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Development of engineered living material platforms for diverse applications in human and planetary health
No full textDevelopments over the past few decades in metabolic engineering and synthetic biology hold great promise for fueling a robust bioeconomy, in which microbial biomanufacturing platforms can be utilized to produce an array of industrial and pharmaceutically important compounds at scale to meet growing demands in a manner that is both environmentally and economically sustainable. Despite this great potential, commercial translation of many research breakthroughs in this space is limited owing to the range of unique challenges hindering outside-the-lab deployment of biology. In response to this challenge, recent advances have emerged in which engineered microbes are coupled with polymeric encapsulation to yield Engineered Living Materials (ELM’s) that can promote cellular metabolic function while augmenting stress resilience, culture stability, and coculture compatibility. Even with these achievements, several limitations persist which prevent widespread deployment of ELMs. In particular, a need remains for platforms with long-term room temperature shelf stability, as well as cold-chain independent production of large proteins. Additionally, ELMs for bioproduction of compounds requiring more than a few enzymatic steps has yet to be established, greatly limiting scope of applicable products. Beyond applications in distributed biomanufacturing, ELMs represent a promising opportunity to create long-term implants for sustained therapeutic manufacturing within the gut microbiome. However, platforms capable of this function have yet to be realized. In order to address ongoing limitations in ELM deployment, this work presents four case studies demonstrating notable progress towards creation of field-deployable ELMs for modular, distributed biomanufacturing as well as dynamic therapeutic delivery within the microbiome. In Chapter 2, we focus on tool development for enhancing ELM deployability in remote settings through development of an optimized procedure for preservation and storage, showcasing room temperature shelf life of yeast-based ELMs for at least one year. Chapters 3 and 4 accentuate expansion of product classes applicable for ELM biomanufacturing, demonstrating cold-chain independent production of recombinant proteins up to 150 kDa as well as application of synthetic consortia for stable, de novo production of biosynthetically complex phenylpropenes, respectively. Chapter 5 demonstrates a proof-of-concept platform for closed-loop treatment of inflammatory disorders within the human GI tract, in which probiotic-laden ELMs are developed which secrete anti-inflammatory therapeutics in response to medically relevant concentrations of disease biomarkers, demonstrating safety and efficacy in vitro. Taken together, this work demonstrates strong progress toward development of field-deployable ELM platforms for diverse outside-the-lab applications spanning distributed biomanufacturing and gut microbiome therapeutic delivery.Chemical Engineerin
Algorithmic spatiality of Web3 : news cartography, data sovereignty, and wallet software
No full textThis project embarks on a spatial inquiry into Web3. Often hailed as the next iteration of the internet, Web3 is more than a facelift; it’s a calculated unveil that prompts us to re-examine Web2’s participatory past. Importantly, Web3’s algorithmic architecture both expands the web’s horizons and reflexively delineates its own perceptual identity. As it rises alongside digital platforms’ hegemony, we must scrutinize the territories it foregrounds — the very “wheres”— and the underlying “whys” that sculpt its distinct vantage for vested agendas.
Drawing insights from media studies, critical data studies, and STS, this project focuses on influential powers sculpting the interplay between corporate developers and the Web3 landscape. The theoretical framework is primarily organized around the concepts of news cartography, architects’ gaze, and software performativity.
Methodologically, this tripartite study leans on multiple ethnographic works to go beyond just studying tech structures, capturing both material and discursive forces that mold them. My empirical focus is grounded in specialist journalistic publications (in chapter 1), ethnographic observations, and aggregated data of sites (in chapters 2 and 3). Each chapter underscores its rationale for data collection, yet aliging with the ethos of infrastructure ethnography.
My research pivots on the argument that Web3 gives rise to “algorithmic spatiality.” It extends beyond software’s materiality, echoing geographers’ assertions that (digital) space is programmed, assembled, and arranged. Thus, I view Web3 not just as a deliberate construct, but also as a dialogical practice of shaping and organizing its very essence. Influenced by Massey’s (1999) portrayal of power as spatial-relational dynamics, I employ “power-geometries” as a foundational lens to discern the varied influences of Web3 on sociality. This juxtaposes with the pervasive power of existing digital platforms, often termed the Web2 status quo, awaiting transition.
