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DOE OSTI2022

Core spectroscopy of oxazole

We have measured, analyzed and simulated the ground state valence photoelectron (PES), X-ray absorption (XAS), X-ray photoelectron (XPS) as well as normal and resonant Auger-Meitner electron (AES) spectra of oxazole at the carbon, oxygen and nitrogen K-edge in order to understand its electronic structure. Experimental data is compared to theoretical calculations performed at the coupled cluster, restricted active space perturbation theory to second order and time-dependent density functional levels of theory. We demonstrate that both N and O K-edge XAS are sensitive to the amount of dynamical electron correlation included in the theoretical description, and that for a complete description of XPS, additional orbital correlation and orbital relaxation effects need to be considered. The normal AES are dominated by a singlet excitation channel and well described by theory. Furthermore, the resonant AES, however, are more complicated. While the participator decay channels, dominating at higher kinetic energies, are well described by coupled cluster theory, spectator channels can only be described satisfactorily using a method that combines restricted active space perturbation theory to second order for the bound part and a one-center approximation for the continuum.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2021

Development and experimental qualification of novel disruption prevention techniques on DIII-D

Novel disruption prevention solutions spanning a range of control regimes are being developed and tested on DIII-D to enable ITER success. First, a new real-time control algorithm has been developed and tested for regulating nearness to stability limits and maintaining safety-margins. Its first application has been for reliable prevention of vertical displacement events (VDEs) by adjusting plasma elongation (κ) and the inner-gap between the plasma and inner-wall in response to real- time open-loop VDE growth rate (γ) estimators. VDEs were robustly prevented up to average open-loop growth rates of 800 rad/s with initial tunings, with only applying shape modification when near safety limits. Second, the disruption risk during fast, emergency shutdown after large tearing and locked modes can be significantly improved by transitioning to a limited topology during shutdown. More than 50% of emergency limited shutdowns after locked modes reach a final normalized current I_N < 0.3 before terminating, scaling to the 3 MA ITER requirement. Furthermore, this is in contrast to diverted shutdowns, the majority of which disrupt at I_N > 0.8. Despite improvements, these results highlight the critical importance of early prevention. Third, a novel emergency shut down method has been developed which excites instabilities to form a warm, helical core post-thermal quench. The current quench extends to ~100ms and avoids VDEs and runaway electron generation. Novel real-time machine learning disruption prediction has been integrated with the DIII-D proximity controller, and a real- time compatible multi-mode MHD spectroscopy technique has been developed. Results presented here were enabled by a focused effort, the Disruption Free Protocol, in DIII-D’s 2019-20 campaign to complement disruption prevention experiments with a large piggy-back program. In addition to testing novel techniques, it is estimated to have helped avoid 32 potential disruptions in piggyback operations with rapid, early shutdowns after large rotating n=1 or locked modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Type Ia supernova magnitude step from the local dark matter environment

ABSTRACT Residuals in the Hubble diagram at optical wavelengths and host galaxy stellar mass are observed to correlate in type Ia supernovae (SNe Ia) (‘magnitude step’). Among possible progenitor channels for the associated explosions, those based on dark matter (DM) have attracted significant attention, including our recent proposal that ‘normal’ SNe Ia from bare detonations in sub-Chandrasekhar white dwarf stars are triggered by the passage of asteroid-mass primordial black holes (PBHs): the magnitude step could then originate from a brightness dependence on stellar properties, on DM properties, or both. Here, we present a method to estimate the local DM density and velocity dispersion of the environment of SN Ia progenitors. We find a luminosity step of $0.52\pm 0.11\,$ mag corresponding to bins of high versus low DM density in a sample of 222 low-redshift events from The Open Supernova Catalog. We investigate whether the magnitude step can be attributed to local DM properties alone, assuming asteroid-mass PBHs. Given the inverse correlation between SN Ia brightness and PBH mass, an intriguing explanation is a spatially inhomogeneous PBH mass function. If so, a strong mass segregation in the DM density-dependent PBH mass scale is needed to explain the magnitude step. While mass segregation is observed in dense clusters, it is unlikely to be realized on galactic scales. Therefore, if DM consists of asteroid-mass PBHs, the magnitude step is more likely to exist, and dominantly to be attributed to local stellar properties.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Low-order aquifer thermal energy storage model for geothermal system simulation

This paper presents a low-order aquifer thermal energy storage (ATES) model for simulation of combined subsurface and above-surface energy systems. The model is included in the Modelica IBPSA Library, which is a free open-source library with basic models for building and district energy and control systems. The model uses a lumped-component method, in which the transient conductive-convective heat and mass transfer equation is radially discretized. To verify the accuracy of the model, we present an inter-model comparison from a simulation test suite. Results show that the Modelica ATES model is in good agreement, with a normalized mean bias error for yearly variation of aquifer temperatures of 1.6×10−2 and 9×10−5 at 1 m and 10 m distance from the well.

