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Theoretical and Machine Learning Modeling and DFT Simulations in Energy-Related Materials and Devices
No full textModern energy-related materials often exhibit complex, multiscale interactions involving strong coupling between mechanical, electronic, and diffusion degrees of freedom. This dissertation addresses key challenges in understanding and predicting the behavior of such systems through an integrated approach that combines analytical modeling, first-principles simulations, experimental interpretation, and machine learning techniques.
We begin by investigating solid-state batteries (SSBs) interfaces, where interfacial degradation and dendrite formation limit performance and reliability. A continuum model is developed to describe how strain-induced suppression of diffusivity leads to a self-limiting reaction mechanism. The model unifies previously fragmented insights into a general theoretical framework that explains self-limiting reaction behavior in a wide range of materials and interface types by quantitative modeling works. Large-scale simulations further connect local self-limiting kinetics with experimentally observed degradation morphology patterns. This work broadens the design space for next-generation batteries from the perspective of dynamic stability design, emphasizing interface engineering and transport dynamics coupled with reaction induced local strain-stress field as critical levers for achieving long-term stability and reliability.
In the context of high-temperature superconductors, the group’s material-dependent DFT computations reveal strong lattice–charge–magnetic coupling in cuprate superconductors. By analyzing anharmonic phonon modes and charge redistribution patterns, dynamic charge fluxes patterns were extracted that unveils their correlation with superconducting T_c. Building on this insight, my work focuses on constructing a quantum theoretical framework where flux fluctuations—characterized by wavevector oscillation and coherence width—mediate an attractive interaction kernel. Theoretical analysis within the random phase approximation (RPA) leads to a derived scaling law for T_c, showing strong dependence on material-specific anharmonicity and coupling strength. These results suggest that flux-mediated interactions, emerging from tightly coupled lattice–charge–spin dynamics, may provide a pathway toward understanding and enhancing unconventional superconductivity.
Next, we study Na-layered oxides and unveil critical structural details in NaxCrO2 electrochemical evolution. Combining experimental XRD with DFT data, we develop a structure optimization framework capable of identifying complex Na-vacancy ordering patterns and explain the existence of Na density wave ordering patterns. The result reveals novel nano-stripe-like vacancy domains under low Na composition and resolves puzzles about charge–discharge asymmetry and metastability, offering new principles for cathode design with improved reversibility and structural stability.
Finally, in the field of battery data science, we present a 2D image-based machine learning framework for battery performance prediction. By encoding cycling curves as binary images and training on various models including deep residual networks end-to-end, we demonstrate enhanced predictive accuracy, robustness and interpretability of 2D representation compared to traditional 1D approaches. The work opens new directions for leveraging advanced vision models to electrochemical degradation and lifetime forecasting for batteries.
Together, these studies highlight the power of multi-method modeling in revealing hidden mechanisms, guiding material selection, and proposing novel design strategies for energy related materials.Engineering and Applied Sciences - Applied Physic
Decision-Focused Learning for the Masses With Applications to Public Health
No full textIn this thesis, I aim to better understand how to best train Machine Learning models for decision-making under uncertainty. Specifically, I focus on the ``Predict-then-Optimize'' framework, in which uncertain quantities are predicted using ML models, and decisions are made by solving optimization problems parameterized by these predictions. While past Decision-Focused Learning (DFL) methods show that optimizing directly for decision quality leads to improved outcomes, existing approaches typically require extensive manual effort—such as designing differentiable surrogate optimization tasks—limiting their applicability to arbitrary problems. Moreover, evaluating the real-world impact of these models in resource-constrained settings poses additional challenges.
This thesis, therefore, addresses the central question: Can we create generalizable methods to train and evaluate decision-focused learning models on arbitrary decision-making tasks so that DFL can be more practically useful? In response, I introduce methods that distill task-specific decision-making structures into a learned, differentiable ``decision loss,'' eliminating the need for handcrafted surrogates. I first propose Locally Optimized Decision Losses (LODLs), demonstrating their improved performance across multiple domains. I then extend this approach via Efficient Global Losses (EGLs), significantly enhancing generalization, efficiency, and theoretical robustness.
