool path change, the shape error due to the deformation of the triangular micropattern in a DOC (depth of a cut) of 1 µm was about 0.39 µm. However, after the tool path was modified, the shape error due to deformation did not occur while maintaining the DOC at 1 µm. Full article
(This article belongs to the Special Issue The High Efficiency Machining Process and Machining of Complex Materials)
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19 pages, 5449 KiB  
Article
Fiber Bragg Gratings Based Cyclic Strain Measuring of Weld Toes of Cruciform Joints
by Guoqian Wei, Shanshan Li, Yongxing Guo and Zhang Dang
Appl. Sci. 2019, 9(14), 2939; https://doi.org/10.3390/app9142939 - 23 Jul 2019
Cited by 5 | Viewed by 3873
Abstract
The real weld toe geometry is generally not mathematically perfect, resulting in obvious stress concentration effects, both on the weld section and along the longitudinal direction of the weld toe. The true stress-strain state at the local weld toe directly affects the fatigue [...] Read more.
The real weld toe geometry is generally not mathematically perfect, resulting in obvious stress concentration effects, both on the weld section and along the longitudinal direction of the weld toe. The true stress-strain state at the local weld toe directly affects the fatigue performance and behavior of the welded structure. Therefore, a Fiber Bragg Grating (FBG) sensor based method for testing the cyclic strain at the weld toe was proposed. Cruciform welded joints were fabricated as specimens on which FBG sensors were arranged at several characteristic points along the weld toe curve. Strains at all the characteristic points under cyclic tensile load were measured and recorded, which showed the proposed measuring method could accurately obtain the complete local strain time histories along the weld toe. The strain time histories clearly reflected the cyclic hardening phenomenon in the early stage and the plastic yielding phenomenon in the final stage. Furthermore, based on the cyclic stress-strain constitutive model of the weld material, the stress-strain response curves of all the characteristic points were drawn. Combined with the fatigue fracture morphology, the mechanism of the unsynchronized initiation of the multiple cracks in the weld toe was investigated. Full article
(This article belongs to the Special Issue Selected Papers from IMETI 2018)
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15 pages, 5227 KiB  
Article
Tempcore Process Simulator to Analyze Microstructural Evolution of Quenched and Tempered Rebar
by Chun Su Park, Hyang Jun Yi, Yong-Tae Kim, Sang Wook Han, Taekyung Lee and Young Hoon Moon
Appl. Sci. 2019, 9(14), 2938; https://doi.org/10.3390/app9142938 - 23 Jul 2019
Cited by 11 | Viewed by 7311
Abstract
Tempcore process simulator (TPS) has been developed in this study to analyze the microstructural evolution of quenched and tempered rebar. There has been an increasing need to relate the complex microstructures to the resulting properties of quenched and tempered rebar. However, information on [...] Read more.
Tempcore process simulator (TPS) has been developed in this study to analyze the microstructural evolution of quenched and tempered rebar. There has been an increasing need to relate the complex microstructures to the resulting properties of quenched and tempered rebar. However, information on such relationships typically requires precise thermal histories imposed on the workpiece. Therefore, TPS, capable of simulating the Tempcore process, has been developed to produce high-fidelity data. TPS mainly consists of a vacuum induction furnace, pilot rolling mill, box furnace, and cooling unit to simulate shop floor operations. A series of experimental tests were successfully carried out with various parameters, such as reheating temperature, water flow, water pressure, and cooling time. The effects of chemical compositions and cooling time on the microstructural evolution and mechanical properties of quenched and tempered rebar have been analyzed to validate the performance of TPS. The results show that TPS can simulate the Tempcore process with a high degree of fidelity and reliability. Full article
(This article belongs to the Special Issue Extreme Sciences and Engineering)
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13 pages, 9251 KiB  
Article
Design and Application Research of All-Dielectric Nanostructure Colorful Display
by Shishang Luo, Junbo Yang, Xin He, Sen Zhang and Ying Chen
Appl. Sci. 2019, 9(14), 2937; https://doi.org/10.3390/app9142937 - 23 Jul 2019
Cited by 3 | Viewed by 2933
Abstract
Structural colors generated by plasmonic resonances in metallic nanostructures have been intensively studied and exciting progress has been made. However, because of the inherent plasmon damping, the saturation of these colors generated by metallic nanostructures could not meet the needs of industrial applications. [...] Read more.
