A
Arun Kumar Thalla
Researcher at National Institute of Technology, Karnataka
Publications - 32
Citations - 1023
Arun Kumar Thalla is an academic researcher from National Institute of Technology, Karnataka. The author has contributed to research in topics: Chemistry & Adsorption. The author has an hindex of 10, co-authored 24 publications receiving 567 citations. Previous affiliations of Arun Kumar Thalla include SupAgro & Indian Institute of Technology Roorkee.
Papers
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Journal ArticleDOI
Green synthesis of iron nanoparticles using different leaf extracts for treatment of domestic waste water
TL;DR: In this article, the authors used various leaf extracts viz. Mangifera indica, Murraya Koenigii, Azadiracta, Magnolia champaca, and to check its potential for treating domestic waste water.
Journal ArticleDOI
Application of life cycle assessment in municipal solid waste management: A worldwide critical review
TL;DR: In this article, the authors analyzed 153 LCA studies published till date since 2013 all over the world and found that the majority of the studies are based in Europe and Asia, while only 66 of the total studies included sensitivity analysis in the assessment.
Book ChapterDOI
Green Synthesis of Nanomaterials
C. P. Devatha,Arun Kumar Thalla +1 more
TL;DR: In this article, a green method for nanoparticle synthesis should be assessed considering three aspects: the solvent, the capping agent, and the reducing agent compared to physical and chemical methods, and various factors affecting the synthesis of nanoparticles, such as pH, temperature, and time, are discussed.
Journal ArticleDOI
Artificial neural network based modeling to evaluate methane yield from biogas in a laboratory-scale anaerobic bioreactor.
TL;DR: The performance of a laboratory-scale anaerobic bioreactor was investigated to determine methane (CH4) content in biogas yield from digestion of organic fraction of municipal solid waste (OFMSW), aimed to focus on the effects of various factors, such as pH, moisture content (MC), total volatile solids (TVS), volatile fatty acids (VFAs), and CH4 fraction onBiogas production.
Journal ArticleDOI
Artificial intelligence models for predicting the performance of biological wastewater treatment plant in the removal of Kjeldahl Nitrogen from wastewater
D. S. Manu,Arun Kumar Thalla +1 more
TL;DR: In this article, support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) were used to assess the removal efficiency of Kjeldahl Nitrogen of a full-scale aerobic biological wastewater treatment plant.