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At least 793 records · Page 44

Capturing the Coverage Dependence of Aromatics’ Adsorption through Mean-Field Models

To capture the dominant interactions (surface-mediated and through-space steric) in catalytic hydrodeoxygenation systems, coverage-dependent mean-field models of aromatic adsorption are developed on Pt(111) and Ru(0001). We derive three key insights from this work: (1) we can universally apply mean-field models to capture the coverage-dependent behavior of oxygenated aromatics on transition metal surfaces, (2) we can deconvolute surface-mediated and throughspace steric interactions from the mean-field model, and (3) we can develop relatively accurate models that predict the adsorption energy of aromatics on transition metal surfaces for the full coverage range using the work function at lowest modeled coverage. In conclusion, our approach enables the rapid prediction of coverage-dependent behavior of oxygenated aromatics on transition metal surfaces, reducing the computational cost associated with these studies by an order of magnitude.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Downscaled CMIP5 projections of physical fire risk understate historical trends

Reliable projections of wildfire risk are important for multi-sector impacts analysis. Statistically downscaled and bias-corrected Earth system model ensemble products are routinely used to analyze regional physical wildfire risk, but evaluations of historical observed trends and variability are lacking. Here, we evaluate physical fire risk over the western United States using the Canadian Forest Fire Weather Index (FWI) by comparing model outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5), statistically downscaled via the Multivariate Adaptive Constructed Analogs (MACA) approach, against the observational target dataset gridMET, a gridded high-resolution surface meteorological product. We analyze multidecadal trends and interannual variability in seasonal average FWI for the historical period and future projections under two emissions scenarios, and we compare MACA-CMIP5 ensemble results with a simple time series model that generates historical and future projections of seasonal FWI based on bootstrapping observed historical trends and variability. Our findings indicate that MACA-CMIP5 accurately captures the magnitude and spatial patterns of seasonally averaged FWI but tends to underestimate historical decadal trends. We show that future increases in fire risk may be underestimated relative to the simple time series model that projects historical variability into the future. We also highlight that model biases in relative humidity contribute significantly to model-data differences. Our results underscore the importance of historical hindcasting exercises for informing broader multi-sector applications.

FWI↗

A multiscale model of the action of a capsid assembly modulator for the treatment of chronic hepatitis B

Chronic hepatitis B virus (HBV) infection is strongly associated with increased risk of liver cancer and cirrhosis. While existing treatments effectively inhibit the HBV life cycle, viral rebound frequently occurs following treatment interruption. Consequently, functional cure rates of chronic HBV infection remain low and there is increased interest in a novel treatment modality, capsid assembly modulators (CAMs). Here, we develop a multiscale mathematical model of CAM treatment in chronic HBV infection. By fitting the model to participant data from a phase I trial of the first-generation CAM vebicorvir, we estimate the drug’s dose-dependent effectiveness and identify the physiological mechanisms that drive the observed biphasic decline in HBV DNA and RNA, and mechanistic differences between HBeAg-positive and negative infection. Finally, we demonstrate analytically and numerically that the relative change of HBV RNA more accurately reflects the antiviral effectiveness of a CAM than the relative change in HBV DNA.

59 BASIC BIOLOGICAL SCIENCES↗

Transient Studies of Nonequilibrium Transport in Two-Dimensional Semiconductors

The overarching objective of research under DOE support has been to investigate emergent carrier phenomena in different two-dimensional (2D) systems, under conditions where they are driven far from equilibrium. The description of nonequilibrium transport has long represented one of the most enduring challenges in condensed-matter physics, in large part due to the need to invoke the role of complex many-body phenomena (electron-phonon and electron-electron coupling) in this regime. In this project, we have explored aspects of this problem in a variety of different two-dimensional systems. These include the modulation-doped two-dimensional electrons gas, or 2DEG, in GaAs/AlGaAs heterostructures; the electron and hole systems in graphene and its related hetero-structures, and; the strongly-confined electron layers in transition-metal dichalcogenide (MoS 2 and WS 2 ) and trichalcogenide (TiS 3 ) materials. Significant understanding has been achieved in a number of different areas, as we elaborate upon in subsequent sections of this proposal: Nanoscale spectroscopy of defect-related barriers in MoS2 Negative differential conductance due to inter-valley scattering in WS 2 under high fields Incipient localization due to scattering from frozen-phonon disorder in quantum point contacts High-field transient transport in graphene/hexagonal BN heterostructures Universal voltage scaling of quantum corrections in graphene under nonequilibrium A defining feature of much of this research has been an approach to problem solving in which novel experimental techniques (such as transient electrical pulsing and scanning-probe microscopy) are combined with the development (in collaboration with colleagues from condensed-matter theory) of sophisticated models, a strategy that we propose to continue in our future research. In recent years, we have developed an increasing capacity for handling atomically-thin materials, and their van der Waals systems, a capacity that is reflected in the balance of topics listed above.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Integrated Mechanical System Pods (CRADA Final Report)

