Research Projects

In this Ph.D. project, I developed a nonlinear mechano-electro-chemical model of biological hair bundles, the key structures responsible for sound transduction in hearing, to study their vibrations under diverse loading conditions. The model aimed to uncover the mechanisms behind experimentally observed phenomena, such as the unique "three-row" arrangement of hair-like cells in mammalian bundles and the biphasic adaptation of transducer currents. By offering a streamlined yet efficient representation, this model enhances our understanding of hair bundle mechanics, with potential applications in refining finite element cochlear models, advancing hearing prostheses, and designing bio-inspired, highly sensitive sensors.

Related Publications:

• https://doi.org/10.1101/2025.04.17.649156.

• https://doi.org/10.5281/zenodo.14217893.

• https://doi.org/10.1121/10.0027617.

• https://doi.org/10.1063/5.0189756.

• https://doi.org/10.1121/10.0018516.

This Ph.D. project explores the implications of a fascinating recent experimental observation in auditory biology. Traditionally, the hair bundles of inner hair cells—responsible for converting sound into signals that activate neurotransmitters—were thought to float freely in the cochlear fluid. However, new micrographs of mammalian hair bundles suggest they may be embedded in overlying structures at specific locations in the cochlea. To investigate this, I developed a fluid-structure interaction model, integrating it with a nonlinear mechano-electro-chemical model of biological hair bundles from a previous project. This combined model examines how the free-floating versus embedded configuration impacts the receptor potential, the key driver of neurotransmitter activation.

For my master’s project, I developed a three-clad acoustic fiber for precise temperature sensing, achieving 86% acoustic energy transmission and 97% accuracy. Using total internal reflection and impedance mismatch, I conducted 150+ material experiments and tested 500+ clad combinations with ABAQUS simulations. Temperature measurement was optimized by engineering periodic notches to analyze pulse-echo time shifts. This innovation has applications in energy systems, manufacturing, and medical diagnostics, enabling efficient and accurate temperature monitoring.

In this research internship project, I investigated the potential of butene-based fuels to reduce harmful emissions, proving they cut emission precursors by 23%, a breakthrough that enhances their commercial viability. Utilizing molecular-beam mass spectrometry (MBMS) with time-of-flight measurement, I conducted over 30 experiments, carefully monitoring four gas flow meters to analyze the behavior of 55 compounds. This analysis revealed critical insights into the effects of different fuel mixtures on ignition, flame propagation, extinction, and pollutant formation. These findings advance the understanding of cleaner combustion processes, paving the way for sustainable fuel technologies with reduced environmental impact.

This research project aimed to create a reliable 2-D numerical model of cold-sprayed metal powders on aluminum using ANSYS software. The model focused on simulating key factors like porosity, flattening ratios, bonding strength, and adhesion during the spray process. By considering energy dissipation and strain recovery, the model provided insights into how the metal particles interact and bond with the surface. The results were successfully validated with experimental data, offering a deeper understanding of cold spraying behavior and enabling accurate predictions of deposition outcomes, all without the need for physical experiments.

This research project focused on measuring the mechanical properties of Trip Steel joints created using Friction Stir Welding (FSW). I analyzed the crystallographic changes and hardness across different zones: the Heat-Affected Zone (HAZ), Thermo-Mechanical Affected Zone (TMAZ), and Stir Zone (SZ). The study revealed both small and large misorientations in the HAZ and TMAZ, as well as a non-uniform distribution of smaller, equiaxed grains in the SZ, caused by complete re-crystallization during the welding process. These findings provide valuable insights into the microstructural behavior and mechanical performance of FSW joints in Trip Steel.

This research internship project involved designing pre-filming twin and single-fluid atomizers using ANSYS and SolidWorks to produce ultra-fine sub-micron level energetic particles. The atomizers were equipped with swirl channels of 400 microns to generate high angular momentum for efficient particle generation. I developed a reliable Discrete Phase Model (DPM) in combination with multi-phase, k-ε turbulent RNG simulations to model the atomization process. The results successfully predicted particle sizes of 50 nm and 3 µm for twin-fluid and single-fluid atomizers, respectively, which were then experimentally validated. This work enhances the understanding of atomizer design for producing fine particles in industrial applications.

Related Publication: 

• https://doi.org/10.1002/prep.201900081.