International Journal of Innovative Research in Physics (IJIIP)
(ISSN Number(Online) - 2687-7902)
(ISSN Number(Print) - 2689-484X)





Volume3 Issue1:



Hydrothermal synthesis of [email protected]/activated carbon composite electrode with enhanced electrochemical performance for supercapacitor applications

Manoranjan Mandal1, Subhasri Subudhi1,Injamul Alam1,BVRS Subramanyam1,Santosini Patra1, and Pitamber Mahanandia1*

1Department of Physics & Astronomy, National Institute of Technology, Rourkela-769008
Page Number: 1-10

We report the preparation of an electrode material made up of MnO2/ graphene/ activated carbon ternary composite by hydrothermal method for supercapacitor (SC) applications. The prepared ternary composite has been characterized by using scanning electron microscopy (SEM), powder X-ray diffraction (XRD), energy dispersive spectroscopy (EDS) and Raman spectroscopy measurements. The prepared objective electrode has been investigated using galvanostatic charge-discharge (GCD) and cyclic voltammetry (CV) measurements in a 3-electrode system using 3M KOH aqueous electrolyte for the analysis of their electrochemical performance. The prepared MnO2/graphene/activated carbon composite results in maximum capacitance of ~ 493.57 F/g at 5 mV/s using CV and moreover the highest capacitance obtained from the GCD measurement is ~ 485.29 F/g at 1 A/g. The long-term cycle stability of the composite electrode is also demonstrated and it shows outstanding cyclic performance where 97% of capacitance is left over 5000 cycles at 1 A/g. Therefore, the composite shows good charge storage performance, as well as tremendous cycle stability and that, reveal the synthesized ternary composite can be a suitable electrode for SC applications.

Keywords: Activated carbon, graphene, galvanostatic charge-discharge, MnO2, cyclic voltammetry.


DOI: doi.org/10.15864/ijiip.3101

Nucleation of Twinning Dislocation Loop in Pt: A Computational Approach

Sweta Kumari1* ,Sri Sadgun Reddy Pulagam2,and Amlan Dutta3

1,2,3Department of Metallurgical and Materials Engineering, Indian Institute of Technology Kharagpur, India – 721302
Page Number: 11-18

Twinning plays a critical part in the plastic deformation of the materials and the strengthening mechanisms and is hence considered as one of the most prevalent deformation mechanisms in metals. Because to the high stacking fault energy of the fcc metals like Al, Pd, and Pt, the extended dislocations are believed to be energetically favored over isolated partials, thereby rendering deformation twinning unfeasible. Nevertheless, some recent experimental researches have confirmed a potential deformation twinning pathway in nanocrystalline platinum. This alternate-shear mechanism has a much lower energy barrier than the usual layer-by-layer twinning. We utilize computations involving atomistic calculations and continuum modeling in this study to examine the genesis of deformation twins in Pt. Atomistic simulations provides the generalized planer fault energy using an EAM (embedded-atom-model) potential. Moreover, a potential energy-based method, namely; a nudged-elastic band (chain of states) has been used to compute the activation energy barrier for the nucleation of the twinning dislocation loop in the alternate-shear model. The critical stress needed for the nucleation of the twinning dislocation loop in platinum is estimated using some of the parameters acquired from atomistic calculations and using them as fitting parameters in the continuum model. The minimum-energy path between the two end states can be identified using this methodology. Through the unusual alternate-shear approach, the results provide a rudimentary but essential dislocationbased perspective of the occurrence of deformation twins in fcc metals

Keywords: Twinning; Atomistic simulations; Dislocation nucleation; Nudged-elastic-band


DOI: doi.org/10.15864/ijiip.3102

Growth kinetics and thermo-opto properties of manganese doped barium phosphate crystals

Delma D’Souza1, Jagannatha N.1*,Nagaraja K. P 1,and Ganavi A. S.2

1Department of Physics, FMKMC College (A constituent college of Mangalore University), Madikeri, Karnataka, India
2Department of Physics, Mangalore University, Mangalagangothri, Karnataka, India
Page Number: 19-31

Manganese doped barium phosphate (MDBP) crystals were grown by gel technique. Phosphoric acid impregnated silica (PIS) gel was optimized by varying gel parameters: pH, specific gravity of sodium meta silicate, concentration of acid and temperature of gelling solution. In an optimized growth environment, Ba2+-Mn2+ cationic mixture was made to diffuse through the set PIS gel to nucleate with intrinsically available (PO4) 3- ions, which yielded high quality MDBP crystals. Energy dispersive X-ray analysis confirmed the constitution of MDBP crystal by the prime elements Ba, Mn, P and O with cationic distribution 8.784 : 1 (Ba2+ : Mn2+). Fourier transform infrared spectral studies identified the phosphate group, water of crystallization and M-O (M= Ba2+, Mn2+) bonds in the crystal armature. Thermogravimetric analysis demonstrated the degradation behavior and ensured the thermal stability upto 500o C in the phosphorus pentoxide state. MDBP crystals exhibited high crystalline nature and adjoined to orthorhombic geometry. The crystals being insulators, ingrained with high band gap energy of 6.08 eV.

