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At least 883 records · Page 49

Influences of Alkali Metal Cation Interactions on N2 Coordination to Iron(I) Beta-Diketiminate Complexes in Electrolyte Solutions

N2 functionalization reactions often use stable, isolable N2-bound complexes and low temperatures or highly activated reagents. However, little work has focused on systems where N2 binds weakly, and the N2 binding equilibrium can be modulated. Here, we describe analysis of surprising trends in alkali metal cation solvation on the formation of an anionic iron(I) beta-diketiminate complex and the subsequent N2 binding equilibrium. Variable temperature UV-vis spectroscopy shows that increased ionic strength in the coordinating solvent tetrahydrofuran promotes N2 coordination. Additionally, less solvated alkali metal cations in noncoordinating 2-methyltetrahydrofuran (MeTHF) stabilize N2 coordination, likely through the formation of contact ion pairs in solution that have enhanced N2 binding. Ionic strength has little effect on the energetics of N2 coordination to these proposed contact ion pairs in MeTHF. When the electrochemical analysis is done at –78 °C, there is an irreversible reduction of iron(II) and an anodically shifted oxidation, which is attributed to the formation of the spectroscopically observed N2 complex. Finally, bulk electrolysis is used to verify the electrochemical formation of the N2-bound anionic iron(I) complex. These studies demonstrate a new strategy for promoting N2 coordination by changing solution properties, which is relevant to homogeneous electrochemical N2 reduction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of Metal Stresses in Arabidopsis thaliana Using Hyperspectral Reflectance Imaging

Industrial accidents, such as the Fukushima and Chernobyl disasters, release harmful chemicals into the environment, covering large geographical areas. Natural flora may serve as biological sensors for detecting metal contamination, such as cesium. Spectral detection of plant stresses typically employs a few select wavelengths and often cannot distinguish between different stress phenotypes. In this study, we apply hyperspectral reflectance imaging in the visible and near-infrared along with multivariate curve resolution (MCR) analysis to identify unique spectral signatures of three stresses in Arabidopsis thaliana : salt, copper, and cesium. While all stress conditions result in common stress physiology, hyperspectral reflectance imaging and MCR analysis produced unique spectral signatures that enabled classification of each stress. As the level of potassium was previously shown to affect cesium stress in plants, the response of A. thaliana to cesium stress under variable levels of potassium was also investigated. Increased levels of potassium reduced the spectral response of A. thaliana to cesium and prevented changes to chloroplast cellular organization. While metal stress mechanisms may vary under different environmental conditions, this study demonstrates that hyperspectral reflectance imaging with MCR analysis can distinguish metal stress phenotypes, providing the potential to detect metal contamination across large geographical areas.

multivariate curve resolution↗

Thresholding Analysis and Feature Extraction from 3D Ground Penetrating Radar Data for Noninvasive Assessment of Peanut Yield

This study explores the efficacy of utilizing a novel ground penetrating radar (GPR) acquisition platform and data analysis methods to quantify peanut yield for breeding selection, agronomic research, and producer management and harvest applications. Sixty plots comprising different peanut market types were scanned with a multichannel, air-launched GPR antenna. Image thresholding analysis was performed on 3D GPR data from four of the channels to extract features that were correlated to peanut yield with the objective of developing a noninvasive high-throughput peanut phenotyping and yield-monitoring methodology. Plot-level GPR data were summarized using mean, standard deviation, sum, and the number of nonzero values (counts) below or above different percentile threshold values. Best results were obtained for data below the percentile threshold for mean, standard deviation and sum. Data both below and above the percentile threshold generated good correlations for count. Correlating individual GPR features to yield generated correlations of up to 39% explained variability, while combining GPR features in multiple linear regression models generated up to 51% explained variability. The correlations increased when regression models were developed separately for each peanut type. This research demonstrates that a systematic search of thresholding range, analysis window size, and data summary statistics is necessary for successful application of this type of analysis. The results also establish that thresholding analysis of GPR data is an appropriate methodology for noninvasive assessment of peanut yield, which could be further developed for high-throughput phenotyping and yield-monitoring, adding a new sensor and new capabilities to the growing set of digital agriculture technologies.

