UC Berkeley

Before a new nuclear reactor design can be constructed and operated, its safety must bedemonstrated using models that are validated with integral effects test (IET) data. However, because scaled integral effects tests are electrically heated, they do not exhibit nuclear reactor feedback phenomena. To replicate the nuclear transient response in electrically heated IETs, we require simulated neutronics feedback (SNF) controllers. Such SNF controllers can then be used to provide SNF capabilities for IET facilities such as the Compact Integral Effects Test (CIET) at the University of California, Berkeley (UC Berkeley). However, developing SNF controllers for IET facilities is non-trivial. To expedite development, we present the use of Digital Twins as testbeds for iterative SNF controller development. In particular, we use a Digital Twin of the Heater within CIET as a testbed for SNF Controller Development. This Digital Twin with SNF Capabilty is run as an OPC-UA server and client written almost entirely in Rust using Free and Open Source (FOSS) code. We then validate the Digital Twin with experimental data in literature. We also verify the transfer function simulation and Proportional, Integral and Derivative (PID) controllers written in Rust using Scilab. Moreover, we demonstrate use of data driven surrogate models (transfer functions) to construct SNF controllers in contrast to using the traditional Point Reactor Kinetics Equations (PRKE) models with the hope that they can account for the effect of spatially dependent neutron flux on reactor feedback. To construct the first surrogate models in this work, we use transient data from a representative arbitrary Fluoride Salt Cooled High Temperature Reactor (FHR) model constructed using OpenMC and GeN-Foam. Using the Digital Twin as a testbed, two design iterations of the SNF controller were developed using the data driven surrogate model. Compared to the potential development time taken in using physical experiments, using the digital twin testbed for SNF controller development resulted in a significant time saving. We hope that the approaches used in this dissertation can expedite testing and reduce expenditure for licensing novel Gen IV nuclear reactor designs.

In this text, I argue that the legislative process has a legal nature, as opposed to its more apparent political facet, and that breaches of procedural lawmaking rules are incompatible with such a characterization. To defend such a viewpoint, I approach the topic in three parts.The first part addresses legislatures’ procedural rules’ force of law, navigating through U.S. and Brazilian cases. Against views that take legislative procedural rules as non-mandatory and merely coordinating tools, I develop my argument upon Hans Kelsen’s and H.L.A. Hart’s theorizations and state that these provisions belong to (hard) law. Hence, though legal interpretation challenges may blur the distinction between the political and legal facets, I affirm that legislative procedures have the force of law and, as such, are binding. The second part deals with justification and overseeing mechanisms. I argue that there are several reasons why lawmakers should abide by the legislative procedural rules. First, it is a matter of the rule of law, meaning that the participants in the lawmaking process have the right to play according to the pertinent provisions. Second, compliance with the established procedures safeguards participation and the flow of diverse opinions and, thus, democratic representativeness. Third, rules’ observance fosters transparency, shedding light on a bill and its motives. Finally, I state that compliance with procedural rules should result from enforcing tools managed by legislators and third parties, such as non-partisan officers in legislatures and, under some restraints, the judiciary. The third part addresses a specific situation: the enactment of executive decrees, provisional measures, directives, or anything similar, with the force of law, to address emergencies. I defend that the misuse or abuse of these expedited lawmaking instruments is incompatible with the legal nature of the legislative process. First, I analyze the ancient Roman Republic’s approach to the circumvention of serious menaces and the theories of John Locke, Carl Schmitt, and Santi Romano in this regard. Then, I assess how governments in Brazil, Italy, and the United States usually take advantage of those instruments not to address threats but to bypass the burdens of ordinary legislative procedures. To avoid such an outcome, I argue that legislatures should enhance their oversight capacity under emergencies or pressing situations while simultaneously providing the judiciary with more specific reviewing standards.

Chapter 1. The field of f-block–transition metal hydride chemistry is introduced and summarized. Key properties of these compounds such as small molecule activation chemistry and H2 uptake and release are outlined. The dearth of actinide–transition metal species despite their potential for fundamental bonding insight and novel reactivity is highlighted, and the motivations for studying these compounds are stated.

Chapter 2. Reaction of K[Cp*IrH3] with actinide halides led to multimetallic actinide–transition metal hydrides U{(μ-H)3IrCp*}4 and Th{[(μ-H)2(H)IrCp*]2[(μ-H)3IrCp*]2}, respectively. These complexes feature an unexpected, significant discrepancy in hydride bonding modes; the uranium species contains twelve bridging hydrides while the thorium complex contains ten bridging hydrides and two terminal, Ir-bound hydrides. Use of a U(III) starting material with the same potassium iridate resulted in the octanuclear complex {U[(μ2-H)3IrCp*]2[(μ3-H)2IrCp*]}2. Computational studies indicate significant bonding character between U/Th and Ir in the tetrairidate compounds, the first reported evidence of actinide-iridium covalency. In addition, these studies attribute the variation in hydride bonding between the tetrairidate complexes to differences in dispersion effects. This work establishes a novel route to synthesizing actinide–transition metal polyhydrides with close metal–metal contacts.

