ACES: Association of Chemical Engineering Graduate Students

2023 Graduate Student Symposium

About the Event

The 16th Annual Graduate Student Symposium will be held September 21st, 2023 from 1:00 pm to 6:00 pm PST.

The Graduate Student Symposium (GSS) bridges the gap between industry and academia. The event is a daylong seminar held as a means for students to share their research with colleagues, faculty, and representatives from industry. It also serves as a forum in which students can practice their presentation skills to a highly interdisciplinary audience and gain valuable feedback from people both in and outside of academia. The event includes an industry keynote speaker, panel discussion, as well as student talks and posters to showcase the latest research in biotechnology, energy, materials engineering, and data science

For the past fifteen years, the GSS has become a vital forum for both graduate students and industry representatives. With over 100 graduate students, faculty, and industry participants this event provides a chance to learn about the innovative research conducted at the University of Washington, meet future research leaders, and help improve the quality of graduate education in the Chemical Engineering department.

Even though we would love to conduct the event fully in person, all invited speakers will be given the option to participate remotely through video conference. This is to reduce non-essential traveling and respect everyone’s comfort level with in-person gatherings.

Format and Schedule

The event will be held in person this year. All activities are listed in Pacific Daylight Time (PDT).

Location: NanoES Building – Room 181, 3946 W Stevens Way NE, Seattle, WA 98105

Agenda

1:00 – Opening Remarks
1:05 – Keynote Speaker:
- Dr. Jill Seebergh – Boeing
2:00 – Student Presentation Session I
2:45 – Break
3:00 – Student Poster Session I
3:40 – Industry Panel
- Jade Hudson – Blue Origin
- Kyle Diederichsen – Exponent
- Arushi Prakash – Apple
- Natalie Winblade Nairn – CDP, Newco
4:30 – Student Presentation Session II
5:15 – Student Poster Session II
5:50 – Closing Remarks

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Keynote Speaker:

Dr. Jill Seebergh

Jill Seebergh is a Boeing Principal Senior Technical Fellow in the Materials and ManufacturinTechnology organization. She leads development and implementation of coating materials and processes across all of Boeing’s business units, with a focus on high-rate production systems and sustainability. Current areas of interest include chromium-free conversion coatings and primers, durable exterior coating systems, anti-microbial surface treatments, anti-icing coatings, and films for drag reduction. She is the immediate past Chair of the Boeing Technical Fellowship and is a member of the Boeing Commercial Airplanes Sustainability Leadership Advisory Team and the Sustainability Technology Board.

Dr. Seebergh earned her Ph.D. in Chemical Engineering from the University of Washington (Seattle WA), where she serves as Boeing’s Executive Focal for the Chemical Engineering department and holds an appointment as an Affiliate Faculty. She is a member of the National Academies Condensed Matter and Materials Research Committee, the Editorial Review Board
for the Journal of Coatings Technology and Research, and the Advisory Board of the International Networking Forum on Aircraft and Aerospace Coatings. Significant recognitions include the CSIRO Gold Medal for Research Achievement, Society of Women Engineers Patent Recognition Awards, University of Washington Chemical Engineering Distinguished Alumni Award, Boeing Chairman’s Safety Award, and Boeing Technical Replication Award.

Cross-Disciplinary Panel

Jade Hudson, M.S. – Blue Origin

Jade Hudson is currently the Director of Production Engineering dedicated to Advanced Development Programs at Blue Origin. 

Jade has 30 years of aerospace experience managing multi-skill teams in manufacturing, process development, and process improvement projects. Her technical and leadership roles have included overseeing aerospace manufacturing operations, leading design/build integration teams, and directing new product development projects. Jade has also managed a variety of material technology teams, specializing in Chemicals, Metals, Composites, and Non-destructive Inspection, Assembly, and most recently Production Engineering. Jade is passionate about people development and has led many skill team activities. She has demonstrated the ability to lead in challenging environments while being driven to achieve results.

