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LaRuAsO crystallizes in the tetragonal P4/nmm space group. The structure is two-dimensional and consists of two lanthanum molecules; two ruthenium molecules; and one AsO sheet oriented in the (0, 0, 1) direction. In the AsO sheet, As3- is bonded in a distorted square co-planar geometry to four equivalent O2- atoms. All As–O bond lengths are 2.15 Å. O2- is bonded in a square co-planar geometry to four equivalent As3- atoms.
As Internet of Things devices and cloud-based platforms become more mature, Energy Management and Information Systems (EMIS) are increasingly gaining momentum in the building industry. In large commercial buildings, Fault-Detection and Diagnostic (FDD) and energy information systems (EIS) are now established technologies with tens of providers and thousands of deployment sites across North America. The new frontier for the EMIS technology is now represented by control systems that use advanced system optimization (ASO) methods to improve the operations of the HVAC system. Given the complexity of the integration of such systems with the existing building automation systems (BAS) and the higher risk involved with direct control of the HVAC, these systems are still emerging in the market. This paper presents the results of a project in which a start-up company partnered with a research institution to develop a cloud-based software EMIS solution and deployed it in a university campus in California. The software system included advanced sensing, data acquisition, storage and advanced control and analytics applications developed on top of the native BAS. The new platform controls ten buildings on the campus and the FDD and the ASO applications deployed on this platform were able to generate energy savings of up to 35% and 25% in certain buildings for each functionality respectively. Where the platform did not save energy, it improved building service (air quality). Lessons learned include the importance of collaborating with and training the building operators and evaluating whether the legacy system can work reliably with the new technology.
The U.S General Services Administration's (GSA's) Green Proving Ground program, in partnership with the National Renewable Energy Laboratory. completed a large pilot study of an Energy Management Information Systems (EMIS) with Automated System Optimization (ASO). Four test bed facilities, each with different building characteristics and systems, were chosen for the implementation of cloud-based EMIS with ASO. Depending on functionality, this tool can be extremely effective in energy management and energy optimization in buildings. The capabilities evaluated in the pilot ranged from energy savings and energy consumption predictions to evaluations of user acceptance, operability, and ease of installation. This report presents the methodology, lessons learned and best practices, and deployment recommendations for the GSA's portfolio of commercial office space, comprising more than 8,500 properties.
While a building’s energy usage is driven largely by its design and use, building operator behavior has a strong influence on its energy consumption. This project developed and piloted a specific, data-driven coaching methodology to help operators understand how they can adjust operations and/or affect no/low-cost repairs or upgrades to their specific building HVAC systems to reduce energy consumption. Named BuildingCoach, the operational optimization method used is based on the Building Re-tuning approach developed by the Pacific Northwest National Laboratory. A building operations analytics market has matured over the past decade, though its potential to affect energy-saving changes has not been fully realized. Training operators to understand the methods for operational optimization with the explicit approach of using building-system performance data is hypothesized to create a more effective, longer lasting result in building energy efficiency, and this strategy is the fundamental premise of this project. With the support of an Industry Advisory Board, the project succeeded in developing materials and recruiting for and delivering three pilot cohorts. Deliverables included twenty-two self-paced training modules (accessed via a Learning Management System) and a web-based platform that includes access to real-time building system data and a repository for building system documentation. The project set out to have 100 participants from 50 buildings in three pilot cohorts. In the end, there were 28 participants from 17 buildings, i.e., a significant shortfall. The first two pilot cohorts had only two buildings in each, and this was partially due to difficulties in deploying the Building Operator Coaching Solution (“the BOCS”), which is technology that extracts the data from the controls network and presents it as prescribed for coaching. In the third cohort, the project team deployed the BOCS successfully to 13 buildings, the methodology was piloted as intended, and numerous opportunities for optimization were identified. The BuildingCoach business plan charts a path to an economically sustainable effort. However, even with a licensing model captured in the final version of the business plan, the scalability is still limited to keeping less than 1,000 buildings affected by 2033. Even so, there are unexplored paths to greater scalability that are being considered. CUNY BPL is working to perpetuate and grow the use of BuildingCoach. As of this writing, about twenty buildings have either been connected or will be connected with operators coached / to be coached in the NYC municipal portfolio, twelve buildings across four campuses in NY State will use BuildingCoach, a NY upstate county wishes for six or seven buildings to participate with the support of funding from NYSERDA, and others have also expressed interest. In the decades to come, there will be an increasing percentage of large and mid-sized buildings that incorporate automated system optimization (ASO), and the building operators’ role will shift to spend more time on maintenance and monitoring. Meanwhile, programs such as BuildingCoach will play a critical role in optimizing operations. And, regardless of the emergence of ASO, operators will still need to understand how their systems operate so that they can monitor them properly. Within that context, BuildingCoach is an important step towards operators’ understanding of efficient building system operations.