Maccarini, Alessandro↗

DOE OSTI2022

Assessing the Contribution of ECa and NDVI in the Delineation of Management Zones in a Vineyard

Precision fertilization implies the need to identify the variability of soil fertility, which is costly and time-consuming. Remotely measured data can be a solution. Using this strategy, a study was conducted, in a vineyard, to delineate different management zones using two indicators: apparent soil electrical conductivity (ECa) and normalized difference vegetation index (NDVI). To understand the contribution of each indicator, three scenarios were used for zone definition: (1) using only NDVI, (2) only ECa, or (3) using a combination of the two. Then the differences in soil fertility between these zones were assessed using simple statistical methods. The results indicate that the most beneficial strategy is the combined use of the two indicators, as it allowed the definition of three distinct zones regarding important soil variables and crop nutrients, such as soil total nitrogen, Mg2+ cation, exchange acidity, and effective cation exchange capacity, and some relevant cation ratios. This strategy also allowed the identification of an ionic unbalance in the soil chemistry, due to an excess of Mg2+, that was harming crop health, as reported by NDVI. This also impacted ECa and NDVI relationship, which was negative in this study. Overall, the results demonstrate the advantages of using remotely sensed data, mainly more than one type of sensing data, and suggest a high potential for differential crop fertilization and soil management in the study area.

Esteves, Catarina (ORCID:0000000327205906)↗

DOE OSTI2020

BISON Robustness and Performance Improvements

BISON is a modern finite-element based nuclear fuel performance code that has been under development at the Idaho National Laboratory (USA) since 2009 [1]. The code is applicable to both steady and transient fuel behavior and can be used to analyze 1D (spherically symmetric), 2D (axisymmetric and generalized plane strain) or 3D geometries. BISON is the fuel performance code used within CASL for LWR fuel under both normal operating and accident conditions. BISON is built using the INL Multiphysics ObjectOriented Simulation Environment, or MOOSE [2, 3]. MOOSE is a massively parallel, finite element-based framework to solve systems of coupled non-linear partial differential equations using the Jacobian-Free Newton Krylov (JFNK) method [4]. This enables investigation of computationally large problems, for example a full stack of discrete pellets in a LWR fuel rod, or every rod in a full reactor core. MOOSE supports the use of complex two and three-dimensional meshes and uses implicit time integration, important for the widely varied time scale in nuclear fuel simulation. An object-oriented architecture is employed which greatly minimizes the programming effort required to add new material and behavioral models. The flexibility of the implicit and fully coupled multiphysics approach comes with a need for constructing suitable approximations for the Jacobian matrix of the coupled system used for either preconditioning a Krylov solve or in a direct Newton solve. Preconditioning options for Bison problems need to be revisited with new preconditioning methods becoming available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Birefringent waveplate and method for forming a waveplate having a birefringent metasurface

The present disclosure relates to a waveplate having a substrate forming an optic. The substrate may have an integral portion forming a plurality of angled columnar features on an exposed surface thereof. The plurality of angled columnar features may further be aligned parallel with a directional plane formed non-parallel to a reference plane, with the reference plane being normal to a surface of the substrate. The metasurface forms a birefringent metasurface.

Feigenbaum, Eyal↗

DOE OSTI2021

Assessment of Clonal Expansion Using CarcSeq Measurement of Lung Cancer Driver Mutations and Correlation With Mouse Strain- and Sex-Related Incidence of Spontaneous Lung Neoplasia

