School of Chemical and Biomolecular Engineering Seminar Series

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School of Chemical and Biomolecular Engineering Seminar Series

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https://hdl.handle.net/1853/70957

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Event Series

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School of Chemical and Biomolecular Engineering

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College of Engineering

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Now showing 1 - 10 of 82

Electrokinetics, Transport and Stability of Metal/Electrolyte Interfaces in Secondary Batteries

(Georgia Institute of Technology, 2019-10-30) Archer, Lynden A.
Shape-Selective Growth of Nanoscale Materials: Insights From Multi-Scale Theory and Simulation

(Georgia Institute of Technology, 2019-10-16) Fichthorn, Kristen

Metal nanocrystals have gained tremendous attention due to their superior performance in various applications, ranging from selective catalysis to electronic devices to plasmonic applications, such as photovoltaics and sensing. The properties of nanocrystals are highly sensitive to their size and shape. To this end, solution-phase synthetic protocols have been highly successful at producing a variety of nanocrystal structures. However, great challenges remain in achieving high selectivity to particular nanostructures. A significant difficulty lies in understanding and controlling shape evolution in these systems. A deep, fundamental understanding of the phenomena that promote selective growth in these syntheses would enable tight control of nanostructure morphologies in next-generation techniques. I will discuss our efforts to understand the workings of PVP, a polymer capping molecule that facilitates the formation of selective Ag nanoparticle shapes. In these studies, we use first-principles density-functional theory (DFT) to characterize the binding of PVP repeat units to Ag(100) and Ag(111) surfaces. To understand the solution-phase binding of PVP to these Ag surfaces, we develop a new metal-organic many-body force field with high fidelity to DFT. We implement this force field into molecular-dynamics (MD) simulations to characterize the potential of mean force and the mean first-passage times for solution-phase Ag atoms to reach PVP-covered Ag facets. Using these mean first-passage times, we predict kinetic shapes of large Ag nanocrystals (around 100 nm) and show that these should be {100}-faceted cubes. We also use MD simulations to characterize the interfacial free energies of PVP-covered Ag facets in solution. The thermodynamic shapes that we predict in these calculations are truncated octahedra, with a predominance of {111} facets. These findings are consistent with experimental observations that sufficiently small Ag nanocrystals tend to have shapes with a predominance of {111} facets and larger nanocrystals become {100}-faceted during solution-phase growth in the presence of PVP. Though our studies are consistent with experiments that demonstrate nanocube growth can be directed by PVP alone, many studies have demonstrated that more robust nanocube syntheses can be achieved in the presence of halide additives. We use DFT-based ab initio thermodynamics calculations to probe the influence of chloride on Ag nanoshapes. Consistent with experiment, these calculations indicate that chloride adsorption alone can lead to truncated Ag cubes. “Late breaking” calculations indicate there is a synergistic interaction between Cl and PVP, whereby the combination of these two additives can lead to “pointy” Ag cubes.
Multiscale Modeling of Tissues, Treatments, and Toxicology

(Georgia Institute of Technology, 2019-10-09) Ford Versypt, Ashlee N.

The Systems Biomedicine and Pharmaceutics research lab at Oklahoma State University led by Dr. Ford Versypt focuses on developing and utilizing multiscale systems engineering approaches including mathematical and computational modeling to determine and understand the mechanisms governing physiological effects of various chemicals, e.g., pharmaceutical drugs, toxins, metabolites, and hormones, on human and animal tissues. We specialize in modeling the transport processes and chemical interactions related to both natural and engineered biomedical and pharmaceutical systems. We also develop and refine the computational software elements to support multiscale modeling of such systems. We draw from an interdisciplinary skillset in chemical engineering, pharmaceutics, physiology, applied mathematics, and computational science. In this seminar, vignettes of recently published work from the lab in four different lines of research will be highlighted including (1) the immune system interplay with tuberculosis granulomas, (2) metastatic cancer spread, (3) bumblebee behaviors in response to chronic exposure to pesticides, and (4) glucose-stimulated damage to kidney cells in diabetes and preventative pharmaceutical treatments. The latter area has recently been funded by an NSF CAREER award and exemplifies the integration of teaching, research, and outreach.
Why Are There So Few Female Faculty Members in Several STEM Fields? What Needs To Be Done?

(Georgia Institute of Technology, 2019-09-11) Kuck, Valerie

Since 2009 women have received a majority of the doctoral degrees granted by U.S. institutions.In several scientific fields women have made great strides, whereas in a number of STEM areas the progress has been substantially slower.ln 2017 women received 53% of the doctorates in Biological and Agricultural Sciences and 70% in the Health and Medical Sciences.In contrast, women earned only 23% of the doctorates in engineering, 25% in mathematics and computer sciences, and 34% in the physical and earth sciences.Over the years, the percentage of tenure-line female faculty members in the physical sciences, engineering and mathematics has remained low. Findings from an analysis of the responses to surveys and site visit discussions that involved over 1200 administrators, chemistry and chemical engineering faculty members, graduate students and post-doctoral fellows will be discussed.The hiring rate of female faculty members and factors contributing to their career choices will also be addressed.
World’s First Commercial CO2 to Methanol Plant