Lipid nanoparticles (LNPs) are versatile carriers for nucleic acid (NA) therapeutics, including ASOs, siRNA, mRNA, and poly-IC. While lipid composition is known to influence LNP properties, the impact of NA length on morphology and internal structure is less understood, particularly during the stages of carrier–cargo assembly. Here, we examine NA length and lipid composition immediately after mixing using high-throughput SAXS, dynamic light scattering, and cryogenic electron microscopy. All LNPs form ordered NA/lipid compartments, with longer NAs promoting inverse hexagonal (H II ) phases and larger intercompartment distances. In contrast, short NAs, especially in formulations with SM102 ionizable lipid, favor lamellar phases. SAXS peak deconvolution quantifies ordered versus disordered phases via a Robustness of Ordered Phase factor, which correlates with particle size and encapsulation efficiency. Formulations with MC3 ionizable and DOPE helper lipids exhibit the most stable H II -phase packing, highlighting the role of helper-lipid curvature in compartment stabilization. Variations in NA compartmentalization indicate differences in payload capacity, offering a framework for rational LNP design across diverse nucleic acid cargos.
Recent progress with the production of 72 As (2.49 Mev β + max (64%), 3.33 Mev β + max (16%), 834 keV (81%), t 1/2 : 26 h) and 77 As (0.683 Mev β- max (97%), 239 keV (1.59%), t 1/2 : 38.8 h) has facilitated their evaluation as a potential “theranostic pair” for PET imaging and radiotherapy. Our 3 rd generation trithiol chelate with two carboxylic acid groups was further developed as a bifunctional chelate for radioarsenic. The As complex with the trithiol chelate was synthesized and characterized. No carrier added (nca) [ 77 As][H 2 AsO 4 - ] was used for radiolabeling studies. Here, the trithiol chelate was conjugated to the RM2 peptide (DPhe-Gln-Trp-Ala-VaI-Gly-His-Sta-Leu-NH 2 ) via solid phase peptide synthesis with two different linkers, Ser-Ser and Glu-Ser. The trithiol chelate and its RM2 bioconjugates were radiolabeled with nca 77 As, and the RM2 bioconjugates were compared in initial biodistribution studies. The As diacid trithiol complex was characterized by 1 H NMR, 13 C NMR and HR-ESI-MS. The trithiol-RM2 precursor and As trithiol bioconjugates were characterized by HR-ESI-MS and/or LC-ESI-MS. Radiolabeling of the RM2 bioconjugates with 77 As resulted in over 85% radiochemical yield for [ 77 As]As-trithiol-Ser-Ser-RM2 ([ 77 As]8) and 90% for [ 77 As]As-trithiol-Glu-Ser-RM2 ([ 77 As]9). Both radiotracers demonstrated excellent in vitro stability (≥ 90% remaining intact through 24 h in PBS buffer) and were more hydrophilic than previous analogues based on log D 7.4 values. Biodistribution results of the two radiotracers in healthy CF-1 male mice demonstrated blockable pancreatic uptake at 1 h (82% for ([ 77 As]8 and 78% for [ 77 As]9) indicating specific gastrin-releasing peptide receptor (GRPR) uptake. The primary route of excretion was through the gastrointestinal system for both radiotracers. A new trithiol chelate with improved hydrophilicity was successfully conjugated to the RM2 peptide via two linkers, and high radiolabeling yield with nca 77 As was achieved. In vivo biodistribution studies with both radiotracers demonstrated blockable pancreatic uptake suggestive of specific receptor uptake.