Chapter 3. Conversion of Cp*OsH5 to K[Cp*OsH4] with KBn, followed by reaction with tetravalent actinide halides results in the synthesis of uranium– and thorium–osmium heterometallic polyhydride complexes. Through these species, An–Os bonding and the reactivity of An–Os interactions are studied. These complexes are formally sixteen-coordinate, the highest observed coordination number for uranium and thorium. Computational studies suggest the presence of a significant bonding interaction between the actinide center and the four coordinated osmium centers, the first report of this behavior between osmium and an actinide. Upon photolysis, these complexes underwent intramolecular C–H activation with the formation of an Os–Os bond, while the thorium complex was able to activate an additional C–H bond of the benzene solvent, resulting in a μ-η1,η1 phenyl ligand across one Th–Os interaction. These results highlight the unique reactivity that can arise from actinide and transition metal centers in proximity, and expand the scope of actinide photolysis reactivity.

Chapter 4. The third Cp*-supported transition metal polyhydride – Cp*ReH6 – was shown to be a competent partner to actinide hydrides. The synthesis of actinide tetrarhenate complexes completed a series of iridate, osmate, and rhenate polyhydrides, allowing for structural and bonding comparisons. Computational studies examine the bonding interactions, particularly between metals, in these complexes. Several factors affect metal–metal distances and covalency for the actinide tetrametallates, including metal oxidation state, coordination number, and dispersion effects. The osmium and rhenium octametallic U2M6 clusters are reported as well, with similar analysis of structure and electronics.

Chapter 5. Reaction of the potassium iridate K[Cp*IrH3] with a bulky uranium(III) metallocene yielded a heterobimetallic U(III)–Ir species. Reactivity of this complex with CS2 is described, resulting in the novel ethanetetrathiolate fragment, as produced via hydride insertion and C–C coupling. This demonstrates the ability to combine the hydride insertion chemistry of transition metal hydrides with C–C coupling observed in U(III) compounds by bringing both metal centers in close proximity.

The advent of advanced computational technologies and artificial intelligence has ushered in a new era of complex systems and applications, notably in the realms of autonomous vehicles (AVs) and robotics. These systems are increasingly required to make decisions autonomously in dynamic and uncertain environments. Reinforcement Learning (RL) has emerged as a pivotal technique in this context, offering a framework for learning optimal decision-making strategies through interactions with the environment. However, ensuring safety and trustworthiness in these decisions remains a critical challenge, especially in safety-critical applications such as autonomous driving.

This dissertation addresses the aforementioned challenge by proposing innovative RL-based approaches, and is structured into three distinct but interconnected parts, each focusing on a unique aspect of RL in the context of safe and trustworthy decision-making.The thread of this dissertation is based on the exploration and advancement of RL techniques to ensure safety and reliability in autonomous decision-making systems, particularly in complex, dynamic environments.

We first establish the foundational aspects of RL in decision-making, particularly in uncertain and dynamic environments. The focus here is on enhancing RL to deal with real-world complexities, such as interacting with unpredictable agents, e.g., human drivers in AV scenarios, and handling distributional shifts in offline RL settings. This sets the stage for understanding and improving the decision-making capabilities of autonomous systems under uncertainty.

Building on the first part, we then explore the integration of hierarchical planning with RL. The emphasis is on creating frameworks that combine different levels of decision-making, balancing immediate, low-level safety concerns with high-level strategic objectives. The approach aims to address the limitations of traditional RL in complex, multi-agent environments and long-duration tasks, demonstrating improved adaptability and efficiency in real-time decision-making.

The final part represents a forward-looking approach to RL, focusing on the integration of offline and online learning methodologies. This part addresses the challenge of training RL agents in a manner that is both safe and effective, particularly in contexts where exploration can be costly or dangerous. By combining the strengths of large-scale offline data (expert demonstrations) with online learning, we present a novel framework for enhancing the safety and performance of RL agents in practical, real-world applications.

