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Algorithms and Application of Sparse Matrix Assembly and Equation Solvers for Aeroacoustics

An algorithm for symmetric sparse equation solutions on an unstructured grid is described. Efficient, sequential sparse algorithms for degree-of-freedom reordering, supernodes, symbolic/numerical factorization, and forward backward solution phases are reviewed. Three sparse algorithms for the generation and assembly of symmetric systems of matrix equations are presented. The accuracy and numerical performance of the sequential version of the sparse algorithms are evaluated over the frequency range of interest in a three-dimensional aeroacoustics application. Results show that the solver solutions are accurate using a discretization of 12 points per wavelength. Results also show that the first assembly algorithm is impractical for high-frequency noise calculations. The second and third assembly algorithms have nearly equal performance at low values of source frequencies, but at higher values of source frequencies the third algorithm saves CPU time and RAM. The CPU time and the RAM required by the second and third assembly algorithms are two orders of magnitude smaller than that required by the sparse equation solver. A sequential version of these sparse algorithms can, therefore, be conveniently incorporated into a substructuring for domain decomposition formulation to achieve parallel computation, where different substructures are handles by different parallel processors.

Watson, W. R.↗

Third-body stabilization of supercritical CO 2 in CO oxidation: development and application of a ReaxFF force field for the CO/O/CO 2 system

Supercritical CO 2 (scCO 2 ) plays a crucial role as a solvent in separation processes, advanced power cycles, and materials processing. Nonetheless, the atomistic comprehension of how the dense scCO 2 matrix influences the fundamental reaction of carbon monoxide (CO) is still insufficiently explored. Experimental studies and molecular dynamics (MD) simulations frequently fail to detect the highly reactive, transient intermediates, such as atomic oxygen (O), that drive these reactions. Here, to address this issue, we have developed a novel ReaxFF reactive force field for the CO 2 /CO/O system. The force field parameters were calibrated using density functional theory and second-order Møller-Plesset calculations to model CO 2 crystal properties, intermolecular interactions, bond dissociation curves, and reaction energy barriers. The force field reproduces the cohesive energy of the CO 2 crystal, the pressure characteristics of bulk scCO 2 , the equation-of-state behavior over a wide pressure–density range, the pressure dependence of the C–O bond length under compression, and the structural properties of liquid and scCO 2 , as documented by experiments, ab-initio MD, and prominent non-reactive models. The force field was subsequently applied to study the CO + O → CO 2 reaction. In a dilute environment, the reaction is inefficient as the newly formed CO 2 rapidly dissociates due to excess kinetic and potential energy acquired from the exothermic reaction. Conversely, in a dense scCO 2 environment, the surrounding matrix acts as an efficient third body, stabilizing the emerging CO2 product via molecular collisions. Statistical analysis confirms an average excess energy dissipation of 133.9 ± 3.6 kcal/mol over 112.4 ± 17.9 ps. Kinetic energy decomposition reveals that ∼ 92% of the excess kinetic energy is stored in internal (rotational and vibrational) degrees of freedom. This ReaxFF force field establishes a mechanistic foundation for third-body stabilization in dense reactive environments.

Chowdhury, Emdadul Haque [Pennsylvania State Univ.↗

Simplified Modeling of Oxidation of Hydrocarbons

A method of simplified computational modeling of oxidation of hydrocarbons is undergoing development. This is one of several developments needed to enable accurate computational simulation of turbulent, chemically reacting flows. At present, accurate computational simulation of such flows is difficult or impossible in most cases because (1) the numbers of grid points needed for adequate spatial resolution of turbulent flows in realistically complex geometries are beyond the capabilities of typical supercomputers now in use and (2) the combustion of typical hydrocarbons proceeds through decomposition into hundreds of molecular species interacting through thousands of reactions. Hence, the combination of detailed reaction- rate models with the fundamental flow equations yields flow models that are computationally prohibitive. Hence, further, a reduction of at least an order of magnitude in the dimension of reaction kinetics is one of the prerequisites for feasibility of computational simulation of turbulent, chemically reacting flows. In the present method of simplified modeling, all molecular species involved in the oxidation of hydrocarbons are classified as either light or heavy; heavy molecules are those having 3 or more carbon atoms. The light molecules are not subject to meaningful decomposition, and the heavy molecules are considered to decompose into only 13 specified constituent radicals, a few of which are listed in the table. One constructs a reduced-order model, suitable for use in estimating the release of heat and the evolution of temperature in combustion, from a base comprising the 13 constituent radicals plus a total of 26 other species that include the light molecules and related light free radicals. Then rather than following all possible species through their reaction coordinates, one follows only the reduced set of reaction coordinates of the base. The behavior of the base was examined in test computational simulations of the combustion of heptane in a stirred reactor at various initial pressures ranging from 0.1 to 6 MPa. Most of the simulations were performed for stoichiometric mixtures; some were performed for fuel/oxygen mole ratios of 1/2 and 2.