Natural or anthropogenic processes can increase the concentration of uranium (U) and arsenic (As) above the maximum contaminant levels in water sources. Bicarbonate and calcium (Ca) can have major impacts on U speciation and can affect the reactivity between U and As. We therefore investigated the reactivity of aqueous U and As mixtures with bicarbonate and Ca for acidic and neutral pH conditions. In experiments performed with 1 mM U and As mixtures, 10 mM Ca, and without added bicarbonate (pCO 2 = 3.5), aqueous U decreased to <0.25 mM at pH 3 and 7. Aqueous As decreased the most at pH 3 (~0.125 mM). Experiments initiated with 0.005 mM As and U showed similar trends. X-ray spectroscopy (i.e., XAS and EDX) and diffraction indicated that U-As-Ca- and U-Ca-bearing solids resemble uranospinite [Ca(UO 2 ) 2 (AsO 4 ) 2 ·10H 2 O] and becquerelite [Ca(UO 2 ) 6 O 4 (OH) 6 ·8(H 2 O)]. These findings suggest that U-As-Ca-bearing solids formed in mixed solutions are stable at pH 3. However, the dissolution of U-As-Ca and U-Ca-bearing solids at pH 7 was observed in reactors containing 10 mM bicarbonate and Ca, suggesting a kinetic reaction of aqueous uranyl-calcium-carbonate complexation. Our study provides new insights regarding U and As mobilization for risk assessment and remediation strategies.
Here, we present neutron diffraction, electronic structure calculations, and optical vibrational spectroscopic characterization of hydronium uranyl phosphate (HUP), the synthetic analog of chernikovite ((H 3 O)(UO 2 )(PO 4 )·3H 2 O) to gain insight into structural features of the hydronium cation in the solid state. HUP crystallizes in P2 1 /c instead of previously reported P4/ncc 1 at room temperature and Pccn below 302 K. Lower symmetry was required due to hydronium and interstitial water positions within the structure. Crystallographic positions of hydronium cations determined from powder neutron diffraction data are bolstered by Raman and attenuated total reflectance infrared spectroscopic measurements and are further informed by density functional theory with phonon eigenvector analysis for spectral assignments. Finally, HUP and its arsenate analog (trogerite, (H 3 O)(UO 2 )(AsO 4 )·3H 2 O), (HUAs) were studied using He 2+ irradiation as an analog for α radiolysis to investigate the irradiation stability of these phases and the stability of hydronium cations in the solid state. Dose studies were employed wherein each sample was irradiated to 5, 10, 15, 25, and 50 MGy. Structural insight regarding irradiated materials is gained using optical vibrational spectroscopy and powder X-ray diffraction. Surprising irradiation stability of HUAs was found up to 50 MGy of dose, which may have important implications for understanding and modeling the geologic stability of legacy U.
The Kitaev model has served as a long-sought-after target in the realization of a quantum spin liquid that could host Majorana Fermions. Such non-Abelian anyons could revolutionize quantum computing if properly implemented to overcome decoherence. A 3d 7 electronic configuration, like Co 2+ , has been explored by theory and experimental work to design Kitaev materials. Here, in this study, we report the synthesis of a new cobaltate honeycomb material KCoAsO 4 . The compound is synthesized through a low-temperature solution route and crystallized in space group R¯3 with lattice parameters a = 5.0394(1) and c = 28.6790(1) as determined by neutron powder diffraction. The crystal structure follows motifs similar to those of the honeycomb compound BaCo2(AsO 4 ) 2 but presents differing magnetic behavior. Magnetization/heat capacity measurements on the powder show antiferromagnetic transition T N = 14 K. Two lower-temperature transitions are present in susceptibility at low field that resemble spin reorientations. Magnetization data as a function of field have curvature indicative of metamagnetic behavior below the magnetic ordering temperature, with the magnetic ordering suppressed upon application of a higher magnetic field. Computational studies suggest the presence of a weak nearest-neighbor Kitaev term, K 1 , consistent with related honeycomb cobaltates. Together, the data suggest that this material should present a new platform for developing Kitaev quantum spin liquids.
Abstract In contrast to phosphine oxides and arsine oxides, which are common and exist as stable monomeric species featuring the corresponding pnictoryl functional group (Pn=O/Pn + –O − ; Pn = P, As), stibine oxides are generally polymeric, and the properties of the unperturbed stiboryl group (Sb=O/Sb + –O − ) remain unexplored. We now report the isolation of the monomeric stibine oxide, Dipp 3 SbO (where Dipp = 2,6-diisopropylphenyl). Spectroscopic, crystallographic and computational studies provide insight into the nature of the Sb=O/Sb + –O − bond. Moreover, isolation of Dipp 3 SbO allows the chemistry of the stiboryl group to be explored. Here we show that Dipp 3 SbO can act as a Brønsted base, a hydrogen-bond acceptor and a transition-metal ligand, in addition engaging in 1,2-addition, O-for-F 2 exchange and O-atom transfer. In all cases, the reactivity of Dipp 3 SbO differed from that of the lighter congeners Dipp 3 AsO and Dipp 3 PO.