A sequence of electron clouds is extracted from an electron plasma reservoir. These clouds are highly reproducible and their E x B drift motion is nearly identical to that of a single particle, making them useful for measurements of electric and magnetic fields. First, by weakening the trapping potential confining the clouds we observe that they move off-axis, and we use this to measure the electric field due to patch potentials. Next, we measure the total charge of these clouds using small shifts in their magnetron frequencies. The misalignment between the trap electrodes and the external magnet is measured by imaging the clouds from different axial locations in the trap. By combining electron cyclotron resonance with the patch potential measurement procedure, we can measure the magnetic field strength up to a millimeter away from the trap axis. Finally, a new magnetometry technique called electron magnetron phase imaging (EMPI) is used to measure the rapidly changing magnetic field involved in observing the effect of gravity on antihydrogen. In EMPI, the magnetron frequency is measured precisely, and then we observe small changes to the magnetron frequency as the magnetic field decreases. In the process of analyzing the experimental data from each of these measurements, subtleties in the motion of electron clouds are revealed. Some of these measurement techniques help us to understand systematic errors in the ALPHA collaboration's test of the weak equivalence principle. Other techniques are used to inform experimental procedures and help explain the behavior of ALPHA's Penning-Malmberg traps. Most of these ideas could be applied to many Penning-Malmberg traps, provided that they have the ability to image charged particles. Unknown magnetic fields, patch potentials, and misalignment pose difficulties for many experiments, so implementing these cloud-based measurements could benefit other research groups.

Subjective Bayesianism and Humean decision theory are dominant as both prescriptive and descriptive accounts of reasoning and rational decision-making. A subsequent genre of work within these paradigms acknowledges that the basic theories suffer from certain limitations or unexplained paradoxes, then seeks to modify them so as to remedy the defect. I develop arguments both against the original, "pure" paradigms and against certain attempts to correct them, making a case for a pluralist account of knowledge and decision-making.

Due to recent technological advances in the generation, manipulation, and detection of non-classical light, quantum light spectroscopy has gained attention as a candidate for expanding the current capabilities of classical laser light spectroscopy. In this dissertation, I develop an input-output formulation of quantum light spectroscopy by combining the input-output theory, traditionally used in the quantum optics community, with the perturbative expansion method for nonliear spectroscopy, traditionally used in the chemical physics community. Using this new spectroscopic formalism, we show that the optical signal in a class of quantum light spectroscopy experiments can be emulated by classical laser spectroscopy experiments. This class of quantum light spectroscopy experiments uses n = 0, 1, 2, · · · classical light pulses and an entangled photon pair (a biphoton state) where one photon acts as a reference without interacting with the matter sample.

To model the interaction between non-classical light and photosynthetic light harvesting systems, we develop a method to simulate the excitonic dynamics coupled to non-Markovian phonon degrees of freedom and to an N-photon Fock state pulse. This method combines the input-output and the hierarchical equations of motion (HEOM) formalisms into a double hierarchy of density matrix equations. We show analytically that, under weak field excitation relevant to natural photosynthesis conditions, an N-photon Fock state input and a corresponding coherent state input give rise to equal density matrices in the excited manifold. However, an N-photon Fock state input induces no off-diagonal coherence between the ground and excited subspaces, in contrast with the coherences created by a coherent state input. Detailed analysis of the absorption and emission behavior are discussed.

This dissertation chronicles the role of optical photon-based detection technologies in the past, present, and future of neutrino physics. The initial chapters summarize the history of the field, following chapters explaining key areas of current research. The focus splits then splits, first covering studies with the current-generation, kiloton-scale SNO+ experiment, which has operated with significant amounts of liquid scintillator as its target since 2020. The next sections highlight work undertaken toward the development of a new paradigm known as “hybrid” detection, which aims to benefit from the two optical light emission mechanisms, Cherenkov radiation and scintillation, currently drawn on separately in today’s experiments.

For SNO+, the experiment is described and this work explores the first demonstrations of α and instrumental background rejection on scintillator data, performed using likelihood-ratio-based classification with hit timing. These demonstrations provide powerful tools for a broad range of physics analyses in SNO+. Additionally, an analysis to determine the 8B solar neutrino flux is performed on two datasets, one from when the SNO+ detector was only partially filled with liquid scintillator for an extended period of time due to the COVID-19 pandemic, and one from when the detector was completely full with the final scintillator cocktail for a period of over a year. The measured flux in both periods, [5.13+1.29−1.11(stat.)+0.45−0.53(syst.)]×10^6 cm^−2 s^−1 and [5.74+0.84−0.77(stat.)]×10^6 cm^−2 s^−1 respectively, is consistent with theoretical predictions from leading Standard Solar Models. This gives confidence in the understanding of SNO+’s operations in this period and adds to the family of measurements made of this flux around the community.

Subsequent discussion introduces the hybrid paradigm and outlines the areas where this technology is maturing. This dissertation presents key explorations into the physics potential at large-scales of this technology using well-motivated modeling and reconstruction for the first time. The potential for neutrinoless double beta decay and CNO solar neutrino flux measurements are examined, with capabilities akin to or exceeding state of the art experiments in a range of scenarios. Also presented is the particle identification capability of the novel scintillating medium water-based liquid scintillator based on lab-measured timing and light yield properties, with substantial rejection power identified between α and β signals. These explorations provide a confirmation of the possibilities for hybrid detection and help pave the way for concrete realizations of these technologies at larger scales.