54 ENVIRONMENTAL SCIENCES↗

Isotopic analysis of sub-nanogram neodymium loads using new ATONA™ amplifiers

The long-term gains of the ATONA™ amplifiers are shown to have less than 1 ppm variability. Repeat measurements of the JNdi-1 reference material demonstrate the ability of the ATONA™ amplification technology to make measurements of 143 Nd/ 144 Nd ratios with 23 ppm external reproducibility on 100-pg loads. The effect of increasing integration time on analytical reproducibility is also displayed as increasing integration time from 10 to 30s reduced the external measurement uncertainty from 37 to 23 ppm. These measurements represent an improvement of more than a factor of 3 in external measurement reproducibility relative to previously published 143 Nd/ 144 Nd measurements of 100-pg loads. Furthermore, this new technology will allow for the measurement of smaller samples for precise isotope ratios and open new avenues of research in the geological and nuclear forensic communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Prognostic Importance of MRI-Detected Extramural Venous Invasion in Rectal Cancer: A Literature Review and Systematic Meta-Analysis

Extramural venous invasion (EMVI) is recognized as a poor prognostic factor in rectal cancer. There are well-documented limitations associated with pathology detection of EMVI, including variable reporting and the inability to use it preoperatively to guide neoadjuvant treatment. Magnetic resonance imaging (MRI)-detected EMVI (mrEMVI) has been proposed as an imaging biomarker. This review assesses the prognostic significance of mrEMVI on survival outcomes and whether regression of mrEMVI after neoadjuvant therapy is associated with improvements in survival.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The frequency of extreme X-ray variability for radio-quiet quasars

ABSTRACT We analyse 1598 serendipitous Chandra X-ray observations of 462 radio-quiet quasars to constrain the frequency of extreme amplitude X-ray variability that is intrinsic to the quasar corona and innermost accretion flow. The quasars in this investigation are all spectroscopically confirmed, optically bright (mi ≤ 20.2), and contain no identifiable broad absorption lines in their optical/ultraviolet spectra. This sample includes quasars spanning z ≈ 0.1–4 and probes X-ray variability on time-scales of up to ≈12 rest-frame years. Variability amplitudes are computed between every epoch of observation for each quasar and are analysed as a function of time-scale and luminosity. The tail-heavy distributions of variability amplitudes at all time-scales indicate that extreme X-ray variations are driven by an additional physical mechanism and not just typical random fluctuations of the coronal emission. Similarly, extreme X-ray variations of low-luminosity quasars seem to be driven by an additional physical mechanism, whereas high-luminosity quasars seem more consistent with random fluctuations. The amplitude at which an X-ray variability event can be considered extreme is quantified for different time-scales and luminosities. Extreme X-ray variations occur more frequently at long time-scales (Δt ≳ 300 d) than at shorter time-scales and in low-luminosity quasars compared to high-luminosity quasars over a similar time-scale. A binomial analysis indicates that extreme intrinsic X-ray variations are rare, with a maximum occurrence rate of $\lt 2.4{{\ \rm per\ cent}}$ of observations. Finally, we present X-ray variability and basic optical emission-line properties of three archival quasars that have been newly discovered to exhibit extreme X-ray variability.

Timlin, III, John D.↗

Comparing traditional and Bayesian approaches to ecological meta‐analysis

Abstract Despite the wide application of meta‐analysis in ecology, some of the traditional methods used for meta‐analysis may not perform well given the type of data characteristic of ecological meta‐analyses. We reviewed published meta‐analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies ( n i ) and the number of studies or records ( k ) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta‐analysis methods for estimating a mean effect size and its uncertainty interval. Our literature review showed that n i and k were highly variable, distributions were right‐skewed and were generally small (median n i = 5, median k = 44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (<40), 95% coverage was achieved by a confidence interval (CI) based on the t distribution that uses an adjusted standard error (the Hartung–Knapp–Sidik–Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z distribution CIs had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta‐analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults. In general, for a simple random‐effects meta‐analysis, the performance of the best frequentist and Bayesian methods was similar for the same combinations of factors ( k and mean replication), though the Bayesian approach had higher than nominal (>95%) coverage for the mean effect when k was very low ( k < 15). Our literature review suggests that many meta‐analyses that used z distribution or bootstrapping CIs may have overestimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta‐analyses.

