Fabrication of conducting composite sheets using cost-effective graphite flakes and amorphous styrene acrylonitrile for enhanced thermistor, dielectric, and electromagnetic interference shielding properties

Panwar, Varij,Gill, Fateh Singh,Rathi, Vikas,Tewari, V.K.,Mehra, R.M.,Park, Jong-Oh,Park, Sukho Elsevier 2017 Materials chemistry and physics Vol.193 No.-

<P><B>Abstract</B></P> <P>The fabrication of strong conducting composite sheets (CCSs) using a simple technique with cost-effective materials is desirable for capacitor, decoupling capacitor, and electromagnetic interference (EMI) shielding applications. Here, we used cost-effective graphite flakes (GFs) as a conducting filler and amorphous poly (styrene-co-acrylonitrile) (PSAN) as an insulating polymer to fabricate a CCS via a simple mechanical mixing and hot compression molding process in 2.5 h, with the aim to save time and avoid the use of toxic reagents, which are generally used in chemical methods. In the present method, the GFs are connected in diffusively adhere polymer matrix, controlled by temperature and pressure that generate the conduction in the CCSs. The resulting PSAN/GF CCSs were characterized by using scanning electron microscopy (SEM), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and hardness tests. The GFs penetrated the interfacial region of PSAN, thus improving the thermistor and dielectric properties (dielectric constant, AC conductivity, and dissipation factor) of the PSAN/GF CCSs. Furthermore, the PSAN/GF CCSs showed enhanced hardness and EMI shielding effectiveness (SE) properties in the X-band frequency range (8.5–12.5 GHz). The percolation theory was implemented to DC and AC conductivity. To detect the transition of the dielectric properties, the dielectric constant of the CCSs was analyzed with increasing volume fraction of GFs in the radio frequency region. The improved dielectric constant, AC conductivity, and dissipation factor of the PSAN/GF CCS, indicated a significant improvement in their EMI shielding properties in the X-band frequency range, which were measured using the waveguide method. The ac conductivity of PSAN/GF CCS shows stable behavior in the higher frequency ranges. The EMISE of PSAN/GF CCS were found to increase with increasing GF content due to the absorbance mechanism.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Enhanced hardness and thermal stability of PSAN/GF conducting composite sheet (CCS). </LI> <LI> Enhanced dielectric and electromagnetic interference shielding of PSAN/GF CCS. </LI> <LI> Cost-effective and fast fabrication method of PSAN/GF CCS. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Changes in the levels of comet parameters before and after fluoxetine therapy in major depression patients

Rajeev Panwar,M,Sivakumar,Vikas Menon,Balasubramaniyan Vairappan 대한해부학회 2020 Anatomy & Cell Biology Vol.53 No.2

Major depression belongs to mood disorders and characterized by worthlessness, no interest or happiness in any activity; lasting for atleast two weeks. Etio-pathological changes of major depression include oxidative stress leading to free radical synthesis which causes damage to carbohydrates, proteins, lipids and nucleic acids. Nucleic acid damage can be identified by either single or double strand breaks and for quantitative estimation of the same, neutral or alkaline comet assay is performed. Fluoxetine is the drug of choice for treatment of major depression having antioxidant function. In the current study eighty drug naïve major depression patients were recruited and comet parameters namely total comet length, head diameter and tail length were measured before starting the treatment and after completion of eight week fluoxetine therapy. The levels of comet parameters were higher in females than males suggesting higher prevalence of major depression among females. On categorizing into three age groups, the numbers of major depression patients belonging to 18-30 year age group were higher than 31-40 and 41-50 year age groups. All the parameters of deoxyribonucleic acid damage were reduced after eight week of fluoxetine therapy indicating that fluoxetine has anti-oxidant action along with its antidepressant properties, which cause reversal of oxidative stress induced damage occurring during major depression.

Adaptive neural controller for space robot system with an attitude controlled base

Kumar, Naveen,Panwar, Vikas,Borm, Jin-Hwan,Chai, Jangbom,Yoon, Jungwon Springer-Verlag 2013 Neural computing & applications Vol.23 No.7

Intelligent Control of Space Robot System using RBF Neural Network

Naveen Kumar,Vikas Panwar 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10

In this paper, an intelligent controller is proposed for a space robot system with an attitude controlled base without joint acceleration measurements. The controller consists of computed torque type part, RBF neural network and an adaptive controller. The controller achieves the required tracking effectively. The controller is able to learn the existing structured and unstructured uncertainties in the system in online manner. The RBF network learns the unknown part of the space robot system dynamics with no requirement of the offline training. The adaptive controller is used to estimate the unknown bounds on unstructured uncertainties and neural network reconstruction error. The overall system is proved to be asymptotically stable in the sense of Lyapunov. Finally numerical simulation studies are performed to evaluate the controller performance.

