4.6 Article

Tri-doped co-annealed zinc oxide semi-conductor synthesis and characterization: photodegradation of dyes and gas sensing applications

Ask authors/readers for more resources

This study synthesized and characterized ZnO nanorods using a simple combustion method, exploring the effects of doping on their properties. Results showed that co-annealing at different temperatures can enhance the crystallinity of the nanorods, with higher temperature samples exhibiting better recovery and reaction time.
Despite the fact that much of the research has been performed on ZnO-based nanoparticles, still a lot of work is unexplored. The synthesis and characterization of the ZnO nanorods have been co-annealed using a simple combustion method and used for gas sensor and photocatalytic degradations applications. Herein pure and In, Sn and Sb tri-dopants were used, i.e. 0.5 at.wt% 1.0 at.wt% and 1.5 at.wt%, while their effects co-annealed on glass substrate at different temperatures at 500 degrees C and 1100 degrees have been studied. These samples were coated onto the chosen substrate using spin coating technique. Crystallite scale was measured to the range of 30-50 nm. At such temperatures, the grain size measured for the samples was in range of 50-70 nm. This showed that the prepared nanorods are well crystalline and have strong optical properties to handle. Studies of X-ray diffraction showed the influential point (101). These coated samples designed for nitrogen gas sensing have been tested for the development of smart and functional instruments. Furthermore, it was observed that the samples prepared at higher temperatures exhibit better recovery and better reaction time. Valance ion process explains the gas sensors fast reaction and long recovery time. Thus prepared ZnO nanoparticles have photocatalytic degradation (99.86%) only in 55 min. We observed optimum exposure at an operating temperature of 105 degrees C. It is notable that morphology of susceptible layer nanoparticles is preserved based on different tri-doping concentrations. The concentration of T2-ZnO nanoparticles for photodegradation of the DR-31 dye and NO2 gas sensing applications were 1.0 at.wt%

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Engineering, Multidisciplinary

Metaheuristic and Machine Learning-Based Smart Engine for Renting and Sharing of Agriculture Equipment

Manik Rakhra, Ramandeep Singh, Tarun Kumar Lohani, Mohammad Shabaz

Summary: The incorporation of technology in farming techniques has divided farmers into different camps, with some willing to accept technology while others expressing hesitation and skepticism due to lack of expertise and cost involved. A special Smart Tillage platform has been developed to provide smart-engine based decision-making and deep learning network-powered recommendations to help farmers improve crop yields and scalability.

MATHEMATICAL PROBLEMS IN ENGINEERING (2021)

Article Medicine, Legal

Novel use of logistic regression and likelihood ratios for the estimation of gender of the writer from a database of handwriting features

Vishal Sharma, Manjot Bains, Rajesh Verma, Neha Verma, Raj Kumar

Summary: This study focuses on using individual characteristics in handwriting to estimate the gender of the writer. Statistical methods were used to analyze the data, and 15 significant characteristics were identified for cost-effective gender estimation. The correct classification rates for females and males were 80% and 76.4% respectively. The likelihood ratio approach was also used to assess the strength of evidence in determining the sex of the unknown person based on these handwriting characteristics.

AUSTRALIAN JOURNAL OF FORENSIC SCIENCES (2023)

Article Mathematical & Computational Biology

Breast Cancer Calcifications: Identification Using a Novel Segmentation Approach

Sushovan Chaudhury, Manik Rakhra, Naz Memon, Kartik Sau, Melkamu Teshome Ayana

Summary: Breast cancer is a common and life-threatening disease among women. While the exact cause is still under research, there are identifiable risk factors such as age, genetics, obesity, birth control, cigarettes, and tablets. Early detection plays a crucial role in successful treatment, with imaging techniques being key in the identification of breast cancer.

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2021)

Article Food Science & Technology

Implementing Machine Learning for Smart Farming to Forecast Farmers' Interest in Hiring Equipment

Manik Rakhra, Sumaya Sanober, Noorulhasan Naveed Quadri, Neha Verma, Samrat Ray, Evans Asenso

Summary: Agricultural automation reduces farmers' physical labor and debt. However, farmers face challenges in finding tools and equipment, so tool renting and sharing become a solution. The study utilizes machine learning models and finds that the decision tree model has the best impact on farmers.

JOURNAL OF FOOD QUALITY (2022)

Article Computer Science, Theory & Methods

Research on Nonlinear Distorted Image Recognition Based on Artificial Neural Network Algorithm

Wensheng Yan, Mohammad Shabaz, Manik Rakhra

Summary: This study focuses on nonlinear distortion image recognition technology and proposes an image recognition model based on the BP neural network. Experimental results demonstrate the effectiveness of the model, indicating that the BP network driving the number term can improve the recognition efficiency of the system.

JOURNAL OF INTERCONNECTION NETWORKS (2022)

Article Food Science & Technology

Implementing Machine Learning for Supply-Demand Shifts and Price Impacts in Farmer Market for Tool and Equipment Sharing

Manik Rakhra, Amitabh Bhargava, Deepshikha Bhargava, Ramandeep Singh, Astha Bhanot, Abdul Wahab Rahmani

Summary: Different attitudes towards the use of technology in agriculture exist across countries. In underdeveloped nations, farmers are cautious about trying new technologies. Smart Tillage, an advanced framework utilizing machine learning, provides tool and equipment recommendations for farmers.

