(4bi) Multiscale Molecular Modeling in Porous Materials: Accurate Predictions for Sustainable Applications

In my work, I leverage molecular simulations to develop sustainable applications of porous materials, with a particular focus on metal-organic frameworks (MOFs). My work addresses key fundamental challenges, such as the effects of deformations of the adsorbent or hysteresis on the adsorption process. This foundational research underpins practical applications in fields like CO₂ capture, separation technologies, water harvesting and adsorption cooling. By synthesizing theoretical insights with high-performance computing and collaborative experimental efforts, I enhance both the understanding and application of these advanced porous materials.

My previous research has focused on the understanding of structural properties and dynamic behaviors in MOFs. By developing a microscopic model that elucidates phonon-adsorption correlations, I identified key low-frequency phonon modes that induce structural changes in flexible MOFs and analyzed phonon-deformation correlations across various materials. Additionally, my work on the dynamic pore environment within MOFs has provided insights into how subtle changes can affect adsorption mechanisms for CO₂ and water, aiding the design of MOFs for applications in carbon capture and water harvesting.

Currently, I aim to advance molecular simulations of vapor adsorption and emphasize accuracy, reproducibility, and comparability in simulation results. I have addressed the need for consistency in molecular model implementations, ensuring agreement between the explicit adsorbate and implicit bulk phases in grand canonical Monte Carlo simulations. Additionally, I performed a comprehensive screening of MOF structures for adsorption cooling, directly considering all thermodynamic aspects of the cycle, yielding a more accurate measurement of process efficiency. I employed novel methods to predict these properties with a high accuracy level, identifying MOFs with enhanced cooling capacities and emphasizing the importance of structural stability in maintaining performance, advancing the use of MOFs for sustainable cooling technologies.

My experience forms a good foundation for future research, in which I aim to design porous materials capable of capturing, storing, and transforming various chemical species, contributing to applications such as carbon capture, water harvesting, and sustainable heating and cooling techniques. My approach will include utilizing multiscale molecular modeling techniques such as Monte Carlo, molecular dynamics, and density functional theory to predict the properties of both synthesized and hypothetical materials with precision. My proposed research emphasizes (i) developing strategies of minimizing adsorption hysteresis to enhance process reversibility, including quantifying hysteresis through molecular simulations and introducing specific structural patterns in multivariate metal-organic frameworks (MTV MOFs) to improve our understanding and control over adsorption reversibility. I also plan to (ii) explore how intrinsic flexibility at different levels – from large-scale structural phase transitions to local changes within pore environments – can improve the performance of porous materials in capturing, storing, and releasing important molecules such as CO­₂ and water. For that I will leverage novel techniques such as machine learning potentials and advanced adsorption simulation tools for this analysis. By applying these insights, I aim to (iii) identify and design materials for specific applications, such as carbon capture and water harvesting. Beyond these, I will place significant emphasis on sustainable heating and cooling applications, including adsorption cooling and thermal energy storage. This approach ensures that these materials address environmental challenges while also contributing to energy sustainability. Efficient data analysis methods, such as large language models, will be applied to understand correlations between material performance and their underlying properties. Close collaboration within a wide network of experimental partners ensures an iterative process between theoretical prediction and experimental validation, grounding the research in practical reality to address real-world challenges.

Teaching Interest

My teaching philosophy is centered around the concept of "education for impact". Rooted in my diverse academic background – transitioning from physics to chemical engineering – I believe teaching goes beyond imparting knowledge; it's about equipping students with the skills to make substantial contributions in their respective fields. This multi-disciplinary approach enables me to guide students in leveraging various methodologies to tackle complex engineering problems.

Throughout my 6-year work as a teaching assistant and assistant professor in Poland, I taught diverse courses, covering topics in molecular modeling, numerical methods, physics, and chemical engineering. The diversity of these courses has not only broadened my understanding but also motivated me to present complex ideas in a way that engages students with varying backgrounds and interests.

During my postdoctoral work in the USA, I had the opportunity to deepen my teaching skills and broaden my academic perspective as a guest lecturer in the Analysis of Chemical Process Systems and Applied Molecular Modeling courses. I have been fortunate to mentor both undergraduate and graduate students throughout my academic journey. These interactions have made it clear to me that adaptive teaching is crucial, as each student possesses unique strengths, weaknesses, and learning styles. Consequently, my teaching philosophy emphasizes flexibility and tailored instruction to meet individual needs.

My teaching expertise spans thermodynamics, heat and mass transfer, and numerical methods in chemical engineering. Reflecting my research interests, I aim to develop a new course addressing the application of molecular modeling in solving modern societal challenges.