Structural colors generated by plasmonic resonances in metallic nanostructures have been intensively studied and exciting progress has been made. However, because of the inherent plasmon damping, the saturation of these colors generated by metallic nanostructures could not meet the needs of industrial applications. As a result, researchers increasingly focus on structural colors generated by all-dielectric nanostructures. In this paper, we discuss a type of all-dielectric nanostructure based on a previous design and analyze its optical properties extensively. The display of character T with different color is realized by using this nanostructure. The study helps the understanding of the influence of structural parameters on structural color and provides some guidance for future experiments. This work can impact the development of the structural color devices which can be applied in color printing, color displays, color filters, imaging, and energy harvesting, etc. Full article
(This article belongs to the Special Issue Advanced Active and Passive Metasurfaces)
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16 pages, 1646 KiB  
Article
Distribution of PM2.5 Air Pollution in Mexico City: Spatial Analysis with Land-Use Regression Model
by Israel Hinojosa-Baliño, Oscar Infante-Vázquez and Maite Vallejo
Appl. Sci. 2019, 9(14), 2936; https://doi.org/10.3390/app9142936 - 23 Jul 2019
Cited by 22 | Viewed by 6651
Abstract
In this study, the spatial distribution of PM2.5 air pollution in Mexico City from 37 personal exposures was modeled. Meteorological, demographic, geographic, and social data were also included. Geographic information systems (GIS), spatial analysis, and Land-Use Regression (LUR) were used to generate [...] Read more.
In this study, the spatial distribution of PM2.5 air pollution in Mexico City from 37 personal exposures was modeled. Meteorological, demographic, geographic, and social data were also included. Geographic information systems (GIS), spatial analysis, and Land-Use Regression (LUR) were used to generate the final predictive model and the spatial distribution map which revealed two areas with very high concentrations (up to 109.3 µg/m3) and two more with lower concentrations (between 72 to 86.5 µg/m3) (p < 0.05). These results illustrate an overview trend of PM2.5 in relation to human activity during the studied periods in Mexico City and show a general approach to understanding the spatial variability of PM2.5. Full article
(This article belongs to the Special Issue Air Pollution)
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13 pages, 1818 KiB  
Article
Deep Learning Resolves Representative Movement Patterns in a Marine Predator Species
by Chengbin Peng, Carlos M. Duarte, Daniel P. Costa, Christophe Guinet, Robert G. Harcourt, Mark A. Hindell, Clive R. McMahon, Monica Muelbert, Michele Thums, Ka-Chun Wong and Xiangliang Zhang
Appl. Sci. 2019, 9(14), 2935; https://doi.org/10.3390/app9142935 - 23 Jul 2019
Cited by 5 | Viewed by 3840
Abstract
The analysis of animal movement from telemetry data provides insights into how and why animals move. While traditional approaches to such analysis mostly focus on predicting animal states during movement, we describe an approach that allows us to identify representative movement patterns of [...] Read more.
The analysis of animal movement from telemetry data provides insights into how and why animals move. While traditional approaches to such analysis mostly focus on predicting animal states during movement, we describe an approach that allows us to identify representative movement patterns of different animal groups. To do this, we propose a carefully designed recurrent neural network and combine it with telemetry data for automatic feature extraction and identification of non-predefined representative patterns. In the experiment, we consider a particular marine predator species, the southern elephant seal, as an example. With our approach, we identify that the male seals in our data set share similar movement patterns when they are close to land. We identify this pattern recurring in a number of distant locations, consistent with alternative approaches from previous research. Full article
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12 pages, 580 KiB  
Review
Digital Manufacturing Platforms in the Industry 4.0 from Private and Public Perspectives
by Jon Kepa Gerrikagoitia, Gorka Unamuno, Elena Urkia and Ainhoa Serna
Appl. Sci. 2019, 9(14), 2934; https://doi.org/10.3390/app9142934 - 23 Jul 2019
Cited by 85 | Viewed by 12867
Abstract
The fourth industrial revolution is characterized by the introduction of the Internet of things (IoT) and Internet of Services (IoS) concepts into manufacturing, which enables smart factories with vertically and horizontally integrated production systems. The main driver is technology, as Industry 4.0 is [...] Read more.
The fourth industrial revolution is characterized by the introduction of the Internet of things (IoT) and Internet of Services (IoS) concepts into manufacturing, which enables smart factories with vertically and horizontally integrated production systems. The main driver is technology, as Industry 4.0 is a collective term for technologies and concepts of value chain organization. Digital manufacturing platforms play an increasing role in dealing with competitive pressures and incorporating new technologies, applications, and services. Motivated by the difficulties to understand and adopt Industry 4.0 and the momentum that the topic has currently, this paper reviews the concepts and approaches related to digital manufacturing platforms from different perspectives: IoT platforms, digital manufacturing platforms, digital platforms as ecosystems, digital platforms from research and development perspective, and digital platform from industrial equipment suppliers. Full article
(This article belongs to the Special Issue New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes)
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17 pages, 10120 KiB  
Article
Virtual Object Manipulation by Combining Touch and Head Interactions for Mobile Augmented Reality
by Ju Young Oh, Ji Hyung Park and Jung-Min Park
Appl. Sci. 2019, 9(14), 2933; https://doi.org/10.3390/app9142933 - 22 Jul 2019
Cited by 8 | Viewed by 5976
Abstract
This paper proposes an interaction method to conveniently manipulate a virtual object by combining touch interaction and head movements for a head-mounted display (HMD), which provides mobile augmented reality (AR). A user can conveniently manipulate a virtual object with touch interaction recognized from [...] Read more.
