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MAGNETIC FIELD ENABLED ASSEMBLY AND PROPULSION OF COLLOIDAL PARTICLES IN A MAGNETIC MEDIUM
No full textColloidal particles are nano/micro meter-sized particles dispersed in a fluid medium and serve as diverse building blocks for assembling complex structures. The ease of tunability of the shape, size, and interparticle interactions of colloidal particles facilitates their assembly into rich structures and phases that mirror the assembly process of atomic systems. Often regarded as big atoms colloidal particles provide an ideal model system for investigating complex phenomena in condensed matter, such as crystallization and nucleation. While the assembly of colloids under thermodynamic equilibrium has been extensively studied, recent interest has shifted toward exploring colloids in non-equilibrium conditions to create dynamic assemblies and drive motion. Achieving the structure and functionality of living matter in synthetic materials requires understanding the underlying principles governing non-equilibrium systems. This Ph.D. dissertation presents strategies to assemble and propel colloidal particles by applying magnetic fields as a source of energy to form dynamic structures under out-of-equilibrium conditions.
Firstly, we achieve magnetic field-guided assembly using colloidal particles as building blocks that range from isotropic spheres to shape-anisotropic particles, resulting in a diverse array of assembled structures. By tuning the magnetic field configuration, we achieve dynamic control over interparticle magnetic interactions, which can be either attractive or repulsive. The in situ tunability of the interparticle interactions through magnetic fields allows for reversible transitions of isotropic spherical colloidal particles between different assembled structures, including crystals, fractal clusters, and low-density Wigner glass. In addition, we investigated the assembly and melting transitions for particles of varying shapes and showed distinct differences in the melting transition depending on the shape anisotropy of the particles.
Secondly, we employ magnetic fields to precisely control the motion of non-spherical microellipsoids particles near a substrate. We demonstrate the contactless capture and transport of cargo particles due to the generation of mobile microvortices by the rotational motion of microellipsoids. To demonstrate the capabilities of microellipsoids as functional microrobots and perform biomedical tasks such as targeted delivery, we developed a feedback-controlled navigation scheme for microellipsoids to transport cargo to the desired position within a complex environment. Lastly, we investigated the motion characteristics of magnetically actuated microellipsoids on topological surfaces relevant to biological environments. We also present design principles for microrobots that enable efficient and robust rolling motion on topological surfaces.
The principles and strategies for colloidal particle assembly and propulsion presented in this dissertation enhance our understanding of non-equilibrium colloidal systems, enabling the development of advanced functional materials and micro-robotic systems
Weathering the Risks: How Risk Communication Shapes Preparedness for Natural Hazards & Extreme Weather in Southeast Louisiana
No full textAs natural hazards and extreme weather events intensify in frequency and severity, the need for effective risk communication strategies that promote household and community preparedness becomes increasingly pressing, particularly among vulnerable populations. This dissertation examines how risk communication professionals, including emergency managers and meteorologists in Southeast Louisiana, convey risk information and how residents perceive and respond to these messages. Utilizing a convergent mixed methods research design, the study explores the relationship between risk communication, individual risk perception, and disaster preparedness behaviors across East Baton Rouge, West Baton Rouge, and West Feliciana parishes.
Quantitative data were obtained through a structured community survey (n = 382), which assessed residentsโ perceptions of risk, preparedness behaviors, trust in local authorities, and communication preferences. Descriptive and inferential statistics, such as Chi-square tests, Mann-Whitney U tests, and Kruskal-Wallis H tests, were employed to examine differences across demographic and geographic groups. The results indicate that older adults, African American respondents, and lower-income households report higher levels of concern yet encounter distinct barriers to preparedness. Additionally, residents of East Baton Rouge Parish exhibited significantly lower levels of preparedness and confidence in local leadership compared to neighboring parishes.
Qualitative data were collected via semi-structured interviews with nine risk communication stakeholders, including meteorologists, emergency managers, and disaster preparedness coordinators. Thematic analysis underscored the importance of message clarity, multi-channel communication strategies, community collaborations, and culturally responsive approaches. The integration of quantitative and qualitative findings demonstrates convergence, such as the vital role of trust, and divergence, including gaps in institutional visibility and barriers to message uptake among vulnerable populations.
