A5048869603- Methane Hydrates and Related Phenomena
- Atmospheric and Environmental Gas Dynamics
- Spacecraft and Cryogenic Technologies
- Carbon Dioxide Capture Technologies
- Hydrocarbon exploration and reservoir analysis
- Hybrid Renewable Energy Systems
- Conducting polymers and applications
- Fuel Cells and Related Materials
- Solar Radiation and Photovoltaics
- Membrane Separation Technologies
- Carbon and Quantum Dots Applications
- Adsorption and biosorption for pollutant removal
- Membrane Separation and Gas Transport
- CO2 Sequestration and Geologic Interactions
- Carbon dioxide utilization in catalysis
- Ammonia Synthesis and Nitrogen Reduction
- Analytical chemistry methods development
- Graphene and Nanomaterials Applications
- Membrane-based Ion Separation Techniques
- Organic Electronics and Photovoltaics
- Energy and Environment Impacts
- Modeling, Simulation, and Optimization
- Energy Load and Power Forecasting
- Photovoltaic System Optimization Techniques
- Environmental Impact and Sustainability
Indian Institute of Technology Madras
2019-2025
KLE Technological University
2025
National Chemical Laboratory
2010-2019
Bharati Vidyapeeth Deemed University
2015
Academy of Scientific and Innovative Research
2014-2015
Council of Scientific and Industrial Research
2014
<title>Abstract</title> The continuous rise in CO₂ emissions is a major contributor to climate change, affecting ecosystems, economies, and public health. Predicting future accurately crucial for designing effective policies mitigation strategies. This study explores multiple machine learning models forecasting, comparing traditional methods like Support Vector Machines (SVM), Linear Regression, Decision Trees with advanced deep techniques such as Long Short-Term Memory (LSTM), Gated...
Geospatial analysis plays a very crucial role in predicting environmental changes, especially the context of CO2 emissions and climate forecasting. This study uses continent-wise geospatial to assess potential patterns implications by 2100, using ML techniques. The objective this research is spatially integrate data with models predict geographical distribution at regional levels, thereby ascertaining which factors are predominant influencing rates emissions. For purpose, world stratified...
Even though there has been a rapid increase in the use of hydrogen production techniques recent years, is still an exigent need for affordable, sustainable and efficient low-carbon generation methods. Based on current United Nations Sustainable Development Goals, decades, alkaline electrolysers proton exchange membrane have reached high commercial industrial levels hydroprocessing industry. The energy generated from wind solar integrated with anion membranes (AEMs) fuel cells (PEMFCs), which...
Ayurveda based nanomaterials are recently conceptualized phenomena for biomedical applications especially imaging and treatment of in vitro cancer cell. Wide range florescent (blue to red emission) quantum dots versatile materials sensing applications. Various procedures precursors fluorescent carbon (CQDs) well established documented the literature. However, expensive production, time consuming process limit their economical design that need be addressed. Herein, we report a cost effective...
Hydrogen is a nearly emission-free energy carrier with many enticing qualities, including wide availability, environmental friendliness, and high calorific value. There have constantly been lot of challenges to establish an entire fledge low carbon hydrogen economy in the past century. This study aims critically analyse economic, environmental, technological, policy implementation division low-carbon find novel solutions, bridging gaps giving perspective approach study. Differentiation...
<title>Abstract</title> The instability of renewable energy sources like solar and wind places significant hurdles on distribution grid stability, thus hampering the race towards sustainable solutions. These instabilities, mainly due to fluctuating weather conditions, may lead surpluses or shortages energy-with inevitable effects grid's reliability. It is proposed that an AI-enabled system based ANN LSTM solutions be developed analyse global trends, predict generation accurately, enhance...
<title>Abstract</title> Solar photovoltaic (PV) systems are central to the world's movement toward renewable power, but their performance declines with time owing a combination of environmental expo- sure and usage stress. In this research, we suggest hybrid machine learning system that incorporates multi-source data such as device logs, weather history, customer endpoints, network endpoints in order make precise predictions about solar panel degradation. The data, which was obtained from...
This research presents a detailed evaluation of global wind power generation, employing cutting-edge machine learning methods to forecast future trends and capacities through 2050. Reviewing the past data various countries, we construct predictive models for analyzing potential increase in capacity factors, regional differences. Using polynomial regression random forest methods, project high growth energy production, pointing key importance installed capacity, technology, geographical...
Surfactants are specific functional materials that form various types of self-assemblies and affect local water ordering alongside solution properties. Such surface active agents used extensively in gas hydrate based applications as kinetic promoters. To understand the effect surfactant micelles on formation kinetics, a novel system capable producing at forming temperature was developed. The presence this new (a combination anionic SDS zwitterionic CAPB) determined through DLS measurements....