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Scalable fabrication and characterization techniques of nano-engineered stainless-steel surfaces for boiling heat transfer
No full textSubmission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01The student, Asif Ahmed, accepted the attached license on 2025-05-02 at 12:23.The student, Asif Ahmed, submitted this Thesis for approval on 2025-05-02 at 13:06.This Thesis was approved for publication on 2025-05-06 at 11:33.DSpace SAF Submission Ingestion Package generated from Vireo submission #22183 on 2025-10-19 at 19:55:42Stainless steel (SS) is commonly used in HVAC industry especially in heat exchangers because of high corrosion resistance and durability. In recent times, surface nano-engineering has become a popular way to achieve micro/ nano structured surfaces for boiling applications, as nano-structured surface exhibits higher roughness and increase surface area that ultimately leads to heat transfer coefficient (HTC) enhancement. In the past studies, researchers mainly focused on two other common materials- aluminum and copper, hierarchical surface development using different approaches. However, there’s hardly any literatures available that dealt with chemical etching of SS. In this thesis, a few novel chemical etching recipes have been introduced which is scalable, cost-effective and easy to apply on SS with effective surface roughness outcome and increased nucleation sites. This work represents a novel and scalable fabrication method of hierarchical network of micro- and nanoscale structures on SS304 surfaces by chemical etching and subsequent surface characterization via SEM, FIB, Confocal 3D microscopy, XPS, XRD and contact angle measurement. The maximum roughness was achieved 10μm after etching. In addition to surface characterization, pool boiling heat transfer performance was studied where the etched SS surface demonstrates a two-times increase in critical heat flux (CHF) at reduced superheat, primarily due to increased nucleation activity within optimally sized cavities formed during etching which underscores the potential for developing compact and efficient thermal systems. Additionally, brazed plate heat exchanger (BPHX) made of SS304 plates was etched using FeCl3 solutions and the post-etched micro-structured HX surface enabled up to 30% condensation HTC enhancement. It is evident that, nanostructures and cavities generated by chemical etching plays a vital role in improving boiling performance in heat exchangers
Mechanistic investigations into the origin of chemoselectivity a methylene (csp3) c-h oxidation in the presence of α-β unsaturated carbonyls and exploration of reaction scope
No full textSubmission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01The student, Marc Hartmann, accepted the attached license on 2025-05-07 at 22:41.The student, Marc Hartmann, submitted this Thesis for approval on 2025-05-07 at 22:57.This Thesis was approved for publication on 2025-05-08 at 17:59.DSpace SAF Submission Ingestion Package generated from Vireo submission #22263 on 2025-10-19 at 19:55:50α-β unsaturated carbonyls are a common structural motif in bioactive natural products and pharmaceuticals. Despite this, methods for (Csp3) C-H to C-O transformations in the presence of this oxidatively sensitive functionality are underexplored and limited exclusively to radical based methods that target the homolytically weak allyic C-H bonds. Recently, our group developed the first method for (Csp3) C-H in the presence of α-β unsaturated carbonyls enabling rapid access to metabolites and analogues of drugs and complex natural products. This thesis documents mechanistic studies designed to uncover the origin of chemoselectivity for strong bond (Csp3) C-H oxidation over epoxidation of the α-β unsaturated carbonyl π system. Through this process, it was discovered that our new Mn(PDP)/HFIP system has a different active oxidant compared to previous our Mn(PDP)/MeCN/ClAcOH system, which is largely responsible for the enhanced chemoselectivity. Additionally, the generality of our method was accessed on both simple and complex α-β unsaturated carbonyl containing compounds
The Catalyst: UIS Research Review, Issue 4
No full textThe Catalyst is a publication by the Research Society at UIS that highlights student research at the university. This issue includes Gretchen Sitki and Emma Konie and their research with Thomas Rothius, Exploration of nutrient removal from fresh water in Lake Springfield using floating treatment wetlands
Towards a theory of logistics urbanism: how the transport fix, racialized low-wage labor, and engagement with the state define Chicago’s role as the inland port city of North America