Grounded in the Protective Action Decision Model (PADM), this research emphasizes how risk perception, risk communication, and social context influence disaster preparedness decision-making. Key implications include the need for participatory risk communication, localized, tailored outreach strategies, and equitable investments in community-based education and preparedness initiatives. The findings contribute to academic scholarship and practical emergency management by identifying pathways to strengthen risk communication and enhance disaster resilience within geographically and socially vulnerable communities
GAIN THRESHOLD OPTIMIZATION USING FANO RESONANCE
Full text linkThe study of resonances in electromagnetics plays a critical role in the design of optical systems. This dissertation investigates the interaction between resonance and gain in optical structures to establish a universal principle for achieving ultra-low-threshold lasing. Through the analysis of geometric symmetries, material properties, and coupling mechanisms, this research develops prototype structures applicable to a wide range of optical and electromagnetic systems. A range of models is considered, starting from a simple onedimensional string-resonator system (based on the model of H. Lamb), then advancing to two- and three-dimensional waveguide models, and culminating with a realistic high-contrast model in open space. A key finding of this work is that Fano resonance, arising from the interaction of bound states and radiation continua, can be exploited to minimize the power input required to reach the lasing threshold. By balancing radiation losses with an appropriate gain mechanism, Fano resonance allows the lasing threshold to be achieved at very low gain, thus enabling more energy-efficient optical components. This work derives a universal law governing the relation between the Fano interaction strength and gain threshold, which is valid in all of the models analyzed. The proposed framework for gain threshold minimization contributes to the development of ultra-low-power optical technologies, providing optimism for applications in telecommunications, quantum computing, and sensing
Energy Equity In The Built Environment: Analyzing Building Energy Consumption For American Low-Income Households
No full textThe built environment consumes a significant amount of energy in the United States, with outdated and inefficient affordable housing increasing financial pressure on low-income households (LIHs) who face high energy burdens. This research aims to assess the energy performance of American households, focusing on LIHs, to promote energy justice by providing data-driven insights and models for energy efficiency improvements. More specifically, this research aims to (1) create a large-scale national residential building energy dataset by integrating the American Housing Survey and the Residential Energy Consumption Survey using machine learning techniques; (2) analyze and model American household occupancy profiles by leveraging time-use surveys and applying machine learning algorithms to predict occupancy patterns based on influential sociodemographic factors; (3) assess the influence of different Energy Efficiency Measures (EEMs) on residential energy consumption across various household types, and (4) develop comprehensive models to support energy improvement decisions and policies at both the building and community levels, focusing on reducing energy burdens and promoting energy justice among LIHs. These contributions aim to advance sustainable and equitable energy use in the built environment, particularly benefiting LIHs facing higher energy burden
Essays in Labor and Immigration Economics
No full textThis dissertation comprises three essays in labor economics, focusing on the long-run effects of historical immigration and the economic impacts of contemporary immigration policies. In Chapter 2, I study how historical immigration-induced shifts in human capital affect the industrial skill structure of US counties. Using a shift-share instrumental variable strategy, I isolate exogenous changes in the skill composition of the working-age population between 1970 and 2010, relying on immigrant settlement patterns from 1850 to 2010. I find that, relative to the share of workers in low-skill industries, an exogenous increase in medium- and high-skill worker shares raises employment and establishment shares in high-skill industries and reduces them in low-skill industries, particularly in nontradable sectors. These findings, supported by a CES model with white- and blue-collar firms, emphasize the importance of historical development in shaping regional policy-making.
In Chapter 3, my co-author and I investigate the causal impact of religiosity on labor market outcomes across US commuting zones. We construct novel instruments for religious affiliations in 1940-2010 using quasi-random historical immigration interacted with origin-specific religiosity shares from 1850 to 2010. Relative to the unaffiliated, higher shares of Protestants and Liminal Christians reduce employment, income, and education, especially for women, whereas a rise in Jewish share has the opposite effects. These patterns extend to marriage and fertility outcomes and are consistent across ethnic groups, highlighting the role of religious and gender norms in shaping economic behavior.
In Chapter 4, I assess the effects of the Deferred Action for Childhood Arrivals (DACA) program on US firm dynamics over the 2008โ2019 period. Exploiting sectoral and geographic variation in pre-policy exposure to DACA-eligible individuals within a triple-difference framework, I find that DACA increases establishment entry by 2.4 percent and temporarily reduces exit rate. It also raises native employment by 2.1 percentage points while reducing employment amongst DACA-ineligible workers, with impacts concentrated in low- and medium-skill sectors. These findings suggest that legalization policies can promote firm creation, facilitate labor reallocation without displacing natives, and improve local economic dynamism through entrepreneurship
Interfacial Engineering Approaches for Solving Mass and Heat Transfer Limitations in Heterogeneous Catalysis
No full textThis work studies the mass and heat transfer issues in heterogeneous catalysis by means of interfacial engineering approaches. Specifically, it deals with two topics: plastic-catalyst interfaces for mass transfer problems in plastic depolymerization and electric heater-catalyst interfaces for heat transfer problems in highly endothermic reactions.
Mass transfer is among the major challenges in heterogeneous catalytic reactions that involve large reactant molecules. One notable example is the depolymerization of plastic waste catalyzed by solid catalysts, which occurs at the interfaces between solid catalysts and solid plastic if operated below the melting points of plastics. The catalytic efficiency is largely constrained by the poor interfacial contact between solid catalysts and solid plastics. In this work, we studied the heterogeneous catalyst layer on polyethylene terephthalate surfaces and extended this method to polycarbonate and polyamide depolymerization. We demonstrated that the construction of plastic-catalyst solid-solid interfaces enables solvent-free depolymerization of polyethylene terephthalate by vapor phase methanolysis at relatively low temperatures.
