Accelerating the Discovery of Bimetallic Catalysts for CO2
Conversion with DFT-assisted Machine Learning
Professor: Ojus Mohan
UID: CL01
Role of epistasis in SARS CoV-2 evolution.
Professor: Supreet Saini
UID: CL02
Optimal operation of batch heat exchanger networks
Professor: Sujit Jogwar
UID: CL03
Membrane transport for fuel cells, electrolyzers and desalination
systems
Professor: Bharatkumar Suthar
UID: CL04
Electrodes for li-ion battery
Professor: Bharatkumar Suthar
UID: CL05
Simulations of drying sessile drops: The Coffee Ring Effect
Professor: Guruswamy Kumaraswamy
UID: CL06
Simulation of Electrostatic Classification of Particles using
COMSOL
Professor: Jyoti R Seth
UID: CL07
Design of Pharmaceutical Formulations Using Machine Learning
Professor: Jyoti R. Seth
UID: CL08
Analysis of spurious currents in lattice Boltzmann model for two
phase flow
Professor: Amol Subhedar
UID: CL09
Techno-commercial analysis of the market for lab-reactors and
pilot plants
Professor: Rahul Nabar
UID: CL10
Green Hydrogen: Analysis of global regulations and safety codes
Professor: Rahul Nabar
UID: CL11
System assessment of CO2 capture, utilization and storage (CCUS)
Professor: Prof. Vikram Vishal
UID: CL12
CL01
Description: Machine learning can be a useful tool for
predicting the activity and selectivity of bimetallic catalysts
for CO2 conversion reactions. By training a machine learning
model on a dataset of known catalysts and their performance in
CO2 conversion reactions, the model can learn patterns and
relationships between catalyst composition, structure, and
reaction performance. The aim of this project is to develop a
machine learning model for predicting the activity and
selectivity of bimetallic catalysts for CO2 conversion
reactions, with the assistance of density functional theory
(DFT) calculations. The project will involve the collection and
preparation of a dataset of bimetallic catalysts, DFT
calculations to generate features that capture the electronic
and geometric properties of the catalysts, the development and
optimization of a machine learning model, and the use of the
model to aid in the design of new bimetallic catalysts. This
project will contribute to developing efficient and accurate
screening methods for potential catalysts, leading to the
discovery of novel, efficient, and selective bimetallic
catalysts for CO2 conversion reactions.
Number of students: 1
Year of study: Students entering 3rd year, Students
entering 4th/5th year
Instructions for assignment:Read the above research paper
CL02
Description: SARS CoV-2 evolved by first switching host
from bats to humans. Thereafter, the virus evolved in human
beings, leading to several viral variants rising and spreading.
What was the "logic" of this viral evolution? In this project,
we will investigate this question in the prism of a phenomenon
called epistasis. We will test if these lessons extend to
evolution of other viruses too (HIV, Influenza)
Number of students: 1-2
Year of study: Students entering 2nd year, Students
entering 3rd year
CPI eligibility criteria: >7
Prerequisites: Strong interest in evolution and comfort
with coding.
Duration: 1 year
Learning outcome: Understanding of evolution; SARS CoV-2
evolution.
Weekly time commitment: 40 hours
CL03
Description: "Heat exchanger networks (HENs) are
embodiment of energy integration in process industry to achieve
sustainability goals. The batch processes, due to their dynamic
behavior, result in complex HENs. However, this complexity can
be exploited to facilitate their optimal operation in the
presence of disturbances. Our research has developed a concept
of energy flow redistribution (EFR) to achieve optimal operation
for continuous HENs. This project aims at extending this
framework to batch HENs. Specifically, the project will involve
simulating the batch HEN by solving couple partial differential
equations (PDEs). Subsequently, a nonlinear programming (NLP)
formulation is developed to optimize HEN operation. Lastly,
these solutions are implemented on the batch HEN using an
optimizing controller like MPC."
Number of students: 1
Year of study: Students entering 3rd year, Students
entering 4th/5th year
CPI: 8 and above
Prerequisites: The student should have taken numerical methods
course to solve partial differential equations. The student
should also have familiarity with using Matlab.
Duration: 3 month
Learning outcome: "1. Perform dynamic simulations of
complex integrated systems 2. Formulate optimization problem and
solve it 3. Design and implement advanced controller like MPC "
Instructions for assignment: Summarize these two papers
in your own words (max 2 pages).
CL04
Description: "Simulation of transport of ions in
membranes. Such simulation will results into improved
understanding of the transport of ions in membranes which will
be critical for development of fuel cells as well as
desalination systems. "
Number of students: 1
Year of study: Students entering 3rd year, Students
entering 4th/5th year
Weekly time commitment: full time. 9 am to 5 pm
(including saturday)
General expectations:
Assignment:
Instructions for assignment:
CL05
Description: Electrodes for li-ion battery
Number of students: 1
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
CPI eligibility criteria: 7.5
Prerequisites: NA
Duration: 3 months
Learning outcome:
Weekly time commitment: full time, 9-5 (including
weekends)
General expectations:
Assignment:
Instructions for assignment:
CL06
Description: When a drop of coffee dries, it leaves an
annular deposit. This is called the coffee ring effects and is a
consequence of the transport of colloidal coffee particles as
the liquid droplet dries. We use a modified version of this
effect to form a disc-like colloidal assembly. The formation of
this assembly is governed by the droplet evaporation and the
flow fields set up in the drop. In this project, you will need
to develop a simulation to describe this effect.