LBNL provided input to setting the requirements related to indoor air quality and contributed to the development of metrics and test plans to evaluate prototypes of the mechanical pods, which were developed by other members of the project team. The testing of prototypes was conducted by and at Syracuse University, another project partner. LBNL also collaborated with RMI to develop a basic plan for data collection when the pods are deployed for field testing in Phase 2.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Performance Benchmark of Commercial and Developmental Fission Chambers in Elevated Temperatures

This report documents the testing of two in-core fission chamber technologies for high-temperature irradiation environments. This work is in collaboration with the French Alternative Energies and Atomic Energy Commission (CEA). The fission chamber evaluated by Idaho National Laboratory is the micro-pocket fission detector (MPFD). The fission chamber evaluated by the CEA are the 3 mm miniaturized fission chamber and the 7 mm high-temperature fission chamber. Demonstrations of the MPFD were performed at the Neutron Radiography Facility and the Massachusetts Institute of Technology Reactor. Demonstrations of the CEA fission chambers were performed at the Ohio State University Research Reactor. All demonstrations were conducted with a heated experiment rig up to 850°C.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Operational Forecasting of Induced Seismicity (CRADA Final Report)

This was a collaborative effort between Lawrence Livermore National Security, LLC ("LLNS"), as manager and operator of Lawrence Livermore National Laboratory ("LLNL"), The Regents of the University of California, as manager and operator of Lawrence Berkeley National Laboratory (Collectively, Contractors) and Nanometrics, Inc. ("Participant"), to develop a toolkit called "Operational Forecasting of Induced Seismicity (ORION)" that includes a decision tree method for operational forecasting of induced seismicity rates related to fluid disposal operations.

58 GEOSCIENCES↗

M3AS-25IN1002073: Analysis of data from irradiation testing of printed strain gauges in prototypic nuclear environments

Advancement in additively manufactured strain gauges help address critical technology gaps to accurately monitor real-time materials behavior in reactor experiments. This is critical as it provides data to inform predictive models and simulations that enhance the development of reactors and fuel cycle systems. In this report, additively manufactured strain gauges are exposed to a neutron irradiation environment at the Ohio State University Research Reactor. This report goes over a 2-week campaign for neutron irradiating printed resistive strain gauges and capacitive strain gauges. These results complement the prior separate effects (i.e., mechanical strain, temperature, etc.) testing that were performed on these additive manufactured sensors and presented in prior milestone reports. These results also help progress our understanding of their usage in harsh environment applications. The outcome of developing advanced sensing and instrumentation capabilities plays an important role in increasing the safety, reliability, and energy efficiency of both next-generation and existing nuclear reactors.

36 - MATERIALS SCIENCE↗

Possibility to Identify the Contributions from Collapsars, Supernovae, and Neutron Star Mergers from the Evolution of the r-process Mass Abundance Distribution

We study the evolution of rapid neutron-capture process (r-process) isotopes in the galaxy. We analyze relative contributions from core-collapse supernovae (CCSNe), neutron star mergers, and collapsars under a range of astrophysical conditions and nuclear input data. Here we show that, although the r-process in each of these sites can lead to a similar (universal) elemental distribution, the detailed isotopic abundances can differ from one site to another. These differences may allow for the identification of which sources contributed to the early evolution of r-process material in the galaxy. Our simulations suggest that the early evolution was dominated by CCSNe and collapsar r-process nucleosynthesis. This conclusion may be testable if the next generation of observatories can deduce isotopic r-process abundances.