Jade holds a bachelor’s degree in Chemical Engineering and a master’s degree in Environmental Engineering, both from the University of Washington.

Outside work, Jade enjoys cooking, hiking and gardening. Her daughter Kaylee is current an engineering student at UW. Her husband recently retired from the Boeing Company and has been active in many environmental preservation activities in the community.

Kyle Diederichsen, Ph.D. – Exponent

Kyle Diederichsen is currently an Associate in the Polymer Science and Materials Chemistry department at Exponent.

Dr. Diederichsen specializes in the design of complex material systems including the relationships between molecular structure and bulk physical properties. He is a trained chemical engineer, skilled in polymer synthesis and characterization, as well as formulation of polyelectrolyte solutions in aqueous and nonaqueous systems. He has extensive experience in battery technology and electrochemistry, including for example, testing of polymer systems in lithium battery cells, engineering of flow battery systems, and fundamental mechanistic analysis of redox reactions. Dr. Diederichsen applies his skills in chemistry, physics, and engineering to support clients in a wide variety of industries, including consumer electronics, construction and infrastructure, medical devices, and automotive.

Dr. Diederichsen holds a bachelor’s degree in Chemical Engineering from University of Colorado Boulder and a Ph.D. in Chemical Engineering from the University of California Berkeley.

Arushi Prakash, Ph.D. – Apple

Arushi Prakash is a Senior Machine Learning Scientist at Apple. Dr. Prakash previously served as an Applied Scientist at Amazon.

Dr. Prakash holds a bachelor’s degree in Chemical Engineering from Birla Institute of Technology & Science and a Ph.D. in Chemical Engineering from the University of Washington.

Natalie Winblade Nairn, Ph.D. – Vice President, CDP Therapeutics; Newco Co-Founder

Natalie Windblade Nairn is currently the Vice President of CDP Therapeutics at Blaze Bioscience.

Natalie Winblade Nairn has had an extensive career in the biotechnology industry. Natalie began their career in 2000 as a Scientist at CombiMatrix. In 2002, they moved to Corixa as a Scientist. In 2005, they took on the role of Director at ALLOZYNE, where they lead formulation chemist with increasing responsibilities developing a protein conjugate therapeutic platform. In 2013, they assumed the role of Principal at Nairn Biotechnology Consulting, as well as Vice President, CDP Therapeutics at Blaze Bioscience, where they led the Blaze Cystine-Dense miniProtein (CDP) therapeutic program in strategy and pipeline creation for oncology and immunology indications and created tozuleristide Drug Product formulation. In 2022, they became Co-Founder, CSO, and CEO at Newco.

Natalie Winblade Nairn earned a Ph.D. in Chemical Engineering from Caltech and a B.S. in Chemical Engineering from the University of Washington.

Oral Presentations

Hinako Kawabe, Marchand Lab

DNA is the instruction manual of life as we know it, using just four nucleic acids (A, T, G, C) to direct complex biochemistry. Humans have learned to manipulate these four letters to advance biotechnology including therapeutics, diagnostics, and genetically engineered organisms capable of making valuable chemicals. While Nature has limited itself to four building blocks, there are now efforts to move beyond these confines. Xenonucleic acids (XNAs) are chemically synthesized nucleic acid analogs that expand the accessible nucleic acid alphabet, pushing the limits of biotechnologies and life itself. The chemical diversity of XNAs has the potential to establish a new generation of biotechnologies that DNA on its own could not accomplish. However, the infrastructures built for DNA do not exist on the same scale as those for XNAs, and many of the tools required to work with XNAs are expensive, require extensive expertise, or do not exist. In this work, we demonstrate how to sequence DNA containing 12 nucleobases (A, T, G, C, and B, S, P, Z, X, K, J, V) using nanopore sequencing. DNA libraries are used to build models to decode the XNAs, and we provide a publicly accessible package that includes a processing pipeline all the way from the raw data to the basecall. The strategies we’ve utilized in this work are versatile and cost-efficient, lowering the barrier of entry for the larger synthetic biology community and bringing xenogenetics closer to robust integration in biotechnology.