Bellan, Josette↗

Physiochemical Machine Learning Models Predict Operational Lifetimes of CH3NH3PbI3 Perovskite Solar Cells

Halide perovskites are promising photovoltaic (PV) materials with the potential to lower the cost of electricity and greatly expand the penetration of PV if they can demonstrate long-term stability under illumination in the presence of moisture and oxygen. The solar cell service lifetime as quantified by the T80 (the time required for the power conversion efficiency to drop to 80% of its starting value) is a useful metric to assess stability. The T80 for utility, commercial, or residential PV systems needs to be several decades in order to yield low-cost electricity, and thus it is not practical to directly measure the T80. It would be useful if T80 could be predicted from the initial dynamics of a solar cell’s performance, but until now no models have been developed to forecast T80. In this work, we report the development of machine learning models to predict T80 of ITO/NiOx/CH3NH3PbI3/C60/BCP/Ag solar cells operating at maximum power point under 1-sun equivalent photon flux in air at varying temperatures and relative humidities. Efficiency losses are driven by short-circuit current and fill factor, indicating that chemical decomposition of the perovskite is a major contributor to degradation. Spatial patterns evident from in situ dark field optical microscopy suggest that the electric field gradient at device edges plays a significant role in perovskite decomposition, along with photochemical reactions with O2 and H2O. Models are trained using a menu of features from three distinct categories: (i) features based on measurements of the initial rates of change of device parameters, (ii) features based on the ambient conditions during operation (temperature, & partial pressure of H2O), and (iii) features based on underlying physics and chemistry. We show that a theory-based physiochemical feature derived from a model of the chemical reaction kinetics of the rate of degradation of the CH3NH3PbI3 is particularly valuable for prediction. This physiochemical feature was selected as the first or second most dominant feature in the best performing models. With a dataset consisting of 45 accelerated degradation experiments with T80 that range over a factor of 30, the model predicts T80 with an accuracy of about 40% (|predicted T80 - observed T80| / observed T80) on samples not used in training. This hybrid ML approach should be effective when applied to other compositions, device architectures, and advanced packaging schemes.

14 SOLAR ENERGY↗

Physiochemical Machine Learning Models Predict Operational Lifetimes of CH3NH3PbI3 Perovskite Solar Cells

Halide perovskites are promising photovoltaic (PV) materials with the potential to lower the cost of electricity and greatly expand the penetration of PV if they can demonstrate long-term stability under illumination in the presence of moisture and oxygen. The solar cell service lifetime as quantified by the T80 (the time required for the power conversion efficiency to drop to 80% of its starting value) is a useful metric to assess stability. The T80 for utility, commercial, or residential PV systems needs to be several decades in order to yield low-cost electricity, and thus it is not practical to directly measure the T80. It would be useful if T80 could be predicted from the initial dynamics of a solar cell’s performance, but until now no models have been developed to forecast T80. In this work, we report the development of machine learning models to predict T80 of ITO/NiOx/CH3NH3PbI3/C60/BCP/Ag solar cells operating at maximum power point under 1-sun equivalent photon flux in air at varying temperatures and relative humidities. Efficiency losses are driven by short-circuit current and fill factor, indicating that chemical decomposition of the perovskite is a major contributor to degradation. Spatial patterns evident from in situ dark field optical microscopy suggest that the electric field gradient at device edges plays a significant role in perovskite decomposition, along with photochemical reactions with O2 and H2O. Models are trained using a menu of features from three distinct categories: (i) features based on measurements of the initial rates of change of device parameters, (ii) features based on the ambient conditions during operation (temperature, & partial pressure of H2O), and (iii) features based on underlying physics and chemistry. We show that a theory-based physiochemical feature derived from a model of the chemical reaction kinetics of the rate of degradation of the CH3NH3PbI3 is particularly valuable for prediction. This physiochemical feature was selected as the first or second most dominant feature in the best performing models. With a dataset consisting of 45 accelerated degradation experiments with T80 that range over a factor of 30, the model predicts T80 with an accuracy of about 40% (|predicted T80 - observed T80| / observed T80) on samples not used in training. This hybrid ML approach should be effective when applied to other compositions, device architectures, and advanced packaging schemes.