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo termsThe student, Jose Acosta-Cordova, accepted the attached license on 2025-06-24 at 23:43.The student, Jose Acosta-Cordova, submitted this Dissertation for approval on 2025-06-25 at 00:03.This Dissertation was approved for publication on 2025-07-16 at 14:06.DSpace SAF Submission Ingestion Package generated from Vireo submission #22367 on 2025-10-20 at 16:57:15The growth of the global logistics economy has profoundly reshaped urban regions, generating new forms of spatial organization, labor segmentation, and political struggle. This dissertation develops a theory of logistics urbanism through an in-depth case study of Chicago, the preeminent inland port city in North America. This study examines three central theoretical contributions: (1) the transport fix—the use of massive investments in transportation infrastructure to resolve spatial and temporal contradictions of capital accumulation; (2) the materialization of the space of flows—the physical inscription of global supply chains onto local urban space through warehouses, intermodal terminals, and distribution centers; and (3) the state as an arena of conflict—the contested role of state institutions in facilitating logistics development while simultaneously mediating its socio-environmental consequences. Chicago’s logistics boom has depended on a highly racialized, segmented, and precarious labor force. Drawing on data from the Integrated Public Use Microdata Series (IPUMS), this dissertation analyzes the racial stratification of low-wage labor across the transportation, distribution, and logistics (TDL) sectors, revealing how Black, Latino, and immigrant workers disproportionately occupy the most vulnerable positions in warehousing, trucking, and delivery. These patterns are situated within broader dynamics of racial capitalism that structure both the labor process and spatial inequalities inherent to logistics urbanism. Furthermore, this dissertation advances the literature by incorporating community-led forms of citizen science as a means of resistance within the state apparatus. The Chicago Truck Count Data Portal—a collaborative project led by environmental justice organizations, citywide nonprofits, and grassroots advocates—serves as a crucial case study of how communities of color leverage scientific practices to contest the environmental and health burdens imposed by logistics infrastructure. In the absence of comprehensive governmental monitoring of truck traffic and its associated air pollution, citizen science initiatives have produced empirical evidence that challenges state-sanctioned development narratives and demands regulatory accountability. Utilizing a mixed-methods approach—combining GIS spatial analysis, secondary data on labor and industry, participant observation, and semi-structured interviews—this dissertation illuminates how logistics urbanism is not simply a technocratic or economic phenomenon, but a deeply contested socio-political process. Ultimately, this work contributes to scholarly debates in urban political economy, logistics geographies, racial capitalism, and environmental justice, offering a framework for understanding how marginalized communities contest the uneven landscapes produced by the global logistics economy
Guiding the development of data-driven models to solve constitutive inverse problems in medical elasticity imaging
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo termsThe student, Will Newman, accepted the attached license on 2025-06-30 at 10:56.The student, Will Newman, submitted this Dissertation for approval on 2025-06-30 at 11:04.This Dissertation was approved for publication on 2025-07-01 at 10:49.DSpace SAF Submission Ingestion Package generated from Vireo submission #22384 on 2025-10-20 at 16:57:21Elasticity imaging is an approach similar to manual palpation that replaces fingertip sensing with images that describe mechanical contrast between tissues. Elasticity images provide physicians with diagnostic information regarding the state of disease in many soft tissues. However, 3D quantitative images of tissue material properties are required to connect tissue-level images to cellular mechanobiology. Those seeking quantitative images of material properties formulate medical elasticity imaging as a 3D constitutive inverse problem. Ideally, measurements of force and displacement would propagate into a complete set of stresses and strains at all points in the medium to invert the constitutive equation and estimate material properties in a volume. However, force can only be measured on the tissue surface, and displacement is typically measured in a 2D plane. How can we propagate sparse measurements of surface force and planar displacement into a set of stresses and strains that can uncover quantitative material properties of tissues? This thesis has spearheaded the development of an ultrasonic-based technique for elasticity imaging throughout a tissue volume using the autoprogressive (AutoP) method. AutoP combines object-specific measurements with finite-element analysis (FEA) to propagate sparse measurements into the stresses and strains needed to uncover constitutive behavior in the tissue volume. A machine learning framework learns spatially varying constitutive behavior from the stresses and strains and replaces the constitutive matrix within FEA. The goal is to provide AutoP with measurements that lead to a physically-consistent, data-driven solution that adequately captures the deformation of the material. In this dissertation, I examine the features that influence model development in AutoP. The focus is on the creation of efficient training strategies and measurement acquisition techniques that can generate a rich training environment. I developed new metrics that can monitor how well the measurements and training parameters contribute to the learning process. Factors that degrade the image quality, specifically those associated with experimental acquisition of measurements, were quantified through measures of spatial resolution and contrast. Knowledge of the image quality metrics led to the validation of this technique using a variety of simulated and manufactured gelatin phantoms targeting BI-RADS features of suspicious breast lesions. This work develops the image science of the AutoP method through rigorous examination of the learning process. The product of this work can be described as a users manual for proper use of AutoP as a tool for imaging the quantitative material properties of tissues in 3D. The scientific developments in this dissertation were a necessary step toward establishing AutoP as a robust tool for diagnostic imaging and mechanobiological discovery