BaCo 2 (AsO 4 ) 2 (BCAO) has seen extensive study since its initial identification as a proximate Kitaev quantum spin liquid candidate. Thought to be described by the highly anisotropic XXZ-J 1 -J 3 model, the ease with which magnetic order is suppressed in the system indicates proximity to a spin liquid phase. Upon chemical tuning via partial arsenic substitution with vanadium, we show an initial suppression of long-range incommensurate order in the BCAO system to T ≈ 3.0 K, followed by increased spin freezing at higher substitution levels. Between these two regions, at around 10% substitution, the system is shown to pass through a critical point where the competing J 1 /J 3 exchange interactions become more balanced, producing a more complex magnetic ground state, likely stabilized by quantum fluctuations. Here, this state shows how slight compositional change in magnetically frustrated systems may be leveraged to tune ground state degeneracies and potentially realize a quantum spin liquid state.
High-energy-resolution fluorescence-detected (HERFD) X-ray absorption near-edge spectroscopy (XANES) is a spectroscopic method that allows for increased spectral feature resolution, and greater selectivity to decrease complex matrix effects compared with conventional XANES. XANES is an ideal tool for speciation of elements in solid-phase environmental samples. Accurate speciation of As in mine waste materials is important for understanding the mobility and toxicity of As in near-surface environments. In this study, linear combination fitting (LCF) was performed on synthetic spectra generated from mixtures of eight measured reference compounds for both HERFD-XANES and transmission-detected XANES to evaluate the improvement in quantitative speciation with HERFD-XANES spectra. The reference compounds arsenolite (As 2 O 3 ), orpiment (As 2 S 3 ), getchellite (AsSbS 3 ), arsenopyrite (FeAsS), kaňkite (FeAsO 4 ·3.5H 2 O), scorodite (FeAsO 4 ·2H 2 O), sodium arsenate (Na 3 AsO 4 ), and realgar (As 4 S 4 ) were selected for their importance in mine waste systems. Statistical methods of principal component analysis and target transformation were employed to determine whether HERFD improves identification of the components in a dataset of mixtures of reference compounds. LCF was performed on HERFD- and total fluorescence yield (TFY)-XANES spectra collected from mine waste samples. Arsenopyrite, arsenolite, orpiment, and sodium arsenate were more accurately identified in the synthetic HERFD-XANES spectra compared with the transmission-XANES spectra. In mine waste samples containing arsenopyrite and either scorodite or kaňkite, LCF with HERFD-XANES measurements resulted in fits with smaller R -factors than concurrently collected TFY measurements. The improved accuracy of HERFD-XANES analysis may provide enhanced delineation of As phases controlling biogeochemical reactions in mine wastes, contaminated soils, and remediation systems.
Layered honeycomb magnets are of interest as potential realizations of the Kitaev quantum spin liquid (KQSL), a quantum state with long-range spin entanglement and an exactly solvable Hamiltonian. Conventional magnetically ordered states are present for all currently known candidate materials, however, because non-Kitaev terms in the Hamiltonians obscure the Kitaev physics. Current experimental studies of the KQSL are focused on 4 d or 5 d transition metal–based honeycombs, in which strong spin-orbit coupling can be expected, yielding Kitaev interaction that dominates in an applied magnetic field. In contrast, for 3 d -based layered honeycomb magnets, spin-orbit coupling is weak, and thus, Kitaev physics should be substantially less accessible. Here, we report our studies on BaCo 2 (AsO 4 ) 2 , for which we find that the magnetic order associated with the non-Kitaev interactions can be fully suppressed by a relatively low magnetic field, yielding a nonmagnetic material and implying the presence of strong magnetic frustration and weak non-Kitaev interactions.
The Southern Great Plains (SGP) exhibits a relatively high frequency of periods with extremely high rainfall rates (RR) and hail. Here, seven months of 2017 are simulated using the Weather Research and Forecasting (WRF) model applied at convection permitting resolution with the Mibrandt-Yau microphysics scheme. Simulation fidelity is evaluated, particularly during intense convective events, using data from ASOS stations, dual-polarization RADAR, gridded data sets and observations at the DoE Atmospheric Radiation Measurement site. The spatial gradients and temporal variability of precipitation and the cumulative density functions for both RR and wind speeds exhibit fidelity. Odds ratios >1 indicate WRF is also skillful in simulating high composite reflectivity (cREF, used as a measure of widespread convection) and RR > 5 mmhr –1 over the domain. Detailed analyses of the ten days with highest spatial coverage of cREF >30 dBZ show spatially similar reflectivity fields and high RR in both RADAR data and WRF simulations. However, during periods of high reflectivity, WRF exhibits a positive bias in terms of very high RR (> 25 mmhr –1 ) and hail occurrence, and during the summer and transition months, maximum hail size is underestimated. For some renewable energy applications fidelity is required with respect to the joint probabilities of wind speed and RR and/or hail. While partial fidelity is achieved for the marginal probabilities, performance during events of critical importance to these energy applications is currently not sufficient. Further research into optimal WRF configurations in support of potential damage quantification for these applications is warranted.
