The goal of this research project is to investigate the how particle properties, such as shape, influence flow structures within industrial setups. The goal is to determine the optimal particle characteristics that can enhance the efficiency and performance of these systems.● Experimetnation:- Designed and built cost-effective experimental setups, including material procurement and assembly. Conduct complex fast optical and X-ray imaging experiments based on DoE methodology. Investigated 2D and 3D flows under various parametric settings using high-speed digital and X-ray imaging. -Investigated particle deposition morphology, energy evolution, velocity (local and bulk), volume fraction, flow rate, fluctuations, frictional and dynamical angles. -Experience with rheometer, shear testers, SEM, X-ray imaging, high-speed imaging, silo and dam-break setups.●Experimental Analysis :- Image processing: Performed image analysis routine incorporating 3D volume generation, image enhancement, morphological operations, segmentation, particle recognition, functional shape fitting, Particle Image Velocimetry (PIV), and Particle Tracking Velocimetry (PTV).-Data analysis: Expertise in data transformation and (2D, 3D) visualization, as well as descriptive statistics. Improved and validated analytical models to describe particle dynamics, and developed a theoretical model to determine the velocity profile based on particle shape.● Soft Skills:-- Collaboration: Productively collaborated on experiments and simulations with researchers from the University of Navarra,, and the Helmholtz Center (HZDR), as part of the European Union consortium ‘CALIPER’.-Project management: Successfully understood and prioritized the tasks, adhered to deadlines, and finished the Ph.D. project within the time frame.- Attended training schools on powder rheology. Participated in teaching the 'Granular Matter' course and supervised master students.

-Flow Dynamics Research: Researched particle-laden flow in a zigzag air classifier, investigating its separation performance and grade efficiency based on particle size, density, and shape. -Data Analysis: Investigated the performance of analytical models by incorporating terminal velocity, forces, and particle properties. Developed a custom machine learning algorithm to identify and quantify particles from video data with 90% accuracy.-Material Selection: Procured polymer particles with different densities and sizes. Designed and 3D printed 70000 particles for seven different shapes.

-Process Optimization: Optimized colorant process for bar soap to enhance the uniformity of soap, reducing rejection from 3% to 2%. Actively participated in monitoring key production processes, including saponification, mixing, and extrusion.-Quality Control: Performed quality control tests for pH, moisture content, TFM, free alkali, color, and overall consistency.

-Optimization of batch reactor for the production of Di-Octyl-Phtalate (DOP)-Performing quality tests including titration, gas chromatography, flammability test and color testing by tintometer

-Participated in daily plant operations, and actively engaged with experienced professionals to enhance practical knowledge of chemical processes-Collaborated closely with the process engineering team to identify areas for optimization in the existing P&ID, ensuring alignment with project objectives and industry standards.