Pappalardo, Paula↗

Fitness-for-Service Analysis of Reactor Components under Flexible Load-Following Operating Conditions

Conventional power-generation plants, including nuclear plants, have been traditionally designed to provide a steady baseload energy capacity, optimizing output efficiency while minimizing variable costs. However, the growing adoption of large-scale renewable energy-generation systems, which rely on intermittent sources such as solar and wind, has introduced more variability into the energy supply in interconnected electricity grids. As a result, the next generation of power plants needs to operate in what is known as the load-following mode, requiring flexible adjustments in electricity production to align with the energy demand on the grid. This transition from the steady baseload operation to load-following operating conditions can significantly increase the number of times various plant components are exposed to transient stresses. This increased thermo-mechanical cycling can lead to accelerated material degradation, thereby elevating the risk of premature failure of a component. It becomes imperative to conduct a comprehensive analysis of fatigue, creep-fatigue, and stress corrosion cracking life, to assess the resilience of the various engineering components under these flexible load-following operating conditions. This study aims to develop a comprehensive numerical model of a light-water reactor pressure vessel (RPV) to investigate its degradation under various operating scenarios. This coupled thermo-mechanical finite element analysis evaluated the stress response of the RPV caused by considering fluctuations in thermal and mechanical loads caused by the varying pressure and temperature occurring during the load-following operation. Critical locations on the RPV are subsequently identified based on the stress response. The stress intensity factors for the postulated flaws at those locations are then calculated, followed by an evaluation of the reactor's life in accordance with the ASME Boiler and Pressure Vessel Code Section XI. This comprehensive life assessment covers a number of transients expected during the flexible load-following operation, providing invaluable insights into the RPV's structural integrity. Moreover, the development methodology can be adapted to other reactor components, as well as components of conventional power stations that are affected by varying operating conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mapping Permafrost Variability and Degradation Using Seismic Surface Waves, Electrical Resistivity, and Temperature Sensing: A Case Study in Arctic Alaska

Subsurface processes significantly influence surface dynamics in permafrost regions, necessitating utilizing diverse geophysical methods to reliably constrain permafrost characteristics. This research uses multiple geophysical techniques to explore the spatial variability of permafrost in undisturbed tundra and its degradation in disturbed tundra in Utqiagvik, Alaska. Here, we integrate multiple quantitative techniques, including multichannel analysis of surface waves (MASW), electrical resistivity tomography (ERT), and ground temperature sensing, to study heterogeneity in permafrost’s geophysical characteristics. MASW results reveal active layer shear wave velocities (V s ) between 240 and 370 m/s, and permafrost V s between 450 and 1,700 m/s, typically showing a low-high-low velocity pattern. Additionally, we find an inverse relationship between in situ V s and ground temperature measurements. The V s profiles along with electrical resistivity profiles reveal cryostructures such as cryopeg and ice-rich zones in the permafrost layer. The integrated results of MASW and ERT provide valuable information for characterizing permafrost heterogeneity and cryostructure. Corroboration of these geophysical observations with permafrost core samples’ stratigraphies and salinity measurements further validates these findings. This combination of geophysical and temperature sensing methods along with permafrost core sampling confirms a robust approach for assessing permafrost’s spatial variability in coastal environments. Our results also indicate that civil infrastructure systems such as gravel roads and pile foundations affect permafrost by thickening the active layer, lowering the V s , and reducing heterogeneity. We show how the resulting V s profiles can be used to estimate key parameters for designing buildings in permafrost regions and maintaining existing infrastructure in polar regions.

54 ENVIRONMENTAL SCIENCES↗

Ice storage model-predictive control in an office building with PV: scenario, error and sensitivity analysis

Thermal energy storage (TES) can enable more building-sited renewable electricity generation and lower utility bill costs for buildings owners and occupants, especially when there are high demand and variable time-of-use (TOU) charges. A model predictive control (MPC) strategy can offer additional savings over a schedule-based control with added complexity and reliance on forecasts. Here, this study examines savings for medium office buildings with chiller plants in three locations with building-installed solar photovoltaics (PV) to understand the impact of MPC. Control setpoints are fixed by a schedule-based control or optimized by nonlinear MPC. These control setpoints are actuated within EnergyPlus building models to simulate the utility cost of the chiller plant. NLP solutions can be unstable or unrealistic, but our results show that by regularizing the NLP, the solutions can be reasonably followed by the building model. MPC models make simplifications that lead to errors once the controller is participating in and changing the operation of the building. These errors average 9 % across the cases, showing that the most important parts of the system are represented. The no-thermal load costs are computed to show that the optimization can in some cases achieve both the minimum TOU and minimum monthly demand costs by demand management while reducing TOU energy costs by energy arbitrage. The MPC saves 35–66 % in the annual chiller plant operating costs, which is an additional savings above the schedule by 1–33 %. PV and TES are complementary and mostly independent, but a load with PV often results in better performance for the schedule. Our case study and sensitivity analysis show the importance of modeling and optimization for complex rates, but also the circumstances wherein a simpler strategy achieves the same performance with less potential for error.

