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Effect of temperature on carrier transport and photoconductivity of Mn-doped FeS2 thin films

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Progress in Natural Science:Materials International 2022年第1期32卷 135-142页

作者： Jugraj Singh Kulwinder Singh Manjot Kaur Anup Thakur Ram K.Sharma Ankush Vij Akshay Kumar Department of Nanotechnology Sri Guru Granth Sahib World University Department of Basic and Applied Sciences Punjabi University Centre for Interdisciplinary Research University of Petroleum and Energy Studies (UPES) Department of Physics University of Petroleum and Energy Studies (UPES)

Thin-film of Mn-doped iron disulfide（FeS2） has been prepared using the thermal evaporation method. This work reports the Hall measurements, temperature and light intensity-dependent photoconductivity, electrical transport mechanism, and photodetection properties of Mn-doped FeS2thin film. The transient photoconductivity measurements of p-type Mn-doped FeS2thin film show a consistent dependence upon temperature and light *** transport mechanism was illustrated using different models. In region-Ⅰ（303–393 K） deposited film followed the thermally activated transport mechanism. Nearest neighbour hopping（NNH） transport mechanism was followed by region-Ⅱ（274–293 K）, and Mott's variable range hopping（VRH） mechanism was dominant in region Ⅲ（108–273 K）. The fabricated device resulted in higher photoconductivity due to collecting charge carriers through electrodes under light illumination. The results also revealed that Mn-doped thin film possessed good photoresponsivity（～19 m A/W） as well as photo-detectivity(～3.4 × 1012Jones) due to the occupation of localized states formed by Mn-doping. Light intensity-dependent photodetection properties suggested the potential for real-time photodetection applications.

关键词： Mn-doped FeS 2 Charge transport Hopping mechanism Photodetection Responsivity

Graphene： from synthesis to engineering to biosensor applications

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Frontiers of Materials Science 2018年第1期12卷 1-20页

作者： Jagpreet SINGH Aditi RATHI Mohit RAWAT Manoj GUPTA Department of Nanotechnology Sri Guru Granth Sahib World University Fatehgarh Sahib-140406 Punjab India Intelligent Material Pvt. Ltd. (Nanoshel LLC) Derabassi-140507 Punjab India Department of Mechanical Engineering National University of Singapore Singapore 117576 Singapore

Graphene is a fascinating material of recent origin whose first isolation was being made possible through micromechanical cleavage of a graphite crystal. Owing to its fascinating properties, graphene has garnered significant attention in the research community for multiple applications. A number of methods have been employed for the synthesis of single-layer and multi-layer graphene. The extraordinary properties of graphene such as its Hall effect at room temperature, high surface area, tunable bandgap, high charge mobility and excellent electrical, conducting and thermal properties allow for the development of sensors of various types and also opened the doors for its use in nanoelectronics, supercapacitors and batteries. Biological aspects of graphene have also been investigated with particular emphasis on its toxicity and drug delivery. In this review, many of the salient aspects of graphene, such as from synthesis to its applications, primarily focusing on sensor applications which are of current interest, are covered.

关键词： graphene nanoelectronics Hall effect tunable bandgap supercapacitors sensors catalysis

Nanomaterials for sensing of formaldehyde in air: Principles, applications, and performance evaluation

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Nano Research 2019年第2期12卷 225-246页

作者： Deepak Kukkar Kowsalya Vellingiri Rajnish Kaur Sanjeev Kumar Bhardwaj Akash Deep Ki-Hyun Kim Department of Nanotechnology Sri Guru Granth Sahib World University Fatehgarh Sahib Punjab 140406 India Department of Civil and Environmental Engineering Hanyang University Seoul 04763 Republic of Korea Environmental and Water Resources Engineering Division Department of Civil Engineering IIT Madras Chennai 600036 India Central Scientific Instruments Organization (CSIR-CSIO) Sector 30C Chandigarh 160030 India

Despite the improvement in sensing technologies, detection of small and highly reactive molecules like formaldehyde remains a highly challenging area of research. Applications of nanomaterials/nanostructures and their composites have increased as effective sensing platforms (e.g., reaction time, sensitivity, and selectivity) for the detection of aqueous or gaseous formaldehyde based on diverse sensing principles. In this review, the basic aspects of important nanomaterial-based sensing systems (e.g., electrochemical, electrical, biological, and mass variation sensors) were evaluated in relation to performance, cost, and practicality of sensing gas phase formaldehyde. Accordingly, existing knowledge gaps in such applications were assessed in various respects along with suitable recommendations for building a new roadmap for the expansion of chemical sensing technology of gas phase formaldehyde.