For new media research, approaching Web3 with an algorithmic and spatial lens invites us to see sociality as a dynamic reshaping, subtly directed by coded practices, often obscuring their corporate genesis. I argue that to truly fathom our unfolding digital landscape, it’s imperative to closely scrutinize the pivotal roles of key actors. Especially, the corporate-scripted agents, in all their forms, actively molding these emerging topographies.Journalism and Medi
Controls on surface-water connectivity in lowland river-floodplain systems
Full text linkRiver floodplains are diverse ecosystems that provide important services such as nutrient retention and carbon storage, while also providing flood attenuation and regulating sediment transport. These services depend on sufficient transport of water and sediment to and through floodplains, not only during extreme flood events but also during moderate discharges. Such transport through floodplains depends in part on river bank topography that allows flow to move laterally across the riverbank, even when river stage is less than bankfull. However, many rivers and floodplains in the world have been disconnected hydrologically for various reasons, such as flood control and improved river navigation, through construction of artificial levees and other structures. In this dissertation, we study how complex floodplain and river bank topography promotes hydrologic connectivity over the range of discharges experienced in a river system in its natural state, using the lower Trinity River in Texas, USA as a natural laboratory.
In the first study, we measured flow depths and velocities through several deep floodplain channels that connect the Trinity River and its floodplain, during a storm event that produced 75 cm of precipitation directly on the floodplain. We developed a high-resolution numerical model to study how flow velocities and residence times in the floodplain are affected by both bank line variability and combined pluvial-fluvial flooding. Our results show how quickly flow paths, flow directions, and residence times in floodplains can change under rapidly changing hydrologic conditions in a river-floodplain system with complex topography.
In the second study, we expanded our study area of the Trinity River to encompass the entire backwater transition upstream of the coast (65 river kilometers). Through measurements of river discharge and numerical modeling, we show that flow into the floodplain occurs at many locations along the reach and is dependent upon bank line variability. On the other hand, return flow from the floodplain to the river occurs only at a few locations, always just upstream of bluffs along the river, which represent constriction points in the floodplain that direct water back to the river. Furthermore, water (and solute) residence times in the floodplain are strongly dependent on the location where the water first entered the floodplain, and residence times can be orders of magnitude longer for flows that enter the floodplain far upstream of those constriction points.
In the third and final study, we developed an idealized river-floodplain model based on the geometry of the Trinity River in the normal-flow reach. We evaluated the combined influence of floodplain storage capacity and river-floodplain connectivity on flood attenuation, and how that influence changes as flood magnitude increases. We show that there are specific discharge thresholds above which flood attenuation transitions from connectivity-limited to storage-limited. More connectivity and bank channelization allows for floodplain inundation at lower discharges, but also fills the floodplain faster and can reduce peak attenuation for larger floods. Each of these studies gives insight on which topographic features of river-floodplain systems control which processes. Understanding both quantitatively and qualitatively how lateral flow exchange, residence times, and inundation volume in floodplains are modulated by floodplain topography, specifically bank line channelization and floodplain width variability, is of great importance to successful management of river systems and future restoration efforts.Civil, Architectural, and Environmental Engineerin
Robust control of photolithography processes
Full text linkPhotolithography processes form the heart of semiconductor manufacturing. The precision with which these processes can be performed fundamentally dictates the limits of how densely transistors and other chip features can be constructed. One of the most important factors in the successful manufacturing of a functioning chip is the control of so-called overlay errors – that is, control of the misalignments between measurement markers on neighboring pattern layers. This thesis will introduce methods for improving the control of overlay errors, while also increasing throughput of photolithography processes. The industrial standard for control of overlay errors is the so-called run-to-run (R2R) control strategy. At the foundation of this strategy lies the assumption that stochastic terms in the underlying overlay models are normal, independent, and identically distributed (NIID). However, since overlay errors occupy the nanometer or even sub-nanometer scale, quantum effects begin to take hold, and the central limit theorem breaks down, meaning that the resulting distributions can significantly deviate from Gaussian forms. Moreover, one can observe from fab data that the distributions of these residuals have both spatial and temporal interdependences. Therefore, the assumption of NIID nature of stochastic terms does not hold, and robust control methods, which are agnostic to the distributions and spatial and temporal structuring of uncertain terms, should be used. In addition, both the R2R control