14 SOLAR ENERGY↗

The Surface Chemistry of Methanol on Cu 3 Pd(111): Effects of Metal Alloying and Reaction with Hydrogen

Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) was used to study the adsorption and surface chemistry of methanol on a Cu 3 Pd(111) model surface. The composition and morphological properties of the pristine Cu 3 Pd(111) substrate were analyzed using a combination of low-energy electron diffraction (LEED), scanning tunneling microscopy (STM), and low-energy ion scattering (LEIS). The results of ion scattering showed segregation of Pd toward the surface, with a Pd/Cu ratio close to 0.5, a larger value than the ratio of 0.33 expected for a Cu 3 Pd bimetallic structure. The surface of the alloy exhibited a good LEED pattern with three-fold long-range periodicities. In STM, clusters of palladium with hexagonal arrays and Pd- Pd distances of 2.7-2.8 Å were detected. Bonding to copper perturbed the electronic properties of the atoms in the Pd clusters, shifting their 4d states toward higher binding energy with respect to the Fermi level. Further, the valence band spectrum of Cu 3 Pd(111) exhibited a line shape that was very different from those displayed by Cu(111) or Pd(111). At low pressures, the adsorption of methanol on Cu 3 Pd(111) at 300 K mainly produced CH 3 O, CO and CH x species. AP-XPS showed that most Pd atoms in the surface of the Cu 3 Pd(111) alloy interacted with the decomposition products of methanol. No significant changes were observed in the core levels of copper upon the adsorption and dissociation of methanol, suggesting that the molecule mainly interacted with Pd sites of the alloy. Reaction with hydrogen led to fast removal of CH x , C and PdC x species from Cu 3 Pd(111) at moderate (< 450 K) temperatures and prevented a CH x → C transformation. If the stability of adsorbed CH 3 O is used as a descriptor for the hydrogenation of CO 2 to methanol, Cu 3 Pd should be a much better catalyst than monometallic palladium. This may be a consequence of electronic and ensemble effects in the alloy that moderate the reactivity of Pd sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamics and superconductivity of S x Se 1 - x H 3

The compression of SH 2 and its subsequent decomposition to SH 3 , presumably in a cubic $Im\bar{3}m$ structure, has lead to the discovery of conventional superconductivity with the highest measured and confirmed T sub>c to date, 203 K at 160 GPa. Recent theoretical studies suggest that a mixture of S with other elements of the chalcogen group could improve the superconducting temperature. Here, we present a detailed analysis of the thermodynamic properties of S and Se mixtures in the bcc lattice with $Im\bar{3}m$ symmetry using a cluster expansion technique to explore the phase diagram of S x Se 1- x H 3 . In contrast to earlier reports, we find that S 0.5 Se 0.5 H 3 is not stable in the pressure range between 150 and 200 GPa. However, phases at compositions S 0.2 Se 0.8 H 3 , S $0.\bar3$ Se $0.\bar6$ H 3 , and S 0.6 Se 0.4 H 3 are stable at 200 GPa, while additional phases at S 0.25 Se 0.75 H 3 and S 0.75 Se 0.25 H 3 are accessible at lower pressures. Electron-phonon calculations show that the values of T c are consistently lower for all ternary phases, indicating that mixtures of S and Se with H might not be a viable route towards compounds with improved superconducting properties.

