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Togedule: Scheduling Meetings with Large Language Models and Adaptive Representations of Group Availability
No full textScheduling is a perennial-and often challenging-problem for many groups. Existing tools are mostly static, showing an identical set of choices to everyone, regardless of the current status of attendees' inputs and preferences. In this paper, we propose Togedule, an adaptive scheduling tool that uses large language models to dynamically adjust the pool of choices and their presentation format. With the initial prototype, we conducted a formative study (N=10) and identified the potential benefits and risks of such an adaptive scheduling tool. Then, after enhancing the system, we conducted two controlled experiments, one each for attendees and organizers (total N=66). For each experiment, we compared scheduling with verbal messages, shared calendars, or Togedule. Results show that Togedule significantly reduces the cognitive load of attendees indicating their availability and improves the speed and quality of the decisions made by organizers
System thinking to analyze the Market penetration of Two-Wheeled vs Four-Wheeled EVs in India
No full textThis thesis analyzes the disparate market penetration rates of electric two-wheelers (E2Ws) and electric four-wheelers (E4Ws) in India, using systems thinking approaches to understand the underlying dynamics and propose strategic interventions. In 2024, while E2Ws have achieved 4.43% market penetration, E4Ws lag significantly at 1.91%, despite similar policy support. Through force field analysis and stakeholder value mapping, this research identifies key factors driving this disparity and evaluates their temporal evolution over three time horizons.
The analysis reveals that E2Ws benefit from stronger driving forces, including urban suitability, favorable total cost of ownership, and simpler charging solutions, with 91% of users relying on home charging. In contrast, E4Ws face more substantial barriers, particularly in upfront costs, charging infrastructure requirements, and range anxiety. Technical modeling of key Figures of Merit (FOMs) demonstrates how different optimization challenges affect each segment's market acceptance.
The research culminates in recommendations for accelerating E4W adoption, emphasizing the need for India-specific models priced similar to internal combustion engine (ICE) vehicle, localized manufacturing ecosystems, robust charging infrastructure, and innovative financing solutions. The findings suggest that while E2W adoption will continue to grow naturally, E4W penetration requires coordinated interventions across manufacturing, technology, infrastructure, policy, and consumer awareness dimensions. This research contributes to understanding how systems thinking can inform strategic planning for electric vehicle adoption in emerging markets, with specific implications for India's goal of 30% EV penetration by 2030.S.M
Design of High-Resolution SAR ADC for Detection of Sub-Cortical Neuron Action Potentials for BMI Applications
No full textThe advancement of brain-machine interfaces (BMIs) requires neural signal acquisition systems that are capable of resolving both fast, low-amplitude action potentials (APs) and slow, higher-amplitude local field potentials (LFPs) under stringent power and area constraints. This thesis presents the design and simulation of a high-resolution, low-power successive approximation register (SAR) analog-to-digital converter (ADC) tailored for sub-cortical neural signal detection. To optimize dynamic range and reduce power consumption, a novel adaptive zoom-and-tracking architecture is introduced, enabling the ADC to dynamically adjust its reference window based on LFP trends while maintaining high-resolution capture of APs. The proposed system integrates a bootstrapped track-and-hold circuit, a differential capacitive DAC, and a strong-arm comparator in the analog front-end, alongside a digital FIR filter and SAR logic with zoom-range control in the digital domain. Simulations validate the functionality of each subsystem independently and in concert, demonstrating the system’s ability to dynamically isolate APs from LFP-dominated baselines while reducing analog power draw by over 60% compared to fixed-range ADCs. This work offers a promising approach for scalable, energy-efficient neural recording architectures suited to future BMI applications.M.Eng
Electrifying Hydroformylation Catalysts Exposes Voltage-Driven C–C Bond Formation
