Use of fluoresent material like ZnO for down conversion in solar
photovoltaics and other energy applications
Professor: Karthik Sasihithlu
UID: EG01
Data driven analysis of particle agglomeration/de-agglomeration in
a vibro-fluidized bed
Professor: Manaswita Bose
UID: EG02
Numerical simulation of fluid flow and heat transfer in a stirred
tank reactor using openfoam
Professor: Manaswita Bose
UID: EG03
Determination of air flow pattern in a model room using Particle
Image Velocimetry
Professor: Manaswita Bose
UID: EG04
EG01
Description: ZnO particles are known to absorb in the UV
and emit in the visible spectra. This allows its use for solar
photovoltaics and also in rooftop cooling paints. While its
utility for photovoltaics has been explored previously, its use
in rooftop cooling paints is novel and has not been explored
before. The student will analyze the properties of ZnO and the
dependence of photoluminescence efficiency with defect states
and radius of particles. Work will involve both modelling as
well as experiments. There will be simultaneous evaluation of
performance of cooling paints developed in our lab, and the
improvement from using ZnO particles.
Number of students: 2
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
CPI eligibility criteria: 7
Prerequisites: Interest in material properties, optical
properties of matter
Duration: 2 months+
Learning outcome: Application of PL material like ZnO in
different devices such as PV cells, radiative cooling paints,
modelling such phenomena, optical scattering from particles,
working with phD students. Getting a feel of how it is work in a
research setting and performing experiments.
Weekly time commitment:35 hours
General expectations: Enthusiasm to learn and discover
Instructions for assignment: Read about both radiative
cooling paint, as well as properties of ZnO. Can you think of
how ZnO will find utility in radiative cooling paint ?
EG02
Description:Agglomeration (de-agglomeration) of cohesive
particles under vertical vibration has applications in dry
coating. The rate of the agglomeration (or de-agglomeration)
process depends on the cohesive energy between the particles and
the energy supplied to the system in the form of wall vibration.
It is important to determine the rate constant for the
agglomeration and the de-agglomeration process under vertical
vibration and express them as functions of the particle
properties and vibration energy. The objective of the project is
to perform numerical simulations using the discrete element
method and generate the database and determine the correlations
following standard linear or non-linear regression method.
Number of students: 1
Students entering 3rd year, Students entering 4th/5th year
CPI eligibility criteria: >=7
Prerequisites: Interest in coding
Duration: 3 months.
Learning outcome: Opensource software LAMMPS, coding,
application of regression methods, one of the fundamental
concept of data driven analysis
Instructions for assignment: "The student is required to
summarize the paper Khalifa and Breuer (2020) Powder Technology;
Data-driven model for the breakage of dry monodisperse
agglomerates by wall impact applicable for multiphase flow
simulations"
EG03
Description:Stirred tank reactors are widely used in
process and pharmaceutical industries. One of the applications
is crystallization. The specific objective of the project is to
understand the fluid flow field in a continuously stirred tank
reactor to investigate the mixing. Simulations will be performed
using the opensource software openfoam. Simulations will be
performed using both rotating frame of reference and laboratory
frame of reference. Effect of shapes on blade on the vortex
formation in tank will be investigated.
Number of students: 1
Year of study: Students entering 4th/5th year
CPI eligibility criteria: NONE
Prerequisites: NONE
Duration: 3 months
Learning outcome: The student will learn to simulate
fluid flow in Openfoam.
Description:Transmission of airborne disease in confined
spaces like classrooms is strongly influenced by indoor
ventilation. Computational Fluid Dynamics (CFD) has emerged as a
diagnostic tool for detecting indoor air movement; however, the
CFD results need to be validated against experimental
measurements before a final conclusion is made. Particle Image
Velocimetry is the state of the art measurement methodology that
can be used to determine the local air velocity. The same can be
used for validating the CFD results. The objective of this
project is to perform experiments in a model classroom and
determine the air velocity patterns using particle image
velocimetry. The data will be used for validation of the CFD
results.
Number of student: 1
Year of study: Students entering 3rd year
CPI: more than 7.5
Prerequisites: Interest in Fluid Mechanics and
Experiments
Description:Driver warning technologies hold the
potential to reduce traffic crashes and save precious human
lives. Scientists and engineers hypothesize that the
measurements obtained from advanced driving simulators can
predict equivalent measurements in the real world that lead to a
better understanding of the driver behaviour in critical driving
situations. The aim of the project is to study the variations in
driver state using a combination of driver behavioural and
driver physiological signals using sensor technologies in
driving simulator. Driver warning can be developed through
statistical analysis and AI techniques.
Number of students: 2
Year of study: Students entering 4th/5th year
CPI eligibility criteria: >8
Prerequisites: Data analysis tools
Duration: 6-8 months
Learning outcome: Statistical data analysis and modeling,
exposure to driver simulators and sensors