Number of students: 1
Year of study: Students entering 3rd year
CPI eligibility criteria: 8 (not hard and fast)
Prerequisites: Must have had a course on transport
phenomena and must have exposure to Matlab or Python (Fluent
Ansys experience would be desirable)
Duration: 2 months
Learning outcome: Learning to set up transport
simulations. Learning the physics of droplet drying.
Introduction to experimental techniques.
Instructions for assignment: Students are expected to
read and review sections 1 and 2 of this paper
CL07
Description: The candidate will setup a simulation using
COMSOL software to understand the mechanisms of powder
classification under applied AC and DC electric fields.
Number of students: 1
Year of study: Students entering 3rd year, Students
entering 4th/5th year
Instructions for assignment: Explain all figures and
conclusions of the above research paper
CL08
Description: Presently, formulation design and
development is largely dependent on design-of experiments,
formulation scientist’s experience in sync with a plethora of
analytical characterisations. Keeping in view the recent
advancements made in the field of Artificial Intelligence (AI),
the current process of formulation design and its optimisation
is a time consuming and labour intensive strategy. A typical
formulation development process involves excipient and process
compatibility studies and its effect on the desired quality
attributes. Machine Learning (ML) is a field of AI which
simluates a process by training a computational model based on a
body of data. While these ML tools have become efficient and
easily accessible, the applications are limited to new molecule
design. However, optimisation models such as commonly used
Bayesian Algorithm hold tremendous potential in identifying
optimal combinations with minimum resource utilisation. ML
supported formulation development would reduce the extent of
DoE, fast tracking the development process and would help
companies to deliver the products faster to the market.
Number of students: 2
Year of study: Students entering 3rd year, Students
entering 4th/5th year
Instructions for assignment: Summarise this manuscript
CL09
Description: Consider a drop of water (with negligible
weight) suspended in the air. At equilibrium, the flow field is
zero everywhere in the continuum limit. Numerical simulation of
this system, however, shows an unphysical flow field near the
water-air interface. This effect is attributed to the diffuse
representation of the water-air interface in the model instead
of a sharp one. The project aims to minimize these unphysical
flow fields, known as spurious currents, by carefully analyzing
discretization errors. The Lattice Boltzmann method will be used
to simulate and analyze the discretization errors.
Number of students: 2
Year of study: Students entering 3rd year, Students
entering 4th/5th year
CPI eligibility criteria: 8
Prerequisites: Basic knowledge of fluid dynamical
equations, numerical methods and c++ programming
Instructions for assignment: Write a two paragraph
summary of the paper
CL10
Description: The goal is to analyse commercially
available reactors in lab and pilot plant settings based on
vendor literature, patents and journal publications. The
approach will be a mix of critical analysis and mathematical
modelling using tools like Comsol, Matlab etc. Technical domains
include heat transfer, mixing and chemical compatibility. The
final output will include a report, numerical analysis and
selection models preferably web based. Scope includes stirred
reactors, pilot plants and flow Reactors including
microreactors. We should be able to predict where reactor
Technology is headed.
Number of students: 1
Year of study: Students entering 3rd year, Students
entering 4th/5th year
CPI eligibility criteria: 9
Prerequisites: Good numerical and programming skills and
interest in industrial chemical engineering
Duration: Summer break. 2.5 months. Extendible based on
performance
Learning outcome: Deep understanding of commerical lab
and pilot reactors and their models.
Weekly time commitment: 30
General expectations:
Assignment:
Instructions for assignment:
CL11
Description: Green hydrogen is a very important part of
the global drive for clean energy and sustainability. However
handling Hydrogen in residential and transportation settings is
a very challenging and dangerous task. Many nations and
organizations have historically had codes and regulations that
apply to Hydrogen users to reduce risk by mandating best
practices. As India enters green Hydrogen in a big way there is
a need to come up with a good framework of regulations in this
area. The goal of this project is to critically analyze global
regulations and understand similarities and differences between
codes from US, Germany and other nations. Finally, the aim is to
make recommendations for a comprehensive Indian code for
Hydrogen use.
Number of students: 1
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
CPI eligibility criteria: 8.8
Prerequisites: NA
Duration: 2 months
Learning outcome: Deep understanding of the safety risks
and mitigation measures for Hydrogen
Weekly time commitment: 30
General expectations:
Assignment:
Instructions for assignment: Come up with a short, half
page summary of what are the major international codes that
apply to hydrogen safety.
CL12
Description: CCUS is a suite of technologies that works
towards removal of CO2 from anthropogenic sources and atmosphere
and converts or stores it for various applications. The National
Centre of Excellence in CCU is a premiere body of the Govt of
India that works on pathways for large-scale decarbonization
through RD&D in this sector. In this project, the candidate will
assist in carrying out the life-cycle and techno-economic
assessment of specific CCUS sites and sectors in India. Further,
a detailed market-based assessment of current status and gaps in
deployment mechanisms will be carried out.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
CPI eligibility criteria: 7
Prerequisites: Basic understanding of one or more of the
following: ArcGIS, IHS Markit, Aspen Plus.
Duration: 8 weeks
Learning outcome: The candidate will gain experience in
leading pathways to decarbonization, specifically with
transferable skills in the sustainability and energy transition
industry.
Weekly time commitment: 40
General expectations: A brief SOP of 15-20 lines may be
provided by the candidate. The shortlisting and selection by the
faculty will be final. Any certification of project work will be
provided only after completion.