74 ATOMIC AND MOLECULAR PHYSICS↗

Mapping Thermal Conductivity at the Atomic Scale: A Step toward the Thermal Design of Materials

We describe a spatial decomposition of the thermal conductivity, termed site-projected thermal conductivity, which quantifies the thermal conduction activity at each atomic site—a critical parameter for the thermal design of materials. The method is based on the Green–Kubo formula and the harmonic approximation and requires the force-constant and dynamical matrices, as well as a relaxed structural model. Throughout the study, it uses high quality models previously tested and compared to many experiments. It discusses the method and underlying approximations for amorphous silicon, carries the detailed analysis for amorphous silicon, and then examines an amorphous-crystal silicon interface and representative carbon materials. This study identifies the sites and local structures that reduce heat transport, and quantify these (estimate the spatial range) over which these “thermal defects” are effective. It identifies filamentary structures in the amorphous silicon network which impact heat transport and electronic structure (the Urbach edge) and electronic transport.

36 MATERIALS SCIENCE↗

Soft functions for generic jet algorithms and observables at hadron colliders

Here, we introduce a method to compute one-loop soft functions for exclusive N - jet processes at hadron colliders, allowing for different definitions of the algorithm that determines the jet regions and of the measurements in those regions. In particular, we generalize the N -jettiness hemisphere decomposition of ref. [1] in a manner that separates the dependence on the jet boundary from the observables measured inside the jet and beam regions. Results are given for several factorizable jet definitions, including anti- k T , XCone, and other geometric partitionings. We calculate explicitly the soft functions for angularity measurements, including jet mass and jet broadening, in pp → L + 1 jet and explore the differences for various jet vetoes and algorithms. This includes a consistent treatment of rapidity divergences when applicable. We also compute analytic results for these soft functions in an expansion for a small jet radius R . We find that the small- R results, including corrections up to O(R 2 ), accurately capture the full behavior over a large range of R .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

O(N) Quantum Molecular Dynamics (QMD) Algorithms, Code Requirements, Release Notes, and Library Deployment

The Exascale Computing Project (ECP) Co-design Center for Particle Applications (CoPA) is addressing the challenges for particle applications to run on upcoming exascale computing architectures. This includes short- and long-range molecular dynamics (MD), particle-in-cell (PIC), and quantum molecular dynamics (QMD). This document addresses $\mathcal{O}(N)$ QMD. The goal of this CoPA team is to develop $\mathcal{O}(N)$ linear scaling methods for QMD optimized for new and next generation architectures. This will provide the capability to simulate larger systems and run for longer timeframes than is possible today. Focus is initially on the density matrix construction. This requires efficient matrix formats and linear algebra operations for distributed architectures. A significant reduction in the wallclock time for an MD timestep is necessary to achieve practical large scale QMD. Equally challenging is to develop scalable distributed implementations. This requires the exploration of efficient data formats (dense, sparse, etc.), data decomposition and distribution across compute nodes using block- and graph-based methods. Traditional programming models such as MPI/OpenMP, hybrid MPI/OpenMP/Accelerator, as well as asynchronous task-based models will be explored to achieve maximum parallelism. Parallelism at the level of a matrix operation, solver, and/or application needs to be explored to gain the most benefit on new and emerging architectures. This report serves as a “living document” of the additions and enhancements throughout the ECP CoPA project for $\mathcal{O}(N)$ QMD. The following sections address the applications we are working with, the quantum chemistry libraries (BML and PROGRESS), and our co-design exploration through the use of a proxy application.

36 MATERIALS SCIENCE↗

Low-temperature access to active iron and iron/nickel nitrides as potential electrocatalysts for the oxygen evolution reaction

Low-temperature, scalable routes to transition metal nitride (TMN) nanoparticles are desirable for a wide range of applications, yet their synthesis typically requires high temperatures (>350 °C) and reactive gas environments (e.g., NH 3 or H 2 /N 2 ). Here, we report a colloidal synthesis of mono- and bimetallic TMN nanoparticles using preformed metal carbonyl clusters as precursors and urea or diethylenetriamine (DETA) as nitrogen sources. This strategy enables access to size-controlled, phase-pure ε-Fe 3 N x and Fe y Ni 3−y N nanoparticles at temperatures below 300 °C, without the need for flowing reactive gas atmospheres. By systematically varying nitrogen precursor, reaction temperature, and cluster identity, we achieve tunable nitrogen stoichiometry (x) and phase selectivity between N-rich and N-poor TMNs. Structural and magnetic characterization confirms clean decomposition of the precursors and phase formation consistent with controlled nitridation at the nanoscale. Preliminary electrochemical measurements in alkaline media demonstrate that these materials exhibit oxygen evolution reaction (OER) overpotentials comparable to RuO 2 , highlighting their viability for future electrocatalytic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Fitting Vibrational Energy Parameters to Falloff Experiments: CH3 + CH3 + He (0.6-2 Torr 200-298 K)

