Alex Mironenko

Alex Mironenko

Alex Mironenko

Alex Mironenko: Bridging disciplines to better understand catalysts

This profile originally appeared in the Spring/Summer 2021 issue of Mass Transfer, the magazine for alumni and friends of Chemical and Biomolecular Engineering at Illinois. For a listing of all our faculty members, please visit our directory or explore the department’s research pages for overviews of our groundbreaking research programs.

Much like the molecules he studies, Alex Mironenko is interested in building bonds to accelerate progress— by bridging disciplines and creating collaborations. Mironenko joined the Department of Chemical and Biomolecular Engineering as an assistant professor in August 2020— but not physically.

In June 2020, he returned to Russia to sort out a visa and was not able to return to the U.S. until April 2021 due to COVID-19- related travel restrictions and consulate closures. For the past eight months, he has been juggling new job responsibilities and the 11-hour time difference.

Mironenko always had an affinity for chemistry. His aptitude for the field was confirmed when he was one of 16 high school students in his home country of Russia who received a 100/100 score on the standardized chemistry test (SAT analog).

A man of many talents and interests, he realized early on that chemical engineering would allow him to pursue many disciplines: chemistry, physics, math, and even software engineering.

Today, his research brings together these fields to determine the best catalysts to speed up critical chemical reactions using a computer as an emerging alternative to traditional trial-and-error experimental approaches.

“To make first-principles predictions in catalysis, material science, or chemistry, we need to compute the energy of molecules as a function of the positions of all atoms within the molecule,” Mironenko said. “If you want to predict new catalysts or materials, you first of all need to figure out how to obtain this crucial piece of information.”

Currently, predictive modeling of catalysts and chemical reactions requires supercomputers and some patience—computations require weeks or even months to determine the structures and energies of all hypothesized reaction intermediates.

“We are working to make these energy calculations significantly faster, which would allow us to do these calculations on a laptop, or on a supercomputer in a shorter amount of time, or to screen many more catalyst candidates, ultimately facilitating scientific progress,” he said.

His career was catalyzed by a Fulbright Fellowship that brought him to the U.S. to earn his master’s degree and study bio-oil model compounds under the direction of professor Bala Subramaniam at the University of Kansas. “That research was very different from what I do now,” Mironenko said. “I have fond memories of my time in the lab—it was an important step forward.”

Mironenko moved on to pursue his doctorate on catalytic biomass conversion with professor Dionisios Vlachos at the University of Delaware, which is where Mironenko first hatched his hypothesis that would lay the foundation for his research efforts today. 

A collaboration between Vlachos and University of Pennsylvania professors Raymond Gorte and Christopher Murray on hydrodeoxygenation of a biomass-derived platform chemical hydroxymethylfurfural yielded an unexpected result: the computational data could not explain why one catalyst was more active than another.

“My colleague couldn’t explain it with this assumption that the catalyst was a bimetallic alloy,” Mironenko said. “I came up with this hypothesis that maybe it’s not a metallic alloy, maybe it has a metallic core with a metal oxide shell on the surface.”

With this assumption, they built a computational model that turned out to be fully consistent with all the available experimental information.

But they still did not have a way to find out the structure of these metal oxide shells outside of controlled experiments in a vacuum, which do not necessarily translate to experimental conditions. The only two available options were to either carry out extensive quantum mechanical calculations, which were prohibitively expensive, or develop new empirical reactive force field models.

Force fields are empirical “energy calculators” that take the positions of atoms within molecules as an input and then yield energy and the forces of a molecule as an output. Force fields can calculate the effect of stretching a chemical bond by a little bit, for example, in methane molecules, whereas it is the reactive force fields that can calculate bond breaking and formation, and thus are suitable for screening metal oxide configurations and computing chemical reaction barriers.

However, these reactive force fields require large datasets and extensive parameter tuning. Unfortunately, the fine-tuned parameters developed for a subset of molecules or materials are not transferable to new applications and systems, like his colleagues’ metal oxide shells.

