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  1. The effect of catalyst addition on H2 evolution from composite electrodes of La0.7Sr0.3TiO3 (LST) and BaZr0.1Ce0.7Y0.1Yb0.1O3−δ (BZCYYb) was studied. Starting with symmetric cells (LST∣∣BZCYYb∣∣LST), Pt was added to one or both electrodes, after which i–V polarization measurements were performed in humidified H2 at 723 and 773 K. The base cells showed very high impedances but these decreased dramatically upon addition of Pt to both electrodes. When Pt was added to only one electrode, the cells performed as diodes, showing that Pt was necessary for H2 dissociation but not for H recombination. The effects of adding Ru, W, Re and Femore »were also studied. DFT calculations helped confirm that H recombination on BaZrO3 is expected to be barrierless. The implications of these results for potential application to electrochemical synthesis of ammonia are discussed.« less
  2. Orchestration tools may support K-12 teachers in facilitating student learning, especially when designed to address classroom stakeholders’ needs. Our previous work revealed a need for human-AI shared control when dynamically pairing students for collaborative learning in the classroom, but offered limited guidance on the role each agent should take. In this study, we designed storyboards for scenarios where teachers, students and AI co-orchestrate dynamic pairing when using AI-based adaptive math software for individual and collaborative learning. We surveyed 54 math teachers on their co-orchestration preferences. We found that teachers would like to share control with the AI to lessen theirmore »orchestration load. As well, they would like to have the AI propose student pairs with explanations, and identify risky proposed pairings. However, teachers are hesitant to let the AI auto-pair students even if they are busy, and are less inclined to let AI override teacher-proposed pairing. Our study contributes to teachers’ needs, preference, and boundaries for how they want to share the task and control of student pairing with the AI and students, and design implications in human-AI co-orchestration tools.« less
  3. Hsiao, I. ; Sahebi, S. ; Bouchet, F. ; Vie, J. J. (Ed.)
    Constructing effective and well-balanced learning groups is important for collaborative learning. Past research explored how group formation policies affect learners’ behaviors and performance. With the different classroom contexts, many group formation policies work in theory, yet their feasibility is rarely investigated in authentic class sessions. In the current work, we define feasibility as the ratio of students being able to find available partners that satisfy a given group formation policy. Informed by user-centered research in K-12 classrooms, we simulated pairing policies on historical data from an intelligent tutoring system (ITS), a process we refer to as SimPairing. As part ofmore »the process for designing a pairing orchestration tool, this study contributes insights into the feasibility of four dynamic pairing policies, and how the feasibility varies depending on parameters in the pairing policies or different classes. We found that on average, dynamically pairing students based on their in-the-moment wheel-spinning status can pair most struggling students, even with moderate constraints of restricted pairings. In addition, we found there is a trade-off between the required knowledge heterogeneity and policy feasibility. Furthermore, the feasibility of pairing policies can vary across different classes, suggesting a need for customization regarding pairing policies.« less
  4. To accurately determine the reliability of SRAMs, we propose a method to estimate the wearout parameters of FEOL TDDB using on-line data collected during operations. Errors in estimating lifetime model parameters are determined as a function of time, which are based on the available failure sample size. Systematic errors are also computed due to uncertainty in estimation of temperature and supply voltage during operations, as well as uncertainty in process parameters and use conditions.
  5. Abstract With the advance of particle accelerator and detector technologies, the neutrino physics landscape is rapidly expanding. As neutrino oscillation experiments enter the intensity and precision frontiers, neutrino–nucleus interaction measurements are providing crucial input. MINERvA is an experiment at Fermilab dedicated to the study of neutrino–nucleus interactions in the regime of incident neutrino energies from one to few GeV. The experiment recorded neutrino and antineutrino scattering data with the NuMI beamline from 2009 to 2019 using the Low-Energy and Medium-Energy beams that peak at 3GeV and 6GeV, respectively. This article reviews the broad spectrum of interesting nuclear and particle physicsmore »that MINERvA investigations have illuminated. The newfound, detailed knowledge of neutrino interactions with nuclear targets thereby obtained is proving essential to continued progress in the neutrino physics sector.« less
    Free, publicly-accessible full text available December 1, 2022
  6. Accelerated lifetime tests are necessary for reliability evaluation of circuits and systems, but the parameters for choosing the test conditions are often unknown. Furthermore, reliability testing is generally performed on test structures that have different properties than actual circuits and systems, which may create inconsistencies in how circuits and systems work in reality. To combat this problem, we use ring oscillators, which are similar to circuits, based on the 14nm FinFET node as the circuit vehicle to extract wearout data. We explore the effects of testing time, sample size, and number of stages on the ability to detect failures formore »various test conditions, focusing on front-end time dependent dielectric breakdown, which is one of the most dominant wearout mechanisms.« less
  7. Effective assessment of degradation induced by electromigration (EM) is necessary for the design of reliable circuits based on FinFET technology. In this paper, a new methodology is proposed where FinFET SRAM cell array activity is used to evaluate the resistance degradation due to EM. The implementation of this methodology consists of analysis of stress evolution, a time-dependent resistance model, cell array activity extraction, and a customized algorithm for cell array reliability evaluation. The stress model is derived from the material transport equation which contains the driving forces due to the gradient of vacancy concentration,temperature, hydrostatic stress, and EM itself. Themore »time-dependent resistance shift describes the effect of stress evolution. The customized algorithm is applied to calculate the resistance degradation while considering the characteristics of metal wire arrays in SRAMs. The statistical degradation in a FinFET SRAM cell array reveals that, for the tested case, in addition to the percentage of the workload in various operating modes, the cell array activity distribution also affects EM degradation. More evenly distributed cell activity results in better EM reliability.« less
  8. Free, publicly-accessible full text available November 1, 2022
  9. Free, publicly-accessible full text available November 1, 2022