(2ki) Sustainable Material Design through Machine Learning and Computer Simulations
AIChE Annual Meeting
2023
2023 AIChE Annual Meeting
Meet the Candidates Poster Sessions
Meet the Faculty and Post-Doc Candidates Poster Session
Sunday, November 5, 2023 - 1:00pm to 3:00pm
In my next professional endeavor, I aspire to establish a research laboratory that integrates molecular dynamics simulations, statistical mechanics, and artificial intelligence to create sustainable polymeric materials and gain an in-depth understanding of the dynamics, rheology, morphology, and function of high-performing battery and membrane materials. Throughout my graduate and postgraduate studies, I have honed my skills in polymer physics, focusing on entangled dynamics, polymer microphase separation, and machine learning. Additionally, I have collaborated with both computational and experimental groups for my research.
The problem of plastic pollution is one that we are currently facing, and it is essential to develop new and sustainable polymer materials for a circular economy. In silico screening and design are crucial for making this transition cost-effective.
Scientifically, my mission entails three primary objectives. Firstly, to achieve sustainable material design, it is fundamental to comprehend the impact of their chemical details. Thus, I envision combining high-throughput atomistic simulations with artificial intelligence to explore and understand the vast chemical space. Secondly, to create genuinely sustainable materials, it is necessary to model materials from cradle to grave. Therefore, I propose an Adaptive-Resolution model capable of capturing rheology and long-time scales simultaneously with chemical reactions such as synthesis and degradation. Lastly, block copolymers have the remarkable ability to form microphase separated morphologies. Although we understand the equilibrium morphologies, dynamics and directed processing still pose challenges.
My ultimate goal is to combine these techniques to develop new materials that facilitate functional computing in materials on the nano-scale.
Teaching Interests
My teaching interests and philosophy are rooted in my passion for mentoring and inspiring students to develop and grow, as well as my experience in academic teaching and coaching sports teams. I believe that teaching is not simply about transferring knowledge but about inspiring a passion for the material and connecting it to real-life examples. By getting to know each student and adjusting the teaching approach to their individual needs and backgrounds, I aim to create a supportive and inclusive classroom atmosphere that fosters critical thinking and learning. To achieve this, I use a range of teaching methods, including didactic reduction and constructive alignment, interactive engagement, and obtaining feedback to adjust the level of material presented. My ultimate goal is to help students apply their knowledge and skills to make a positive impact on society's problems, such as designing renewable energies and sustainable materials.
Currently, I am supervising three graduate students and have previously supervised seven undergraduate students, resulting in three publications. In addition to my research, I have gained valuable experience in academic teaching. I have taught a course on my own at a German university and co-taught a course with another postdoc at the University of Chicago. I also have extensive experience as a teaching assistant. Through these teaching experiences, I have honed my skills in course design, lecturing, and leading discussions, and I continuously seek to improve my teaching effectiveness.