Nels Schimek, Nance Lab

Multiple particle tracking (MPT) is a microscopy technique capable of simultaneously tracking hundreds to thousands of nanoparticles in a biological sample and has been used extensively in recent years to characterize the brain extracellular space. Machine learning techniques have been applied to MPT datasets in order to predict the diffusion mode of nanoparticle trajectories as well as more complex biological variables. In this study, we develop a machine learning pipeline and evaluate its effectiveness across three different MPT datasets: varying age, varying region, and a non-treated versus treated condition. We utilize unsupervised learning, supervised classification, and feature importance calculations to determine which datasets can be predicted with the highest accuracy, and to glean biological insights from each dataset. Finally, we determine the effect that the diffusion mode of a trajectory has on training a supervised machine learning model.

Brendan Butler, Nance Lab

Energy depletion, driven by mitochondrial abnormality, is a pathological outcome and precursor in a variety of neurological injuries and disease states, but cellular and extracellular outcomes and interactions are yet to be studied in a system that recapitulates in vivo conditions. Organotypic whole-hemisphere (OWH) slice models preserve native cytoarchitecture and parenchymal architecture and are robust platforms for spatiotemporally probing stimuli response regionally and across biological scale (organelle to extracellular matrix). Prior work in our lab established an OWH slice model of hypoxia-ischemia to characterize the cellular and extracellular responses to oxygen-glucose deprivation (OGD). In this work, we develop an OWH slice model of mitochondrial abnormality, a hallmark of neurodegeneration and long-term outcome of hypoxia-ischemia. We expose slices to low-grade doses of mitochondrial toxin rotenone (ROT) to disrupt mitochondrial function. We incorporate live- and fixed-slice imaging, nanoparticle tracking technology, and molecular biology techniques to monitor the slice response acutely and over 4 days, in two distinct brain regions. Establishing a slice model of mitochondrial abnormality enables a screening platform for energy regeneration therapeutics and a clinically-relevant opportunity to study the interactions between hypoxia-ischemia and mitochondrial abnormalities.

Nada Naser, Baneyx Lab

High information content biomacromolecules, such as peptides and proteins, are desirable building blocks for the synthesis of self-assembled, hierarchical, and hybrid nanomaterials due to their monodispersity, programmability, and functional diversity. They have proven valuable to expanding the range of compositions, morphologies, and crystallographies observed in natural biomineralization processes while retaining the ability to mineralize inorganic materials under mild aqueous conditions. Here, we combine the mineralization properties of solid-binding peptides (SBPs) with the tunable thermoresponsive phase separation behavior of elastin-like polypeptides (ELPs) to control the formation of Au and SiO 2 -based nanomaterials. We use a gold-binding ELP to synthesize monodisperse gold nanospheres, cap their growth to 10 nm in diameter, and mediate their reversible aggregation into plasmonically-coupled 100 nm clusters via temperature increase. With a SiO 2 -binding ELP, we template the synthesis of monodisperse 60-nm silica nanoparticles through self-assembled micelles that display SBP corona above the ELP transition temperature. We also show that, beyond temperature, solution conditions profoundly affect the polydispersity and size of the mineralized products. Our work provides a platform to synthesize stimuli responsive functional nanomaterials that possess unique optical and catalytic properties with applications in energy storage and conversion, drug delivery, cancer therapy, and others.

