M.Tech, B-Tech, BE

Vinoj Vasu currently serves as Assistant Professor at Department of Chemical Engineering, School of Engineering, Coimbatore Campus. His areas of research include Polymer Product Design and Materials Science.



2006 B. Tech. in Polymer Technology Cochin University of Science and Technology
1988 B. E. in Polymer Engineering University of Pune, Maharashtra, India

Certificates, Awards, Honors, And Societies



  • Computer Aided Engineering
  • Multiscale Modeling methods


Multiscale modeling

The successful synthesis of a tailored material would depend upon the development of successful multiscale modelling techniques. The characteristics of materials arise from their composition across various scales. The interaction mechanisms on the different scales and their influence on the effective, macroscopic properties are of enormous importance for understanding material behavior in general, and for designing material behavior by demand, in particular.


MEC 100 Engineering Mechanics
CHE 351 Modern Separation Methods
CHE 372 Transport Phenomena Laboratory
CHE 384 Plastics - Materials, Processing and Properties
CHE 385 Composites for Aerospace Applications


Publication Type: Conference Proceedings

Year of Publication Title


Vinoj Vasu and Dr. Murali Rangarajan, “Semi-Empirical Simulations of Graphene Oxide and Bisphenol A”, International Conference on Multifunctional and Hybrid materials for Chemical process, Energy, Environment and medical applications (ICMHCEE 2019). NIT Tiruchirappalli, Tamil Nadu., 2019.


Vinoj Vasu and Rangarajan, M., “Semi-Empirical Simulations of Interactions between Edge Functionalized Graphene Oxide and Bisphenol A”, International Conference on Advanced Materials for Clean Energy and Health Applications (AMCEHA-2019). University of Jaffna, Sri Lanka, 2019.[Abstract]

Semi-empirical (PM6) simulations of the interactions between edge-functionalized graphene oxide (GO) sheets and bisphenol A (BPA) are reported. A lattice containing 59 hexagonal cells (C150H34), with one of the edges modified by carbonyl/carboxyl groups, is used to examine interactions with BPA. It is seen that the hydrogen/oxygen atoms of the phenolic group(s) of BPA interact primarily with the oxygen atoms of the carbonyl/carboxyl groups or the hydrogen atoms of the carboxyl group/graphene edges. These interactions are predominantly polar and non-covalent in nature, e.g., hydrogen bonds, in addition to dispersion. Optimized structures, charges and the corresponding interaction energies (DH2) are presented.

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Vinoj Vasu and Dr. Murali Rangarajan, “Semi-Empirical Simulations of Base functionalized Graphene Oxide and Bisphenol A”, 2nd International Conference on Recent Trends in Analytical Chemistry (ICORTAC-2018), University of Madras, Chennai. University of Madras, Chennai., 2018.

Publication Type: Journal Article

Year of Publication Title


Vinoj Vasu and Dr. Murali Rangarajan, “Semi-empirical simulations of interactions between edge-functionalized graphene oxide and bisphenol A”, Materials Today: Proceedings , 2019.


The work on advanced materials in the CoE-AMGT (Center of Excellence in Advanced Materials and Green Technologies) and the experimental data being generated in material synthesis labs and characterization labs, has led me into the field of multiscale modelling.

Multiscale modeling in physics and chemistry is aimed at gaining understanding of material properties or system behavior on one level, using information or models from multiple levels. At each level specific approaches are used for achieving an accurate description of a system. The following levels are usually distinguished: level of quantum mechanical models (information about electrons is included), level of molecular dynamics models (information about individual atoms is included), mesoscale or nano level (information about groups of atoms and molecules is included), level of continuum models, level of device models. Each level addresses a phenomenon over a specific window of length and time. Multiscale modeling is particularly important in integrated computational materials engineering since it allows to predict material properties or system behavior based on knowledge of the atomistic structure and properties of elementary processes.