Material Informatics

Materials models and simulation tools are necessary in order to eliminate trial-and-error loops during the development of materials, components and manufacturing processes, to illustrate complex load scenarios and to make reliable predictions of the behavior of existing materials and components as well as for those in the process of development.

We work on a theoretical and experimental study of the aggregation kinetics of oppositely charged nanoparticles. Kinetic Monte Carlo simulations are performed for symmetric, charge-asymmetric and size-asymmetric systems of oppositely charged nanoparticles. Simulation results show that both the weight and number average aggregate size kinetics exhibit power law scaling with different exponents for small and intermediate time of evolution.

In addition to these, , we work with the theoretical predication of various properties of different materials using Machine Learning which can be used in place of other computational methods like DFT. Apart from that, we work with several Multiphysics software to simulate the biological and other environments to study the effect of Materials in them. For example – Study of Chromium doped Ferrous Oxide in treatment of Adenocarcinoma and many such projects.

Related Publication:

[1]. Kulveer Singh, Anubhav Raghav, Prateek K Jha, Soumitra Satapathi, “Effect of size and charge asymmetry on aggregation kinetics of oppositely charged nanoparticles”, Nature Scientific Reports, 9 (1), 3762, 2019.

[2]. Kulveer Singh, Prateek K. Jha, and Soumitra Satapathi, “Controllable Bulk Heterojunction Morphology by Self-Assembly of Oppositely Charged Nanoparticles”, Journal of Physical Chemistry C, 121, 16045−16050,2017.

[3]. Kulveer Singh, Soumitra Satapathi, Prateek K Jha, “Ant-Wall” model to study drug release from excipient matrix”, Physica A: Statistical Mechanics and its Applications, 519, 1, 98-108, 2018.