79 ASTRONOMY AND ASTROPHYSICS↗

A new technique to retrieve aerosol vertical profiles using micropulse lidar and ground-based aerosol measurements

Accurately characterizing the vertical distribution of aerosols and their cloud-forming properties is crucial for understanding aerosol-cloud interactions and their impact on climate. This study presents a novel technique for retrieving vertical profiles of aerosols, cloud condensation nuclei (CCN), and ice nucleating particles (INP) by combining micropulse lidar, radiosonde, and ground-based aerosol measurements. Herein, the technique is applied to data collected by our team at Texas A&M University during the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) campaign. Ground-based aerosol size distribution and CCN counter data are used to estimate the value of the aerosol hygroscopicity parameter, κ. The derived κ, together with Mie scattering theory and the relative humidity profile from the radiosonde, is used to estimate aerosol size growth and the associated increase in backscatter at each altitude. We then correct the lidar backscatter to dry conditions to produce the dry aerosol backscatter coefficient profile. The dry aerosol backscatter coefficient profile is linearly scaled to collocated surface measurements of aerosols, CCN, and INP to produce corresponding vertical profiles. Combining lidar backscatter profiles with aerosol and cloud nucleation measurements leads to a more realistic representation of vertical distributions of aerosol properties. The method could be readily applied to lidar measurements in future field campaigns.

Chen, Bo [Texas A & M Univ., College Station, TX (↗

Systematic computational study of oxide adsorption properties for applications in photocatalytic CO 2 reduction

While the adsorption properties of transition metal catalysts have been widely studied, leading to the discovery of various scaling relations, descriptors of catalytic activity, and well-established computational models, a similar understanding of semiconductor catalysts has not yet been achieved. In this work, we present a high-throughput density functional theory investigation into the adsorption properties of 5 oxides of interest to the photocatalytic CO 2 reduction reaction: TiO 2 (rutile and anatase), SrTiO 3 , NaTaO 3 , and CeO 2 . Using a systematic approach, we exhaustively identify unique surfaces and construct adsorption structures to undergo geometry optimizations. We then perform a data-driven analysis, which reveals the presence of weak adsorption energy scaling relations, the propensity of adsorbates of interest to interact with oxygen surface sites, and the importance of slab deformation upon adsorption. Our findings are presented in the context of experimental observations and in comparison to previously studied classes of catalysts, such as pure metals and tellurium-containing semiconductors, and reinforce the need for a comprehensive approach to the study of site-specific surface phenomena on semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decomposition of liquid-liquid extraction organic phase structure into critical and pre-peak contributions

Solution nanostructure induced by amphiphile self-association plays an important role in various chemical and physical processes, including liquid-liquid extraction (LLE). Small angle scattering techniques are an essential means of probing this structure, but, due to non-uniqueness of scattering patterns, their interpretation is not trivial. Here, in this study, we decompose small angle x-ray scattering (SAXS) patterns for a range of binary LLE organic phases into two components: Ornstein-Zernike and pre-peak contributions resulting from, respectively, critical concentration fluctuations and packing of the amphiphilic extractant molecules in the nonpolar aliphatic diluent. While we previously applied Ornstein-Zernike scattering models to similar organic phases, including the pre-peak explicitly in the fit allows us to measure weak fluctuations at high extractant concentration and simultaneously obtain information on the position and intensity of the correlation peak related to amphiphile packing. Scattering patterns and partial structure factors calculated from molecular dynamics simulations support this interpretation. We demonstrate how this minimal scattering model describes nanostructuring for a large number of extractant types over their entire extractant/diluent composition ranges, suggesting simple and universal behavior. The straightforward assignment of these structural contributions facilitates the comparison of these features between different classes of extractant molecules and will enable further studies of organic phase aggregation. Applicability to more complex, process-relevant organic phases is illustrated with post-contact organic phases containing significant quantities of extracted lanthanide nitrate salt, which we find are readily described by this model.

74 ATOMIC AND MOLECULAR PHYSICS↗

Observation of d(t,n) α Neutrons Following d(d,p)t Reactions in a Deuterium Gas Cell: An Attempt to Repeat Ruhlig’s 1938 Observation of Secondary Reactions