Another topic of the proposed research is solving heat transfer problems in heterogeneous catalysis. We developed internal electric heating to shorten the heat transfer distance between the heating source and catalytic sites. The new design holds promise in decarbonizing the heating process in several major endothermic reactions. Proper integration of catalyst layers onto electric heaters represents a major challenge for the new design. We explored interfacial engineering approaches to address this challenge. The results showed success in solution deposition of nickel oxide nanostructures and washcoating of fumed SiO2 and zeolite layer catalysts onto nickel metal foam. We studied the catalytic performance and energy efficiency of these catalysts in methane reforming and prepared for alkane dehydrogenation/cracking using electric heating
Pear shape and tetrahedral shape competition in actinide nuclei
No full textShape competition and coexistence between the pear- and the tetrahedral-shape octupole deformations in actinide nuclei is investigated by employing the realistic nuclear mean-field theory with the phenomenological, so-called \u27universal\u27 Woods-Saxon Hamiltonian with newly adjusted parameters containing no parametric correlations. Both types of octupole deformations exhibit significant effects in , , and isotones. Nuclear potential energy calculations within the multi-dimensional deformation spaces reveal that the tetrahedral deformation effects generally lead to deeper energy minima in most nuclei with and . Interestingly, in the nuclei , , and , selected for the illustration of the studied effects, the influence of pear-shape octupole deformation is comparable to that of tetrahedral octupole deformation. Consequently, the coexistence of both kinds of octupole shapes is predicted by the potential energy calculations. In particular, we have reproduced the experimental results known for pear-shape rotational bands obtaining in this way an estimate of the quality of the modelling parametrisation. With the same Hamiltonian, we have predicted the properties of the tetrahedral symmetry rotational bands. To facilitate the possible experiment-theory cooperation we have derived the exact spin-parity tetrahedral-band structures by applying the standard methods of the group representation theory for the T d point-group
A Novel Highly Segmented Neutrino Detector: The Super Fine Grained Detector for the Upgraded T2K ND280 Near Detector
No full textThe T2K neutrino experiment in Japan obtained a first indication of CP violation in neutrino oscillations. To obtain better sensitivity, T2K upgraded the near detector. A novel 3D highly granular scintillator detector called SuperFGD of a mass of about 2 tons will be functioning as a fully-active neutrino target and a 4ฯ detector of charged particles from neutrino interactions. It consists of about two millions of 1 cm3 optically-isolated plastic scintillator cubes. Each cube is read out in three orthogonal directions with wave-length shifting fibers coupled to compact photosensors, micro pixel photon counters (MPPCs). SuperFGD was installed into the ND280 magnet and exposed to the neutrino beam since October 2023. In this presentation, the main detector parameters, detection of first neutrino events, and its performance in the neutrino beam are described
Multiphoton quantum imaging using natural light
No full textIt is thought that schemes for quantum imaging are fragile against realistic environments in which the background noise is often stronger than the nonclassical signal of the imaging photons. Unfortunately, it is unfeasible to produce brighter quantum light sources to alleviate this problem. Here, we overcome this paradigmatic limitation by developing a quantum imaging scheme that relies on the use of natural sources of light. This is achieved by performing conditional detection on the photon number of the thermal light field scattered by a remote object. Specifically, the conditional measurements in our scheme enable us to extract quantum features of the detected thermal photons to produce quantum images with improved signal-to-noise ratios. This technique shows an exponential enhancement in the contrast of quantum images. This measurement scheme enables the possibility of producing images from the vacuum fluctuations of the light field. This is experimentally demonstrated through the implementation of a single-pixel camera with photon-number-resolving capabilities. As such, we believe that our scheme opens a new paradigm in the field of quantum imaging. It also unveils the potential of combining natural light sources with nonclassical detection schemes for the development of robust quantum technologies
Introducing a Markov chain-based time calibration procedure for multi-channel particle detectors: application to the SuperFGD and ToF detectors of the T2K experiment
Full text linkInter-channel mis-synchronisation can be a limiting factor to the time resolution of high performance timing detectors with multiple readout channels and independent electronics units. In these systems, time calibration methods employed must be able to efficiently correct for minimal mis-synchronisation between channels and achieve the best detector performance. We present an iterative time calibration method based on Markov Chains, suitable for detector systems with multiple readout channels. Starting from correlated hit pairs alone, and without requiring an external reference time measurement, the method solves for fixed per-channel offsets, with precision limited only by the intrinsic single-channel resolution. A mathematical proof that the method is able to find the correct time offsets to be assigned to each detector channel in order to achieve inter-channel synchronisation is given, and it is shown that the number of iterations to reach convergence within the desired precision is controllable with a single parameter. Numerical studies are used to confirm unbiased recovery of true offsets. Finally, the application of the calibration method to the Super Fine-Grained Detector (SuperFGD) and the Time of Flight (TOF) detector at the upgraded T2K near detector (ND280) shows good improvement in overall timing resolution, demonstrating the effectiveness in a real-world scenario and scalability