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At least 1,063 records · Page 59

Automatic and rapid calibration of urban building energy models by learning from energy performance database

Urban building energy modeling (UBEM) is attracting increasing attention in the energy modeling filed. Unlike modeling a single building using detailed building systems information, UBEM generally uses limited high-level building stock data to infer default assumptions about building characteristics and operations. Additionally, this practice inherently brings uncertainty to UBEM. This study introduced a novel method of automatic and rapid calibration of UBEM based on the annual electricity and natural gas energy use data by learning the correlations between crucial model input parameters and the building energy use from the reference building models. A case study was presented to calibrate 72 large office buildings built before 1978 in San Francisco. Seventeen model parameters were selected and Monte Carlo sampling was used to create 1000 samples that reasonably represent the parameter space. Then 1000 simulations were performed for the reference building model to create an energy performance database. The results showed that by learning from the energy performance database, it took less than four simulation runs on average to calibrate a building model. After the calibration, the distributions of each parameter were obtained to replace their single predefined default values. For example, the default lighting power density of 21.39 W/m 2 was calibrated to be 7.50 W/m 2 on average. The case study successfully demonstrated the effectiveness of the novel calibration method for UBEM in the mild climate. The method will be further tested in future for other climate zones and other building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Plasma catalytic ammonia synthesis on Ni nanoparticles: The size effect

Herein we demonstrate the synthesis of ammonia via atmospheric DBD plasma discharge over nickel nanoparticles supported on silica. We evaluated the performance of nickel nanoparticles with average sizes of 5.6nm and 13.5 nm. The smallest nanoparticle size sample resulted in an ammonia synthesis rate at least 2 times higher than that of the larger nanoparticle size sample and nickel bulk at equimolar composition. This allowed us to observe experimentally, for the first time, the size effect in the area of plasma catalysis. Moreover, the presented results allowed us to investigate a hydrogen sink metal such as nickel under atmospheric plasma conditions and determine the gas composition that resulted beneficial for this surface chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shrub and sedge rhizosphere communities display distinct affinities toward exudates and soil organic matter degradation: a quantitative stable isotope probing analysis

Warming temperatures are accelerating permafrost thaw and changing tundra vegetation, where woody shrubs are displacing sedges. Shrubs, such as Betula nana, and sedges, such as Eriophorum vaginatum, exhibit distinct life strategies including unique root-associated, or rhizosphere microbial communities. As permafrost thaws it unlocks previously unavailable carbon and nutrient sources resulting in deeper roots and a translocation of rhizosphere communities. Because permafrost microbial communities contain lower diversity and biomass than rhizosphere communities, the coalescence of rhizosphere and permafrost microbial communities could alter soil organic matter (SOM) degradation rates and increase greenhouse gas emissions. To identify metabolic strategies across distinct rhizosphere and permafrost microbial communities we conducted an isotope tracing incubation experiment. We inoculated thawed permafrost with shrub and sedge rhizosphere communities while adding exudates or water daily and compared this to an uninoculated control. After 46 days, we spiked samples with 18O enriched water or 13C enriched exudates and measured isotope incorporation into microbial DNA with quantitative stable isotope probing (qSIP). Our results indicate that exudate additions had little effect on uninoculated permafrost communities but the addition of exudates and rhizosphere inoculants had a compounding effect on respiration rates. We found that soils inoculated with shrub rhizosphere communities contained a mixture of exudate and SOM degraders while soils inoculated with sedge rhizosphere communities contained mainly SOM degraders. Finally, we found that individual microbial taxa exhibited maximum growth rates under specific combinations of microbial inoculant communities and exudate addition treatments. Our results reveal that microbial niches are strongly influenced by substrate preferences and community context, and suggest that a reduction in sedges and an expansion of shrubs may provide a mechanism by which permafrost carbon losses are mitigated through corresponding shifts in microbial communities and their substrate preferences.