In order to benchmark methods used to calculate reaction-in-flight fusion reactions in inertial confinement fusion and address issues related to the first claimed observation of d(t,n)α reactions in 1938, secondary d(t,n)α reactions have been observed following d(d,p)t reactions in deuterium gas. A pulsed 200-nA, 2.2-MeV deuterium beam from the Triangle Universities Nuclear Laboratory FN tandem accelerator was injected into a cylindrical multiatmosphere deuterium gas target. The incident beam traversed along the target cylinder’s 3-cm symmetry axis after its passage through a Havar entrance foil. Two different Havar foil thicknesses were used to obtain 1.5- and 0.6-MeV deuteron beams entering the deuterium cell. The cylinder’s radius was 2 cm to allow for d(d,p)t tritons emitted perpendicular to the beam to range out in the deuterium gas. The neutron emission from the cell was observed via its time of flight to a liquid scintillator placed at various angles to the beam direction, at a distance of 243 cm. Pulse-shape-discrimination techniques were used to separate neutron and gamma-ray signals seen in the liquid scintillator. The observed probability of ~2 × 10 –4 for inducing secondary d(t,n)α fusion in the gas cell per d(d,p)t reaction is consistent with theoretical expectations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART)

This report contains key findings from a project titled Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART), which was carried out through a collaborative effort of a team of researchers from Texas A&M Engineering Experiment Station, Temple University, and Quanta Technology, LLC. The in-kind support came from OSIsoft (acquired by AVEVA), which provided their PI Historian software to demonstrate the use case of streaming PMU data. The first section of the report describes the project goals and objectives related to the development of Machine Learning (ML) models capable of detecting and classifying events by processing phasor measurements captured in the field by Phasor Measurement Units (PMUs). The data for this study was contributed by the utilities/ISOs from the Western and Eastern interconnects and ERCOT, further referred to as Interconnect B (IC B), Interconnect A (IC A), and Interconnect C (IC C), respectively. The approach that the BDSMART Research Team proposed and the key research tasks defined by the team are outlined in this section. The next section describes the technical approach. We first discuss the data constraints related to the PMU measurements and data interpretation constraints imposed by the data contributors. They provided neither the topological information of the grid nor PMU placement locations and captured recorded data at very few locations in the system with the reporting rate of either 30 or 60 fps. The recordings are mostly positive sequence voltage, frequency, and ROCOF, and in some limited cases, three-phase voltages and currents. We then reflect on the bad data issues that stem from poor recording practices and vague definitions of the PMU status bits to supposedly be used for bad data identification. Finally, the data discovery points to imprecise time stamps with incomplete event start/end time, as well as inconsistent and incomplete event labeling, which combined make the implementation of the data models using supervising learning quite challenging. Following the data discovery study, we hypothesize that because the IC B data has the most complete labels, we should focus our model development on that data and then test it on data from other interconnects. We also define the common metrics used to evaluate the results from the ML algorithm tests. We concluded this section by summarizing the common ML models we used and explaining how we implemented and tested them. The issues from this section are expanded in the Training Dataset Report from this project. The final section of this report deals with the accomplishments and conclusions. As the accomplishments, we formulate the problem we are solving and what is achieved by solving the problem. We then reflect on each of the analytics tools we developed and point out the performance of each tool when applied to solving the mentioned problems. We reference this work for further details to the papers we published on each tool. In the conclusions, we give recommendations on how to improve future PMU recording practices to facilitate the ML algorithm implementation and guidance for the future standardization work aimed at clarifying the ambiguities associated with the PMU status bits. We finally list future tasks that can bring about further improvements in the proposed algorithms. The issues from this section are expanded in the Training, and Test Dataset Report filed at the project completion date.

97 MATHEMATICS AND COMPUTING↗

Iron-corrected Single-epoch Black Hole Masses of DESI Quasars at Low Redshift

We present a study on the possible overestimation of single-epoch supermassive black hole (SMBH) masses in previous works, based on more than 55,000 type 1 quasars at 0.25 < z < 0.8 from the Dark Energy Spectroscopic Instrument (DESI). We confirm that iron emission strength serves as a good tracer of the Eddington ratio, and estimate SMBH masses using an iron-corrected R–L relation for Hβ, where R is the broad-line region size and L is the continuum luminosity. Compared with our measurements, previous canonical measurements without the iron correction are overestimated by a factor of 1.5 on average. The overestimation can be up to a factor of 5 for super-Eddington quasars. The fraction of super-Eddington quasars in our sample is about 5%, significantly higher than 0.4% derived from the canonical measurements. Using a sample featuring both Hβ and Mg II emission lines, we calibrate Mg II -based SMBH masses using iron-corrected, Hβ-based SMBH masses and establish an iron-corrected R–L relation for Mg II . The revised relation features a flatter luminosity dependence with a slope of 0.36 and incorporates an additional term of −0.21R Fe , where R Fe denotes the relative iron strength. We use this formula to build a catalog of about 0.5 million DESI quasars at 0.6 < z < 1.6. If these iron-corrected R–L relations for Hβ and Mg II are valid at high redshift, current mass measurements of luminous quasars at z ≥ 6 would have been overestimated by a factor of 2.3 on average, alleviating the tension between SMBH mass and growth history in the early universe.