14 SOLAR ENERGY↗

Hourly water-carbon interactions modulate decadal water-use efficiency trends inferred from ecosystem-scale measurements

Plant stomatal conductance regulates photosynthesis and transpiration. This physiological link affects ecosystem responses to microclimate and harmonizes carbon, energy, and water exchanges between the biosphere and atmosphere. The relationship between water losses via transpiration and carbon gains via photosynthesis can be quantified by plant water-use efficiency (WUE). While leaf- and ecosystem-scale observations both suggest rising WUE in recent decades, WUE trends inferred from the ecosystem scale are much larger than those inferred from the leaf scale or implied by theory. The unexpectedly large ecosystem-scale WUE trends complicate interpretation of ecophysiological responses to changing environmental conditions. Here, we analyze ecosystem-scale WUE inferred from 40 FLUXNET sites, each with at least 10 years of measurements. Furthermore, our results demonstrate that observed ecosystem-scale WUE trends are more sensitive to hourly weather conditions than longer-term changes in atmospheric carbon dioxide or vapor pressure deficit. Our analysis shows that Earth System Models participating in CMIP6 did not capture the observed WUE sensitivity to inter-site variability and microclimatic conditions. Collectively, our findings suggest that ecosystem-scale WUE trends reflect water-carbon interactions across multiple temporal scales, and disentangling factors contributing to emergent ecosystem responses is needed to infer ecophysiological relationships and model structures from observations.

54 ENVIRONMENTAL SCIENCES↗

Linking human-building interactions in shared offices with personality traits

Occupant behavior influences office building energy performance. The level of human-building interactions (HBIs) in shared offices strongly influences building energy use and occupant well-being. This study explored the link between occupant personality types and their behaviors of sharing energy and environment control systems and interactions with their colleagues. Inspired by the Five-Factor Model (FFM), we classified HBI behaviors into four dimensions: willingness to share control, knowledge of control, group decision behavior, and adaptive strategies. These four variables can be mapped to the four personality traits proposed by the FFM: agreeableness, openness, extraversion, and conscientiousness. Our cluster analysis identified six behavioral patterns: average (17.7%), reserved (15.3%), environmentally friendly (16.6%), role model (24.2%), self-centered (17.2%), and mechanist (9.0%). We further applied association rules, a widely utilized machine learning technique, to discover how demographics, building-related contextual factors, and perception-attitudinal factors influence HBI behaviors. Country, control feature accessibility, and group dynamics were found to be the three most influential factors that determine occupants’ HBI behaviors. Finally, the study provides insights about building design and operation, as well as policy to promote socially and environmentally desirable HBI behaviors in a shared office environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Ocean circulation and climate variability in the northern South China Sea during the Greek Minimum derived from coral Δ 14 C and Sr/Ca records

Ocean circulation transports heat, salt and nutrients, and has profound impacts on the marine environment and climate change. However, the seasonal to centennial variations of the paleocirculation of the South China Sea (SCS) and their driving forces are still unclear due to limited records. Here we reconstructed a high-resolution Δ 14 C record of a coral from Sanya to investigate the seasonal variations of the SCS ocean circulation around 2300 cal yr BP during a grand solar minimum (GSM) period. The seasonal Δ 14 C variability shows the influence of coastal upwelling caused by the East Asian Summer Monsoon (EASM) in summer and the effect of water intrusion from the western Pacific Ocean driven by the Kuroshio Intrusion (KI) in winter. Here we compiled the marine radiocarbon reservoir correction (ΔR) records since 2500 cal yr BP, which indicate a gradual decrease of upwelling significantly correlated with the EASM. Comparisons with other climate records suggest that both the EASM and KI may regulate the ocean circulation variability on centennial time scales. As a good index of the sea surface temperature (SST), our Sr/Ca record and spectral analysis results show a low temperature and a low frequency of El Niño-Southern Oscillation (ENSO) events around 2300 cal yr BP. Moreover, the composite coral Sr/Ca-SST and ENSO index records since 2500 cal yr BP show relatively low SST and weak ENSO during GSMs, supporting the modulation of tropical SST and ENSO by solar activity. Our study has provided high-resolution proxy data and revealed the driving forces of ocean circulation and climate change in the SCS at multiple time scales, which should be considered in further modeling work.