There are many reported experiments and theoretical calculations for the combination of methyl free radicals diluted in a non-reactive 'deactivator. At high pressure the ethane (C2H6) combination product is the sole product; with decreasing pressure the chemically activated C2H6 will decompose. The falloff in the observed rate coefficient is the result of the competition between collisional stabilization of the chemically activated CA and unimolecular decomposition. The dependence of the rate coefficient on pressure, temperature and collision properties is complex and can not be calculated from first principles. The understanding of this system is not only of fundamental importance but is relevant to the recent detection of methyl free radicals in the atmospheres of Saturn - and Neptune. The temperatures of these outer planet atmospheres are in the 140-200 K region with total pressures (predominately H2 and He) less than 0.2 Torr. Experimentally determined rate coefficients have been reported for this reaction at T = 296-906 K and T = 200-408 K mostly with argon as the deactivator. At T = 200 K only the high pressure rate coefficient has been determined. Complete falloff curves over a wide temperature range (200-1600 K) with a variety of weak collider models used to simulate argon as the deactivator have also been reported by Klippenstein and Harding (KH). More recently we have reported the experimental rate coefficients in the falloff region with helium as the deactivator at 200 and 298 K. In this paper we have used the calculated falloff curves reported by KH for argon to determine the average energy transferred per collision for helium in our recently reported experiments. Collision rates were converted using Lennard Jones parameters; the temperature dependence of this conversion factor is noted. The helium experiments were consistent with a down of approximately 100 cm (exp-1); the temperature dependence was slight. The magnitude of down and its temperature dependence will be compared to other systems with similar substrate complexity and reaction energetics.

Tardy, Dwight C.↗

Investigations Using Laboratory Testbeds to Interpret Flight Instrument Datasets from Mars Robotic Missions

The Astromaterials Research and Exploration Science Directorate at the NASA Johnson Space Center (JSC) has laboratory instrumentation that mimic the capabilities of corresponding flight instruments to enable interpretation of datasets returned from Mars robotic missions. The lab instruments have been and continue to be applied to datasets for the Moessbauer Spectrometer (MB) on the Mars Exploration Rovers (MER), the Thermal & Evolved Gas Analyzer (TEGA) on the Mars Phoenix Scout, the CRISM instrument on the Mars Reconnaissance Orbiter Missions and will be applied to datasets for the Sample Analysis at Mars (SAM), Chemistry and Mineralogy (CheMin) and Chemistry & Camera (ChemCam) instruments onboard the Mars Science Laboratory (MSL). The laboratory instruments can analyze analog samples at costs that are substantially lower than engineering models of flight instruments, but their success to enable interpretation of flight data depends on how closely their capabilities mimic those of the flight instrument. The JSC lab MB instruments are equivalent to the MER instruments except without flight qualified components and no reference channel Co-57 source. Data from analog samples were critical for identification of Mg-Fe carbonate at Gusev crater. Fiber-optic VNIR spectrometers are used to obtain CRISM-like spectral data over the range 350-2500 nm, and data for Fephyllosilicates show irreversible behavior in the electronic transition region upon dessication. The MB and VNIR instruments can be operated within chambers where, for example, the absolute H2O concentration can be measured and controlled. Phoenix's TEGA consisted of a calorimeter coupled to a mass spectrometer (MS). The JSC laboratory testbed instrument consisted of a differential scanning calorimeter (DSC) coupled to a MS configured to operate under total pressure (12 mbar), heating rate (20 C/min), and purge gas composition (N2) analogous to the flight TEGA. TEGA detected CO2 release at both low (400-680 C) and high (725-820 C) temperature and an endothermic reaction in concert with the high temperature release. The high-temperature thermal decomposition is consistent with calcite, dolomite, or ankerite, (3-6 wt.%) or any combination of these phase based upon laboratory testbed experiments. Recent laboratory experiments suggest that the low temperature CO2 release was caused by a reaction between calcium carbonate and hydrated magnesium perchlorate; although, CO2 release by the oxidation of organic materials and Fe-/Mg-rich carbonates cannot be ruled out. MSL landed in Gale crater on August 5, 2012. Although numerous analog samples have been analyzed on the JSC laboratory testbeds, no SAM, CheMin, or ChemCam analyses have been acquired by MSL to date. The JSC SAM laboratory testbed consists of a thermal analyzer coupled with a MS configured to operate under total pressure (30 mbar), heating rate (35 C/min), and purge gas composition (He) analogous to the flight SAM. The CheMin and ChemCam laboratory testbeds were developed and built by inXitu, Inc. and Los Alamos National Laboratory, respectively, to acquire datasets relevant to the MSL CheMin and ChemCam flight instruments.