This paper proposes an interaction method to conveniently manipulate a virtual object by combining touch interaction and head movements for a head-mounted display (HMD), which provides mobile augmented reality (AR). A user can conveniently manipulate a virtual object with touch interaction recognized from the inertial measurement unit (IMU) attached to the index finger’s nail and head movements tracked by the IMU embedded in the HMD. We design two interactions that combine touch and head movements, to manipulate a virtual object on a mobile HMD. Each designed interaction method manipulates virtual objects by controlling ray casting and adjusting widgets. To evaluate the usability of the designed interaction methods, a user evaluation is performed in comparison with the hand interaction using Hololens. As a result, the designed interaction method receives positive feedback that virtual objects can be manipulated easily in a mobile AR environment. Full article
(This article belongs to the Special Issue Augmented Reality: Current Trends, Challenges and Prospects)
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16 pages, 3454 KiB  
Article
Real-Time Implementation of an Expert Model Predictive Controller in a Pilot-Scale Reverse Osmosis Plant for Brackish and Seawater Desalination
by Raul Rivas-Perez, Javier Sotomayor-Moriano, Gustavo Pérez-Zuñiga and Mario E. Soto-Angles
Appl. Sci. 2019, 9(14), 2932; https://doi.org/10.3390/app9142932 - 22 Jul 2019
Cited by 20 | Viewed by 5404
Abstract
This article addresses the design and real-time implementation of an expert model predictive controller (Expert MPC) for the control of the brackish and seawater desalination process in a pilot-scale reverse osmosis (RO) plant. This pilot-scale plant is used in order to obtain the [...] Read more.
This article addresses the design and real-time implementation of an expert model predictive controller (Expert MPC) for the control of the brackish and seawater desalination process in a pilot-scale reverse osmosis (RO) plant. This pilot-scale plant is used in order to obtain the optimal operation conditions of the RO desalination process through the implementation of different control strategies, as well as in the training of operators in the new control and management technologies. A dynamical mathematical model of this plant has been developed based on the available field data and system identification procedures. Predictions of the obtained model were in good agreement with the available field data. The designed Expert MPC is distinguished by having a plant identification block and an expert system. The expert system, using a rule-based approach and the evolution of the plant variables, can modify the plant identification block, the plant prediction model, and/or the optimizer in order to improve the performance, robustness and operational safety of the overall control system. The real-time comparison results of the designed Expert MPC and a well-designed model predictive controller (MPC) show that the proposed Expert MPC has a significantly better performance and, therefore, higher accuracy and robustness. Full article
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16 pages, 3843 KiB  
Article
Multi-Robot Exploration Based on Multi-Objective Grey Wolf Optimizer
by Albina Kamalova, Sergey Navruzov, Dianwei Qian and Suk Gyu Lee
Appl. Sci. 2019, 9(14), 2931; https://doi.org/10.3390/app9142931 - 22 Jul 2019
Cited by 21 | Viewed by 6041
Abstract
In this paper, we used multi-objective optimization in the exploration of unknown space. Exploration is the process of generating models of environments from sensor data. The goal of the exploration is to create a finite map of indoor space. It is common practice [...] Read more.
In this paper, we used multi-objective optimization in the exploration of unknown space. Exploration is the process of generating models of environments from sensor data. The goal of the exploration is to create a finite map of indoor space. It is common practice in mobile robotics to consider the exploration as a single-objective problem, which is to maximize a search of uncertainty. In this study, we proposed a new methodology of exploration with two conflicting objectives: to search for a new place and to enhance map accuracy. The proposed multiple-objective exploration uses the Multi-Objective Grey Wolf Optimizer algorithm. It begins with the initialization of the grey wolf population, which are waypoints in our multi-robot exploration. Once the waypoint positions are set in the beginning, they stay unchanged through all iterations. The role of updating the position belongs to the robots, which select the non-dominated waypoints among them. The waypoint selection results from two objective functions. The performance of the multi-objective exploration is presented. The trade-off among objective functions is unveiled by the Pareto-optimal solutions. A comparison with other algorithms is implemented in the end. Full article
(This article belongs to the Special Issue Mobile Robots Navigation)
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13 pages, 778 KiB  
Article
A Hybrid Approach Using Fuzzy AHP-TOPSIS Assessing Environmental Conflicts in the Titan Mining Industry along Central Coast Vietnam
by Manh Tien Dao, An Thinh Nguyen, The Kien Nguyen, Ha T.T. Pham, Dinh Tien Nguyen, Quoc Toan Tran, Huong Giang Dao, Duyen T. Nguyen, Huong T. Dang and Luc Hens
Appl. Sci. 2019, 9(14), 2930; https://doi.org/10.3390/app9142930 - 22 Jul 2019
Cited by 29 | Viewed by 5251
Abstract
Environmental conflict management gains significance in rational use of natural resources, ecosystem preservation and environmental planning for mineral mines. In Central Coast Vietnam, titan mines are subject to conflicting use and management decisions. The paper deals with an empirical research on applying a [...] Read more.
