Effects of Alkyl Chain Length on Interfacial Structure and Differential Capacitance in Graphene Supercapacitors: A Molecular Dynamics Simulation Study

Jo, Sungsik,Park, Sang-Won,Shim, Youngseon,Jung, YounJoon Elsevier 2017 ELECTROCHIMICA ACTA Vol.247 No.-

<P><B>Abstract</B></P> <P>Supercapacitors with graphene electrodes are studied via molecular dynamics simulation. As an electrolyte, we consider three different room-temperature ionic liquids (RTILs), each of which is made up of the same anion BF<SUB>4</SUB> <SUP>−</SUP>, and different cations, 1-C<SUB>n</SUB>(n=2,4,6)-3-methylimidazolium, respectively. We investigate how the alkyl chain length of the cation affects their interfacial structure and electrical properties for electric double layer capacitors. As a whole, cations and anions make layering structures between two parallel electrodes. Cations in the nearest layer orient predominantly in parallel to the electrode. Imidazolium rings of cations form π-stacking with graphene, then the alkyl chains of cations align parallel to the electrode. Differential capacitances in three RTILs are found to decrease with an increase of the magnitude of electrode potentials. The ion size and orientation affect both structure and capacitance behavior. The parallel orientations of cations become stronger with an increase of the alkyl chain length for the considered RTILs. The differential capacitance tends to decrease with raising the alkyl chain length over a wide range of the electrode potential. This is ascribed to a steric effect caused by larger cation size. It is also found that anodic capacitance is higher than cathodic one due to a higher screening efficiency by small anions, and an asymmetry in the peak of capacitance biased to the cathodic side becomes weaker as the alkyl chain length increases. Comparing electrode charge with ion numbers near the electrodes, with respect to their changes in response to the electrode potential, we find that the interfacial layer of the electrolyte mainly governs capacitive behavior of the systems.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The structure and electrical properties of the supercapacitors consisting of imidazolium-based ionic liquids are studied via molecular dynamics simulation. </LI> <LI> A longer alkyl chain of cations results in an enhanced π-stacking with the graphene electrode, but a lower differential capacitance. </LI> <LI> Ionic layers are defined from the ion number density distribution as a function of electrode charge. </LI> <LI> differential ion capacity shows a good correlation with the differential capacitance, indicating the importance of the interfacial layer of the electrolyte. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Computer simulation study of differential capacitance and charging mechanism in graphene supercapacitors: Effects of cyano-group in ionic liquids

Jo, Sungsik,Park, Sang-Won,Noh, Chanwoo,Jung, YounJoon Elsevier 2018 ELECTROCHIMICA ACTA Vol.284 No.-

<P><B>Abstract</B></P> <P>Molecular dynamics simulation is employed to study graphene supercapacitors. Four different ionic liquids are considered as an electrolyte, each of which is combination of the same cation 1-ethyl-3-methylimidazolium([emim]<SUP>+</SUP>), and different, cyano-containing anions, thiocyanate ([SCN]<SUP>–</SUP>), dicyanamide ([N(CN)<SUB>2</SUB>]<SUP>–</SUP>), tricyanomethanide ([C(CN)<SUB>3</SUB>]<SUP>–</SUP>), and tetracyanoborate ([B(CN)<SUB>4</SUB>]<SUP>–</SUP>), respectively. In particular we investigate how electric double layer structure and electrical properties are affected by the structure of cyano containing anions. Cations and anions make alternating structure near charged electrode. Differential capacitances in four ionic liquids are found to have a maximum value at negative potential. The maximum capacitances are comparable to each other, but the corresponding potential shifts to the negative side as more cyano groups are attached to the anion. Starting from the interfacial layer, the effects of the further ionic layers on differential capacitance are systematically investigated. Comparing charges of the electrode and those of ionic layers, we find that differential capacitance behavior mainly stems from the ion exchange between electric double layer and bulk region. The ion exchange behaviors are decomposed into cation and anion contributions. The differential charging mechanisms of the system are strongly dependent on the electric potential. The maximum capacitances are consequence of rapid desorption of respective anions.</P>

Accelerated Monte Carlo analysis of flow-based system reliability through artificial neural network-based surrogate models

