Naresh Kumar Wagri
AMPRI, KTH Royal Institute of Technology, Indian Institute of Technology Indore, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Corporate Institute of Science and Technology
About
I am a postdoctoral researcher at the Department of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
The primary focus of my research is to quantify and analyse the slag infiltration into refractory materials at high-temperature applications.
Also, the chemistry between ash-refractory interaction and the properties of materials.
Machining of metal, heat treatment, material characterization, manufacturing process, production, and industrial engineering.
Thermochemical equilibrium analysis by using FactSage software and characterization of material properties with SEM, EDX, and XRD.
Employment
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AMPRI Senior Project Associate2026 - 2026
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KTH Royal Institute of Technology Postdoc2024 - 2026
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Corporate Institute of Science and Technology Assistant Professor2017 - 2019
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Rajiv Gandhi Proudyogiki Vishwavidyalaya Assistant Professor (Contract)2016 - 2017
Education
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Indian Institute of Technology Indore Mater of Technology (M.Tech)2014 - 2016
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Rajiv Gandhi Proudyogiki Vishwavidyalaya Bachelor of Engineering2010 - 2014
Projects & Funding
Projects & funding information is unavailable.
Publications (22)
- Characterization of the Spent MgO-Based Refractory Lining from a Rotary Lime Kiln Cofired with Fossil Fuels and Potassium-Rich Biomass Save
- Phytosynthesized Silver Nanoparticles from Waste Kigelia africana Flowers: Characterization and Functional Applications Save
- Accelerating Bulk Modulus Design of High-Entropy Alloys Through Explainable Machine Learning and SHAP-Driven Insights Save
- Central India Medicinal Plant Dataset (CIMPD) Save
- Predicting the magnetic behaviour of homogenized CoCrFeNiAlx high entropy alloys at different aluminium content and temperatures: Reducing experimental dependency through machine learning approaches Save
- Starch–Biomacromolecule Complexes: A Comprehensive Review of Interactions, Functional Materials, and Applications in Food, Pharma, and Packaging Save
- Machine Learning Approaches for Predicting Mechanical Performance and Reducing Experimentation in Refractory High‐Entropy Alloys Save
- Reducing experimental dependency: Machine-learning-based prediction of Co effects on the mechanical properties of AlCrFeNiCox high-entropy alloys Save
- High temperature exposure of MgO-based refractory material to biomass and coal ash with/without quicklime Save
- Renewable energy carriers in rotary lime kilns: insights from collaborative research Save