Ryan Francis, DeForest Lab

Ryan Gharios, DeForest Lab

Poster Presentations

Seancarlos Gonzalez, Bergsman Lab

Vapor phase infiltration (VPI) is a variation of atomic layer deposition (ALD) which takes advantage of long hold times to allow reactants to diffuse into a porous substrate. Recently, VPI has been used for the post-synthesis modification of polymers by infusing metal oxides into the polymer matrix to improve crucial membrane properties such as solvent stability and separation performance. However, characterizing polymers modified by infiltration, such as the depth and concentration of infiltrated reactants, can be challenging. Ellipsometry can be used to characterize surface thickness, but it cannot determine the depth to which the infiltration is successful or the elemental composition as a function of thickness. Cross-sectional SEM can determine elemental composition, but its resolution for certain elements is limited to only very thick layers. XPS can depth profile to determine elemental composition, but this technique is extraordinarily time and cost intensive. In this work, we examine the use of glow-discharge optical emission spectroscopy (GD-OES) to characterize polymer membranes treated by infiltration. This technique uses plasma to sputter a crater into a sample, and then measure the atomic emissions of the sputtered elements. Signals are produced for each element as a function of time, which can yield quantitative data of elemental composition as a function of depth when calibrated to a standard. We demonstrate the use of GD-OES to explore the effectiveness of VPI on thin polymers by determining the depth to which infiltration was successful and comparing the elemental compositions of polymers infiltrated under different conditions.

Renyu Zheng, Chen Lab

Self-assembly is a process of crucial importance in creating hierarchical biomaterials in living organisms. However, understanding the forces and dynamics that drive the process to control material synthesis is challenging due to the various non-covalent forces involved, including ionic effects, hydrophobic effects, hydrogen bonds, and backbone chirality. Therefore, developing sequence-defined synthetic polymers with simplified molecular interactions to mimic biomolecular self-assembly becomes a good approach to understanding the self-assembly mechanism and controlling the process. Peptoid (N-substituted glycine) is a peptidomimetic molecule that exhibits high tunability in molecular interactions through side-chain chemistry and provides a simplified system with no backbone chirality and backbone hydrogen bonds for mechanistic understanding. Here we report a short-sequence amphiphilic peptoid with an anisotropic hydrophobic domain to self-assemble into flexible lipid-like bilayers. The bilayer 2D structure can be further controlled to fold and twist into 3D helical structures. Time-dependent characterization demonstrates the formation of nanosheets through helical fibers as early-stage intermediates and polymeric transition from nanosheets to helices upon the annealing process. The short 6-mer peptoid also allows the self-assembly process to be computationally tractable at the atomistic level. We combine the molecular dynamics simulation and experimental results to understand the molecular packing and driving forces for the helix-sheet transition. In addition, we also designed other sequences and experimental conditions to control the self-assembly morphologies. We anticipate our system will provide a facile platform to translate peptoid sequences and chemistries into molecular interactions, self-assembly dynamics, and morphologies.

Sydney Floryanzia, Nance Lab

Oxygen-glucose deprivation (OGD) is used extensively ex vivo to model in vivo ischemic conditions. OGD exposure to brain cells or tissues results in inflammation, cell death, and other hallmarks of pathology in the brain. OGD can be performed to evaluate the therapeutic efficacy of drugs or drug delivery systems and cell-specific response to OGD. Previously, we have applied OGD to cultured brain slices, yet these studies do not elucidate individual cell contributions to the response to OGD. Additionally, our previous studies have assessed parenchymal cells and not cells associated with blood-brain barrier function. Brain slices also do not retain in vivo capillary blood flow conditions which impact cellular response. In this study, we investigate the effect of OGD on primary astrocytes and pericytes isolated from the developing rat brain in an exposure and time-dependent manner. We utilized 3 model systems: 2D mono-culture, 3D microfluidic monoculture, and a 3D microfluidic co-culture with flow. Cell death and morphology were assessed using MTT and confocal imaging. We demonstrated that pericytes and astrocytes respond differently to OGD, and their response is model dependent. We identified that OGD exposure and assessment time after OGD significantly impacted cell morphology and viability. Importantly, we identified that the 3D microfluidic co-culture model with flow showed the most “in-vivo” response to OGD. Our data establish the importance of modeling injury response in a physiologically relevant system. Ongoing studies use the 3D multi-cellular model with flow to investigate mechanisms of nanotherapeutic interaction at this interface, in response to stimuli.