strategy and recently developed robust L² control strategy seek to minimize a sum of squared overlay errors observed across a pattern layer. However, in the production of electrical circuits, overlay errors in even one measurement marker can lead to a non-functional circuit, meaning the die or entire wafer may need to be scrapped. Therefore, it is the maximum observed overlay error, not the commonly utilized sum of squared overlay errors, which determines the yield of a process, and hence is the very quantity that should be optimized. Therefore, this doctoral thesis describes a novel robust L∞ norm-based control strategy which seeks to minimize the largest overlay error across a pattern layer, subjected to the worst-case scenario of stochastic parameters in the underlying overlay model. The newly proposed approach for robust control of maximal overlay errors was evaluated using models and data obtained from a major 300mm wafer fabrication facility (fab) was compared to the traditional run-to-run (R2R) control strategy, as well as the recently introduced robust L² norm-based control strategy. The robust control approach proposed in this thesis consistently and often dramatically outperformed those benchmark approaches across all investigated metrics. This doctoral research recognizes that the performance of microelectronic devices is not only limited by the alignment between consecutive pattern layers, known as overlay errors, but is also greatly impacted by the alignments between non-neighboring pattern layers, known as stack-up overlay errors. To that end, this doctoral thesis expands upon the robust L∞ norm-based control strategy to incorporate the ability to factor in multilayer considerations weighted by their relative importance. Models and data from a major 300 mm semiconductor fab are used to evaluate the newly proposed approach to controlling overlay and stack-up overlay errors and compare its performance to that of the industrial-standard R2R controller. Finally, advances in control of overlay errors were utilized to address the question of optimal overlay inspection policies. Inspection of a pattern layer is a significant part of the underlying process cycle time and the time required to obtain measurements of overlay errors in a pattern layer is directly dependent on the number of measurement markers used. Larger number of overlay measurement markers implies longer inspection times and vice versa. Consequently, decreasing the number of measurement markers used for process control decreases the cycle time and increases process throughput. However, at the same time, decreasing the number of measurement markers used to inform the control process, decreases the quality of estimation of underlying process parameters and prediction of inherent process biases, leading to deteriorated performance of the control system. The interaction between the reduction of measurement times and consequent cycle times versus deterioration of the resulting overlay control process is not well understood. Considering this, this doctoral thesis introduces a methodology to formally investigate the effects of reducing the number of measurement markers used to inform the optimal control command of the newly introduced robust L∞ norm-based overlay control strategy. Performance of the control process based on a set of measurement markers is considered as the metric describing how good or how bad that specific set of markers is. Based on that, the best-performing selections of measurement markers used for each proportion of measurement markers that are to be kept are found using a Genetic Algorithm. Thusly determined selections of measurement markers used in conjunction with the robust L∞ norm-based control strategy are compared with the results obtained using the industrial standard R2R overlay control strategy, which inherently uses all measurement markers, all the time. Lastly, a case study is performed in which an objective function encompassing benefits of producing good quality products and quality losses, which will grow as one measures less and performs the process faster, is optimized in pursuit of an optimal tradeoff between the two.Mechanical Engineerin
Uncovering translational predictors of outcome in preclinical models of traumatic brain injury
Full text linkTraumatic brain injury (TBI) is a major public health concern affecting all age groups, genders, and ethnicities. TBI triggers a cascade of events that can last for years, leading to progressive neurodegeneration resulting in cognitive, physical, and emotional impairments. Clinical tools reveal the heterogeneity of TBI, with the extent of structural damage not reliably predicting neurological deficits or long-term prospects for recovery. To address this disconnect, I employed reproducible pediatric and adult rodent model of TBI to investigate early age-independent biological predictors of acute pathogenesis and long-term behavioral consequences. The controlled cortical impact (CCI) model was studied in genetically engineered “catchup” mice with fluorescent neutrophils (Chapters 2 and 3) and in the adult rat (Chapter 4). In three studies, I investigated surgical analgesia as a predictor of acute inflammation, neutrophil infiltration as a predictor of acute TBI pathogenesis and long-term behavioral outcomes, and CO2 reactivity as a predictor of long-term learning and memory deficits. Rodents were exposed to CCI or sham surgery at postnatal day 21 or at adulthood and were evaluated for acute pathogenesis and long-term functional outcomes. In the developing brain, acute inflammation was measured by quantifying neutrophils (mCherry+) and microglia (Iba-1+). Cell death (caspase-3) was used as an indicator of secondary pathogenesis in chapter 3. Analgesia did not alter the acute inflammatory