JOURNAL OF FOOD QUALITY (2022)

Article Food Science & Technology

Design and Evaluation of a Hybrid Technique for Detecting Sunflower Leaf Disease Using Deep Learning Approach

Arun Malik, Gayatri Vaidya, Vishal Jagota, Sathyapriya Eswaran, Akash Sirohi, Isha Batra, Manik Rakhra, Evans Asenso

Summary: This manuscript investigates the recognition and classification of sunflower diseases using deep learning techniques. It proposes a hybrid model that combines VGG-16 and MobileNet for classification purposes, and uses stacking ensemble learning approach. The study compares the proposed model with existing deep learning models based on accuracy using the same dataset.

JOURNAL OF FOOD QUALITY (2022)

Article Nanoscience & Nanotechnology

Characterization of Fabricated Gold-Doped ZnO Nanospheres and Their Use as a Photocatalyst in the Degradation of DR-31 Dye

Neha Verma, Vishal Jagota, Arnold C. Alguno, Alimuddin, Manik Rakhra, Pawan Kumar, Betty Nokobi Dugbakie

Summary: This study presents a method for manufacturing gold-doped zinc oxide nanospheres and investigates the use of zinc oxide nanoparticles as photocatalysts for dye degradation. The research finds that gold-doped zinc oxide nanoparticles are the most effective for this degradation.

JOURNAL OF NANOMATERIALS (2022)

Article Nanoscience & Nanotechnology

Morphological, Structural, and Optical Properties of Doped/Codoped ZnO Nanocrystals Film Prepared by Spin Coating Technique and Their Gas Sensing Application

Neha Verma, Vishal Jagota, Alimuddin, Arnold C. Alguno, Manik Rakhra, K. Chanthirasekaran, Betty Nokobi Dugbakie

Summary: In this study, nanostructured ZnO with wurtzite structure was created using the spin coating approach. The impact of doped and codoped films on structural, optical properties, and morphological was examined. It was found that antimony-doped ZnO has a larger band gap than Al and antimony-codoped ZnO, making it suitable for gas sensors and solar cells.

JOURNAL OF NANOMATERIALS (2022)

Article Health Care Sciences & Services

A Novel Hybrid Deep Learning Approach for Skin Lesion Segmentation and Classification

Puneet Thapar, Manik Rakhra, Gerardo Cazzato, Md Shamim Hossain

Summary: This study proposes a reliable method for diagnosing skin cancer using deep learning and swarm intelligence algorithms to segment and classify dermoscopy images. The proposed method shows advantages in multiple performance measures.

JOURNAL OF HEALTHCARE ENGINEERING (2022)

Article Biotechnology & Applied Microbiology

Fuzzy Logic-Based Systems for the Diagnosis of Chronic Kidney Disease

G. Murugesan, Tousief Irshad Ahmed, Jyoti Bhola, Mohammad Shabaz, Jimmy Singla, Manik Rakhra, Sujeet More, Issah Abubakari Samori

Summary: Kidney failure occurs when the kidney stops functioning properly, leading to the potential development of chronic kidney disease. Early diagnosis can delay its progression and reduce treatment costs. The use of fuzzy and adaptive neural fuzzy inference systems improves the accuracy of medical diagnostics in determining the stage of chronic renal disease.

BIOMED RESEARCH INTERNATIONAL (2022)

Article Engineering, Electrical & Electronic

Intelligent Water Drops Algorithm-Based Aggregation in Heterogeneous Wireless Sensor Network

S. Nonita, Pardayev Abdunabi Xalikovich, C. Ramesh Kumar, Manik Rakhra, Issah Abubakari Samori, Yuselino Maquera Maquera, Jose Luis Arias Gonzales

Summary: This paper introduces a novel implementation of the intelligent water drops (IWD) method for resolving data aggregation issues in heterogeneous wireless sensor networks (WSN). The research demonstrates that by tuning parameters and modifying algorithms, the traffic situations of WSN can be appropriately modified when the aggregating node transmits data to the base station. The proposed improvement, IIWD, takes into consideration the heterogeneity of nodes in practical scenarios, resulting in better accuracy and effectiveness compared to traditional methods in terms of residual energy, dead nodes, payload, and network lifespan.

JOURNAL OF SENSORS (2022)

Article Engineering, Multidisciplinary

Artificial intelligence technology in electronic communication engineering for medical applications

Youwen Lin, Zhijie Zhang, Vishal Jagota, Manik Rakhra, Bhupesh Kumar Singh

Summary: The application of artificial intelligence technology, particularly LPWAN technology, can enhance the security and efficiency of wireless communication systems, while reducing the frame error rate.

JOURNAL OF ENGINEERING-JOE (2022)

Proceedings Paper Computer Science, Artificial Intelligence

Machine Learning-Based Heart Patient Scanning, Visualization, and Monitoring

Ahmed Al Ahdal, Deepak Prashar, Manik Rakhra, Ankita Wadhawan

Summary: Heart diseases are one of the leading causes of death globally, with early detection and diagnosis being crucial for effective treatment. Machine learning techniques are being used to predict and detect these diseases accurately, with the goal of improving healthcare outcomes.

2021 INTERNATIONAL CONFERENCE ON COMPUTING SCIENCES (ICCS 2021) (2021)

No Data Available