Quantification of variation in levels of spontaneously occurring cancer driver mutations (CDMs) was developed to assess clonal expansion and predict future risk of neoplasm development. Specifically, an error-corrected next-generation sequencing method, CarcSeq, and a mouse CarcSeq panel (analogous to human and rat panels) were developed and used to quantify low-frequency mutations in a panel of amplicons enriched in hotspot CDMs. Mutations in a subset of panel amplicons, Braf, Egfr, Kras, Stk11, and Tp53, were related to incidence of lung neoplasms at 2 years. This was achieved by correlating median absolute deviation (MAD) from the overall median mutant fraction (MF) measured in the lung DNA of 16-week-old male and female, B6C3F1 and CD-1 mice (10 mice/sex/strain) with percentages of spontaneous alveolar/bronchioloalveolar adenomas and carcinomas reported in bioassay control groups. A total of 1586 mouse lung mutants with MFs > x 10-4 were recovered. The ratio of nonsynonymous to synonymous mutations was used to assess the proportion of recovered mutations conferring a positive selective advantage. The greatest ratio was observed in what is considered the most lung tumor-sensitive model examined, male B6C3F1 mice. Of the recurrent, nonsynonymous mouse mutations recovered, 55.5% have been reported in human tumors, with many located in or around the mouse equivalent of human cancer hotspot codons. MAD for the same subset of amplicons measured in normal human lung DNA samples showed a correlation of moderate strength and borderline significance with age (a cancer risk factor), as well as age-related cumulative lung cancer risk, suggesting MAD may inform species extrapolation.

Toxicology↗

DOE OSTI2025

An Observational Evaluation of RKW Theory over the U.S. Southern Great Plains

The theory of Rotunno et al. (“RKW” theory) addresses the behavior of squall-line cold pools in vertically sheared flows. It predicts that, within a given thermodynamic environment, a balance between baroclinic vorticity generation by the cold pool and low-level environmental vertical wind shear induces an upright updraft along the gust front that maximizes the initiation of new convective cells. Although this theory has been evaluated numerically, its applicability to observed systems remains unclear and is limited by a lack of critical measurements, including high-frequency thermodynamic and wind profiles across the gust front. Herein, observations from the Atmospheric Radiation Measurement Southern Great Plains (ARM-SGP) observatory near Lamont, Oklahoma, are used to evaluate RKW theory for 10 well-observed squall lines over a 11-yr period. For this evaluation, RKW parameters including cold-pool intensity (c), low-level ambient, line-normal vertical shear (ΔV n ), subcloud and cloud-layer updraft tilts, and multiple measures of system intensity are estimated. Furthermore, the c estimates rely on thermodynamic retrievals from the Atmosphere Emitted Radiance Interferometer (AERI), which are uncertain but verify reasonably well against independent observations. As predicted by the theory, for c/ΔV n ≥ 1, c/ΔV n correlates positively with updraft tilt and negatively with system intensity, but these results are not always statistically significant and are also sensitive to the method by which ΔV n is evaluated. Specifically, ΔV n evaluations that extend above the cold-pool top yield greater consistency with RKW predictions. Also, some measures of intensity correlate more strongly with standard moist instability metrics than with RKW parameters.

Cold pools↗

DOE OSTI2021

Measurement of 227 Ac impurity in 225 Ac using decay energy spectroscopy

225 Ac is a valuable medical radionuclide for targeted $\alpha$ therapy, but 227 Ac is an undesirable byproduct of an accelerator-based synthesis method under investigation. Sufficient detector sensitivity is critical for quantifying the trace impurity of 227 Ac, with the 227 Ac/ 225 Ac activity ratio predicted to be approximately 0.15% by end-of-bombardment (EOB). Superconducting transition edge sensor (TES) microcalorimeters offer high resolution energy spectroscopy using the normal-to-superconducting phase transition to measure small changes in temperature. By embedding 225 Ac production samples in a gold foil thermally coupled to a TES microcalorimeter we can measure the decay energies of the radionuclides embedded with high resolution and 100% detection efficiency. This technique, known as decay energy spectroscopy (DES), collapses several peaks from $\alpha$ decays into single Q-value peaks. In practice there are more complex factors in the interpretation of data using DES, which we will discuss in this paper. Using this technique we measured the EOB 227 Ac impurity to be (0.142 ± 0.005)% for a single production sample. This demonstration has shown that DES is a useful tool for quantitative measurements of complicated spectra.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2020

Enhanced Electrocatalytic Hydrogen Evolution Activity in Single-Atom Pt-Decorated VS 2 Nanosheets