Ming, D. W.↗

Reactions of Propyl Radicals: A Shock Tube - VUV Photoionization Mass Spectrometry Study

The pyrolytic reactions of n-propyl and i-propyl radicals and their precursors have been investigated at elevated temperatures and pressures (600 – 900 K and 5 – 8 bar). The studies were performed in a miniature high repetition rate shock tube with synchrotron vacuum ultraviolet photoionization mass spectrometry yielding comprehensive datasets of temporal and photoionization energy dependencies of reagents and products. The propyl radicals were generated by pyrolysis of alkyl nitrites. In addition to the main decomposition path, NO elimination, the mass spectra allowed an alternative minor path via HNO elimination to be identified and quantified. For the n-propyl precursor the HNO elimination route accounted for 9% of the alkyl nitrite while for the i-propyl precursor it was 2.5%. These values are in good agreement with a recent study on i-butyl radicals in the same apparatus at similar conditions. The ratio of disproportionation/recombination was obtained for n- propyl from the relative concentrations of n-hexane and propene and for i-propyl from 2,3-dimethyl butane and propene. For n-propyl the ratio is 0.3 and 1.2 for i-propyl, both are independent of temperature and pressure over the experimental range. The disproportionation/recombination ratios are about a factor of 2 higher than prior evaluations that are based mainly on room temperature data. The experimental results are some of the first from the apparatus used and comments are made about the technique, challenges encountered, and suggestions for future developments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Subcritical Water Extraction of Amino Acids from Atacama Desert Soils

Amino acids are considered organic molecular indicators in the search for extant and extinct life in the Solar System. Extraction of these molecules from a particulate solid matrix, such as Martian regolith, will be critical to their in situ detection and analysis. The goals of this study were to optimize a laboratory amino acid extraction protocol by quantitatively measuring the yields of extracted amino acids as a function of liquid water temperature and sample extraction time and to compare the results to the standard HCl vapor- phase hydrolysis yields for the same soil samples. Soil samples from the Yungay region of the Atacama Desert ( Martian regolith analog) were collected during a field study in the summer of 2005. The amino acids ( alanine, aspartic acid, glutamic acid, glycine, serine, and valine) chosen for analysis were present in the samples at concentrations of 1 - 70 parts- per- billion. Subcritical water extraction efficiency was examined over the temperature range of 30 - 325 degrees C, at pressures of 17.2 or 20.0 MPa, and for water- sample contact equilibration times of 0 - 30 min. None of the amino acids were extracted in detectable amounts at 30 degrees C ( at 17.2 MPa), suggesting that amino acids are too strongly bound by the soil matrix to be extracted at such a low temperature. Between 150 degrees C and 250 degrees C ( at 17.2 MPa), the extraction efficiencies of glycine, alanine, and valine were observed to increase with increasing water temperature, consistent with higher solubility at higher temperatures, perhaps due to the decreasing dielectric constant of water. Amino acids were not detected in extracts collected at 325 degrees C ( at 20.0 MPa), probably due to amino acid decomposition at this temperature. The optimal subcritical water extraction conditions for these amino acids from Atacama Desert soils were achieved at 200 degrees C, 17.2 MPa, and a water- sample contact equilibration time of 10 min.

biomarkers↗

Statistical analysis of Al III and C III ] emission lines as virial black hole mass estimators in quasars