active galactic nuclei↗

Constraining the particle-scale diversity of black carbon light absorption using a unified framework

Abstract. Atmospheric black carbon (BC), the strongest absorber of visible solar radiation in the atmosphere, manifests across a wide spectrum of morphologies and compositional heterogeneity. Phenomenologically, the distribution of BC among diverse particles of varied composition gives rise to enhancement of its light absorption capabilities by over twofold in comparison to that of nascent or unmixed homogeneous BC. This situation has challenged the modeling community to consider the full complexity and diversity of BC on a per-particle basis for accurate estimation of its light absorption. The conventionally adopted core–shell approximation, although computationally inexpensive, is inadequate not only in estimating but also capturing absorption trends for ambient BC. Here we develop a unified framework that encompasses the complex diversity in BC morphology and composition using a single metric, the phase shift parameter (ρBC), which quantifies how much phase shift the incoming light waves encounter across a particle compared to that in its absence. We systematically investigate variations in ρBC across the multi-space distribution of BC morphology, mixing state, mass, and composition as reported by field and laboratory observations. We find that ρBC>1 leads to decreased absorption by BC, which explains the weaker absorption enhancements observed in certain regional BC compared to laboratory results of similar mixing state. We formulate universal scaling laws centered on ρBC and provide physics-based insights regarding core–shell approximation overestimating BC light absorption. We conclude by packaging our framework in an open-source Python application to facilitate community-level use in future BC-related research. The package has two main functionalities. The first functionality is for forward problems, wherein experimentally measured BC mixing state and assumed BC morphology are input, and the aerosol absorption properties are output. The second functionality is for inverse problems, wherein experimentally measured BC mixing state and absorption are input, and the morphology of BC is returned. Further, if absorption is measured at multiple wavelengths, the package facilitates the estimation of the imaginary refractive index of coating materials by combining the forward and inverse procedures. Our framework thus provides a computationally inexpensive source for calculation of absorption by BC and can be used to constrain light absorption throughout the atmospheric lifetime of BC.

54 ENVIRONMENTAL SCIENCES↗

On the statistical theory of self-gravitating collisionless dark matter flow

Dark matter, if it exists, accounts for five times as much as the ordinary baryonic matter. Compared to hydrodynamic turbulence, the flow of dark matter might possess the widest presence in our universe. This paper presents a statistical theory for the flow of dark matter that is compared with N-body simulations. By contrast to hydrodynamics of normal fluids, dark matter flow is self-gravitating, long-range, and collisionless with a scale-dependent flow behavior. The peculiar velocity field is of constant divergence nature on small scale and irrotational on large scale. The statistical measures, i.e., correlation, structure, dispersion, and spectrum functions, are modeled on both small and large scales, respectively. Kinematic relations between statistical measures are fully developed for incompressible, constant divergence, and irrotational flow. Incompressible and constant divergence flow share the same kinematic relations for even order correlations. The limiting correlation of velocity $\mathrm{ρ_{L}=1/2}$ on the smallest scale ( r = 0) is a unique feature of collisionless flow (⁠$\mathrm{ρ_{L}=1}$ for incompressible flow). On large scale, transverse velocity correlation has an exponential form $T_{2}∝e^{–r/r_2}$ with a constant comoving scale r 2 =21.3 Mpc/h that may be related to the horizon size at matter–radiation equality. All other correlation, structure, dispersion, and spectrum functions for velocity, density, and potential fields are derived analytically from kinematic relations for irrotational flow. On small scale, longitudinal structure function follows one-fourth law of ${S}_{2}^{1}∝r^{1/4}$. All other statistical measures can be obtained from kinematic relations for constant divergence flow. Vorticity is negatively correlated for scale r between 1 and 7 Mpc/h. Divergence is negatively correlated for r > 30 Mpc/h that leads to a negative density correlation.

79 ASTRONOMY AND ASTROPHYSICS↗