关键词： nanomaterials formaldehyde hazardous pollutant sensing

Recognition of newspaper printed in gurumukhi script

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Journal of Central South university 2019年第9期26卷 2495-2503页

作者： Rupinder Pal Kaur Manish Kumar Jindal Munish Kumar Post Graduate Department of Computer Science Guru Nanak College for GirlsSri Muktsar SahibPunjabIndia Department of Computer Science&Applications Panjab University Regional CentreSri Muktsar SahibPunjabIndia Department of Computational Sciences Maharaja Ranjit Singh Punjab Technical UniversityBathindaPunjabIndia

In this work,a system for recognition of newspaper printed in gurumukhi script is *** feature extraction techniques,namely,zoning features,diagonal features,parabola curve fitting based features,and power curve fitting based features are considered for extracting the statistical properties of the characters printed in the *** combinations of these features are also applied to improve the recognition *** recognition,four classification techniques,namely,k-NN,linear-SVM,decision tree,and random forest are used.A database for the experiments is collected from three major gurumukhi script newspapers which are Ajit,Jagbani and Punjabi *** 5-fold cross validation and random forest classifier,a recognition accuracy of 96.19%with a combination of zoning features,diagonal features and parabola curve fitting based features has been reported.A recognition accuracy of 95.21%with a partitioning strategy of data set(70%data as training data and remaining 30%data as testing data)has been achieved.

关键词： newspaper recognition feature extraction classification gurumukhi script random forest

Analysis of Protein-Ligand Interactions of SARS-CoV-2 Against Selective Drug Using Deep Neural Networks

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Big Data Mining and Analytics 2021年第2期4卷 76-83页

作者： Natarajan Yuvaraj Kannan srihari Selvaraj Chandragandhi Rajan Arshath Raja Gaurav Dhiman Amandeep Kaur St.Peter’s Institute of Higher Education and Research Information Communication Technology AcademyChennai 600096India Department of Computer Science and Engineering SNS College of Engineering641107India Department of Computer Science and Engineering Jagannath Educational Health and Charitable Trust College of Engineering and TechnologyCoimbatore 641105India B.S.Abdur Rahman Crescent Institute of Science and Technology Chennai 600048India Department of Computer Science Government Bikram College of CommercePatiala 147001India Department of Computer Science and Engineering Sri Guru Granth Sahib World UniversityFatehgarh 140406India

In recent time, data analysis using machine learning accelerates optimized solutions on clinical healthcare systems. The machine learning methods greatly offer an efficient prediction ability in diagnosis system alternative with the clinicians. Most of the systems operate on the extracted features from the patients and most of the predicted cases are accurate. However, in recent time, the prevalence of COVID-19 has emerged the global healthcare industry to find a new drug that suppresses the pandemic outbreak. In this paper, we design a Deep Neural Network(DNN)model that accurately finds the protein-ligand interactions with the drug used. The DNN senses the response of protein-ligand interactions for a specific drug and identifies which drug makes the interaction that combats effectively the virus. With limited genome sequence of Indian patients submitted to the GISAID database, we find that the DNN system is effective in identifying the protein-ligand interactions for a specific drug.

关键词： Deep Neural Network(DNN) coronavirus protein-ligand interactions deep learning clinical healthcare system

Characterizations of Null Holomorphic Sectional Curvature of GCR-Lightlike Submanifolds of Indefinite Nearly Khler Manifolds

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Analysis in Theory and Applications 2016年第2期32卷 122-134页

作者： Rachna Rani Sangeet Kumar Rakesh Kumar R. K. Nagaich Department of Mathematics University College Moonak 148033 Punjab India Department of Mathematics Sri Guru Teg Bahadur Khalsa College Sri Anandpur Sahib 140118 Punjab India Department of Basic and Applied Sciences Punjabi University Patiala 147002Punjab India Department of Mathematics Punjabi University Patiala 147002 Punjab India

We obtain the expressions for sectional curvature, holomorphic sectional curvature and holomorphic bisectional curvature of a GCR-lightlike submanifold of an indefinite nearly Kahler manifold and obtain characterization theorems for holo- morphic sectional and holomorphic bisectional curvature. We also establish a condi- tion for a GCR-lightlike submanifold of an indefinite complex space form to be a null holomorphically fiat.

关键词： Indefinite nearly K/ihler manifold GCR-lightlike submanifold holomorphic sectional curvature holomorphic bisectional curvature.