Land-atmosphere interactions and the predictability of the South American low-level jet
No full textSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo termsThe student, Chu-Chun Chen, accepted the attached license on 2025-07-15 at 11:06.The student, Chu-Chun Chen, submitted this Dissertation for approval on 2025-07-15 at 11:57.This Dissertation was approved for publication on 2025-07-17 at 16:29.DSpace SAF Submission Ingestion Package generated from Vireo submission #22578 on 2025-10-20 at 16:58:30Soil moisture plays a critical role in shaping regional atmospheric circulation and hydrological extremes, particularly in regions characterized by strong land-atmosphere coupling. This dissertation investigates how soil moisture anomalies influence the South American low-level jet (SALLJ) and associated moisture transport into southeastern South America (SESA) using a multi-pronged approach that integrates simulations, reanalysis, and forecasts. The overarching goal of this work is to examine how antecedent soil moisture anomalies affect the SALLJ, moisture transport, and precipitation over SESA, and to assess how this knowledge can be leveraged to improve subseasonal forecast skill. Three primary research questions are addressed: 1. How do dry soil moisture anomalies and their spatial distribution affect moisture transport and precipitation over SESA in both simulations and reanalysis at monthly timescales? 2. How do antecedent soil moisture conditions influence the intensity and structure of SALLJ events in reanalysis data at daily timescales? 3. How does the representation of soil moisture in forecast models influence the accuracy of SALLJ predictions at subseasonal timescales? Through three independent yet interconnected studies, this work explores the physical mechanisms, observational evidence, and predictive implications of land surface conditions at subseasonal timescales. In the first study, idealized experiments using the Community Earth System Model (CESM) reveal that the location of large-scale dry soil moisture anomalies significantly affects regional moisture transport and precipitation. The simulations establish a causal mechanism in which dry soils enhance lower tropospheric heating, deepen the thermal low east of the Andes, and strengthen poleward moisture transport. The second study uses the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) dataset to identify strong Chaco jet events and assess the surface conditions prior to the events. The analysis quantifies the climatological contribution of these jets to regional moisture flux and confirms that dry antecedent soil conditions consistently precede enhanced jet intensity. The third study evaluates ensemble forecasts from the ECMWF Subseasonal to Seasonal (S2S) Prediction Project. It shows that ensemble members with more accurate representations of dry soil moisture are associated with more skillful forecasts of SALLJ-related meridional wind anomalies, with improvements evident up to four weeks in advance. Together, these studies demonstrate that soil moisture is not only a modulator of regional climate dynamics but also a source of predictability at subseasonal timescales. The findings advance our understanding of land-atmosphere interactions in SESA and provide actionable insights into improving subseasonal forecasts of extreme weather events in the region
Perceptions of agency in teachers within international baccalaureate primary years programmes in the Chicago public schools
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo termsThe student, Freeda Pirillis, accepted the attached license on 2025-07-15 at 17:59.The student, Freeda Pirillis, submitted this Dissertation for approval on 2025-07-15 at 18:16.This Dissertation was approved for publication on 2025-07-17 at 11:52.DSpace SAF Submission Ingestion Package generated from Vireo submission #22591 on 2025-10-20 at 16:58:35While the achievement gap between students of color and White students in the United States continues to exist, there have been efforts towards identifying models of education that may better serve students from lower socio-economic and minoritized backgrounds (Chae & Gray-Rice, 2019; Conner, 2008; Cortes et al., 2013; Saavedra, 2014). An International Baccalaureate (IB) education has been viewed as a vehicle for increasing student achievement while also preparing students for college and the global labor market (Cortes et al., 2013; Dvir et al., 2018). The focus at the federal level to fund the IB as a mechanism for closing the achievement gap has been researched with studies suggesting an IB education may positively impact students from low-income backgrounds (Connor, 2008; Hemelt, 2014; Perna et al., 2015; Stillisano et al., 2011). The recent and rapid expansion of IB programming in the Chicago Public Schools (CPS), the focus of this research, has signaled a shift for students and families from what has been historically been considered ‘school choice’ to ‘choice schools’ as more neighborhood schools offer the IB among other specialty programs to students from minoritized communities (Chicago