Environmental conflict management gains significance in rational use of natural resources, ecosystem preservation and environmental planning for mineral mines. In Central Coast Vietnam, titan mines are subject to conflicting use and management decisions. The paper deals with an empirical research on applying a combination of the fuzzy Analytic Hierarchy Process (AHP) and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to measure environmental conflicts emerging as a result of titan mining in Vietnam. The methodology used in the paper combines the fuzzy AHP and the fuzzy TOPSIS to rank environmental conflicts and propose conflict prevention solutions in the titan mining industry of Ky Khang coastal commune (Ky Anh district, Central Coast Vietnam). Data was collected by using a questionnaire with 15 locals, 8 communal authorities, 2 district authorities, and 12 scientific experts on titan mining, environmental geology, and sustainability management. The result shows that, titan mining conflicts with the eight criteria of economic sectors at five alternative sites including beach, protected forest, agricultural area, settlement area, and industrial area. The conflicts between titan mining and forestry, agriculture, settlements, fishing and aquaculture are highly valued. The beach area shows most environmental conflict as a result of titan mining, followed by the agricultural area and settlement area. Based on the empirical findings, legal and procedural tools such as environmental impact assessments, strategic environmental assessments, integrated coastal zone management, marine spatial planning, and multi-planning integration advancing environmental management for titan mines in Vietnam are suggested. Full article
(This article belongs to the Special Issue Coastal Deposits: Environmental Implications, Mathematical Modeling and Technological Development)
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13 pages, 10613 KiB  
Article
Augmented Reality Implementations in Stomatology
by Aleš Procházka, Tatjana Dostálová, Magdaléna Kašparová, Oldřich Vyšata, Hana Charvátová, Saeid Sanei and Vladimír Mařík
Appl. Sci. 2019, 9(14), 2929; https://doi.org/10.3390/app9142929 - 22 Jul 2019
Cited by 13 | Viewed by 3634
Abstract
Augmented reality has a wide range of applications in many areas that can extend the study of real objects into the digital world, including stomatology. Real dental objects that were previously examined using their plaster casts are often replaced by their digital models [...] Read more.
Augmented reality has a wide range of applications in many areas that can extend the study of real objects into the digital world, including stomatology. Real dental objects that were previously examined using their plaster casts are often replaced by their digital models or three-dimensional (3D) prints in the cyber-physical world. This paper reviews a selection of digital methods that have been applied in dentistry, including the use of intra-oral scanning technology for data acquisition and evaluation of fundamental features of dental arches. The methodology includes the use of digital filters and morphological operations for spatial objects analysis, their registration, and evaluation of changes during the treatment of specific disorders. The results include 3D models of selected dental arch objects, which allow a comparison of their shape and position during repeated observations. The proposed methods present digital alternatives to the use of plaster casts for semiautomatic evaluation of dental arch measures. This paper describes some of the advantages of 3D digital technology replacing real world elements and plaster cast dental models in many areas of classical stomatology. Full article
(This article belongs to the Special Issue Augmented Reality: Current Trends, Challenges and Prospects)
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25 pages, 1505 KiB  
Article
Address Space Layout Randomization Next Generation
by Hector Marco-Gisbert and Ismael Ripoll Ripoll
Appl. Sci. 2019, 9(14), 2928; https://doi.org/10.3390/app9142928 - 22 Jul 2019
Cited by 27 | Viewed by 15168
Abstract
Systems that are built using low-power computationally-weak devices, which force developers to favor performance over security; which jointly with its high connectivity, continuous and autonomous operation makes those devices specially appealing to attackers. ASLR (Address Space Layout Randomization) is one of the most [...] Read more.
Systems that are built using low-power computationally-weak devices, which force developers to favor performance over security; which jointly with its high connectivity, continuous and autonomous operation makes those devices specially appealing to attackers. ASLR (Address Space Layout Randomization) is one of the most effective mitigation techniques against remote code execution attacks, but when it is implemented in a practical system its effectiveness is jeopardized by multiple constraints: the size of the virtual memory space, the potential fragmentation problems, compatibility limitations, etc. As a result, most ASLR implementations (specially in 32-bits) fail to provide the necessary protection. In this paper we propose a taxonomy of all ASLR elements, which categorizes the entropy in three dimensions: (1) how, (2) when and (3) what; and includes novel forms of entropy. Based on this taxonomy we have created, ASLRA, an advanced statistical analysis tool to assess the effectiveness of any ASLR implementation. Our analysis show that all ASLR implementations suffer from several weaknesses, 32-bit systems provide a poor ASLR, and OS X has a broken ASLR in both 32- and 64-bit systems. This is jeopardizing not only servers and end users devices as smartphones but also the whole IoT ecosystem. To overcome all these issues, we present ASLR-NG, a novel ASLR that provides the maximum possible absolute entropy and removes all correlation attacks making ASLR-NG the best solution for both 32- and 64-bit systems. We implemented ASLR-NG in the Linux kernel 4.15. The comparative evaluation shows that ASLR-NG overcomes PaX, Linux and OS X implementations, providing strong protection to prevent attackers from abusing weak ASLRs. Full article
(This article belongs to the Special Issue Security Issues and Solutions of Smart Contracts in Blockchain Technology)
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17 pages, 6417 KiB  
Review
Magnetic Nanomaterials for Magnetically-Aided Drug Delivery and Hyperthermia
by Madumali Kalubowilage, Katharine Janik and Stefan H. Bossmann
Appl. Sci. 2019, 9(14), 2927; https://doi.org/10.3390/app9142927 - 22 Jul 2019
Cited by 33 | Viewed by 5735
Abstract
Magnetic nanoparticles have continuously gained importance for the purpose of magnetically-aided drug-delivery, magnetofection, and hyperthermia. We have summarized significant experimental approaches, as well as their advantages and disadvantages with respect to future clinical translation. This field is alive and well and promises meaningful [...] Read more.