No full textElectrochemical reactions can access a significant range of driving forces under operationally mild conditions and are thus envisioned to play a key role in decarbonizing chemical manufacturing. However, many reactions with well-established thermochemical precedents remain difficult to achieve electrochemically. For example, hydroformylation (thermo-HFN) is an industrially important reaction that couples olefins and carbon monoxide (CO) to make aldehydes. However, the electrochemical analogue of hydroformylation (electro-HFN), which uses protons and electrons instead of hydrogen gas, represents a complex C-C bond-forming reaction that is difficult to achieve at heterogeneous electrocatalysts. In this work, we import Rh-based thermo-HFN catalysts onto electrode surfaces to unlock electro-HFN reactivity. At mild conditions of room temperature and 5 bar CO, we achieve Faradaic efficiencies of up to 15% and turnover frequencies of up to 0.7 h-1. This electro-HFN rate is an order of magnitude greater than the corresponding thermo-HFN rate at the same catalyst, temperature, and pressure. Reaction kinetics and operando X-ray absorption spectroscopy provide evidence for an electro-HFN mechanism that involves distinct elementary steps relative to thermo-HFN. This work demonstrates a step-by-step experimental strategy for electrifying a well-studied thermochemical reaction to unveil a new electrocatalyst for a complex and underexplored electrochemical reaction
Nuclear Ship Safety Handbook
No full textAt present, there exists no clear, unified public document in the incorporation of design safety for nuclear civilian ships. Historically, there has been developed research into this area due to political development in the “Atoms for Peace” era. However, as of recent, the only development has been through standards institutions related to Floating Nuclear Power Plants (commonly known as FLOPPS) and by the Russian Federation with their nuclear icebreaker development. This paper uses this research data and standards and combines it with the operational experiences during civilian maritime nuclear operations to provide unique insights into potential issues and resolutions in the design efficacy of maritime nuclear operations. The goal, therefore, is to provide a strong basis for initial safety on key areas that require nuclear and maritime regulatory research and development in the coming years to prepare for nuclear propulsion in the maritime industry. The paper is isolated into multiple chapters in the areas that involve overlapping nuclear/maritime safety design decisions that will be encountered by engineers. Chapter 1 establishes the principles andm philosophy behind the safety discussion for nuclear maritime and discusses key topics that relate to the overall ship design. Chapter 2 provides design details on the reactor compartment and other considerations when designing the reactor compartment. Chapter 3 describes the various hazards the reactor plant should be resilient against and avenues in establishing resiliency. Chapter 4 discusses the propulsion system and key considerations when evaluating different propulsion designs. Chapter 5 provides emergency power considerations for design determinations. Chapter 6 provides an event tree analysis on the major initiating events when operating a nuclear ship. Chapter 7 outlines the port operating procedures including avenues for establishing porting requirements for nuclear ships
High-resolution direct thrust characterization of electrospray thrusters with EMI-BF4 at different temperatures and polarities
No full textElectrospray thrusters have garnered significant attention throughout the years as an exceptional propulsion technology for nano- and picosatellites due to their efficiency and precise thrust control. They operate on the principle of electrostatically accelerating charged particles (liquid droplets, pure ions or their mixtures) from ionic liquids and other low-volatility propellants, which are extracted from a Taylor-cone formation on top of porous emitter arrays. In this work we characterized the thrust performance of electrospray thrusters with the ionic liquid 1-ethyl-3-methylimidazoliumtetrafluoroborate (EMI-BF4) as well as an attempt with an acetate-based ionic liquid. The arrays were operated at different polarities and at elevated temperatures of up to 43 °C which led to a decrease in viscosity and enhanced current emission for EMI-BF4 with a factor of 1.43 at equal voltage levels. Temperature related effects resulted in a thrust difference of 3% between the maximum and minimum temperature throughout the tested current range. Thrust measurements for emission currents between 10 µA and 200 µA revealed a detectable and temperature independent difference between the positive and negative mode in favor of the negative polarity, indicating different ion-regimes compared to most data found in literature. The paper presents a novel thrust measurement setup for micro-propulsion systems based on a counterbalanced double pendulum thrust balance that achieves nanonewton resolution with the option to heat several thrusters. A comprehensive overview of the test setup and calculations of obtained electrospray parameters from experimental data is presented