Public Schools, 2018; Chicago Public Schools, 2021; Danns, 2018). The primary purpose of this research was to explore the impact of the IB Primary Years Programme (PYP) within the CPS system on teachers with a focus on perceptions of agency, or the amount of voice, choice, and ownership they have in their classroom and school. This included understanding how IB PYP teachers conceptualize and operationalize agency in their local context, and ultimately, how this influenced their work in classrooms that primarily serve students from minoritized backgrounds. Due to the lack of research to date on the PYP in the district, the secondary purpose of this study was to explore the impact of the IB on schools who have been authorized to offer the PYP, specifically within the Chicago urban school setting. Using an exploratory qualitative design, 11 IB PYP teachers and IB Coordinators were recruited using a screening questionnaire, then interviewed using a semi-structured format via Zoom. Interview questions were focused on teachers’ perceptions of agency, as well as how classroom and schoolwide practices that contribute to a higher degree of agency for teachers and students. Results indicate how IB PYP teachers and IB Coordinators conceptualized and operationalized agency contributes to classroom practices that are also perceived to support the development of agency within students. Schoolwide practices were elevated by participants to either hinder or increase teachers’ feelings of autonomy and agency within their context while participants’ belief systems, as well as programmatic or student outcomes emerged as an unexpected finding when exploring the impact of the IB PYP in CPS. Ultimately, the IB PYP appears to have a positive impact on students from minoritized communities and contributes to the limited existing research on the IB Diploma Programme in the district
Dairy milk matrix modulation of inflammation and muscle protein synthesis in adults with excess adiposity
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo termsThe student, Takeshi Barnes, accepted the attached license on 2025-05-28 at 10:29.The student, Takeshi Barnes, submitted this Dissertation for approval on 2025-05-28 at 10:38.This Dissertation was approved for publication on 2025-05-30 at 09:42.DSpace SAF Submission Ingestion Package generated from Vireo submission #22311 on 2025-10-20 at 20:14:44Obesity is associated with anabolic resistance of muscle protein synthesis rates (MPS) to protein ingestion, which impairs skeletal muscle protein remodeling. The factors leading to the impaired MPS are multifaceted, but likely chronic inflammation plays a role. As such, nutritional strategies aimed at eliciting robust MPS responses are important for managing obesity as they will help ensure a protein pool of high metabolic quality. Indeed, dairy milk may represent a particularly favorable protein food choice for obesity management due to its high-quality protein and bioactive lipid components, contributing to a unique food matrix. Therefore, this dissertation aimed to examine (AIM 1) the effect of dairy milk matrix manipulations on acute postprandial MPS using primed constant stable isotope methods and muscle biopsy collections, (AIM 2) the postprandial systemic and muscle inflammatory response, (AIM 3) 7-day integrated MPS based on the D2O method, and (AIM 4) 7-day changes in inflammatory markers in individuals with excess adiposity. To accomplish these dissertation AIMS, thirty-three overweight and obese participants (BMI ≥25 kg∙m-2) were block-randomized to full-fat milk (FFD; n=12), non-fat milk (NFD; n=11), or isonitrogenous, macronutrient-matched non-dairy control beverage (CTL; n=10) conditions. For AIMS 3-4, a 7-day, fully controlled, dietary intervention was utilized, with each participant consuming dairy milk (FFD or NFD) or the control beverage 3 times daily for 7 days. For AIMS 1-2, an acute feeding trial was conducted following the final day of the 7-day intervention, with participants ingesting 2 servings of dairy milk (FFD or NFD) or the control beverage. Acutely, only the CTL condition significantly elevated postprandial MPS during the 5-hour postprandial period (P 0.05). Thus, this dissertation demonstrated that neither FFD nor NFD conditions induced superior anabolic or anti-inflammatory benefits compared to the CTL. These findings suggest that in individuals with excess adiposity, when consuming moderate amounts of protein (2 servings of dairy; >17g protein), free amino acid-based beverages stimulate acute MPS more effectively than dairy milk. Yet, this was not reflected over a longer (7 days) period. Similarly, acute perturbation in postprandial inflammation did not modify fasted inflammation markers following a 7-day intervention
Robot motion planning: configuration space exploration and estimation