We test the usefulness of the intermediate ionisation lines Al IIIλ1860 and C III]λ1909 as reliable virial mass estimators for quasars. We identified a sample of 309 quasars from the Sloan Digital Sky Survey Data Release 16 (SDSS DR16) in the redshift range 1.2 ≤ z ≤ 1.4 that have [O II]λ3728 recorded on the same spectrum as Al IIIλ1860, Si III]λ1892, and C III]λ1909. We set the systemic quasar redshift using careful measurements of [O II]λ3728. We then classified the sources as Population A (Pop. A), extreme Population A (Pop. xA), and Population B (Pop. B), and analysed the 1900 Å blend using multi-component models to look for systematic line shifts of Al IIIλ1860 and C III]λ1909 along the quasar main sequence. We do not find significant shifts of the Al IIIλ1860 line peak in Pop. B or in the vast majority of Pop. A. For Pop. xA, a small median blueshift of -250 km s -1 was observed, motivating a decomposition of the Al III line profile into a virialised component centred at rest frame and a blueshifted component for an outflow emission. For Pop. B objects, we proved the empirical necessity to fit a redshifted very broad component, clearly seen in C III], and analysed the physical implications on a Pop. B composite spectrum using CLOUDY simulations. We find consistent black hole mass estimations using Al III and C III] as virial estimators for the bulk of Pop. A. Al III (and even C III]) is a reliable virial black hole mass estimator for Pop. A and Pop. B objects. The Pop. xA sources deserve special attention due to the significant blueshifted excess observed in the line profile of Al III, although it is not as large as the excess observed in C IVλ1549.

79 ASTRONOMY AND ASTROPHYSICS↗

Synthesis of phase-pure U 2 N 3 microspheres and its decomposition into UN

Uranium mononitride (UN) is important as a nuclear fuel. Fabrication of UN in its microspherical form also has its own merits since the advent of the concept of accident-tolerant fuel, where UN is being considered as a potential fuel in the form of TRISO particles. But, not many processes have been well established to synthesize kernels of UN. Therefore, a process for synthesis of microspherical UN with a minimum amount of carbon is discussed herein. First, a series of single-phased microspheres of uranium sesquinitride (U 2 N 3 ) were synthesized by nitridation of UO 2 +C microspheres at a few different temperatures. Resulting microspheres were of low-density U 2 N 3 and decomposed into low-density UN. The variation of density of the synthesized sesquinitrides as a function of its chemical composition indicated the presence of extra (interstitial) nitrogen atoms corresponding to its hyperstoichiometry, which is normally indicated as α-U 2 N 3 . Average grain sizes of both U 2 N 3 and UN varied in a range of 1–2.5 μm. In addition, these had a considerably large amount of pore spacing, indicating the potential sinterability of UN toward its use as a nuclear fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Biotransformation of furanic and phenolic compounds with hydrogen gas production in a microbial electrolysis cell

In this study, furanic and phenolic compounds are problematic byproducts resulting from the decomposition of lignocellulosic biomass during biofuel production. This study assessed the capacity of a microbial electrolysis cell (MEC) to produce hydrogen gas (H 2 ) using a mixture of two furanic (furfural, FF; 5-hydroxymethyl furfural, HMF) and three phenolic (syringic acid, SA; vanillic acid, VA; and 4-hydroxybenzoic acid, HBA) compounds as the sole carbon and energy source in the bioanode. The rate and extent of biotransformation of the five compounds, efficiency of H 2 production, as well as the anode microbial community structure were investigated. The five compounds were completely transformed within 7-day batch runs and their biotransformation rate increased with increasing initial concentration. At an initial concentration of 1,200 mg/L (8.7 mM) of the mixture of the five compounds, their biotransformation rate ranged from 0.85 to 2.34 mM/d. The anode coulombic efficiency was 44-69%, which is comparable to wastewater-fed MECs. The H 2 yield varied from 0.26 to 0.42 g H 2 -COD/g COD removed in the anode, and the bioanode volume-normalized H 2 production rate was 0.07-0.1 L/L-d. The major identified fermentation products that did not transform further were catechol and phenol. Acetate was the direct substrate for exoelectrogenesis. Current and H 2 production were inhibited at an initial substrate concentration of 1,200 mg/L, resulting in acetate accumulation at a much higher level than that measured in other batch runs conducted with a lower initial concentration of the five compounds. The anode microbial community consisted of exoelectrogens, putative degraders of the five compounds, and syntrophic partners of exoelectrogens. The H 2 production route demonstrated in this study has proven to be an alternative to the currently used process of reforming natural gas to supply H 2 needed to upgrade bio-oils to stable hydrocarbon fuels.

08 HYDROGEN↗