Keywords: impregnated, doped crystals, spectral studies.


DOI: doi.org/10.15864/ijiip.3103

Non-destructive assessment of basic parts of the plant grown in hydroponic medium using image processing algorithms

Shubhashri Kumari1*, and Anil Kumar Nirala1

1Biomedical Optics Laboratory, Department of Physics, Indian institute of technology (Indian school of mines), Dhanbad, Jharkhand 826004, India
Page Number: 32-35

In the proposed work, laser biospeckle technique has been used for visual inspection as well as quantitative evaluation of basics parts of the plant grown in hydroponic medium for the first time. Co-Occurrence matrix, Inertia Moment, Absolute Value Difference and Parameterized Global Average Fujii algorithms have been used for biospeckle activity analysis. It is concluded that biospeckle activity obtained using the algorithms can be used for visual inspection as well as quantitative evaluation successfully. In addition, it is also concluded that biospeckle activity has been found highest in the roots and more in leaf in comparison to stem and seed.

Keywords: hydroponic medium, laser biospeckle technique, image processing algorithms, biospeckle activity.


DOI: doi.org/10.15864/ijiip.3104

Opto-electromagnetic Responses of Tamm Plasmon Polariton Modes in a Symbiotic Dual-Metallic architecture

Nilanjan Mukherjee 1and Partha Sona Maji 1

1Department of Physics, Amity University, Major Arterial Road (South-East), AA II, Newtown, Kolkata, India.
Page Number: 36-45

We report a Tamm plasmon polariton (TPP) arrangement whose design consists of a thin Silver (Ag) film which is the plasmon-active metal and lies adjacent to the distributed Bragg Reflector (DBR) structure. The DBR consists of periodically stratified layers of Ta2O5 and SiO2. TPP modes are excited through normal incidence using a white light source and we have obtained the corresponding reflectivity spectrum as a function of wavelength. The excitation spectrum is characterized by a sharp and distinguishable reflectivity dip within the photonic band-gap of DBR. Extending this version of the idea, we have replaced the single plasmon-active metal by two metals to overrule the drawbacks of these single metals concerning their physiochemical properties like propagation length, chemical stability, and various losses during propagation of the plasmon wave, etc. Hence, we have obtained the reflectivity characteristics for different bimetallic architecture supporting TPP resonances. Thereafter, we have also obtained the Full Width at Half Minimum (FWHM) wavelengths and Quality Factor (Q-Factor) characteristics as a function of metal thickness for two different plasmon active metallic combinations, where the total bimetallic thickness remains constant. The shortcomings of a particular metal are nullified by the presence of the other metal with it. Such an arrangement is envisioned for the fabrication of nanoscale smart devices like optical and biosensors having potential applications in social welfare domain like monitoring the levels of food adulteration and food safety, etc.

Keywords: Tamm Plasmon, distributed Bragg Reflector (DBR), Reflectivity Spectrum, Dual-metallo-dielectric architecture, Quality Factor (Q-Factor).


DOI: doi.org/10.15864/ijiip.3105

Air Quality Index Prediction in Realtime Using SVM based model in Machine Learning

Rajarshi SinhaRoy1, Swarnendu Sarkhel2

1 Computer Science, St. Xavier's College, Kolkata 700016.
2 Computer Science, Government General Degree College Singur.
Page Number: 46-53

The air quality index is an index to decide the situation of the air quality. The air quality index is a measure of how air pollutants impact a persons' fitness within a time period. It is a standardized degree this is used to suggest the pollutant (so2, no2, pm 2.5, pm 10, etc.) levels. We designed a model that could estimate the air quality index based totally on ancient records of a few preceding years. The performance of this model is progressed through making use of numerous Estimation-Problem logics. Our model could be able to correctly predict the air quality index of a complete county or any nation or any bounded area supplied with the ancient records of pollutant concentration. In our model by implementing a support-vector machine, we achieved better performance than other models and for that our model gets an accuracy of 96%. With the help of support-vector machine, our model estimates the air quality to predict the air quality index of a given location primarily based totally on its ancient records of the pollution of a few preceding years. Our purpose is to increase a non-linear updatable version for real-time air quality index forecasting, to doubtlessly update the models presently being used.

Keywords: Air quality index, Support vector machine, Prediction, Machine Learning.


DOI: doi.org/10.15864/ijiip.3106