Sungsik Yoon,Young-Joo Lee,Hyung-Jo Jung 국제구조공학회 2020 Smart Structures and Systems, An International Jou Vol.26 No.2

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

Flow-based seismic resilience assessment of urban water transmission networks

Sungsik Yoon,Young-Joo Lee,Hyung-Jo Jung 국제구조공학회 2021 Structural Engineering and Mechanics, An Int'l Jou Vol.79 No.4

In this study, a new framework of seismic resilience estimation for urban water transmission networks was developed. The proposed resilience estimation model consists of three phases: input earthquake generation, hydraulic analysis, and recovery of network facilities. In the earthquake generation phase, the uncertainty of the ground motion is determined using the spatially correlated seismic attenuation law. In the hydraulic analysis phase, a hydraulic simulation is performed in conjunction with EPANET analysis. In the recovery phase, network components are restored, and the performance of the recovered network is evaluated through hydraulic analysis. Then, the seismic resilience curve and recovery costs are calculated. For a numerical simulation, a MATLAB-based computer code was developed for pressure-driven analysis in EPANET simulation. To demonstrate the proposed model, an actual water transmission network in South Korea was reconstructed based on geographic information system data. The performance of the network system was evaluated according to two performance indices: system and nodal serviceability. Finally, the cost of repairing the network facilities and water loss are estimated according to earthquake magnitude and interdependency. Numerical results show that the recovery slope of the resilience curve tends to decrease as the earthquake magnitude and interdependency with the power facilities increase.

Bridge Inspection and condition assessment using Unmanned Aerial Vehicles (UAVs): Major challenges and solutions from a practical perspective

Hyung-Jo Jung,Jin-Hwan Lee,Sungsik Yoon,김인호 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.24 No.5

Bridge collapses may deliver a huge impact on our society in a very negative way. Out of many reasons why bridges collapse, poor maintenance is becoming a main contributing factor to many recent collapses. Furthermore, the aging of bridges is able to make the situation much worse. In order to prevent this unwanted event, it is indispensable to conduct continuous bridge monitoring and timely maintenance. Visual inspection is the most widely used method, but it is heavily dependent on the experience of the inspectors. It is also time-consuming, labor-intensive, costly, disruptive, and even unsafe for the inspectors. In order to address its limitations, in recent years increasing interests have been paid to the use of unmanned aerial vehicles (UAVs), which is expected to make the inspection process safer, faster and more cost-effective. In addition, it can cover the area where it is too hard to reach by inspectors. However, this strategy is still in a primitive stage because there are many things to be addressed for real implementation. In this paper, a typical procedure of bridge inspection using UAVs consisting of three phases (i.e., pre-inspection, inspection, and post-inspection phases) and the detailed tasks by phase are described. Also, three major challenges, which are related to a UAV’s flight, image data acquisition, and damage identification, respectively, are identified from a practical perspective (e.g., localization of a UAV under the bridge, high-quality image capture, etc.) and their possible solutions are discussed by examining recently developed or currently developing techniques such as the graph-based localization algorithm, and the image quality assessment and enhancement strategy. In particular, deep learning based algorithms such as R-CNN and Mask R-CNN for classifying, localizing and quantifying several damage types (e.g., cracks, corrosion, spalling, efflorescence, etc.) in an automatic manner are discussed. This strategy is based on a huge amount of image data obtained from unmanned inspection equipment consisting of the UAV and imaging devices (vision and IR cameras).

고승압 대전력 확장에 적합한 비절연 소프트 스위칭 DC-DC 컨버터

박성식(Sungsik Park),박요한(Yohan Park),최세완(Sewan Choi),조진상(Jinsang Jo),김태희(Taehee Kim) 전력전자학회 2009 전력전자학술대회 논문집 Vol.2009 No.1

본 논문에서는 고승압의 연료전지 응용에 적합한 새로운 비절연 다상 DC-DC 컨버터를 제안한다. 제안하는 컨버터는 CCM에서도 스위치의 ZVS 턴온이 가능하며 다이오드의 ZCS 턴오프 동작으로 역방향 회복으로 인한 서지가 없다. 또한 병렬수와 직렬수를 적절히 선택하면 대전력 및 고승압 응용에서도 가격과 수급이 용이한 부품 사용이 가능하다. 또한 모든 소자의 전압 정격과 수동소자의 부피도 기존 부스트 컨버터보다 작다.