54 ENVIRONMENTAL SCIENCES↗

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

59 BASIC BIOLOGICAL SCIENCES↗

Laser interference structuring of Cu for adhesive joining of HVAC equipment

Due to potential energy and cost savings benefits, adhesive joining has been recently considered for heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems. HVAC adhesive bonding requires cost-effective and adequate surface preparations of adherents. Here, this article investigates the use of abrasion, traditional single-beam laser, and a laser-interference technique as surface preparations of copper surfaces. Surface morphology is characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM). Effective submicrometer peak-to-valley structuring with a periodicity of ∼2.7μ⁢m was demonstrated for laser-interference processing. Single-lap shear tests were conducted for 89 joints made with bondline thicknesses of 0.15 and 0.3 mm. Data on process variables and measured variables included open-time, bond length, maximum load, displacement at failure, shear lap strength, and failure mode. A statistical analysis was conducted on each lot to determine the lower limit with 95% confidence intervals for displacements at failure and shear lap strengths. A comparison is presented between the properties of laser-structured joints with respect to those prepared by abrasion, which is considered the baseline surface preparation technique. Based on this comparison, one single-beam laser technique and two laser-interference techniques were shown to exhibit vastly superior performance over the joints made with abraded specimens.

Sabau, Adrian S. [Oak Ridge National Laboratory (O↗

Assessing the Influence of Climate on the Spatial Pattern of West Nile Virus Incidence in the United States

West Nile virus (WNV) is the leading cause of mosquito-borne disease in humans in the United States. Since the introduction of the disease in 1999, incidence levels have stabilized in many regions, allowing for analysis of climate conditions that shape the spatial structure of disease incidence. Our goal was to identify the seasonal climate variables that influence the spatial extent and magnitude of WNV incidence in humans. We developed a predictive model of contemporary mean annual WNV incidence using U.S. county-level case reports from 2005 to 2019 and seasonally averaged climate variables. We used a random forest model that had an out-of-sample model performance of R 2 =0.61. Our model accurately captured the V-shaped area of higher WNV incidence that extends from states on the Canadian border south through the middle of the Great Plains. It also captured a region of moderate WNV incidence in the southern Mississippi Valley. The highest levels of WNV incidence were in regions with dry and cold winters and wet and mild summers. The random forest model classified counties with average winter precipitation levels <23.3 mm/month as having incidence levels over 11 times greater than those of counties that are wetter. Among the climate predictors, winter precipitation, fall precipitation, and winter temperature were the three most important predictive variables. We consider which aspects of the WNV transmission cycle climate conditions may benefit the most and argued that dry and cold winters are climate conditions optimal for the mosquito species key to amplifying WNV transmission. Our statistical model may be useful in projecting shifts in WNV risk in response to climate change.

60 APPLIED LIFE SCIENCES↗

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States, 2022 Edition

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The latest edition of the report focuses on systems installed through year-end 2021, and is based on data from roughly 2.5 million systems. New to the report this year is an expanded coverage of paired PV-plus-storage systems, including details on system design and pricing trends. The report describes trends related to: -Project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership -Median installed-price trends, both nationally and by state, including preliminary data for first half of 2022 -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive and econometric analysis

14 SOLAR ENERGY↗

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States (2023 Edition) [Slides]

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) and paired PV+storage systems in the United States. For the purpose of this report, distributed solar includes residential systems, roof-mounted non-residential systems, and ground-mounted systems up to 5 MW-AC. Ground-mounted systems larger than 5 MW-AC are covered in Berkeley Lab’s companion annual report, Utility-Scale Solar. The latest edition of the report is based on 3.2 million systems installed through year-end 2022, representing more than 80% of systems installed to date. The report describes and discusses key trends related to: -Project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership -Median installed-price trends, both nationally and by state -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive and econometric analysis The report also includes a multi-variate regression analysis to estimate the effects of key pricing drivers for residential systems installed in 2022.

14 SOLAR ENERGY↗