Schaefer, Sean R [Natural Resources and Earth Syst↗

A study of the central stellar populations of galaxies in SDSS-IV MaNGA: identification of a subsample with unusually young and massive stars

ABSTRACT This paper describes a search for galaxy centres with clear indications of unusual stellar populations with an initial mass function flatter than Salpeter at high stellar masses. Out of a sample of 668 face-on galaxies with stellar masses in the range $10^{10}\!-\!10^{11} \, \mathrm{M}_{\odot }$, I identify 15 galaxies with young- to intermediate-age central stellar populations with unusual stellar population gradients in the inner regions of the galaxy. In these galaxies, the 4000-Å break is either flat or rising towards the centre of the galaxy, indicating that the central regions host evolved stars, but the H α equivalent width also rises steeply in the central regions. The ionization parameter [O iii]/[O ii] is typically low in these Galactic Centres, indicating that ionizing sources are stellar rather than AGN. Wolf–Rayet features characteristic of hot young stars are often found in the spectra and these also get progressively stronger at smaller galactocentric radii. These outliers are compared to a control sample of galaxies of similar mass with young inner stellar populations, but where the gradients in H α equivalent width and 4000-Å break follow each other more closely. The outliers exhibit central Wolf–Rayet red bump excesses much more frequently, they have higher central stellar and ionized gas metallicities, and they are also more frequently detected at 20-cm radio wavelengths. I highlight one outlier where the ionized gas is clearly being strongly perturbed and blown out either by massive stars after they explode as supernovae, or by energy injection from matter falling on to a black hole.

Kauffmann, Guinevere↗

Robust and High Throughput Tools for Characterization of Wet Cellulosic Biogas Feedstocks and Co-Products: Cooperative Research and Development Final Report, CRADA Number CRD-21-21472

This project will develop standardized analytical procedures to support understanding of the chemical composition of wet manure feedstocks, and the digestate formed following anaerobic digestion of organic waste to produce renewable natural gas (RNG). The developed methods will be validated to improve component mass closure, eliminate ambiguities around key constituents, and document the precision and accuracy of the methods. Following validation of the analytical laboratory methods for characterization of wet organic waste feedstocks and digestate, NLR will use the same samples to build and validate near-infrared (NIR) models for high throughput analysis, potentially deployable at commercial facilities, enabling increased production of low carbon intensity RNG from wet organic wastes.

09 BIOMASS FUELS↗

An assessment of ocean alkalinity enhancement using aqueous hydroxides: kinetics, efficiency, and precipitation thresholds

Abstract. Ocean alkalinity enhancement (OAE) is a promising approach to marine carbon dioxide removal (mCDR) that leverages the large surface area and carbon storage capacity of the oceans to sequester atmospheric CO2 as dissolved bicarbonate (HCO3-). One OAE method involves the conversion of salt in seawater into aqueous alkalinity (NaOH), which is returned to the ocean. The resulting increase in seawater pH and alkalinity causes a shift in dissolved inorganic carbon (DIC) speciation toward carbonate and a decrease in the surface ocean pCO2. The shift in the pCO2 results in enhanced uptake of atmospheric CO2 by the seawater due to gas exchange. In this study, we systematically test the efficiency of CO2 uptake in seawater treated with NaOH at aquarium (15 L) and tank (6000 L) scales to establish operational boundaries for safety and efficiency in advance of scaling up to field experiments. CO2 equilibration occurred on the order of weeks to months, depending on circulation, air forcing, and air bubbling conditions within the test tanks. An increase of ∼0.7–0.9 mol DIC per mol added alkalinity (in the form of NaOH) was observed through analysis of seawater bottle samples and pH sensor data, consistent with the value expected given the values of the carbonate system equilibrium calculations for the range of salinities and temperatures tested. Mineral precipitation occurred when the bulk seawater pH exceeded 10.0 and Ωaragonite exceeded 30.0. This precipitation was dominated by Mg(OH)2 over hours to 1 d before shifting to CaCO3,aragonite precipitation. These data, combined with models of the dilution and advection of alkaline plumes, will allow the estimation of the amount of carbon dioxide removal expected from OAE pilot studies. Future experiments should better approximate field conditions including sediment interactions, biological activity, ocean circulation, air–sea gas exchange rates, and mixing zone dynamics.