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo termsThe student, Stav Ashur, accepted the attached license on 2025-06-24 at 14:18.The student, Stav Ashur, submitted this Dissertation for approval on 2025-06-24 at 14:18.This Dissertation was approved for publication on 2025-06-25 at 15:55.DSpace SAF Submission Ingestion Package generated from Vireo submission #22361 on 2025-10-20 at 20:14:51Fully or semi-autonomous machines, such as robots, are increasingly present in every domain of human society. Cleaning robots, self-driving cars, assembly machines in factories, and exploration vessels for deep sea and space. One of the core challenges when designing and deploying these robots is motion planning, which encompasses almost every action of the robot that requires the operation of a motor -- traveling by land, water, or air, grasping, pushing, or pulling objects, and positioning and utilizing tools, all require motion planning capabilities. Motion planning is frustratingly easy for people -- consider tasks such as assembling a LEGO set or cutting a vegetable into equal parts. Meanwhile, these tasks are quite difficult to automate. The conceived easiness of the task is misleading - young children cannot perform these actions, and years of ``training'' are required to develop the prerequisite set of skills. These tasks require precise motions using a large number of muscles operating in coordination, happening in some space significantly more complicated than the 3D physical workspace, all done by technology that took hundreds of millions of years to emerge via evolution. In this dissertation, we present research on robot motion planning performed in the robot configuration space, a space that captures the complexity of motions problems, striving to improve and utilize methods that efficiently search the space for solutions. We use novel techniques to improve the speed of motion planning algorithms, by modifying the exploration strategies, and the representations of the search space they use. Two of our methods can be easily incorporated in many motion planning algorithms, improving their performance, as measured by runtime, sampling efficiency, or length of the solution. Significantly, these improvements are also present in highly constrained scenarios where motion planning is difficult. We show that these techniques are beneficial when used with various types of robots, suggesting they are widely applicable. We also present a method to update quickly motion planning roadmaps, enabling planning in the presence of changing environments. This method out-performs the state of the art dynamic roadmap, and thus leads to faster planning. We also show the applicability of the new dynamic data-structure to another task planning problem, in which the robot is required to rearrange objects
Uncertainty in interactive decision-making: learning, incentives, and robustness
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo termsThe student, Shiliang Zuo, accepted the attached license on 2025-06-30 at 14:20.The student, Shiliang Zuo, submitted this Dissertation for approval on 2025-06-30 at 14:31.This Dissertation was approved for publication on 2025-07-07 at 15:49.DSpace SAF Submission Ingestion Package generated from Vireo submission #22385 on 2025-10-20 at 20:14:54This thesis investigates decision-making under uncertainty, particularly in interactive settings where outcomes depend on both the decision-maker’s actions and the responses of a dynamic or strategic environment. We study decision-making from three interconnected perspectives: learning, incentives, and robustness. The sequential decision-making with partial feedback framework models settings in which a decision-maker repeatedly interacts with an environment and improves their actions based on observed feedback. This framework captures the learning aspect of interactive decision-making, where the agent must adapt and improve over time using only partial and often noisy signals. The principal-agent model focuses on strategic environments in which a principal must design mechanisms that incentivize an agent—who may hold private information or take unobservable actions—to act in ways that align with the principal's objectives. This captures the incentive alignment component of decision-making under strategic uncertainty. These two frameworks often interact. In many real-world problems, the feedback the learner receives may be generated by strategic agents, or the environment may adapt in response to the learner’s behavior. In such cases, we study how to design learning algorithms that can adapt to strategic responses from a strategic source. At the same time, robustness emerges as a critical design objective across both settings. In online learning, we study how to design algorithms that remain effective when feedback is adversarially corrupted. In principal-agent problems, we study how the robustness of mechanisms can be measured and how to design such mechanisms. The first theme of the thesis is the study of online learning with adversarial corruption. We design corruption-robust algorithms for the contextual search problem, a problem motivated by applications such as dynamic pricing. We also study stochastic bandits under adversarial corruption, showing how minimal corruption can manipulate widely used algorithms such as UCB and Thompson Sampling. The second theme is learning and robustness in contract design problems. We show how tools from the first-order approach, traditionally used in economic theory to characterize optimal contracts, can be adapted for algorithmic learning. We also study the multi-task principal-agent problem, analyzing linear contracts from both robustness, fairness, and learning perspectives. Our results identify conditions under which linear contracts are worst-case optimal and explore how to estimate optimal contracts from data. Finally, we study the greedy algorithm in structured bandit problems. We provide a sharp characterization of when greedy succeeds or fails, based on a condition we call self-identifiability. This property determines whether greedy learning leads to asymptotically optimal behavior or suffers from linear regret