Ruby Jin, Nance Lab

Preterm neonates are especially susceptible to inflammation and oxidative stress due to hypoxic-ischemic (HI) brain injury. As one of the leading causes of morbidity and mortality in neonates nationally and globally, HI brain injury triggers energy failure, overwhelms antioxidant defenses, provokes inflammatory responses, and disrupts cellular integrity in the neonatal brain. As a result, white matter damage and abnormalities in cortical maturation are frequently observed in infants born preterm. Preterm infants are also at increased risk of neurodevelopmental problems, along with complications of prematurity and their severe sequelae. Neuroprotective interventions currently used for infants with preterm brain injury include prenatal steroids, magnesium sulfate, delayed cord clamping and postnatal caffeine, but none are globally neuroprotective. Effective therapeutic interventions that can achieve neuroprotection across multiple brain regions and target different mechanistic pathways of injury are therefore critically needed for this population.

Preliminary data in the HI ferret model of preterm brain injury showed extensive white matter injury and behavioral changes consistent with those seen in premature infants. Therefore, the ferret model appears to provide a clinically-relevant model of preterm brain injury. We utilized an organotypic whole hemisphere (OWH) ex vivo brain slice model, which retains multicellular interaction and tissue architecture, to analyze regional responses to both HI brain injury and responses to multiple neurotherapeutic reagents alone and in combination.

Nuo Xu, Nance Lab

Therapeutic development for pediatric use has advanced in the last few decades, yet the off-label use of adult medications in pediatrics remains a significant clinical problem. The development of therapeutics for pediatrics is challenged by the lack of pharmacokinetic (PK) data in the pediatric population, a gap in data even more significant for neonates. Additionally, the role of nanomedicine, which can improve PK profiles of many therapeutics, has prominently focused on applications in adults. The US and European based pediatric formulation initiatives to investigate nanomedicine formulations for pediatric use necessitates greater understanding and greater data availability of nanomedicines in the pediatric population. In this study, we focused on poly(lactic-co-glycolic acid)-poly(ethylene glycol) (PLGA-PEG) nanoparticles, which play an important role in drug delivery and have been widely studied in adults, to quantify the PK profiles and biodistribution of polymeric nanoparticles in neonatal rats [1]. Meanwhile, we investigated the effect of surfactant on the PK, biodistribution, and cellular association of PLGA-PEG nanoparticles in the term-equivalent brain. Our main results provide fundamental PK data in the term-equivalent rat. These data can be used to build physiologically based pharmacokinetic (PBPK) or similar models to support first-in-human predictions in neonates. Our findings also provide guidance for design and delivery of therapeutic polymeric nanoparticles in neonatal populations.

Huat Chiang, Pozzo Lab

Artificial Intelligence (AI) driven closed systems, which are usually composed of an AI agent to plan experiments, robots to perform experiments, and a high throughput characterization method to evaluate experiments have recently shown to be successful in optimizing structural properties of colloidal nanoparticles. However, a limitation of these kinds of systems is that they have only been demonstrated in constrained design spaces which is where the targeted structure has a high probability of being formed. In addition, while many samples are being synthesized and characterized, minimal amounts of information on the relationship between experimental design parameters and the structure of the nanoparticles is obtained from the experiment. To solve these problems, we introduce a novel AI driven closed system and test it with a model system of silver nanoparticle synthesis with the objective of synthesizing nanoplates. Our method first searches the design space for silver nanoplates based on UV-Vis spectroscopy curves, which are autonomously classified into “plates” or “not plates” using a distance metric. This information is then used to train a gaussian process classifier which then iteratively suggests experimental parameters for a new batch of samples that are likely to be nanoplates. After the chemical design space is constrained to contain mostly nanoplates, we then use small angle x-ray scattering characterization to obtain size/shape parameters. This information is used to train a gaussian process regressor, from which we can extract design rules such as the effect of the composition of the reagents on the obtained size/shape parameters.