Magnetic nanoparticles have continuously gained importance for the purpose of magnetically-aided drug-delivery, magnetofection, and hyperthermia. We have summarized significant experimental approaches, as well as their advantages and disadvantages with respect to future clinical translation. This field is alive and well and promises meaningful contributions to the development of novel cancer therapies. Full article
(This article belongs to the Special Issue Magnetic Nanomaterials for Drug Delivery and Therapy)
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16 pages, 4146 KiB  
Article
Synthesis and Diagnostics of Nanostructured Micaless Microcomposite as a Prospective Insulation Material for Rotating Machines
by Jaroslav Hornak, Václav Mentlík, Pavel Trnka and Pavol Šutta
Appl. Sci. 2019, 9(14), 2926; https://doi.org/10.3390/app9142926 - 22 Jul 2019
Cited by 6 | Viewed by 3263
Abstract
This paper deals with the topic of composite insulation materials for rotating machines and it is primarily pointed to the synthesis of new three-component insulation system. In connection with this research, the basic components of the insulation system are selected and described by [...] Read more.
This paper deals with the topic of composite insulation materials for rotating machines and it is primarily pointed to the synthesis of new three-component insulation system. In connection with this research, the basic components of the insulation system are selected and described by different diagnostic methods. The proposed insulation material is composed of epoxy resin based on bisphenol-A diglycidyl ether, magnesium oxide nanofiller (1 wt %) with its own surface treatment technology using epoxysilane coupling agent ( γ -glycidoxypropyltrimethoxysilane) and polyethylene naphthalate as a reinforcing component. Following the defined topic of the paper, the proposed three-component insulation system is confronted with commonly used insulating systems (PET reinforced and Glass reinforced mica composites) in order to verify the basic dielectric properties (dielectric strength, volume resistivity, dissipation factor) and other parameters determined from phenomenological voltage and current signals, respectively. Full article
(This article belongs to the Section Nanotechnology and Applied Nanosciences)
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30 pages, 2542 KiB  
Review
Graphene Composites for Lead Ions Removal from Aqueous Solutions
by Mukesh Kumar, Jin Suk Chung and Seung Hyun Hur
Appl. Sci. 2019, 9(14), 2925; https://doi.org/10.3390/app9142925 - 22 Jul 2019
Cited by 36 | Viewed by 6573
Abstract
The indiscriminate disposal of non-biodegradable, heavy metal ionic pollutants from various sources, such as refineries, pulp industries, lead batteries, dyes, and other industrial effluents, into the aquatic environment is highly dangerous to the human health as well as to the environment. Among other [...] Read more.
The indiscriminate disposal of non-biodegradable, heavy metal ionic pollutants from various sources, such as refineries, pulp industries, lead batteries, dyes, and other industrial effluents, into the aquatic environment is highly dangerous to the human health as well as to the environment. Among other heavy metals, lead (Pb(II)) ions are some of the most toxic pollutants generated from both anthropogenic and natural sources in very large amounts. Adsorption is the simplest, efficient and economic water decontamination technology. Hence, nanoadsorbents are a major focus of current research for the effective and selective removal of Pb(II) metal ions from aqueous solution. Nanoadsorbents based on graphene and its derivatives play a major role in the effective removal of toxic Pb(II) metal ions. This paper summarizes the applicability of graphene and functionalized graphene-based composite materials as Pb(II) ions adsorbent from aqueous solutions. In addition, the synthetic routes, adsorption process, conditions, as well as kinetic studies have been reviewed. Full article
(This article belongs to the Special Issue Nanocomposites for the Sustainable Environment)
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11 pages, 3288 KiB  
Article
Performance Improvement for PMSM Driven by DTC Based on Discrete Duty Ratio Determination Method
by Dazhi Wang, Tianqing Yuan, Xingyu Wang, Xinghua Wang, Sihan Wang and Yongliang Ni
Appl. Sci. 2019, 9(14), 2924; https://doi.org/10.3390/app9142924 - 22 Jul 2019
Cited by 4 | Viewed by 2867
Abstract
In order to improve the performance of the servo control system, which is composed ofthe permanent magnet synchronous motor (PMSM) driven by novel direct torque control based on the fixed sector division criterion (FS-DTC) utilizing the composite active vectors, a discrete duty ratio [...] Read more.
