This is a project which is currently making use of HPC facilities at Newcastle University. It is active.
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This study focuses on evaluating the influence of mineral catalysts on the biomass pyrolysis process through a multi-scale analytical framework. The investigation will incorporate the development of single-particle models to examine localized reaction behavior and transport phenomena, complemented by density functional theory (DFT) calculations to elucidate catalyst–biomass interactions and reaction energetics at the molecular level. In addition, reactor design considerations and process simulations will be used to analyze heat and mass transfer behavior during pyrolysis, enabling a more comprehensive understanding of the impact of mineral catalysis across both particle- and reactor-scale systems.
The proposed work will utilize a combination of atomistic modelling, continuum-scale simulations, and data-intensive post-processing workflows on the HPC facility. At the molecular scale, density functional theory (DFT) calculations will be performed using established electronic structure packages such as VASP or Quantum ESPRESSO to investigate mineral-biomass interactions, reaction energetics, and catalytic pathways. These simulations will employ plane-wave basis sets with periodic boundary conditions, requiring parallel execution across multiple compute nodes and efficient use of MPI-based architectures.
At the particle and reactor scale, numerical simulations will be conducted using ANSYS Fluent to model heat and mass transfer, reaction kinetics, and multiphase flow behavior during biomass pyrolysis. Custom kinetic models and user-defined functions will be integrated to capture mineral-catalyzed reaction mechanisms. In addition, MATLAB and Python (with libraries such as NumPy, SciPy, and pandas) will be used for developing single-particle models, parameter estimation, sensitivity analysis, and coupling between kinetic and transport models.
Post-processing, visualization, and large dataset handling will be carried out using Python-based tools and ParaView for high-resolution analysis of simulation outputs. Where required, workflow automation and job scheduling will be managed using shell scripting and SLURM.