Enhancing catalytic activity by decorating noble metals in catalysts provides an opportunity for promoting the electrocatalytic hydrogen evolution reaction (HER) application. However, there are few systematic studies on regulating the structures of noble metals in catalytic materials and investigating their influence on HER. Herein, Pt catalysts with different structures including single atoms (SAs), clusters, and nanoparticles well-controllably anchored on VS 2 nanosheets through a cost-effective optothermal method are reported, and their HER performance is studied. The most efficient Pt-decorated VS 2 catalyst (with both Pt SAs and clusters) delivers an overpotential of 77 mV at 10 mA cm –2 , close to that of Pt/C (48 mV). However, the optimal mass activity of Pt (normalizing to Pt content) is obtained from only SA Pt-decorated VS 2 (i.e., 22.88 A mg Pt –1 at 200 mV) and is 12 times greater than that of the Pt/C (1.87 A mg Pt –1 ), attributed to the greatly enhanced Pt utilization. Additionally, the theoretical simulations reveal that Pt SA decoration makes the adsorption free energy of H* closer to the thermoneutral value and improves the charge-transfer kinetics, significantly enhancing HER activity. Furthermore, this work offers a pathway to prepare the desired catalyst based on synergy of Pt structures and VS 2 and reveals the intrinsic mechanism for enhancing catalytic activity, which is important for HER applications.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Correlating Thermodynamic and Kinetic Hydricities of Rhenium Hydrides

The kinetics of hydride transfer from Re( R bpy)(CO) 3 H (bpy = 4,4'-R-2,2'-bipyridine; R = OMe, t Bu, Me, H, Br, COOMe, CF 3 ) to CO 2 and seven different cationic N-heterocycles were determined. Additionally, the thermodynamic hydricities of complexes of the type Re( R bpy)(CO) 3 H were established primarily using computational methods. Linear free-energy relationships (LFERs) derived by correlating thermodynamic and kinetic hydricities indicate that, in general, the rate of hydride transfer increases as the thermodynamic driving force for the reaction increases. Kinetic isotope effects range from inverse for hydride transfer reactions with a small driving force to normal for reactions with a large driving force. Hammett analysis indicates that hydride transfer reactions with greater thermodynamic driving force are less sensitive to changes in the electronic properties of the metal hydride, presumably because there is less buildup of charge in the increasingly early transition state. Bronsted α values were obtained for a range of hydride transfer reactions and along with DFT calculations suggest the reactions are concerted, which enables the use of Marcus theory to analyze hydride transfer reactions involving transition metal hydrides. It is notable, however, that even slight perturbations in the steric properties of the Re hydride or the hydride acceptor result in large deviations in the predicted rate of hydride transfer based on thermodynamic driving forces. This indicates that thermodynamic considerations alone cannot be used to predict the rate of hydride transfer, which has implications for catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Elastocaloric determination of the phase diagram of Sr 2 RuO 4

One of the main developments in unconventional superconductivity in the past two decades has been the discovery that most unconventional superconductors form phase diagrams that also contain other strongly correlated states. Many systems of interest are therefore close to more than one instability, and tuning between the resultant ordered phases is the subject of intense research. In recent years, uniaxial pressure applied using piezoelectric-based devices has been shown to be a particularly versatile new method of tuning, leading to experiments that have advanced our understanding of the fascinating unconventional superconductor Sr 2 RuO 4 . Here we map out its phase diagram using high-precision measurements of the elastocaloric effect in what we believe to be the first such study including both the normal and the superconducting states. We observe a strong entropy quench on entering the superconducting state, in excellent agreement with a model calculation for pairing at the Van Hove point, and obtain a quantitative estimate of the entropy change associated with entry to a magnetic state that is observed in proximity to the superconductivity. The phase diagram is intriguing both for its similarity to those seen in other families of unconventional superconductors and for extra features unique, so far, to Sr 2 RuO 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Tightest Mixed-Integer Programming Formulations for Quadratic SCUC Optimization

In this project, we developed new, tighter Mixed-Integer Programming (MIP) formulations for the combined Alternating Current (AC) Security-Constrained Unit Commitment (SCUC) and Security-Constrained Optimal Power Flow (SCOPF). The work addresses a critical challenge in power system operations: efficiently determining which generation units to commit and how to optimally dispatch them while maintaining network reliability constraints for both normal and contingency scenarios. Our efforts: 1. Advance the Understanding of SCUC/SCOPF Modeling: By introducing tighter MIP formulations and leveraging cutting-edge optimization tools (Julia/JuMP, PowerModels.jl), this project has pushed forward the state of the art in efficient power systems scheduling. 2. Enhance Technical and Economic Feasibility: The methods developed provide more accurate and potentially faster solutions to large-scale, realistic scheduling and dispatch problems in electric power systems, which can translate into improved reliability and potentially lower costs for grid operations. 3. Benefit to the Public: Greater efficiency in power system operations leads to cost savings for utilities and end-users. Improved reliability and integration of advanced modeling approaches can facilitate the adoption of clean energy resources and better accommodate uncertainties in renewable generation. Because this technology could impact bulk power markets and reliability, these innovations have far-reaching public benefits in terms of cost savings, reliability, and sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study include: CA-OAS, CA-OBS, US-NR1, US-TON, US-VAR, US-SRM, US-WHS, US-WKG. Snotel sites Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP) are included as well 16 east river locations with different vegetation types denoted by evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO). Trained models and metrics for parameters for the Fluxnet sites were added in an update on November 2, 2020; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. NDVI datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