In order to improve the performance of the servo control system, which is composed ofthe permanent magnet synchronous motor (PMSM) driven by novel direct torque control based on the fixed sector division criterion (FS-DTC) utilizing the composite active vectors, a discrete duty ratio determination method (FS-DDTC) is proposed in this paper. The determination of the accurate duty ratio is the key to obtain the desired error compensational results for PMSM, which is related to the performance of the servo system directly. As the applied master vector and slave vector during each control period are the adjacent vectors, therefore, the direction of the synthetic vector is between the directions of the two applied active vectors. Additionally, the analytical relationship between the sector angle of the synthetic vector and the error rate, which can realize the determination of the discrete duty ratio value without complicated calculations is deduced first. Furthermore, the duty ratio values of the two applied active vectors in FS-DTC are obtained through the selections of the duty ratio scale in the novel discrete duty ratio determination method directly, which can simplify the calculation process of the accurate duty ratio values effectively. The effectiveness of the proposed discrete duty ratio determination method is verified through the experimental results on a 100-W PMSM drive system. Full article
(This article belongs to the Section Energy Science and Technology)
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20 pages, 8735 KiB  
Article
Wind Resource Assessment on Puná Island
by Yuri Merizalde, Luis Hernández-Callejo, Javier Gracia Bernal, Enrique Telmo Martínez, Oscar Duque-Perez, Francisco Sánchez and Andrés Llombart Estpopiñán
Appl. Sci. 2019, 9(14), 2923; https://doi.org/10.3390/app9142923 - 22 Jul 2019
Cited by 3 | Viewed by 3357
Abstract
Puná Island, located in the Pacific Ocean off the southern coast of Ecuador, has a population of approximately 3344 inhabitants. However, not all inhabitants have access to electricity, which is largely supplied by diesel generators. Therefore, to identify a renewable, sustainable, environmentally friendly [...] Read more.
Puná Island, located in the Pacific Ocean off the southern coast of Ecuador, has a population of approximately 3344 inhabitants. However, not all inhabitants have access to electricity, which is largely supplied by diesel generators. Therefore, to identify a renewable, sustainable, environmentally friendly and low-cost alternative, a 40-m-high anemometer tower was installed for wind resource assessment and to determine the possibility of generating electricity from wind energy. Based on mathematical models for electricity generation from wind energy, data were analyzed using the software Windographer and WAsP, to determine a long-term wind speed of 4.8 m/s and a mean wind power density of 272 W/m2. By simulating the use of a 3.3-MW wind turbine, we demonstrated that as much as 800 kWh could be generated during the hours when the wind reaches its highest speed. In addition to demonstrating the technical feasibility of meeting the electricity demands of Puná Island through wind power, this study exemplifies a method that can be used for wind resource assessment in any location. Full article
(This article belongs to the Section Energy Science and Technology)
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11 pages, 1509 KiB  
Article
Using the Characteristics of Pulse Waveform to Enhance the Accuracy of Blood Pressure Measurement by a Multi-Dimension Regression Model
by Shing-Hong Liu, Li-Jen Liu, Kuo-Li Pan, Wenxi Chen and Tan-Hsu Tan
Appl. Sci. 2019, 9(14), 2922; https://doi.org/10.3390/app9142922 - 22 Jul 2019
Cited by 12 | Viewed by 3944
Abstract
With the advancement of wearable technology, many physiological monitoring instruments are gradually being converted into wearable devices. However, as a consumer product, the blood pressure monitor is still a cuff-type device, which does perform a beat-by-beat continuous blood pressure measurement. Consequently, the cuffless [...] Read more.
With the advancement of wearable technology, many physiological monitoring instruments are gradually being converted into wearable devices. However, as a consumer product, the blood pressure monitor is still a cuff-type device, which does perform a beat-by-beat continuous blood pressure measurement. Consequently, the cuffless blood pressure measurement device was developed and it is based on the pulse transit time (PTT), although its accuracy remains inadequate. According to the cardiac hemodynamic theorem, blood pressure relates to the arterial characteristics and the contours of the pulse wave include some characteristics of the artery. Therefore, the purpose of this study was to use the contour characteristics of the pulses measured by photoplethysmography (PPG) to estimate the blood pressure using a linear multi-dimension regression model. Ten subjects participated in the experiment, and the blood pressure levels of the subjects were elevated by exercise. The results showed that the mean and standard deviation (mean ± SD) of the root mean square error of the estimated systolic and diastolic pressures within the best five parameters were 6.9 ± 2.81 mmHg and 4.0 ± 0.65 mmHg, respectively. Compared to the results that used one parameter, the PTT, for estimating the systolic and diastolic pressures, 8.2 ± 2.1 mmHg and 4.5 ± 0.79 mmHg, respectively, our results were better. Full article
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17 pages, 4472 KiB  
Article
An Automated ECG Beat Classification System Using Deep Neural Networks with an Unsupervised Feature Extraction Technique
by Siti Nurmaini, Radiyati Umi Partan, Wahyu Caesarendra, Tresna Dewi, Muhammad Naufal Rahmatullah, Annisa Darmawahyuni, Vicko Bhayyu and Firdaus Firdaus
Appl. Sci. 2019, 9(14), 2921; https://doi.org/10.3390/app9142921 - 22 Jul 2019
Cited by 68 | Viewed by 6870
Abstract
An automated classification system based on a Deep Learning (DL) technique for Cardiac Disease (CD) monitoring and detection is proposed in this paper. The proposed DL architecture is divided into Deep Auto-Encoders (DAEs) as an unsupervised form of feature learning and Deep Neural [...] Read more.
