Catalysis and Reaction Engineering

The Reaction Engineering and Catalysis group pursues excellence in both theoretical and experimental aspects, targeting commercially important applications from a fundamental standpoint with a mix of classical and modern concepts and techniques. Thus, the focus of the group is on classical areas such as process design and optimization as well as modern  areas such as biofuels (from raw materials to products), advanced energy technologies such as fuel cells, electro-synthesis of new products by green and sustainable technologies,  catalysis (synthesis, characterization and performance evaluation) for fine chemicals, and chemical technologies for semiconductor applications (Chemical vapor deposition of silicon as an alternative to Czochralski process). Some of the research by the group is specific to India such as underground coal gasification of high ash content coals which is primarily available  in India. In addition, the group is also engaged in providing smart engineering solutions to Indian Industries. The group has expertise both in theoretical aspects involving    modeling and computational studies of industrial as well as bio-reactors and experimental aspects involving performanceevaluation of scaled down reactors, electrochemical systems, catalyst synthesis and characterization etc. The emphasis of the group is always on fundamental understanding. The facilities available with the group and the department allow a    multidimensional and multiscale understanding of the problems related to catalysis and reaction engineering. The students working on different aspects of catalysis and reaction engineering are trained on sophisticated instruments and advanced computational techniques which will be critical when they take positions in academia or industry. Thus the group  serves a vital national interest in providing trained manpower. Quite often the spectrum of research on catalysis and reaction engineering intersect with chemistry, biology and materials science. Thus, the students are trained to learn and apply concepts and methodologies from these areas. The group encourages students to broaden the horizons of scientific learning and equips them with the tools to do so. As the group looks to the future, it aims to develop new chemicals and processes, green and viable technologies, process and technologies targeted to meet India’s needs in terms of energy, environment and chemicals.

Sub Research areas

Design and synthesis studies of porous/catalytic materials

The synthesis of porous catalytic materials has profound impact in the chemical industries. The effectiveness of these materials is governed by the structure and surface morphology which is controlled by the synthesis parameters (such as temperature, synthesis time, pH, additives). This project is aimed at understanding role of synthesis parameters for the better control over porosity, surface morphology and structure of porous catalytic materials using simulations and possible experiments.

Noise propagation in enzymatic cascades with retroactivity

Enzymatic cascades consisting of phosphorylation-dephosphorylation reaction cycles (PdPCs), are crucial, ubiquitously conserved, building-blocks of cellular signalling networks. Aberrant functioning of PdPCs such as Raf/MEK/ERK MAPK cascade has been implicated in many diseases such as cancer. Cells employ retroactivity due to downstream load to enable two-way communication in a linear pathway.

Single-cell data guided modeling of phenotype switching

Tumor necrosis factor alpha, a pleiotropic cytokine capable of exhibiting pro-survival, apoptosis, or necrotic phenotypes, is implicated in several cancers and rheumatoid arthritis. Understanding the underlying mechanism that governs a cell’s decision to the phenotypic response can help obtain insights on how signal flow can be modulated to achieve a desired phenotype.

Computational design of bimetallic catalysts

Bimetallic catalysts are synthesized using two different metals. For instance, Ag-Au, Pt-Ni, Au-Pt are examples of bimetallic catalysts. For some reactions these materials are more promising than pure metal catalyst. A question arises about the role of the individual metal species. We shall employ a combination of state-of-the-art density functional theory, molecular dynamics and kinetic Monte Carlo simulations to study the effect of Au-Pt composition, surface arrangement and other experimental parameters on the rate of methanol electro-oxidation reaction.

Machine learning techniques applied to molecular simulations

Molecular simulations of catalytic and catalyst support materials are often computationally expensive. These simulations can directly provide information about how chemical rates may depend on atomic position, or the interactions between atoms. Here we explore the use of machine learning techniques. Machine learning techniques (neural network, random forest, clustering, gaussian process regression) will be used to develop atomic scale models for catalytic and fast ion conductors.