V-REP-based navigation of automated wheeled robot between obstacles using PSO-tuned feedforward neural network

Anish Pandey,Vikas Singh Panwar,Md. Ehtesham Hasan,Dayal R. Parhi 한국CDE학회 2020 Journal of computational design and engineering Vol.7 No.4

This paper describes the navigation of an automated Pioneer P3-DX wheeled robot between obstacles using particle swarm optimization (PSO) algorithm tuned feedforward neural network (FNN). This PSO algorithm minimizes the mean square error between the actual and predicted values of the FNN. In this work, 2 separate DC motors and 16 ultrasonic sensors have been used for making differential drive steering angle and for collecting the distance from obstacles, respectively. The proposed without tuned FNN and PSO-tuned FNN receives obstacle’s distance as inputs form ultrasonic sensors and control the steering angle of a differential drive of automated Pioneer P3-DX wheeled robot as output. We have compared the results between without tuned FNN and PSO-tuned FNN, and it has been found that PSO-tuned FNN gives a better trajectory and takes less distance to reach the target. Virtual Robot Experimentation Platform software has been used to design the real-time simulation results. A comparative study between without tuned FNN and PSO-tuned FNN verifies the effectiveness of PSO-tuned FNN for automated Pioneer P3-DX wheeled robot navigation. Also, we have compared this winner PSO-tuned FNN to the previously developed PSO-optimized Fuzzy Logic Controller navigational technique to show the authenticity and real-time implementation of PSO-tuned FNN.

Neural Network Based Hybrid Force/Position Control for Robot Manipulators

Naveen Kumar,Vikas Panwar,Nagarajan Sukavanam,Shri Prakash Sharma,범진환 한국정밀공학회 2011 International Journal of Precision Engineering and Vol. No.

This paper presents a neural network based adaptive control scheme for hybrid force/position control for rigid robot manipulators. Firstly the robot dynamics is decomposed into force, position and redundant joint subspaces. Based on this decomposition, a neural network based controller is proposed that achieves the stability in the sense of Lyapunov for desired interaction force between the end-effector and the environment as well as regulate robot tip position in cartesian space. A feedforward neural network is employed to learn the parametric uncertainties, existing in the dynamical model of the robot manipulator. Finally numerical simulation studies are carried out for a two link rigid robot manipulator.

Tracking Control of Redundant Robot Manipulators using RBF Neural Network and an Adaptive Bound on Disturbances

Naveen Kumar,범진환,Vikas Panwar,채장범 한국정밀공학회 2012 International Journal of Precision Engineering and Vol. No.

In this paper, a hybrid trajectory tracking controller is designed for redundant robot manipulators, consisting of RBF neural network and an adaptive bound on disturbances. The controller is composed of computed torque type part, RBF neural network and an adaptive controller. The controller achieves end-effector trajectory tracking as well as subtask tracking effectively. The controller is able to learn the existing structured and unstructured uncertainties in the system in online manner. The RBF network learns the unknown part of the robot dynamics with no requirement of the offline training. The adaptive controller is used to estimate the unknown bounds on unstructured uncertainties and neural network reconstruction error. The overall system is proved to be asymptotically stable in the sense of Lyapunov. Finally, numerical simulation studies are performed on a 3R planar robot manipulator to show the effectiveness of the control scheme.

Tracking Control of Redundant Robot Manipulators using RBF Neural Network and an Adaptive Bound on Disturbances

Kumar, Naveen,Borm, Jin-Hwan,Panwar, Vikas,Chai, Jangbom 한국정밀공학회 2012 International Journal of Precision Engineering and Vol.13 No.8

In this paper, a hybrid trajectory tracking controller is designed for redundant robot manipulators, consisting of RBF neural network and an adaptive bound on disturbances. The controller is composed of computed torque type part, RBF neural network and an adaptive controller. The controller achieves end-effector trajectory tracking as well as subtask tracking effectively. The controller is able to learn the existing structured and unstructured uncertainties in the system in online manner. The RBF network learns the unknown part of the robot dynamics with no requirement of the offline training. The adaptive controller is used to estimate the unknown bounds on unstructured uncertainties and neural network reconstruction error. The overall system is proved to be asymptotically stable in the sense of Lyapunov. Finally, numerical simulation studies are performed on a 3R planar robot manipulator to show the effectiveness of the control scheme.