Baneyx Research Group

Nada Naser, Yifeng Cai, William Wixson, Zhixing Lin

Research in the Baneyx Lab lies at the interface of microbiology, nanotechnology, molecular engineering and materials science. We seek to understand the rules that underpin the interactions of solid-binding peptides with inorganic and synthetic interfaces. We genetically install peptides of different functionalities and binding affinities within the framework of protein scaffolds to fabricate stimuli-responsive hybrid systems and self-organizing living materials. Applications for hybrid materials range from biomedicine and bionanoelectronics to biomineralization and catalysis. We are a lead lab in CSSAS, the Center for the Science of Synthesis Across Scales, an Energy Frontier Research Center (EFRC) directed by Prof. Baneyx that brings together researchers from six universities and the Pacific Northwest National Laboratory.

Ma Research Group

Braden Griebel, Erick Tieu, Braden Carroll

The rise of drug-resistant pathogens poses a major global health challenge. In the US alone, 2 million people are infected with drug-resistant bacteria each year, leading to 23,000 deaths and several billion dollars in healthcare costs. To devise novel therapies that are safe, potent, and difficult for microbes to evade, our lab studies the effects of drug treatment on infection. Our research premise is that drugs elicit molecular changes in both host and pathogen, and these responses are predictive of future outcomes. By measuring and analyzing patterns in host and pathogen molecular responses to different drugs, we seek to identify key drivers of treatment outcomes. These insights will reveal novel biology and inform new strategies to identify candidate host-directed therapies and optimize efficacy and toxicity of multidrug regimens.

Marchand Research Group

Hinako Kawabe, Nick Kaplan

Nucleic acids form the blueprint of life as we know it, forming DNA and encoding the 20 standard amino acids. The ability to manipulate nucleic acids has also been integral to the development of biotechnologies such as vaccines and biosensors. Inspired by the strides DNA has allowed in the biotechnology space, nucleic acid research has begun to push beyond the confines of Nature itself. Xenonucleic acids (XNAs) are chemically synthesized, nucleic acid analogs that allow for biochemical diversity with the potential to transform biotechnologies as we know it. However, the tools to work with XNAs very much lag behind the tools available for standard bases. The goal of the Marchand Lab is the robust integration of these XNAs in synthetic biology and beyond. This poster highlights the biotechnologies that can be improved by the integration of XNAs, including genetic code expansion and XNAzyme formation. It will also outline the challenges that must be overcome, and the types of tools the Marchand Lab has developed to work with non-standard bases including nanopore sequencing of XNAs.

Rorrer Research Group

Julia Hancock, Maddie Soltani

The accumulation of waste plastics in the environment and the contribution of plastics manufacturing to global warming have necessitated the development of a circular economy for synthetic polymers. In order to properly confront these challenges, new plastics recycling solutions are needed. Heterogeneous catalytic chemical upcycling of waste plastics is one such technology, as it enables the conversion of waste plastics into molecular intermediates that allow for remanufacture into new products. However, current methods of hydrocracking and waste valorization often fail to achieve economic viability due to their use of expensive catalysts and reagents. For instance, the use of molecular hydrogen in many depolymerization reactions adds safety, transportation, and financial limitations to widespread technological implementation. Additional complications arise from the use of nonrenewable and expensive rare earth metals in these processes. In the Rorrer lab, we strive to develop novel reaction materials, conditions, and techniques that push the field of chemical recycling forward.

Z Lab

Ayça Ersoy, Rishabh Sanghavi

The Z Lab leverages a unique computational tool set to investigate the self-assembly, transport, and effective properties of colloidal materials, particularly those driven by or responsive to electromagnetic fields. Broadly, we are interested in (1) developing new computational methods that are both fast and accurate, (2) elucidating fundamental relationships among electromagnetic fields, colloid structure, colloid dynamics, and effective properties, and (3) applying this fundamental understanding for application-specific design of colloidal material technologies. Our specific interests include designing new optical metamaterials incorporated in optoelectronic devices, understanding field-driven transport of magnetic colloids within porous media for biomedical applications, and understanding charge transport in soft material electrolytes.