Ringham, Mallory C. (ORCID:0000000348020185)↗

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗

First lithium experiments in HIDRA and evidence of helium retention during quasi-steady-state stellarator plasma operations

Recent experiments in Hybrid Illinois Device for Research and Applications (HIDRA) have had operational discharges between t discharge = 60 and 1000 s using electron cyclotron resonant heating (ECRH) of the plasma. This means that quasi-steady-state plasma discharges reach conditions to study long-pulse plasma material interactions (PMIs). The newly commissioned HIDRA-Material Analysis Test-stand PMI diagnostic is used to place a drop of lithium onto a heated tungsten surface, transfer the sample in-vacuo and expose it in a helium plasma. Helium is of interest as there is an open question to whether lithium will be able to remove helium ash in real fusion devices. The introduction of the W-Li sample in HIDRA resulted in evaporation of lithium into the helium plasma during a 600 s pulse and caused a reduction of over 90% in neutral pressure during the discharge. It was also observed that the plasma density and temperature increased by over 2.5 times. Using spectroscopy and a helium collisional radiative model, the peak temperature and density of the helium plasma can be monitored during the discharge. During lithium evaporation, as significant lithium ionization occurs, there is a 85% drop in the HIDRA vessel neutral pressure, despite a constant flow rate of He gas. This reduction in neutral pressure is supported by spectroscopy data with corresponding reductions in He I line intensities (587 nm, 667 nm, 706 nm, and 728 nm), as well as those of other impurities. At one point in the discharge a lithium plasma is created, as indicated by an increase in Li + emission and a complete reduction in He + emission, but the electron density jumps from ne = 3 × 10 18 m –3 to over ne = 8 × 10 18 m –3 while the core temperature stays relatively constant between Te = 16 eV and 20 eV. Once lithium has completely evaporated from the sample and the majority of the ionized lithium has diffused from the plasma to the vessel walls, pressure and spectroscopy data paired with He collisional radiative model calculations shows a re-establishment of a helium plasma in a low recycling regime. In this regime, the density drops down to ne = 2 × 10 18 m –3 and the electron temperature increases from T e = 20 eV to over T e = 50 eV indicating an increase in helium heating efficiency. This is also indicated by the He+ emission re-establishing and having a higher intensity. Here, we show the results from the first lithium campaign in HIDRA. In the presence of lithium, and in particular when lithium ions are present, the helium disappears from the plasma via an as of yet unknown complex relationship that needs to be further studied. The most likely explanation is that the lithium ions are distributed around the vessel and able to trap helium to the surface turning HIDRA into a large gettering surface. These results have potential implications on future plasma facing component design using liquid lithium for impurity and recycling control using limiters and divertors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Machine learning to predict biomass sorghum yields under future climate scenarios

Crop yield modeling is critical in the design of national strategies for agricultural production, particularly in the context of a changing climate. Forecasting yields of bioenergy crops at fine spatial resolutions can help to evaluate near-term and long-term pathways for scaling up bio-based fuel and chemical production, and for understanding the impacts of abiotic stressors such as severe droughts and temperature extremes on potential biomass supply. In this work we used a large dataset of 28,364 Sorghum bicolor yield samples (uniquely identified by county and year of observation), environmental variables, and multiple approaches to analyze historical trends in sorghum productivity across the USA. We selected the most accurate machine learning approach (a variation of the random forest approach) to predict future trends in sorghum yields under four greenhouse gas (GHG) emission scenarios and two irrigation regimes. We identified irrigation practices, vapor pressure deficit, and time (a proxy for technological improvement) as the most important predictors of sorghum productivity. Our results showed a decreasing trend of sorghum yields over future years (on average 2.7% from 2018 to 2099), with greater decline under a high GHG emissions scenario (3.8%) and in the absence of irrigation (4.6%). Geographically, we observed the steepest predicted declines in the Great Lakes (8.2%), Upper Midwest (7.5%), and Heartland (6.7%) regions. Our study demonstrates the use of machine learning to identify environmental controllers of sorghum biomass yield and predict yields with reasonable accuracy. These results can inform the development of more realistic biomass supply projections for bioenergy if sorghum production is scaled up. (c) 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

09 BIOMASS FUELS↗

Chemical changes in thirdhand smoke associated with remediation using an ozone generator