The LANL Accelerator Strategy Office (ASO) requires the support of AOT-MDE to perform a trade study on the current manufacturing capabilities required to modernize the Los Alamos Neutron Science Center (LANSCE). The purpose of the study will be to identify and potentially minimize cost and schedule risks that could impact the LANSCE Modernization Project (LAMP).
Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.
This data collection was contributed to the Visualisation Hackathon 2022 (#VisMetHack2022), in conjunction with the Using ECMWF's Forecasts (UEF2022) workshop. The European Center for Medium-Range Weather Forecasts (ECMWF) and the Oak Ridge National Laboratory (ORNL) are pleased to announce access to the data collection from global 1-km nature run (NR) simulations using the Integrated Forecast System (IFS) with explicit convection. We invite you to join us in exploring this precursor to a digital twin of the earth! The NR simulations reveal unprecedented detail of the earth’s atmosphere, and the then outgoing Editor-in-Chief of AGU JAMES commended the project as one of “stunning ambitions,” enabled by computational capacity at scale. The project also won the 2020 HPCwire Readers Choice Award for Best Use of HPC in Physical Sciences. A set of two NR seasonal simulations have been completed, one corresponding to the northern hemispheric winter months (NDJF) and the other for the North Atlantic tropical cyclone season (ASO). The project used the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). The simulations were facilitated with an INCITE award from the US Department of Energy Office of Science. For the first seasonal run of four months (NDJF), the hydrostatic IFS model was initialized at 00Z on 1 November 2018. The NR for the TC season (AS) was initialized at 00Z on 1 August 2019. The NR simulations were constrained only by sea surface temperatures (SST) at the lower boundary. The IFS output was saved every 3 hours. After feedback and interest from the scientific community, the simulations were rerun for four specific extreme events, with output every 15 minutes. The special cases include a tropical cycle and three severe storm events over the continental USA.
The U.S. General Services Administration's (GSA's) Green Proving Ground (GPG) program, in partnership with the National Laboratory of the Rockies (NLR), completed a field study of a Grid-Interactive Efficient Buildings (GEB) software solution. The study focused on a single testbed facility to test the GEB functionality of the software solution, along with other features. The testbed facility - a courthouse - is a common building type in GSA's vast building portfolio, offering potentially impactful findings on a scalable level. The study evaluated Prescriptive Data's technology, Nantum OS, a connected building operating system ("GEB Solution") which aggregates multiple sources of previously siloed building data and combines that data with external sources, such as weather information or utility signals, into a single integrated platform. A GEB Solution is a type of Energy Management Information System (EMIS). EMIS is defined as a system of devices, data services, and software applications that communicates with any building system or third-party data source to aggregate and transform data into new capabilities to aid in the optimization of energy use at the building, campus, or agency level. This specific GEB Solution is an EMIS with ASO, automated system optimization, offering supervisory control of certain aspects of the Building Automation System (BAS). Multiple features were evaluated including, but not limited to, Continuous Demand Management to avoid setting new monthly kilowatt (kW) peaks, energy efficiency for reduction of kilowatt hours (kWh) and natural gas consumption, and automated demand response (ADR) for purposes of lowering demand during a utility called Demand Response (DR) event. The testbed facility was the Foley Federal Building and US Courthouse ("Foley Federal Building") located in Las Vegas, NV. This is a 209,496 sq. ft. building constructed in the 1960s with major renovations in 2004. The facility was a good candidate due to the large prevalence of office and courthouse spaces in the GSA portfolio of buildings. It also has many features which allow integration into and control of the building and a strong facilities team to assist with the study. Quantitative and qualitative performance objectives were developed using GSA's GPG GEB project template along with input from the vendor and building facility staff; these are outlined in Table 1. The quantitative performance objectives focused on continuous demand management, energy efficiency, and automated demand response. The qualitative performance objectives focused on the ease of installation and commissioning as well as the operability of the GEB solution. Other performance metrics that are reported on include carbon reduction, cost effectiveness, and occupant acceptance.