The relentless global pursuit of food and fiber production, often at the expense of natural ecosystems, has resulted in agricultural systems that degrade local biodiversity and environmental quality. While farmers have traditionally possessed the knowledge to maintain soil health and ecosystem balance, modern industrial agriculture has shifted towards simplistic, input-dependent practices. Organic farming offers a step towards sustainability by reducing synthetic inputs, yet it often falls short, still relying on organic substitutes and failing to address deeper ecological concerns. In contrast, soil health management practices, rooted in principles from the Natural Resource Conservation Service (NRCS), offer holistic strategies beyond mere input substitution. These practices prioritize maximizing living roots and soil cover, fostering biodiversity, and minimizing soil disturbance. However, practices that put these principles into action such as cover crops and reduced tillage remain underutilized, even among organic farmers. Understanding the barriers to the adoption of soil health management is crucial for transitioning to a more balanced agricultural paradigm that sustains productivity and environmental integrity.Most of our current understanding of the impacts of soil health management comes from research-station trials that isolate 1-2 practices at a time, within a single edaphic and climatic context. Recent on-farm research endeavors to bridge this gap by examining how management practices impact soil health metrics in real-world settings. Rebuilding soil organic matter (SOM) is a core goal of soil health management, given its manifold benefits, including supporting soil life and enhancing structure and nutrient availability. Increasing SOM levels aligns with short- and long-term goals of bolstering soil health and combating climate change through carbon sequestration. However, it isn’t clear how implementation of soil health practices, as utilized on actively managed farms, impacts these different carbon goals. Beyond carbon, soils provide many critical ecosystem services, and the impacts of soil health management on various soil-mediated ecosystem services and general multifunctionality is not well resolved. Managing farms for multiple ecosystem services beyond crop production can also present challenges, as trade-offs and conflicting priorities often arise. Understanding the intricate interplay between local soil characteristics, management practices, and various stakeholder objectives is essential for crafting effective policies. My dissertation addresses these challenges by delving into three key areas of agricultural development: identifying barriers to adopting soil health practices, exploring the impacts of management on soil carbon, and assessing the relationship between management practices and multiple ecosystem services. By integrating social, economic, and environmental perspectives, my dissertation informs policies that facilitate the transition to sustainable soil management practices, fostering a more resilient and environmentally sound food system. Briefly, we find that different farming models face unique and varied challenges in adopting soil health practices. On farms with higher levels of continuous living cover, reduced disturbance, and crop diversity, we observe higher carbon stocks and increased mineral-associated and particulate organic matter. We also find that management tends to be more influential on distinct carbon outcomes relative to inherent soil properties. Lately, we identified eleven beneficial relationships between various soil health practices and soil-mediated ecosystem services including yield, soil fertility, carbon sequestration, nutrient cycling, soil microbial diversity, and mitigating excess end-of-season soil nitrate. Continuous living cover in particular emerges as a key practice to enhance multiple services simultaneously (ecosystem multifunctionality). While not a panacea, improving soil management practices represents a crucial step toward achieving multifunctional and sustainable agricultural landscapes.

This dissertation provides a distinct class-based explanation of China’s transition from socialism to capitalism. Its overarching argument is that the way in which urban industrial workers – ideologically and rhetorically celebrated as the “leading class” of Chinese socialism – interacted with the Party-state in the late 1970s and throughout the 1980s was a crucial causal ingredient in the making of China’s transition to capitalism. More specifically, this dissertation argues that the patterns and modes of interaction between workers and the Party-state during this period shaped and derailed the Party leaders’ efforts to pursue incipient marketization within the parameters of socialism (i.e. to build “market socialism” in China). Whereas the post-Mao Party leadership turned to market socialism as a way out of the profound crisis of the late 1970s, the patterns and modes of interaction between urban industrial workers and the Party-state set off one crisis after another throughout the 1980s. China’s market socialism collapsed within a decade under the strain of these intensifying crisis cycles. It was only in the context of such derailment of China’s market socialism did a full-blown transition to capitalism become an appealing option for the ruling elite, which they relentlessly pursued in the 1990s.

Based on a wide range of historical source materials, I explicate this argument by tracing a series of political contestations and policy maneuvers centered on the issue of workplace democracy, along with their economic and political aftermaths, over China’s “long 1980s” (the period between the end of the Mao era in 1976 and the pro-democracy movements in 1989). These contestations and maneuvers played a pivotal role in shaping not only the trajectory of China’s enterprise reform, but also the fate of China’s socialist political economy more broadly.