300㎾급 발전용 연료전지 PCS의 부피저감을 위한 DC-DC 컨버터 최적 설계

박성식(Sungsik Park),권준범(Junbum Kwon),최세완(Sewan Choi),조진상(Jinsang Jo),김태희(Taehee Kim) 전력전자학회 2008 전력전자학술대회 논문집 Vol.- No.-

기존의 발전용 연료전지 PCS 는 주로 DC-DC 컨버터 없이 인버터만 있는 방식이거나 3상의 DC-DC 컨버터에 인버터를 사용하는 방식이다. 본 논문에서는 발전용 연료전지 PCS의 부피저감과 고효율을 위한 DC-DC 컨버터의 최적 설계를 제안한다. 제안하는 DC-DC 컨버터는 DCM에 의한 소프트 스위칭으로 스위칭 주파수를 증가시킴과 동시에 상수를 증가시키는 방식으로 다상의 인터리빙으로 인해 필터 부피가 작아져 전체 PCS 효율을 높게 유지하면서 부피를 저감할 수 있다. 본 논문에서 PCS의 이론적 효율계산을 통해 DC-DC 컨버터의 최적 상수를 선정하였다.

Seismic fragility analysis of a buried pipeline structure considering uncertainty of soil parameters

Yoon, Sungsik,Lee, Do Hyung,Jung, Hyung-Jo Elsevier 2019 The International journal of pressure vessels and Vol.175 No.-

<P><B>Abstract</B></P> <P>In this study, the seismic fragility analysis for a buried gas pipeline of API 5L X65 was performed considering the uncertainty of soil parameters. For this purpose, nonlinear time history analyses were carried out for the pipeline considering soil-pipeline interaction represented by beam on nonlinear Winkler foundation model. A total of 12 input ground motions were employed and four different analytical cases were considered to evaluate the effect of the uncertainty of soil parameters. The four cases proved that uncertainty of soil parameters needs to be taken into account for the assessment of the pipeline response. Using results of the nonlinear time history analyses, seismic fragility analyses were conducted in accordance with three damage states. Analytical predictions indicated that seismic fragility curves with the uncertainty of soil parameters exhibit higher failure probability than those without the uncertainty. It is thus concluded that the present study is promising for the exploration of the seismic fragility analysis considering the uncertainty of soil parameters.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Seismic fragility analysis has been carried out for a buried gas pipeline considering uncertainty of soil parameters. </LI> <LI> Beam on nonlinear-Winkler foundation model was utilized for soil-pipeline interaction. </LI> <LI> An efficient Monte Carlo Simulation employing Latin Hypercube Sampling was adopted. </LI> <LI> Unit-weight has been identified as dominant factor affecting the behavior of pipeline. </LI> <LI> Seismic fragility curve that takes into account the uncertainty of soil parameters was more vulnerable to earthquakes. </LI> </UL> </P>

흐름 기반 상수도 네트워크의 지진 회복력 평가

윤성식(Yoon, Sungsik),이영주(Lee, Young-Joo),정형조(Jung, Hyung-Jo) 대한토목학회 2019 대한토목학회 학술대회 Vol.2019 No.10

HILS of Deep Learning-based TAS Sensor fail-safe technology for Heavy Commercial 100Nm Electro-Hydraulic Power Steering Systems

Soon-Woong Cha(차순웅),Sungsik Jo(조성식),Elango Rakeshwar 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.11

The primary motive of this research is to recover permanent sensor fault. In Lane Keeping Assistant Systems, sensors play a necessary role in control. So, the robustness of sensors is very important. An Artificial Neural Network was developed and trained to completely recover the sensor fault. Steering Angle Sensor and Torque sensors were used for this research. If one sensor is failed another sensor is used to recover the failed sensor data. Finally, Hardware in Loop testing was done in a commercial heavy-duty vehicle system to verify the recovered sensor performance.