response. However, systematic immuno-depletion of neutrophils significantly reduced infiltrating neutrophils, as well as reactive microglia in the injured brains of male mice, and cell death in the injured brains of female mice. Long-term behavioral deficits were assessed following injury to the developing brain using open field, novel object recognition, and Barnes maze, and to the adult brain using fear conditioning and extinction tests. Neutrophil depletion improved hippocampal-dependent behaviors in both novel object recognition and Barnes maze. In adults, CCI did not cause extinction deficits, and this was not predicted by CO2 reactivity. These studies highlight the role of neutrophils in the acute secondary damage and long-term behavioral changes that follow TBI, and indicate that pathology may vary across age and species. They offer valuable insights into managing TBIs in adults and children by identifying key predictors of recovery.Psycholog
Development of transition metal catalyzed amination of olefins and metal-free borylation of arenes
Full text linkMy research in the Hull group focuses on the development of transition metal catalyzed amination reaction and metal-free borylation of arenes. I have developed an Ir-catalyzed hydroamination of allylic amines, an Ir- and Rh-catalyzed regiodivergent hydroamination of homoallylic amines with anilines, and an Ir-catalyzed hydroamination of internal olefins with aryl and aliphatic amines. These methods allow for access to valuable diamines with a wide range of amine nucleophiles. Mechanistic studies suggest that the reactions with terminal olefins proceed via inner-sphere amination while the reaction with internal olefins undergoes outer-sphere amination. I also worked on the development of a Cu-catalyzed carboamination of dienes. This method is highly modular, efficient, and has excellent functional group tolerance. We were able to demonstrate that a myriad of alkyl bromides, dienes, and nucleophiles can be used in the reaction. I also developed a metal-free borylation of arenes. The reaction is selective for the functionalization at the more hindered positions. Initial mechanistic studies suggest a formation of a boryl radical.Chemistr
Observation and high-resolution simulation of convective activity in equatorial Africa
Full text linkEquatorial Africa, defined here as the African continent roughly between 10°S and 10°N, is dependent on rainfall to sustain the Congo rainforest, Lake Victoria, and rain-fed agriculture. Advancing our basic understanding of extreme rainfall and rainfall processes in this region is critical to safeguard vulnerable communities and to build resilient economic and cultural systems. This study aims to improve our understanding of the variability and observation of extreme rainfall and to physically diagnose future changes to rainfall through high-resolution simulations of the equatorial African climate. The dissertation is divided into three projects. In the first project, mesoscale convective systems (MCSs) are identified using IMERG precipitation estimates and their contribution to Congo Basin (10°E – 28°E) rainfall is quantified at the seasonal and diurnal scales. The seasonality of Congo Basin rainfall is determined by the seasonality of MCSs. These storms account for ≥80% of rainfall within 5° latitude of the equator year-round and contribute ≥70% of rainfall between 5°-10° outside of the winter season. MCSs also drive the diurnal cycle of Congo Basin rainfall, accounting for ≥80% of rainfall during the 15Z rainfall maximum and ≥90% during the secondary 04Z maximum. In the second project, a high-resolution simulation is used to evaluate the relationship between surface rainfall rates and storm updraft intensity as well as the ability of cloud-top brightness temperature (T[subscript b]) to serve as a proxy for surface rainfall in western and central equatorial Africa (6.5°E – 28°E). For grid points with rainfall in the 99.99th percentile, 64%-73% are associated with extreme T[subscript b] values (≥99.9th percentile) and strong updrafts (≥11 m/s), consistent with the typical rainfall - T[subscript b] - updraft relationship. However, 19%-25% of extreme rainfall grid points are associated with non-extreme T[subscript b] values (<90th percentile) and weaker updrafts (≥6 m/s). These convectively-weak storms occur exclusively over the saturated Atlantic coast and produce extreme rainfall without strong updrafts through enhanced warm-rain processes. In the third project, ensemble high-resolution simulations are used to project end-of-century rainfall changes in the Lake Victoria Basin (30°E – 36°E, 4°S – 0.5°N) under an IPCC SSP5-8.5 emission forcing and to diagnose underlying physical mechanisms. In the future, annual basin rainfall is projected to increase by 41.2% (+0.69 mm/day) although seasonal averages vary significantly. Differences in seasonal rainfall projections are influenced by a variety of mechanisms ranging from the local to large scale.Earth and Planetary Science
Fragile futures : examining the management of hope in environmental movements
Full text linkDuring a time of failing trust in institutions and civic life, all forms of activism are on the rise. The 2020 coronavirus pandemic both heightened awareness of environmental issues and climate change during lockdown and blunted it. It turns out, apocalypse fatigue can hinder movement progress. Therefore, how hope is managed becomes a devastatingly important question.
Keeping in mind the sociological dimensions that explain modern collective action, and the communication and technological dimensions that explain how social movements can spread their messages, I contend that environmental movements manage hope through unique rhetorical signatures designed to mobilize for better policies.