Additionally, I develop rigorous statistical estimators for accurately evaluating DFL models in resource allocation scenarios. Applying these estimators to real-world randomized control trials reveals insights previously hidden by existing methods. Collectively, these contributions establish a broadly applicable, reliable framework for decision-focused learning, making DFL more practically viable across diverse decision-making contexts.Engineering and Applied Sciences - Computer Scienc
Metabolic flux sensing of sugars in Saccharomyces cerevisiae
No full textA canonical view of nutrient sensing is that cells sense the concentration of nutrients. However, it is sometimes beneficial to regulate cellular processes based on the metabolic flux through a pathway, instead of the concentration of a nutrient. The mechanisms to achieve metabolic flux sensing remain largely unclear. The observation of flux-dependent regulation is also limited.
This dissertation work explores the phenomena and mechanisms of metabolic flux sensing of sugars in budding yeast Saccharomyces cerevisiae. Galactose and glucose are two types of sugar used by cells as carbon sources for growth. Cells sense the sugars for proper regulation of their metabolism. In the case of galactose, cells sense galactose for deciding the induction of the galactose-utilization (GAL) pathway. In the case of glucose, cells sense glucose for repressing genes involved in utilizing other carbon sources.
To study the metabolic sensing processes, first, a series of tools are developed to enable the necessary genetic perturbation and control of metabolism in living cells. A high-throughput imaging method is developed to monitor the perturbations and measure signaling readout of the pathway. Then, we study the signaling role of galactokinase Gal1 in the GAL pathway, and report that the enzyme can couple its catalytic activity to signaling, resulting in a signaling output proportional to the metabolic flux. Next, in the glucose repression pathway, I find that glucose repression depends on metabolic flux of glucose. However, I rule out the signaling role of hexokinase Hxk2, and find that Mig1 controls glucose repression via a non-canonical mechanism. Some candidate metabolites potentially for determining glucose repression are identified through differential perturbations of glycolytic metabolites and model predictions. Last, I describe a growth curve measurement device I developed, which enables easy and accurate measurement of growth curves.Systems Biolog
Metal–Organic Frameworks for Permanent Microporosity in Aqueous Media
No full textAqueous media with high gas solubility are critical to the development of many emerging biomedical and energy technologies. From a biological standpoint, most physiological processes depend on cellular interaction of gases with water, while the design and synthesis of sustainable energy materials often require efficient gas-liquid mass transfer in an aqueous medium. However, water lacks the ability to store and transport significant amounts of gas due to its high energetic penalty against cavity formation required to solubilize gas molecules. To overcome this limitation, herein, we establish a generalizable method towards instilling permanent microporosity in aqueous media for increased gas carrying capacities. Specifically, we utilize metal–organic frameworks (MOFs) to instill stable, hydrophobic pores in aqueous media that can readily adsorb gas while excluding water from their pores. This novel approach towards creating aqueous gas carriers allows for not only unprecedented gas solubility in water but also provides a model platform upon which the interfacial effects between water and the micropore can be investigated.
Chapter One introduces gas solubilization in water, and the associated thermodynamic challenges. The concept of instilling permanent free volume towards increased gas solubility is introduced in the context of porous liquids, and the limits of its steric exclusion approach in aqueous systems discussed. The grounds for establishing thermodynamic exclusion of water molecules from hydrophobic MOF micropores are proposed instead to establish permanent microporosity in water.
Chapter Two outlines the design and synthesis of aqueous gas carriers via stably dispersing hydrophobic microporous solids – termed “microporous water” – and the development of in situ analytical methods for directly probing the gas solubility and release of these microporous water systems. Through this study, we report that these microporous water systems can concentrate gases to densities magnitudes higher than what is possible for other aqueous gas carriers, which has exciting implications for biomedical and energy applications.
Chapters Three and Four investigate the fundamental factors that govern water intrusion into hydrophobic micropores through a 1-dimensional (1D) pore channel MOF. We find that pore size, in addition to ligand hydrophobicity, plays a critical role in determining water intrusion into 1D micropores and establish design principles towards de novo synthesis of 1D channel MOFs with microporous water behavior. In addition to structural factors that influence water intrusion, we also explore the effects of pore chemical environment on water intrusion behavior, in which the ligands of a fully water-intruded MOF are systematically functionalized to understand the effects of varying degrees of hydrophobicity and steric bulk.
