Applied Computations for Engineered Sustainability (ACES) Research Group performs cutting edge research in the fundamental aspects of engineering sciences, process engineering, material design and development for sustainable environment and in polymeric systems, using various computational tools. Computational tools are of great importance as it help the Chemical Engineers and Industries to achieve improved engineering performance, using location-specific control on the process and of material properties. 

Multiscale modelling ranges from micro- to macro-length & time scale and arrives at a detailed engineered insight of the process and system for further development. Research in this dimension includes multiscale modelling and simulations followed by rigorous analysis based on thermodynamic calculations and established thermo-physical theories, which then provides engineers and scientists to overcome futile, expensive trial experiments and thus save their effort and time in a cost-effective manner.

Our research group focuses on the following non-exhaustive list of interesting thrust areas:

• Molecular Modelling & Simulations inside Porous Media

• Theoretical Material Design for  

  • Carbon dioxide & Green-house gas Capture

  • Hydrogen Storage 

  • Water Treatment 

  • Fuel Cell 

• Continuum Modelling & Simulations dealing with

  • Fire and Explosion Modelling 

  • Steady and Transient State Transport and Chemical Process Modelling 

  • Safety Modelling

  • Predictive Modelling for AI-based Control

Facilities: 

• 160 cores computational facility: Intel Xeon Gold 6230 Processor 256 GB

• Software: Quantum ATK, MCCCS-Towhee, LAMMPS, VMD, RasMol, Java, MATLAB, etc.

The overarching goal of the ACES group is to strive in providing new understandings at the length scales from sub-atomic level to macroscopic engineering dimensions by the predictive design of materials and systems. We attempt to do this by using various regime of modelling & simulations approaches and by using theories in the range of the atomistic to the macro-scale length scale.