Instead of applying this empirical platform in an ad hoc manner, and trying various energy expressions until he came across the one that magically worked, Mironenko’s idea was to carry out reactive force field development in the most systematic way possible, beginning with fundamental quantum mechanical principles.

He proposed to simplify the Kohn-Sham equations of the density functional theory to arrive at a reactive force field model that would be free of arbitrary energy expressions with the fewest number of parameters.

It wasn’t until Mironenko became a Kadanoff-Rice Postdoctoral Scholar at the University of Chicago that he was able to explore this idea of developing non-empirical force fields—thanks to this fellowship and the creative freedom granted by his advisor, professor Gregory Voth.

Building on two seminal, but long forgotten 1968/1969 articles on localized atomic orbitals, written by a 1977 Physics Nobel Laureate Philip W. Anderson (who grew up in Urbana, Illinois, and passed away last year at the age of 96)— Mironenko finally realized his vision for bottom-up computational approaches to construct reactive force fields.

“Unlike methods that are currently available, our method doesn't have any parameters,” he said. “It is all physicsbased, which is a huge advantage.”

This spring, his graduate student Lanie Leung replicated his original proof-ofconcept results to show that this method works on the simplest chemically bonded structure: a hydrogen molecule.

“It’s thrilling to have a second person in the world who can verify the original idea and who can also share the excitement about the method matching much more expensive calculations,” he said.

Mironenko’s lab is continuing this fundamental research to develop simplified, non-empirical force field simulations. The goal is to apply this method to hydrocarbons, oxygenates, and ultimately, to traditional metal-based catalysts to identify the optimal structure and composition of catalysts for specific reactions that are relevant to renewable energy and chemicals production.

Of course, he also plans to apply this new force field method to finally understand the structure of those metal oxide shells that spurred his original hypothesis.

Mironenko is pursuing other applied research projects related to catalysis by zeolites, metal carbides, and selective carbon-carbon bond formation.

He is collaborating with associate professor David Flaherty to develop computational models of catalytic sites inside zeolite pores, filled with a solvent, which would be consistent with high-precision calorimetry and reaction rate measurements—something which has not been done before.

“Accurate atomistic models of a catalytic site and its environment, validated by experiments, provide crucial fundamental insights into catalyst behavior that will guide new experiments, and ultimately, pave a way toward more active, selective, and stable catalysts,” Mironenko said.

He is also working with Richard C. Alkire Chair Professor Hong Yang to use computational approaches to explain the formation and activity of unique molybdenum carbide nanoclusters that catalyze electrooxidation of organic molecules for fuel cell applications.

Another primary interest of the Mironenko Lab is to bridge quantum mechanics with coarse-grained molecular dynamics.

Quantum mechanics is too computationally expensive to be used to describe the entire surface of a catalyst and model all the atoms in the system. Instead, Mironenko is working toward describing one part of the surface using quantum mechanics and then filling in the rest of the puzzle with a simplified version using the method of bottom-up coarse-graining.

“Effectively, we replace groups of atoms with fewer coarse-grained beads,” Mironenko said. “With fewer particles, we can run the model more efficiently and in a shorter amount of time.”

Mironenko is not intimidated by quantum mechanics, coarse-grained molecular dynamics, or force fields. Instead, he says, his greatest challenge is tackling teaching for the first time.

Luckily, he has his wife Olga Mironenko, a teaching assistant professor in the Department of Electrical and Computer Engineering, to show him the ropes. They are thrilled to finally be reunited in Champaign-Urbana after spending so much of the past year apart.

This fall, he taught Chemical Engineering Thermodynamics for the first time from the same desk in his parent’s house in Russia where he studied for his own undergraduate chemical engineering exams at Omsk F.M. Dostoevsky State University, where he completed his bachelor’s degree.

“It’s a bit surreal,” he said. “The fact that I was able to converge the activities that I have been interested in for so long—like chemistry, math, physics, and programming—into my research program is quite fascinating. I feel that I'm doing exactly what I'm supposed to do."