Chapter Five extends the microporous water concept towards microporous hydrogels for applications in controlled gas delivery. Through leveraging the surface hydrophobicity of aqueous MOF dispersions, we can achieve colloidal MOF hydrogels without the addition of extensive polymer matrices that may infiltrate the pores at the detriment of gas capacity. This proof-of-concept system opens a new avenue for incorporating dry porosity in hydrogels, enabling the sustained delivery of gaseous species previously considered elusive within a water-spanned matrix.Chemical Physic
Erosion of Democracy: Viktor Orban, Hungarian Voters, and the Desire for Autocracy
No full textThe rise of illiberal democracies within the European Union presents a profound
challenge to the post-Cold War liberal democratic order. This thesis examines the case of
Hungary under Prime Minister Viktor Orbán, investigating the erosion of democratic
values in an EU member state. It argues that the longevity of Orbán and the Fidesz party
is not merely the result of political maneuvering but is deeply rooted in a significant
segment of the Hungarian electorate’s desire for autocracy, a desire borne from historical
trauma, post-communist disillusionment, and economic anxiety.
This paper analyzes the historical and socio-economic factors, including the
Treaty of Trianon and the failures of the post-1989 transition to democracy, that created
pathway for a leader such as Orbán to gain support for a national shift towards autocracy.
Furthermore, it details specific mechanisms of state level mass mobilization employed by
Orbán and the Fidesz party to consolidate control of state media, rewrite the constitution,
and isolate Hungary from the EU. The thesis concludes that Hungary is a successful
model of an electoral autocracy which has consistently gained the support of Hungarian
voters and therefore represents a significant challenge to the normative foundation of
European integration and the broader liberal democratic order.Extension Studie
House of Five
No full textThis thesis presents the opening chapters of my novel, House of Five. Set in Fig
Town, a fictional port on the Aegean Sea, the four chapters move between an empire’s
final years in the 1910s and the era of its modern republic. Irene arrives at the Lyre
House, which is perched above the harbor, blaming herself for her mother’s death and
certain she doesn’t belong. Half orphanage, half choir school, the Lyre House is unlike
any other place to grow up. Though reluctant at first, Irene finds purpose there in singing
alongside girls drawn from across the fading empire—Aysel, Francesca, Nara, and
Rivka—under exacting foreign instructors. She has always sensed the untamed power in
her voice, and the Lyre House shows her what it can do when interwoven with theirs. As
the empire fractures and the patrons come to prize solos and favors, the girls are tempted
into rivalry, threatening the fragile chorus. Over a century later, the Lyre House stands in
ruins. Developers circle the crumbling building, one intent on demolition, the other
attuned to what lives on in the walls. Narrated by Irene’s lingering spirit, now fused with
the house itself, House of Five is a novel about plural belonging in fractured time and the
architecture of memory: how a building preserves what people forget.Extension Studie
Switching between Existing and New Trade Agreements: Evidence from Japan’s Imports from Vietnam
Get PDFapplication/pdfIDP000988_001We empirically investigate the utilization rates of the two existing regional trade agreements (RTAs) in Japan’s monthly imports from Vietnam from January 2017 to December 2021. In particular, we explore the changes in these rates before and after the commencement of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), focusing on the products for which CPTPP offered the lowest tariffs. We did not find significant changes in the utilization rates of either existing RTAs or the most-favored nation (MFN) regime before CPTPP’s entry in January 2019. However, exporters familiar with the use of preferences (i.e., existing RTA users) appear to have switched to CPTPP first, followed by unfamiliar users (MFN users) who switched to it gradually. Consequently, the introduction of a new RTA was associated with a sustained expansion of trade, unlike the gradual tariff reduction in a single RTA observed in the previous study.technical repor
The EU’s structuring role for interorganisational relations: the case of AU-ECOWAS on peacekeeping in West Africa
Get PDFapplication/pdfIDP000990_001African regional organisations have been intervening in state crises for decades. Although the AU and subregional organizations are expected to function based on subsidiarity, no clear official division of labour exists among them. In practice, they have found differing roles in conflict management in Africa. However, the factors that drive their learning processes and adaptations under particular circumstances remain unclear. Based on the fact that peacekeeping operations in Africa are significantly supported by external actors, particularly, their financial assistance, this study analyses how European Union (EU) financial assistance has impacted the African Union (AU)-Economic Community of West African States (ECOWAS) relationship. An empirical analysis of the EU’s financial assistance for conflict management in West African countries demonstrates that EU support has helped develop the division of labour between the AU and ECOWAS over the years, especially since the period from the late 2000s. The research presented here contributes to studies on interorganisational relations by showing a case of the EU’s structural influence on the AU-ECOWAS relationship in their intervention to key recent crises in West Africa.technical repor