Ozonation is a common remediation approach to eliminate odors from mold, tobacco and fire damage in buildings. Little information exists to: 1) assess its effectiveness; 2) provide guidance on operation conditions; and 3) identify potential risks associated with the presence of indoor ozone and ozonation byproducts. The goal of this study is to evaluate chemical changes in thirdhand smoke (THS) aerosols induced by high levels of ozone, in comparison with THS aerosols aged under similar conditions in the absence of ozone. Samples representing different stages of smoke aging in the absence of ozone, including freshly emitted secondhand smoke (SHS) and THS, were collected inside an 18-m 3 room-sized chamber over a period of 42 h after six cigarettes were consumed. The experiments involved collection and analysis of gas phase species including volatile organic compounds (VOCs), volatile carbonyls, semivolatile organic compounds (SVOCs), and particulate matter. VOC analysis was carried out by gas chromatography/mass spectrometry with a thermal desorption inlet (TD-GC/MS), and volatile carbonyls were analyzed by on-line derivatization with dinitrophenylhydrazine (DNPH), followed by liquid chromatography with UV/VIS detection. SVOCs were extracted from XAD-coated denuders and Teflon-coated fiberglass filters in the absence of ozone. In those extracts, tobacco-specific nitrosamines (TSNAs) and other SVOCs were analyzed by gas chromatography with positive chemical ionization-triple quadrupole mass spectrometric detection (GC/PCI-QQQ-MS), and polycyclic aromatic hydrocarbons (PAHs) were quantified by gas chromatography with ion trap mass spectrometric detection (GC/IT-MS) in selected ion monitoring mode. Particulate matter concentration was determined gravimetrically. In a second experiment, a 300 mg h -1 commercial ozone generator was operated during 1 h, one day after smoke was generated, to evaluate the remediation of THS by ozonation. VOCs and volatile carbonyls were analyzed before and after ozonation. Extracts from fabrics that were exposed in the chamber before and after ozonation as surrogates for indoor furnishings were analyzed by GC/IT-MS, and aerosol size distribution was studied with a scanning mobility particle sizer. Ozone concentration was measured with a photometric detector. An estimated 175 mg ozone reacted with THS after 1 h of treatment, corresponding to 58% of the total O 3 released during that period. Fabric-bound nicotine was depleted after ozonation, and the surface concentration of PAHs adsorbed to fabric specimens decreased by an order of magnitude due to reaction with ozone, reaching pre-smoking levels. These results suggest that ozonation has the potential to remove harmful THS chemicals from indoor surfaces. However, gas phase concentrations of volatile carbonyls, including formaldehyde, acetaldehyde and acetone were higher immediately after ozonation. Ultrafine particles (UFP, in most cases with size <60 nm) were a major ozonation byproduct. UFP number concentrations peaked shortly after ozonation ended, and remained at higher-than background levels for several hours. Based on these results, minimum re-entry times after ozone treatment were predicted for different indoor scenarios. Clearly defining re-entry times can serve as a practical measure to prevent acute exposures to ozone and harmful ozonation byproducts after treatment. This study evaluated potential benefits and risks associated with THS remediation using ozone, providing insights into this technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simultaneous Control of Flexibility and Rigidity in Pore-Space-Partitioned Metal–Organic Frameworks

Flexi-MOFs are typically limited to low-connected (< 9) frameworks. Here we report a platform-wide approach capable of creating a family of high-connected materials (collectively called CPM-220) that integrate exceptional framework flexibility with high rigidity. We show that the multi-module nature of the pore-space-partitioned pacs (partitioned acs net) platform allows us to introduce flexibility as well as to simultaneously impose high rigidity in a tunable module-specific fashion. The inter-modular synergy has remarkable macro-morphological and sub-nanometer structural impacts. A prominent manifestation at both length scales is the retention of X-ray-quality single crystallinity despite huge hexagonal c-axial contraction (≈ 30%) and harsh sample treatment such as degassing and sorption cycles. CPM-220 sets multiple precedents and benchmarks on the pacs platform in both structural and sorption properties. Furthermore, they possess exceptionally high benzene/cyclohexane selectivity, unusual C 3 H 6 and C 3 H 8 isotherms, and promising separation performance for small gas molecules such as C 2 H 2 /CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of Kariya ( Hildegardia barteri (Mast.) Kosterm) Seed Oil Fatty Acid Methyl Ester Prepared from Basic Catalytic Transesterification

