Research
Polymer crystallization
Polymer crystallization is the transformation of polymer molecules from a disordered (amorphous) state into an ordered (crystalline) one. At conditions suitable for polymer crystallization, as commonly modeled, there exists a free energy barrier between the amorphous and crystalline states. Nucleation is the initial stage of the crystallization in which a small sized crystalline domain, called as seed or nucleus, start to form until the time the seed passes the free energy barrier. Growth is the second stage of crystallization, and it starts when the free energy barrier is overcome by the seed growing in size.
Our capacity in developing polymeric materials with improved properties, depend heavily on our ability to manipulate the physical and chemical events occurring during the processing of polymers, which relies on a better understanding of the physics behind these events. For instance, the extent of crystallization is known to be related to the durability of a polymeric product and thus exploring how the polymer crystallization happens most likely help us produce high strength polymeric materials.
Polymer crystallization is one of the most important problems in polymer science. There has been a tremendous amount of scientific work devoted to understanding the polymer crystallization phenomenon. Yet, there has not yet been a unified understanding of how it proceeds in spite of this huge effort. Although with the advance of experimental techniques we learned a lot about this process, it is still not possible to produce experimental results in the nanometer length scale resolution. One can experimentally count in how many samples, each having a size of tens of nanometers, crystallization happens, but it is not possible with the current technology to see what is happening inside a nanometer sized droplet. Molecular simulations provide a fantastic set of tools to monitor what may happen inside a polymeric droplet during the crystallization. Results from such simulations to uncover polymer crystallization in nanodroplets, have been reported to a limited extent.
In our work performed with polymer droplets of various sizes, we remarkably found that the nucleation rate per unit volume increased with decreasing droplet size. Furthermore, we found that the nucleation primarily occurred near the surface of the droplets. The reason why the nucleation rate increases with decreasing droplet size remains to be uncovered. We need more work on the simulation of polymer crystallization within nanodroplets to better understand this process in such systems.
Quantum computation
Quantum computing emerged in the 1980s with the pioneering ideas of physicists like Richard Feynman and David Deutsch, who proposed that quantum systems could be used to perform computations beyond the reach of classical computers. The development of algorithms such as Shor’s algorithm for integer factorization and Grover’s search algorithm in the 1990s demonstrated the theoretical potential of quantum computers to solve specific problems exponentially or quadratically faster than classical counterparts. These breakthroughs laid the foundation for what we now call quantum advantage—the ability of a quantum computer to outperform the best known classical algorithm for a given task.
Building on this foundation, our research focuses on the design and exploration of new quantum algorithms that could offer such an advantage. Using Qiskit, an open-source framework developed by IBM, we aim to prototype and analyze algorithms that exploit uniquely quantum resources such as superposition, entanglement, and interference. The central goal is to identify and develop efficient algorithmic strategies that can outperform classical methods in areas such as optimization, simulation, or data processing. This work is intended to contribute to the growing body of knowledge guiding the transition from theoretical promise to practical, real-world quantum computing applications.
Educational research
Our educational research focuses on improving undergraduate education in chemical engineering with the goal of enhancing student learning and supporting academic success. We investigate how curricular design, instructional strategies, and learning environments influence student outcomes, with particular attention to identifying and addressing barriers to success. We collect and analyze data on student experiences, perceptions, and performance to inform evidence-based improvements to teaching practices. Our work aims to foster more inclusive, engaging, and effective learning experiences that better prepare students for the challenges of both academia and industry.