Wireless Systems for a Sustainable Future: From Battery-Free Subsea IoT to THz-Based Agriculture Monitoring
No full textThis thesis describes how wireless sensing can drive significant advancements in climate and sustainability. Specifically, it shows how we can leverage diverse signals—acoustics, ultrasound, THz, and optics— in unconventional ways to unlock new capabilities in underwater climate monitoring, food safety, and disaster response. The thesis introduces two novel technologies. The first technology enables long-term, ultra-low power ocean sensor networks for use in climate modeling, marine monitoring, and sustainable aquaculture. Unlike existing IoT technologies – like Bluetooth, WiFi, and GPS – which cannot work underwater, we design and implement an ultra-low power subsea backscatter communication system, enabling battery-free underwater imaging, sensing and localization. Second, the thesis describes a new technology that can support sustainability in agriculture through real-time food quality assessment that reduces food waste. In contrast to existing food quality technologies that require direct contact with produce, we introduce a new wireless system for accurate, non-invasive sensing using sub-THz signals. We describe the design, implementation, and evaluation of multiple systems that leverage these technologies to monitor the ocean and food waste: First, we present a ultra-wideband metamaterial sensor design that facilitates scalable, and long-range battery-free underwater communication. Next, we describe a system that can push the throughput of this technology using higher order modulation. Beyond building sensor networks, we demonstrate their real-world potential through two systems: one for underwater localization that uses rich spatio-temporal-spectral features for accurate positioning, and another for battery-free imaging that fuses acoustic and optical signals to capture color images in the dark. Finally, we present a novel solution for accurate fruit ripeness sensing using sub-terahertz wireless signals. These systems unlock new IoT applications in climate modeling, aquaculture, robotics, and agriculture.Ph.D
Automation and Microfluidics for the Efficient, Fast, and Focused Reaction Development of Asymmetric Hydrogenation Catalysis
No full textAutomation and microfluidic tools potentially enable efficient, fast, and focused reaction development of complex chemistries, while minimizing resource- and material consumption. The introduction of automation-assisted workflows will contribute to the more sustainable development and scale-up of new and improved catalytic technologies. Herein, the application of automation and microfluidics to the development of a complex asymmetric hydrogenation reaction is described. Screening and optimization experiments were performed using an automated microfluidic platform, which enabled a drastic reduction in the material consumption compared to conventional laboratory practices. A suitable catalytic system was identified from a library of RuII-diamino precatalysts. In situ precatalyst activation was studied with 1H/31P nuclear magnetic resonance (NMR), and the reaction was scaled up to multigram quantities in a batch autoclave. These reactions were monitored using an automated liquid-phase sampling system. Ultimately, in less than a week of total experimental time, multigram quantities of the target enantiopure alcohol product were provided by this automation-assisted approach
Nonlinear Ion Dynamics Enable Spike Timing Dependent Plasticity of Electrochemical Ionic Synapses
No full textProgrammable synaptic devices that can achieve timing-dependent weightupdates are key components to implementing energy-efficient spiking neuralnetworks (SNNs). Electrochemical ionic synapses (EIS) enable theprogramming of weight updates with very low energy consumption and lowvariability. Here, the strongly nonlinear kinetics of EIS, arising from nonlineardynamics of ions and charge transfer reactions in solids, are leveraged toimplement various forms of spike-timing-dependent plasticity (STDP). Inparticular, protons are used as the working ion. Different forms of the STDPfunction are deterministically predicted and emulated by a linearsuperposition of appropriately designed pre- and post-synaptic neuronsignals. Heterogeneous STDP is also demonstrated within the array tocapture different learning rules in the same system. STDP timescales arecontrollable, ranging from milliseconds to nanoseconds. The STDP resultingfrom EIS has lower variability than other hardware STDP implementations,due to the deterministic and uniform insertion of charge in the tunablechannel material. The results indicate that the ion and charge transferdynamics in EIS can enable bio-plausible synapses for SNN hardware withhigh energy efficiency, reliability, and throughput