The rising global energy demand, alongside concerns regarding environmental deterioration due to the use of fossil fuels, has spurred extensive investigation into renewable energy alternatives. Biomass-derived biodiesel, especially from lesser-known oil sources, emerges as a promising option. This research focuses on analyzing the fatty acid methyl esters (FAMEs) derived from Kariya (Hildegardia barteri (Mast.) Kosterm) seed oil through basic catalytic transesterification using gas chromatography–flame ionization detector (GC–FID) analysis, assessing its potential as a biodiesel feedstock. Oil extraction from Kariya seeds was carried out using three solvents (n-hexane, ethanol, and a 1:1 blend of hexane and ethanol), followed by transesterification with methanol. Gas chromatography–mass spectrometry (GC–MS) and GC–FID analyses were utilized to identify and quantify FAMEs in the resulting biodiesel. The results revealed various FAMEs, including methyl myristate, methyl palmitate, methyl stearate, methyl oleate, methyl linoleate, and methyl linolenate. Significant differences in FAME composition were observed among the samples, with hexane–ethanol Kariya oil biodiesel (HE-KOB) showing the highest FAME content (76.1%). This combination of solvents exhibited synergistic effects on the composition of HE-KOB, suggesting potential optimization strategies for biodiesel production. Fourier transform infrared spectroscopy (FTIR) provided additional insights into the molecular composition of the biodiesel samples, confirming their biodiesel nature through the identified functional groups such as methyl, methylene, hydrocarbon, ester, aldehyde, and alkene. Thermogravimetric analysis (TGA) for thermal decomposition also gave an insight into FAME composition and its contribution to the degree of conversion of biodiesel to energy. These findings highlight the feasibility of utilizing Kariya seed oil as a biodiesel feedstock, emphasizing the importance of solvent selection and transesterification conditions in optimizing FAME yield and composition. This research contributes to the exploration of underutilized oil sources for sustainable biodiesel production, aligning with the global shift towards cleaner and renewable energy sources.

09 BIOMASS FUELS↗

Gamma-Ray Emission from Galaxies Hosting Molecular Outflows

Many star-forming galaxies and those hosting active galactic nuclei show evidence of massive outflows of material in a variety of phases including ionized, neutral atomic, and molecular. Molecular outflows in particular have been the focus of recent interest as they may be responsible for removing gas from the galaxy, thereby suppressing star formation. As material is ejected from the cores of galaxies, interactions of the outflowing material with the interstellar medium can accelerate cosmic rays and produce high-energy gamma rays. In this work, we search for gamma-ray emission from a sample of local galaxies known to host molecular outflows using data collected by the Fermi Large Area Telescope. We employ a stacking technique in order to search for and characterize the average gamma-ray emission properties of the sample. Gamma-ray emission is detected from the galaxies in our sample at the 4.4σ level with a power-law photon index of Γ ≈ 2 in the 1–800 GeV energy range. The emission is found to correlate with tracers of star formation activity, namely the 8–1000 μm infrared luminosity. We also find that the observed signal can be predominantly attributed to H II galaxies hosting energy-driven outflows. While we do not find evidence suggesting that the outflows are accelerating charged particles directly, galaxies with molecular outflows may produce more gamma rays than galaxies without outflows. In particular, the set consisting of gamma-ray-detected galaxies with molecular outflows are nearly perfect calorimeters and may be future targets for searches of high-energy neutrinos.

79 ASTRONOMY AND ASTROPHYSICS↗

3D Geologic Framework Modelling of the Los Alamos National Laboratory Site and Pajarito Plateau: Integrating a realistic 3D fault network and modelling subsurface relationships in a sparsely sampled and complex geologic region

The subsurface geology beneath the Pajarito Plateau is critical to understanding the seismic hazard of the Pajarito Fault System, yet our understanding of this geology is relatively poor. While previous 3D geologic framework models of the area have been created for the purposes of understanding hydrogeologic flow, they are inadequate for the purposes of understanding the Pajarito Fault System. The specific challenges of using oil and gas software for this purpose include: (1) the geologic complexities resulting from volcanism and tectonism; (2) a need for a high level of stratigraphic detail over a large area; (3) a near complete lack of seismic data; and (4) sparse wellbore data. Presented here is a workflow that handles these challenges of adapting commercially available software used by the oil and gas industries to this seismic hazard problem.