When enlisting a case study for this inquiry, I compared the messaging content of Fridays for Future, Just Stop Oil, and the Sunrise Movement. These comparisons elucidate how various social movements communicate their vision and goals through the lenses of nihilism, pessimism, and optimism. I conceptualize a scale of rhetorical signatures ranging from Apocalyptic Nihilism to Optimistic Futurism, noting that hope is demonstrably not merely the absence of pessimism or cynicism.
Overall, I found that all the groups expressed (1) optimism when describing (and romanticizing) their own past actions and (2) pragmatism when using data to inform their future actions. When reacting to current events, environmental movements are full of anger and pessimism and, on occasion, nihilism as a means of emoting through despair. However, platform norms often dictate the tone of messaging found on specific social media channels, with content on TikTok and Instagram being more optimistic than that found on Twitter or Facebook. Finally, each one of the case study groups represents a specific age cohort among young activists. I found that optimism tends to wane with age, at least as demonstrated by movement messaging. Simply put, managing hope with despair is a delicate balancing act for environmentalists when confronting the future. My study adds considerable nuance to the rhetorical dimensions involved in pursuit of that goal.Communication Studie
Infectious disease prevention and treatment : a case study of desiccation tolerance of Acinetobacter baumannii and antimicrobial nanobody development
Full text linkAntibiotic resistance is a growing crisis. The development of novel classes of antibiotics is not keeping pace with the spread of resistance in bacterial pathogens. To tackle this crisis, we will need to rely on both infection prevention and treatment. The thesis starts with a briefly review of the history of infectious disease, focusing on infection prevention and antibiotic discovery. It will then get to the two aspects with specific research projects in two sections. Section 1 is about desiccation tolerance of Acinetobacter baumannii. Desiccation tolerance has been implicated as an important characteristic that potentiates the spread of the bacterial pathogen A. baumannii on dry surfaces. In this section, we will explore several factors influencing desiccation survival of A. baumannii. At the macroscale level, we find that desiccation tolerance is influenced by cell density and growth phase. At the molecular level, we find that an increase in total cellular protein aggregates, which is often considered deleterious, correlates positively with the ability of A. baumannii to survive desiccation. We show that inducing protein aggregate formation prior to desiccation increases survival, and importantly, that proteins incorporated into cellular aggregates can retain activity. Our results suggest that protein aggregates may promote desiccation tolerance in A. baumannii through preserving and protecting proteins from damage during desiccation until rehydration occurs. In section 2, we will explore a type of large biologics, nanobodies, for their potential to have antimicrobial activity. we take two steps to develop the first antimicrobial nanobodies. The first step is to resurface a nanobody scaffold to carry positive charges. As gram-negative bacterial outer membranes are negatively charged, resurfaced nanobodies are attracted to and associated with bacterial outer membranes. Thus, positive charges anchor the nanobody molecules to the bacterial surface. Our second step is to screen the complementarity determining regions (CDRs) of a nanobody library for bacterial growth inhibition when the nanobody is anchored to the bacterial surface by a display platform. We recovered ~100 hits from the screening and selected two for further characterization. Adding the CDRs onto a resurfaced nanobody scaffold resulted in nanobodies with antimicrobial activity.Microbiolog
Computational approach to displacement damage metrics for semiconductor materials in neutron environments
Full text linkNeutron displacement damage in electronic devices provides challenges for operating in radiation environments. Providing adequate metrics for quantifying displacement damage is critical for operating in these extreme conditions. Previous metrics did not directly take into consideration the damage modes relevant to minority carrier devices in neutron environments and relied upon experimental calibration. Molecular dynamics (MD), binary-collision approximation codes (BCA), and defect migration models provide a methodology for capturing the relevant damage mode of degradation in minority carrier life-time. Legacy models did not take into consideration the short-term annealing from “thermal spikes” that originate during the initial primary knock-on atom (PKA) event. Furthermore, for semiconductor materials, only defects that increase the recombination rate are relevant to the degradation of the minority carrier life-time. Existing work focuses on individual components of the proposed methodology, such as molecular dynamics cascades within lattice materials for defect formation studies or the use of finite-difference/kinetic Monte Carlo (KMC) for defect chemistry. This work establishes a unified computational methodology that integrates molecular dynamics, binary-collision approximation, and defect migration models to address the limitations of legacy displacement damage models for neutron environments and to provide insight on the mechanisms that impact damage efficiencies for various neutron environments.Mechanical Engineerin