Publications

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We present a proof-of-concept demonstration of a narrow linewidth $^{87}$Rb magneto-optical trap (MOT) operating on the narrow linewidth $5S_{1/2}$ → $6P_{3/2}$ transition at 420 nm. We stabilized the absolute frequency of the 420 nm laser to an atomic transition in $^{87}$Rb and demonstrate a MOT using 420 nm light driving the $5S_{1/2}$, $F = 2$ → $6P_{3/2}, F' = 3$ transition. We then use tome-of-flight measurements to characterize the 420 nm MOT temperature, observing a minimum temperature of about $T^{(420)}_{horizontal}$ = 150μK and $T^{(420)}_{vertical}$ = 250μK before the opportunity to perform significant characterization and optimization. Although this temperature is significantly higher then the expected 420 nm Doppler cooling limit ($T_D^{(420)}$ ≈ 34 μK), these are already approaching the Doppler limit of a standard 780 nm MOT ($T_D^{(780)}$ ≈ 146 μK). We believe that with further optimization the Doppler cooling limit of ≈ 34 μK can be achieved. This initial result answers our key research question and demonstrates the viability of applying narrow linewidth laser cooling as a robust technique for future fieldable quantum sensors.

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This document is a reference guide to the Xyce™ Parallel Electronic Simulator, and is a companion document to the Xyce™ Users' Guide. The focus of this document is (to the extent possible) exhaustively list device parameters, solver options, parser options, and other usage details of Xyce™. This document is not intended to be a tutorial. Users who are new to circuit simulation are better served by the Xyce™ Users' Guide.

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A collection of x-ray computed tomography scans of candy.

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A collection of x-ray computed tomography scans of mineral specimens from private collections.

Accurate representation of environmental controllers of soil organic carbon (SOC) stocks in Earth System Model (ESM) land models could reduce uncertainties in future carbon–climate feedback projections. Using empirical relationships between environmental factors and SOC stocks to evaluate land models can help modelers understand prediction biases beyond what can be achieved with the observed SOC stocks alone. In this study, we used 31 observed environmental factors, field SOC observations (n = 6,213) from the continental United States, and two machine learning approaches (random forest [RF] and generalized additive modeling [GAM]) to (a) select important environmental predictors of SOC stocks, (b) derive empirical relationships between environmental factors and SOC stocks, and (c) use the derived relationships to predict SOC stocks and compare the prediction accuracy of simpler model developed with the machine learning predictions. Out of the 31 environmental factors we investigated, 12 were identified as important predictors of SOC stocks by the RF approach. In contrast, the GAM approach identified six (of those 12) environmental factors as important controllers of SOC stocks: potential evapotranspiration, normalized difference vegetation index, soil drainage condition, precipitation, elevation, and net primary productivity. The GAM approach showed minimal SOC predictive importance of the remaining six environmental factors identified by the RF approach. Our derived empirical relations produced comparable prediction accuracy to the GAM and RF approach using only a subset of environmental factors. The empirical relationships we derived using the GAM approach can serve as important benchmarks to evaluate environmental control representations of SOC stocks in ESMs, which could reduce uncertainty in predicting future carbon–climate feedbacks.

Barium titanate (BTO) is a ferroelectric material used in capacitors because of its high bulk dielectric constant. However, the impact of the size of BTO on its dielectric constant is not yet fully understood and is highly contested. Here, we present an investigation into the dielectric constant of BTO nanoparticles with diameters ranging between 50 and 500 nm. BTO nanoparticles were incorporated into acrylonitrile butadiene styrene and injection molded into parallel plate capacitors, which were used to determine nanocomposite dielectric constants. The dielectric constants of BTO nanoparticles were obtained by combining experimental measurements with computational results from COMSOL simulations of ABS-matrix nanocomposites containing BTO. The dielectric constant of BTO was observed to be relatively constant at nanoparticle diameters as small as 200 nm but sharply declined at smaller nanoparticle sizes. These results will be useful in the development of improved energy storage and power conditioning systems utilizing BTO nanoparticles.

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Battery storage systems are increasingly being installed at photovoltaic (PV) sites to address supply-demand balancing needs. Although there is some understanding of costs associated with PV operations and maintenance (O&M), costs associated with emerging technologies such as PV plus storage lack details about the specific systems and/or activities that contribute to the cost values. This study aims to address this gap by exploring the specific factors and drivers contributing to utility-scale PV plus storage systems (UPVS) O&M activities costs, including how technology selection, data collection, and related and ongoing challenges. Specifically, we used semi-structured interviews and questionnaires to collect information and insights from utility-scale owners and operators. Data was collected from 14 semi-structured interviews and questionnaires representing 51.1 MW with 64.1 MWh of installed battery storage capacity within the United States (U.S.). Differences in degradation rate, expected life cycle, and capital costs are observed across different storage technologies. Most O&M activities at UPVS related to correcting under-performance. Fires and venting issues are leading safety concerns, and owner operators have installed additional systems to mitigate these issues. There are ongoing O&M challenges due the lack of storage-specific performance metrics as well as poor vendor reliability and parts availability. Insights from this work will improve our understanding of O&M consideration at PV plus storage sites.

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