A feasible order-arbitrarily-tunable optical differentiator

We propose a feasible temporal filtering (or spectrum weighting) system to implement optical differentiation with arbitrarily-tunable order. Differentiation order is tuned by programming the temporal weighting mask (TWM) as power function of different exponents, not limited by the structure of the system. Assembly of the system is feasible, since the active parts are implemented by electro-optic elements and some key elements are reused between sub-systems involved in the scheme. Tuning of the system is simple, since electronically pre-stored TWMs are easy to switch among each other. The order-tunable functionality is verified by numerically testing the differentiation cases of normalized input pulse duration ranging from 0.1 to 0.4, and of differentiation order tuned from 1 to 10. Good accuracy is achieved, and measured by root mean square error lower than 0.1. Feasibilities of the system are also verified in terms of accuracy maintaining and distortion avoiding. Compared with existing methods, apart from the arbitrary order-tunable capacity and good accuracy, our proposed optical differentiator also possesses properties of good compactness and constant complexity. The proposed differentiator has unique applications on multi-peak waveform generation for optical communications and photonics-aided Radars with enhanced agility and feasibility.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)

Building electrical load profiles can improve understanding of building energy efficiency, demand flexibility, and building-grid interactions. Current approaches to generating load profiles are time-consuming and not capable of reflecting the dynamic and stochastic behaviors of real buildings; some approaches also trigger data privacy concerns. In this study, we proposed a novel approach for generating realistic electrical load profiles of buildings through the Generative Adversarial Network (GAN), a machine learning technique that is capable of revealing an unknown probability distribution purely from data. The proposed approach has three main steps: (1) normalizing the daily 24-hour load profiles, (2) clustering the daily load profiles with the k-means algorithm, and (3) using GAN to generate daily load profiles for each cluster. The approach was tested with an open-source database – the Building Data Genome Project. We validated the proposed method by comparing the mean, standard deviation, and distribution of key parameters of the generated load profiles with those of the real ones. The KL divergence of the generated and real load profiles are within 0.3 for majority of parameters and clusters. Additionally, results showed the load profiles generated by GAN can capture not only the general trend but also the random variations of the actual electrical loads in buildings. We report the proposed GAN approach can be used to generate building electrical load profiles, verify other load profile generation models, detect changes to load profiles, and more importantly, anonymize smart meter data for sharing, to support research and applications of grid-interactive efficient buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Sequential Kalman tuning of the t -preconditioned Crank-Nicolson algorithm: efficient, adaptive and gradient-free inference for Bayesian inverse problems

Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for the approximate solution of Bayesian inverse problems with expensive forward models. However, when applied to the Bayesian inverse problem EKI is only exact in the regime of Gaussian target measures and linear forward models. Here, in this work we propose embedding EKI and Flow Annealed Kalman Inversion, its normalizing flow (NF) preconditioned variant, within a Bayesian annealing scheme as part of an adaptive implementation of the t-preconditioned Crank-Nicolson (tpCN) sampler. The tpCN sampler differs from standard pCN in that its proposal is reversible with respect to the multivariate t-distribution. The more flexible tail behaviour allows for better adaptation to sampling from non-Gaussian targets. Within our Sequential Kalman Tuning (SKT) adaptation scheme, EKI is used to initialize and precondition the tpCN sampler for each annealed target. The subsequent tpCN iterations ensure particles are correctly distributed according to each annealed target, avoiding the accumulation of errors that would otherwise impact EKI. We demonstrate the performance of SKT for tpCN on three challenging numerical benchmarks, showing significant improvements in the rate of convergence compared to adaptation within standard SMC with importance weighted resampling at each temperature level, and compared to similar adaptive implementations of standard pCN. The SKT scheme applied to tpCN offers an efficient, practical solution for solving the Bayesian inverse problem when gradients of the forward model are not available. Code implementing the SKT schemes for tpCN is available at https://github.com/RichardGrumitt/KalmanMC.

97 MATHEMATICS AND COMPUTING↗