An automated classification system based on a Deep Learning (DL) technique for Cardiac Disease (CD) monitoring and detection is proposed in this paper. The proposed DL architecture is divided into Deep Auto-Encoders (DAEs) as an unsupervised form of feature learning and Deep Neural Networks (DNNs) as a classifier. The objective of this study is to improve on the previous machine learning technique that consists of several data processing steps such as feature extraction and feature selection or feature reduction. It is also noticed that the previously used machine learning technique required human interference and expertise in determining robust features, yet was time-consuming in the labeling and data processing steps. In contrast, DL enables an embedded feature extraction and feature selection in DAEs pre-training and DNNs fine-tuning process directly from raw data. Hence, DAEs is able to extract high-level of features not only from the training data but also from unseen data. The proposed model uses 10 classes of imbalanced data from ECG signals. Since it is related to the cardiac region, abnormality is usually considered for an early diagnosis of CD. In order to validate the result, the proposed model is compared with the shallow models and DL approaches. Results found that the proposed method achieved a promising performance with 99.73% accuracy, 91.20% sensitivity, 93.60% precision, 99.80% specificity, and a 91.80% F1-Score. Moreover, both the Receiver Operating Characteristic (ROC) curve and the Precision-Recall (PR) curve from the confusion matrix showed that the developed model is a good classifier. The developed model based on unsupervised feature extraction and deep neural network is ready to be used on a large population before its installation for clinical usage. Full article
(This article belongs to the Special Issue Electrocardiogram (ECG) Signal and Its Applications)
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21 pages, 6600 KiB  
Article
Visualization of the Strain-Rate State of a Data Cloud: Analysis of the Temporal Change of an Urban Multivariate Description
by Lorena Salazar-Llano and Camilo Bayona-Roa
Appl. Sci. 2019, 9(14), 2920; https://doi.org/10.3390/app9142920 - 22 Jul 2019
Viewed by 2868
Abstract
One challenging problem is the representation of three-dimensional datasets that vary with time. These datasets can be thought of as a cloud of points that gradually deforms. However, point-wise variations lack information about the overall deformation pattern, and, more importantly, about the extreme [...] Read more.
One challenging problem is the representation of three-dimensional datasets that vary with time. These datasets can be thought of as a cloud of points that gradually deforms. However, point-wise variations lack information about the overall deformation pattern, and, more importantly, about the extreme deformation locations inside the cloud. This present article applies a technique in computational mechanics to derive the strain-rate state of a time-dependent and three-dimensional data distribution, by which one can characterize its main trends of shift. Indeed, the tensorial analysis methodology is able to determine the global deformation rates in the entire dataset. With the use of this technique, one can characterize the significant fluctuations in a reduced multivariate description of an urban system and identify the possible causes of those changes: calculating the strain-rate state of a PCA-based multivariate description of an urban system, we are able to describe the clustering and divergence patterns between the districts of a city and to characterize the temporal rate in which those variations happen. Full article
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15 pages, 4828 KiB  
Communication
Shape Memory Effect in Micro-Sized Shape Memory Polymer Composite Chains
by Xin Lan, Weimin Huang and Jinsong Leng
Appl. Sci. 2019, 9(14), 2919; https://doi.org/10.3390/app9142919 - 22 Jul 2019
Cited by 9 | Viewed by 3813
Abstract
Since the shape memory effect (SME) has been confirmed in micron and submicron sized polyurethane (PU) shape memory polymer (SMP), it might be used in novel micro/nano devices even for surgery/operation inside a single cell. In this study, micron sized protrusive PU SMP [...] Read more.
Since the shape memory effect (SME) has been confirmed in micron and submicron sized polyurethane (PU) shape memory polymer (SMP), it might be used in novel micro/nano devices even for surgery/operation inside a single cell. In this study, micron sized protrusive PU SMP composite chains are fabricated via mixing ferromagnetic nickel micro powders with PU SMP/dimethylformamide solution and then cured under a low magnetic field. Depending on the amount of nickel content, vertical protrusive chains with a diameter from 10 to 250 µm and height from 200 to 1500 µm are obtained. The SME in these chains is investigated to confirm the SME in SMP composites at microscale. An array of such protrusive chains may be utilized to obtain re-configurable surface patterns in a simple manner for applications, such as remarkable change in wetting and friction ability. Finally, its potential applications for micro electro mechanical systems (MEMS) and biomedical device are proposed. Full article
(This article belongs to the Special Issue Synthesis, Characterization and Application of Hybrid Composites)
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22 pages, 8070 KiB  
Article
Congestion-Free Ant Traffic: Jam Absorption Mechanism in Multiple Platoons
by Prafull Kasture and Hidekazu Nishimura
Appl. Sci. 2019, 9(14), 2918; https://doi.org/10.3390/app9142918 - 22 Jul 2019
Cited by 6 | Viewed by 3490
Abstract
In this paper, an agent-based model of ant traffic on a unidirectional single-lane ant trail is presented to provide better understanding of the jam-free traffic of an ant colony. On a trail, the average velocity of ants remains approximately constant irrespective of density, [...] Read more.