58 GEOSCIENCES↗

High resolution identification and quantification of diffuse deep groundwater discharge in mountain rivers using continuous boat-mounted helium measurements

Discharge of deeply sourced groundwater to streams is difficult to locate and quantify, particularly where both discrete and diffuse discharge points exist, but diffuse discharge is one of the primary controls on solute budgets in mountainous watersheds. The noble gas helium is a unique identifier of deep groundwater discharge because groundwater with long residence times is commonly enriched in helium. In this study, a portable mass spectrometer was used to measure longitudinal variation in dissolved helium concentrations in two mountainous rivers at high spatial resolution not feasible with traditional sampling techniques. Helium profiles were then simulated using a mass-balance model to quantify longitudinal variation in groundwater discharge to the receiving rivers. Results indicate helium concentrations were enriched by multiple orders of magnitude above atmospheric equilibrium in both rivers and that this persisted for up to 18 km below observed pulse inputs in the Colorado River. Helium mass-balance models match observed longitudinal patterns with the exception of sharp initial increases in helium observed in the rivers. Increased longitudinal groundwater discharge rates correspond to mapped geologic structures in both watersheds that likely transport deep geothermal water. Models show variable sensitivity to spatial assignment of input variables representing the groundwater source, illustrating the importance of collecting data from discrete groundwater discharges where possible. The methodology shows promise for field experiments designed to assess air–water exchange rates and to quantify total groundwater discharge from a combination of discrete and diffuse sources.

Deep groundwater↗

Quasar clustering at redshift 6

Large-scale surveys over the last years have revealed about 300 quasi-stellar objects (QSOs) at redshifts above 6. Follow-up observations have identified surprising properties, such as the very high black hole (BH) masses, spatial correlations with surrounding cold gas of the host galaxy, and high CIV-MgII Velocity shifts. In particular, the discovery of luminous high-redshift quasars suggests that at least some BHs likely have high masses at birth and grow efficiently. Our aim is to quantify quasar pairs at high redshift for a large sample of objects. This provides a new key constraint on a combination of parameters related to the origin and assembly for the most massive BHs: formation efficiency and clustering, growth efficiency, and the relative contribution of BH mergers. We observed 116 spectroscopically confirmed QSOs around redshift 6 with the simultaneous seven-channel imager Gamma-ray Burst Optical/Near-infrared Detector in order to search for companions. Applying colour-colour cuts identical to those which led to the spectroscopically confirmed QSOs, we performed Le PHARE fits to the 26 best QSO pair candidates, and obtained spectroscopic observations for 11 of them. We do not find any QSO pair with a companion brighter than M 1450 (AB) < –26 mag within our 0.1–3.3 h –1 cMpc search radius, in contrast to the serendipitous findings in the redshift range 4–5. However, a small fraction of such pairs at this luminosity and redshift is consistent with indications from present-day cosmological-scale galaxy evolution models. In turn, the incidence of L- and T-type brown dwarfs, which occupy a similar colour space to z ~ 6 QSOs, is higher than expected, by a factor of 5 and 20, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

A single column separation method for barium isotope analysis of geologic and hydrologic materials with complex matrices

Abstract The increasing significance of barium (Ba) in environmental and geologic research in recent years has led to interest in the application of the Ba isotopic composition as a tracer for natural materials with complex matrices. Most Ba isotope measurement techniques require separation of Ba from the rest of sample prior to analysis. This paper presents a method using readily available materials and disposable columns that effectively separates Ba from a range of geologic and hydrologic materials, including carbonate minerals, silicate rocks, barite, river water, and fluids with high total dissolved solids and organic content such as oil and gas brines, rapidly and without need for an additional cleanup column. The technique involves off-the-shelf columns and cation exchange resin and a two-reagent elution that uses 2.5 N HCl followed by addition of 2.0 N HNO 3 . We present data to show that major matrix elements from almost any natural material are separated from Ba in a single column pass, and that the method also effectively reduces or eliminates isobaric interferences from lanthanum and cerium.

Matecha, R. M.↗

High-speed two-dimensional terahertz spectroscopy with echelon-based shot-to-shot balanced detection

By using a reflective-echelon-based electro-optic sampling technique and a fast detector, we develop a two-dimensional terahertz (THz) spectrometer capable of shot-to-shot balanced readout of THz waveforms at a full 1-kHz repetition rate. To demonstrate the capabilities of this new detection scheme for high-throughput applications, we use gas-phase acetonitrile as a model system to acquire two-dimensional THz rotational spectra. The results show a two-order-of-magnitude speedup in the acquisition of multidimensional THz spectra when compared to conventional delay-scan methods while maintaining accurate retrieval of the nonlinear THz signal. Our report presents a feasible solution for bringing the technique of multidimensional THz spectroscopy into widespread practice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