We are exceedingly proud of Jayashree's success and that of CBEE students in past 3MT competitions!

Photo credit: Dr. Ghosh. 

Alt Description: Ph.D. student, Mandar Bokare, preparing to analyze a passive sampler in the laboratory.

His talk, titled "Disruptive Innovation to Reduce Health Care Costs", described emerging technologies that are designed to empower people to take charge of their own health and presented several critical technology platform. 

The production of synthetic zeolites for use as catalysts and adsorbents is a multi-billion-dollar industry. Zeolites are materials having molecule-scale pores that enable catalytic applications in petroleum refining, automotive emissions treatment, and biomass processing. Zeolites frequently catalyze chemical reactions in water, as is the case when producing renewable fuels and chemicals from biomass. The interactions of water molecules with the zeolite catalysts are incredibly complex, but it is important to understand how these systems behave so that zeolites can be optimized for application-based performance. Unfortunately, existing computational modeling tools struggle to both accurately and efficiently predict how complex chemical mixtures interact with zeolite catalytic active sites. This project will develop simulation techniques that will enable orders-of-magnitude improvements over current approaches, thereby generating fundamental knowledge of how water interacts with zeolite catalyst active sites. Symbolic regression, a machine learning tool for identifying equations that represent a given dataset, will also be explored for describing fundamental interactions between acids and bases. Community-based learning and outreach activities are planned to engage high school students in symbolic regression for math, science, and machine learning.

This project will advance Monte Carlo simulation methods to enable efficient sampling of water adsorption in acidic zeolites. Specific aims include 1) introducing Monte Carlo moves for directly sampling protonation states of water clusters in zeolites, 2) demonstrating simulations of competitive adsorption of water and alkanes using literature force fields, and 3) generating interatomic potentials for acid-base interactions by using symbolic regression to learn equations from quantum chemistry calculations. The anticipated outcomes will lay the groundwork for simulations of competitive chemisorption in porous materials with active sites, as well as discover new equations for simply characterizing potential energy surfaces of acid-base interactions.

The move to Bioprocessing 4.0 depends heavily on advancing sensor technology. Only then can one accurately monitor and control biochemical reactions occurring in living cells. At the University of Maryland, Baltimore County (UMBC), Govind Rao, PhD, professor of chemical, biochemical, and environmental engineering, and director of the center for advanced sensor technology (CAST), and his colleagues develop new sensors that help bioprocessors move from batch to continuous processing. One of the key elements to monitor is oxygen.

“Oxygen is the critical metabolic requirement for aerobic cells in culture and is the hardest to supply to cells due to its low solubility,” Rao explained. “Consequently, monitoring its presence is critical.”

Optical sensors offer promise in this area for oxygen and more. When asked about the most important recent advance in optical sensors that can be used in bioprocessing, Rao said that it’s “the ability to monitor multiple parameters in a non-invasive manner.”

Although research on optical sensors plays a fundamental role in their development, bioprocessors look for technology that can go into manufacturing facilities. That’s just what Rao develops. “All our sensors are designed for commercial application and in fact several are on the market,” he said

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• Screen Printing Tissue Models Using Chemically Cross-Linked Hydrogel Systems: A Simple Approach To Efficiently Make Highly Tunable 
  https://doi.org/10.1021/acsbiomaterials.1c00902 
  Narendra Pandala1, Michael A. LaScola1, Yanchun Tang, Maria Bieberich, LaShanda T.J. Korley, and Erin Lavik2

• Stability of proteins encapsulated in Michael-type addition polyethylene glycol hydrogels
https://doi.org/10.1002/bit.27949
Zahra Ghassemi1, Samuel Ruesing, Jennie B. Leach2, Silviya P. Zustiak3

• Development and testing of a fully-coupled subsurface-land surface-atmosphere hydrometeorological model: High-resolution application in urban terrains
  https://doi.org/10.1016/j.uclim.2021.100985
  Mahdad Talebpour1, Claire Welty2, Elie Bou-Zeid

• Emerging Nanotechnology for Treatment of Alzheimer’s and Parkinson’s Disease
   https://doi.org/10.3389/fbioe.2021.672594
  Amanda Li, Joel Tyson1, Shivni Patel, Meer Patel, Sruthi Katakam, Xiaobo Mao and Weiwei He

• Micafungin-Induced Cell Wall Damage Stimulates Morphological Changes Consistent with Microcycle Conidiation in Aspergillus nidulans
  https://doi.org/10.3390/jof7070525
  Samantha Reese, Cynthia Chelius3, Wayne Riekhof, Mark R. Marten2 and Steven D. Harris

• The RNA-binding protein and stress granule component ATAXIN-2 is expressed in mouse and human tissues associated with glaucoma pathogenesis
  https://doi.org/10.1002/cne.25228
  Chad A. Sundberg1, Monika Lakk, Sharan Paul, Karla P. Figueroa, Daniel R. Scoles, Stefan M. Pulst, David Križaj

1 Current CBEE Graduate Student

2 CBEE Faculty

3 CBEE Graduate Student Alumni