In this paper, an agent-based model of ant traffic on a unidirectional single-lane ant trail is presented to provide better understanding of the jam-free traffic of an ant colony. On a trail, the average velocity of ants remains approximately constant irrespective of density, thereby avoiding jamming. Assuming chemotaxis, we analyze platoon-related scenarios to assess the marching-platoon hypothesis, which claims that ants on a trail form a single platoon in which they march synchronously, thereby reducing hindrances due to increasing density. Contrary to that hypothesis, our findings show that ants on a trail do not march synchronously and do experience stop-and-go motion. However, more interestingly, our study also indicates that the ants’ chemotaxis behavior leads to a peculiar jam absorption mechanism, which helps to maintain free flow on a trail and avoids jamming. Again, contrary to the marching-platoon hypothesis, our findings also indicate that, rather than assisting traffic flow, forming a single cluster actually triggers jamming. Full article
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19 pages, 6691 KiB  
Article
Extracting Crop Spatial Distribution from Gaofen 2 Imagery Using a Convolutional Neural Network
by Yan Chen, Chengming Zhang, Shouyi Wang, Jianping Li, Feng Li, Xiaoxia Yang, Yuanyuan Wang and Leikun Yin
Appl. Sci. 2019, 9(14), 2917; https://doi.org/10.3390/app9142917 - 22 Jul 2019
Cited by 15 | Viewed by 3458
Abstract
Using satellite remote sensing has become a mainstream approach for extracting crop spatial distribution. Making edges finer is a challenge, while simultaneously extracting crop spatial distribution information from high-resolution remote sensing images using a convolutional neural network (CNN). Based on the characteristics of [...] Read more.
Using satellite remote sensing has become a mainstream approach for extracting crop spatial distribution. Making edges finer is a challenge, while simultaneously extracting crop spatial distribution information from high-resolution remote sensing images using a convolutional neural network (CNN). Based on the characteristics of the crop area in the Gaofen 2 (GF-2) images, this paper proposes an improved CNN to extract fine crop areas. The CNN comprises a feature extractor and a classifier. The feature extractor employs a spectral feature extraction unit to generate spectral features, and five coding-decoding-pair units to generate five level features. A linear model is used to fuse features of different levels, and the fusion results are up-sampled to obtain a feature map consistent with the structure of the input image. This feature map is used by the classifier to perform pixel-by-pixel classification. In this study, the SegNet and RefineNet models and 21 GF-2 images of Feicheng County, Shandong Province, China, were chosen for comparison experiment. Our approach had an accuracy of 93.26%, which is higher than those of the existing SegNet (78.12%) and RefineNet (86.54%) models. This demonstrates the superiority of the proposed method in extracting crop spatial distribution information from GF-2 remote sensing images. Full article
(This article belongs to the Special Issue Machine Learning Techniques Applied to Geospatial Big Data)
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10 pages, 3571 KiB  
Article
Theoretical Study of SOF2 Adsorption on Pd/Pt-Ni(111) Bimetallic Surfaces
by Shiming Gan, Yingang Gui, Xiaoyan Bao and Dong Chen
Appl. Sci. 2019, 9(14), 2916; https://doi.org/10.3390/app9142916 - 22 Jul 2019
Cited by 2 | Viewed by 3146
Abstract
Partial discharge has become a serious threat to the stable operation of gas-insulated switchgears. SOF2 is a characteristic decomposition component of SF6 decomposition components under partial discharge, which further deteriorate the severity of partial discharge. In order to find an excellent [...] Read more.
Partial discharge has become a serious threat to the stable operation of gas-insulated switchgears. SOF2 is a characteristic decomposition component of SF6 decomposition components under partial discharge, which further deteriorate the severity of partial discharge. In order to find an excellent adsorbent for SOF2, Pd/Pt-Ni(111) composite surface is raised as an adsorbent to investigate its adsorption ability of the SOF2 molecule. The results of the study show that Pd or Pt composite layer on Ni(111) atoms can significantly enhance the adsorption capacity, the adsorption ability to SOF2 is in the sequence of Pt-Ni(111) > Pd-Ni(111) > Ni(111) > Ni-Pd-Ni(111) > Ni-Pt-Ni(111). However, the adsorption of SOF2 on Pt-Ni(111) and Pd-Ni(111) surfaces is strong chemisorption, which is an irreversible adsorption process. On the contrary, Ni-Pd-Ni(111) and Ni-Pt-Ni(111) show moderate physisorption of SOF2. In addition, the density of electronic states, and electron density difference are further calculated to analyze the adsorption mechanism of SOF2. This research provides important theoretical support for developing an ideal SOF2 adsorbent. Full article
(This article belongs to the Section Nanotechnology and Applied Nanosciences)
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