(Georgia Institute of Technology, 2019-08-28) Richter, Christaan

The George Olah CO2 to methanol plant, commissioned in April 2012, currently produces ~ 5 million liters/year renewable methanol and capture and convert up to ~ 5600 ton CO2/year [Lim 2016, Nature, 526(630)]. This Carbon Recycling International (CRI) plant is located in Svartsengi, near Grindavik, Iceland. The process was originally developed by a small CRI team in Reykjavik, and has undergone several iterations to arrive at the present state of technology and functionality. Taking the process from pilot scale to industrial scale was not trivial. Several difficulties encountered along the way were resolved to arrive at the current robust version of the technology. The high purity renewable methanol currently produced is sold as gasoline additive, similar to ethanol in the USA. Perhaps the most consequential lesson learned from this enterprise is that producing methanol from CO2 need not be as expensive as most experts estimated; the production cost of the ‘green methanol’ produced at the George Olah plant is only approximately twice that of natural gas derived methanol. A second interesting lesson involves the optimal process configuration: There exist two viable catalytic routes to convert CO2 to methanol. The most familiar option is to first reduce CO2 to CO through the RWGS reaction and then reduce CO with H2 to methanol in a second step or reactor. The CRI process instead implements the direct hydrogenation of CO2 with H2 over a mixed metal oxide catalyst. The presentation will include a brief history of the R&D and early development of the process, followed by a discussion of selected process features. Currently two world-wide implementation opportunities are actively pursued, namely the transformation of stranded H2 into a liquid commodity and a combined CCU and energy storage option for intermittent renewables. The presentation will conclude with a motivation for the ongoing research addressing the main barriers to bringing renewable CO2-derived methanol even closer to becoming cost competitive with refinery CH4-derived methanol.
Biomass as Fuel and Feedstock for Reduction of Carbon Emissions

(Georgia Institute of Technology, 2018-10-17) Belmont, Erica

Biomass holds great promise as a fuel or feedstock for carbon-neutral or even carbon-negative processes, including power, heat and chemical production. This talk discusses pathways for biomass utilization as a fuel or chemical feedstock, various challenges of utilization, and a few avenues of conversion that are currently under investigation in the speaker's laboratory and elsewhere. Finally, a perspective of future biomass utilization and research is discussed.
Electrokinetic Control of Interfacial Instabilities

(Georgia Institute of Technology, 2018-10-10) Bazant, Martin Z.

This talk will describe three examples of interfacial patterns – viscous fingers, deionization shocks, and metal dendrites – whose stability can be controlled by electrokinetic phenomena in charged porous media, as evidenced by both theory and experiments. Potential applications include electrically enhanced oil recovery, water desalination and purification by shock electrodialysis, and energy storage with rechargeable metal batteries.
Computational Design of Organic Photocatalysis

(Georgia Institute of Technology, 2018-10-03) Musgrave, Charles

Inorganic catalysts have been workhorses in many important industrial processes while many biological systems, such as photosynthesis, rely on organic catalysts. In this talk I will discuss the use of computational chemistry to examine organic catalysts and photocatalysts for visible light activated atom transfer radical polymerization (ATRP) and CO₂ reduction into fuels. In both cases, dearomatization of the catalysts leads to powerful reducing agents capable of challenging reductions either by electron transfers or hydride transfers. Using various substituents the thermodynamic and kinetic properties of these catalysts can be optimized for various reductions to make them fast, yet energy efficient. Our ATRP photocatalyst designs were synthesized and characterized for their efficacy, which confirmed that the best designs effectively photocatalyze polymerizations by ATRP using visible light and result in polymers and block copolymers with no metal contamination and properties that rival the best materials catalyzed with optimized, but expensive metal catalysts.
Gaussian Processes for Hybridizing Analytical & Data-Driven Decision-Making

(Georgia Institute of Technology, 2018-09-26) Misener, Ruth

Surrogate models are widely appreciated in chemical engineering. The typical setting focuses on expensive-to-evaluate, possibly uncertain functions. Resources are typically limited, so effective decision-making requires data-efficient learning. The data science and statistical machine learning communities typically focus on models learned solely from observed data. But chemical engineering applications may also require explicit, parametric models, e.g. modeling known process constraints, operations constraints, and cost objectives. So work has integrated semi-algebraic functions with those learned from data or developed semi-physical modeling techniques. We consider three new probabilistic modeling applications and extend methodologies to meet these hybrid situations: Design of experiments for model discrimination. We bridge the gap between classical, analytical methods and Monte Carlo-based approaches. Classical methods may have difficulty managing nonanalytical model functions and data-driven Monte Carlo approaches come at a high computational cost. We replace the original, parametric models with probabilistic, non-parametric Gaussian process surrogates learned from model evaluations. The surrogates are flexible regression tools that extend classical analytical results to non-analytical models, while providing us with model prediction confidence bounds and avoiding the computational complexity of Monte-Carlo approaches. Multi-objective optimization. We make novel extensions to Bayesian multi-objective optimization in the case of one analytical objective function and one black-box, i.e. simulation-based, objective function. The resulting method has been applied to a bone neotissue application and a more general test suite. Scheduling plant operations under uncertainty. For processes with equipment degradation, we use Gaussian processes to approximate large-scale, mixed-integer optimization problems. We close by offering a broad outlook on applying probabilistic surrogate models to chemical engineering.
The Moral and Ethical Imperatives to Achieve Health Equity

(Georgia Institute of Technology, 2018-09-19) Montgomery Rice, Valerie

As partisan politics becomes more and more entrenched in our society and continue to creep into the policy decisions that impact the everyday lives of individuals, the fight for health equity is becoming an increasingly moral one. This lecture evaluates the three main arguments for advancing health equity for all: the national security argument, the economic argument, and the moral argument. It will underscore the notion that while all three should have a place in societal discourse, it is the moral argument that should strike the most compelling chord. Key to this analysis is recognition of the alarming statistics that highlight the health disparities that many minority groups face in spite of the numerous resources that we have to offer as a country. This lecture concludes with a call to action, to champion the advancement of health equity, that should be heeded by all leaders and concerned citizens, as there are not only the moral and ethical imperatives compelling such, but also because it is inherently the American thing to do.