Functional material simulations refer to the use of computer modeling and simulation techniques to study the properties and behaviors of functional materials. These materials are substances that have specific functions or properties that make them useful in various applications, such as electronics, energy storage, and structural materials.
Functional material simulations allow researchers and engineers to predict and understand the behavior of these materials under various conditions, such as temperature, pressure, and applied fields. This can help in the design and optimization of materials for specific applications, as well as in the development of new materials with improved properties.
There are several different techniques that can be used in functional material simulations, including density functional theory (DFT), molecular dynamics (MD), and Monte Carlo methods. These techniques can be used to simulate a wide range of materials, including metals, semiconductors, insulators, and polymers.
Overall, functional material simulations are an important tool in designing and developing functional materials, helping researchers and engineers to predict and understand the behavior of these materials and optimize their properties for specific applications.
| Module 1 (6 months) | Modeling Thermoelectric Materials |
| Topics and Software | -Introduction to various crystal structure databases for materials
– Structure buildup using VESTA and XCrysden tools – Studying optimization methodologies for structure minimization -Prediction of Electronic Properties for a chosen material -Confirming its stability using Phonon Calculations -Prediction of Electronic Transport Properties using electronic Boltzmann Transport Equations -Prediction of Phonon Transport properties using phononic Boltzmann Transport Equations -Quantification of Material Thermoelectric Efficiency -Analysis of the results -Report writing
Tools Used: Quantum Espresso, Boltztrap1/2, ShengBTE Visualization Tools: VESTA, XCrysden tools Data Plotting: Gnuplot, Xmgrace |
| Module 2 (6 months) | Modeling Materials for Catalytic Applications |
| Topics and Software | – Introduction to various crystal structure databases for materials
– Structure buildup using VESTA and XCrysden tools – Modeling of specific surface of the Bulk Material – Studying optimization methodologies for structure minimization – Prediction of Electronic Properties for a chosen material – Confirming its stability using Phonon Calculations – Screening of various reaction pathways on material surface -Analysis of the results -Report writing
Tools Used: Quantum Espresso, Siesta Visualization Tools: VESTA, XCrysden tools Data Plotting: Gnuplot, Xmgrace |
B.Tech. in (Biotechnology/ Industrial Biotechnology/ Bioinformatics/Material Sciences/Computer Sciences)
M.Sc. in (Biotechnology/Microbiology/Chemistry/Biochemistry/Bioinformatics/Life sciences/Material Sciences)
M.Tech. in (Biotechnology/Bioinformatics/ Industrial Biotechnology/Computer Sciences)
B. Pharmacy/M.Pharmacy
Computational design of biosensors refers to using computer simulations and modeling techniques to design and optimize the performance of biosensors. Biosensors are devices that use living cells or biomolecules to detect and measure specific environmental substances or conditions.
In the industrial setting, the computational design of biosensors can be used to optimize the sensitivity, selectivity, and stability of these devices, as well as to predict their performance under various operating conditions. This can help develop biosensors with improved accuracy and reliability, which are critical for applications such as environmental monitoring, food safety, and medical diagnosis.
In addition to its industrial applications, the computational design of biosensors also has significant benefits for researchers. By using computational techniques to design and optimize biosensors, researchers can better understand the underlying biological processes involved in their operation and identify new opportunities for improving their performance. This can help develop more effective biosensors for a wide range of applications.
| Module – 6 months | Modeling Biosensor/Chemosensor |
| Topics and Sofware | – Introduction to various crystal structure databases for materials
– Structure buildup using VESTA and XCrysden tools – Building model for analyte (for example, gas, drug, ligands) to be sensed – Probing the minimized structure of material-ligand complex – Conformational searching of ligand on Biosensor/Chemosensor material surface – Studying optimization methodologies for structure minimization – Studying physical/chemical properties (for example Adsorption energy) – Calculation of Density of States and other relevant properties -Analysis of results -Report writing
Tools Used: Quantum Espresso, Siesta Visualization Tools: VESTA, XCrysden tools Data Plotting: Gnuplot, Xmgrace |
B.Tech. in (Biotechnology/ Industrial Biotechnology/ Bioinformatics/Material Sciences/Computer Sciences)
M.Sc. in (Biotechnology/Microbiology/Chemistry/Biochemistry/Bioinformatics/Life sciences/Material Sciences)
M.Tech. in (Biotechnology/Bioinformatics/ Industrial Biotechnology/Computer Sciences)
B. Pharmacy/M.Pharmacy