Prof Nipu Modak
Professor
| Department of Mechanical Engineering
Jadavpur University
West Bengal
Expertise:
Mechanical Engineering
65
Publications
2
Projects
459
Scopus Citations
386
CrossRef
19 Years 8 Months Total Experience
Scopus
459
Citations
13
h-index
CrossRef
386
Citations
12
h-index
Google Scholar
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Professional Recognition
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Personal Details
Doctor of Philosophy
2011
National Institute of Cholera and Enteric Diseases
Professor
Jan 2007 – Present
Jadavpur University
| Department of Mechanical Engineering
Engineering and Technology
Scholarly Work
Fabrication and development of mg2si reinforced magnesium metal matrix composite
CompletedExperimental Investigations of Tribological and Mechanical Properties of Fibre Reinforced Composites
CompletedThe Effect of Nano-Oxide Addition in Alumina Ceramics and its Impact on Mechanical and Tribological Properties
Magnetic Bead Based Immunomagnetic Separation for Lab-on-a-Chip Devices
Developing a framework for Engineering Product Development in the Indian Context
Preparation and TribologicalCharecterization of Aluminium Particulate Filled Glass Fiber Reinforced Epoxy Composites
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Scholarly Publications
Managerial Support to Control Entrepreneurial Culture in Integrating Environmental Impacts for Sustainable New Product Development
Determinants of Sustainable New Product Development and Their Impacts in Manufacturing Companies
Vehicle Mounted Solar and Wind Power Energy System
Congo Red Dye Removal From Wastewater using TiO2 Nanorod-coated River Sand under Visible Light
Influence of bismuth content on the properties of glass-ceramics with composition xBi2O3-(0.40-x)B2O3-0.15ZnO-0.45P2O5: Synthesis, structural, thermal analysis, and dielectric relaxation process
Interfacial molecular structuring governs mechanical performance in hybrid rubber–epoxy composites: Insights from experiments and atomistic simulations
10.1016/j.compositesa.2026.109687
Scopus: 1
Compositional tuning of thermal stability, elastic moduli, and dielectric relaxation in Bi₂O₃-doped molybdenum-vanadium phosphate glasses
A Machine Learning Approach to Predict Dye Degradation Efficiency Using ANN in Photocatalytic Systems
Showing 1 to 8 of 65 publications