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DOE OSTI2021

Higher-order kinematical effects in deeply virtual Compton scattering

We study the deeply virtual Compton scattering cross-section in twist-two generalized parton distribution (GPD) approximation, and show that different choices of light-cone vectors and gauges for the final photon polarization will lead to different higher-order kinematical corrections to the cross-section formula. The choice of light-cone vectors affects kinematic corrections at the twist-three level, accounting for the differences between the cross-section formulas in the literature. On the other hand, kinematical corrections from higher-twist GPDs should eliminate the light-cone dependence at twist three. Those light-cone dependencies are studied systematically at JLab 12 GeV and future EIC kinematics. They serve as the intrinsic systematic uncertainties in extracting the Compton form factors through the cross-section formula. More importantly, they are also necessary for understanding cross-section measurements with higher-twist precision and to reconstruct higher-order Compton form factors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Search for the doubly charmed baryon $ {\varXi}_{cc}^{+} $ in the $ {\varXi}_c^{+}{\pi}^{-}{\pi}^{+} $ final state

A search for the doubly charmed baryon $ {\varXi}_{cc}^{+} $ is performed in the $ {\varXi}_c^{+}{\pi}^{-}{\pi}^{+} $ invariant-mass spectrum, where the $ {\varXi}_c^{+} $ baryon is reconstructed in the pK - π + final state. The study uses proton-proton collision data collected with the LHCb detector at a centre- of-mass energy of 13 TeV, corresponding to a total integrated luminosity of 5.4 fb -1 . No significant signal is observed in the invariant-mass range of 3.4–3.8 GeV/ c 2 . Upper limits are set on the ratio of branching fractions multiplied by the production cross-section with respect to the $ {\varXi}_{cc}^{++} $ →( $ {\varXi}_c^{+} $ → pK - π + ) π + decay for different $ {\varXi}_{cc}^{+} $ mass and lifetime hypotheses in the rapidity range from 2.0 to 4.5 and the transverse momentum range from 2.5 to 25 GeV/ c . The results from this search are combined with a previously published search for the $ {\varXi}_{cc}^{+} $ → $ {\varLambda}_c^{+} $ K - π + decay mode, yielding a maximum local significance of 4.0 standard deviations around the mass of 3620 MeV/ c 2 , including systematic uncertainties. Taking into account the look-elsewhere effect in the 3.5–3.7 GeV/ c 2 mass window, the combined global significance is 2.9 standard deviations including systematic uncertainties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Process-driven roadmap for depositing super duplex stainless steel via wire Arc additive manufacturing

Here, this study systematically investigates the effects of shielding gas, bead spacing, weld mode, and travel speed on the phase balance, porosity, and hardness of wire arc additively manufactured (WAAM) super duplex stainless steel (ER2594). Robotic WAAM was employed to fabricate multilayer walls under systematically varied process conditions, followed by phase transformation simulations, X-ray computed tomography (XCT), electron backscatter diffraction (EBSD), and microhardness evaluation. Thermodynamic simulations predicted rapid cooling of AM process can suppress the potential formation of deleterious precipitates which was later validated via cross-sectional microstructure analyses of printed samples. XCT revealed porosity levels below 0.2% for all deposits, with reduced travel speed significantly lowering defect volume. Microstructural analyses revealed the evolution of various austenite precipitates, including grain boundary austenite (GBA), Widmanstätten austenite (WA), and intergranular austenite (IGA), sequentially upon cooling of the ferrite phase. Among all process parameters, weld transfer mode exhibited the strongest influence on phase balance; pulsed mode promoted higher ferrite retention (~ 36%) compared to RapidX mode. No consistent relationship between stabilized phase fraction and captured microhardness was observed. This work provides critical insights for optimizing WAAM parameters to control phase balance and mechanical performance, which is essential for producing high-integrity super duplex stainless-steel components for nuclear and marine applications.

Grain orientation↗

DOE OSTI2020

Deletion analysis of the itaconic acid biosynthesis gene cluster components in Aspergillus pseudoterreus ATCC32359

The filamentous fungus Aspergillus terreus has been successfully used for industrial production of itaconic acid (IA) for many years. The IA biosynthesis pathway has recently been characterized at a molecular genetic level as an IA gene cluster (IA cluster) by a clone-based transcriptomic approach. The cluster consists of four genes, including genes for cis-aconitic acid decarboxylase (cadA), a predicted transcription factor (tf), mitochondrial organic acid transporter (mttA), and MFS (Major Facilitator Superfamily) type transporter (mfsA). In this research, we performed EST (Expressed Sequence Tag) analysis and systematic gene deletions to investigate the role of those genes in IA biosynthesis in A. pseudoterreus ATCC32359. EST analysis showed a similar expression pattern among those four genes that was distinct from neighbouring genes and further confirmed that they belong to the same biosynthesis cluster. Systematic gene deletion analysis demonstrated that tf, cadA, mttA, and mfsA genes in the cluster are essential for IA production. Deletion of any of them will either completely abolish the IA production or dramatically decrease amount of IA produced. More importantly, a significant amount of aconitic acid was detected in the cadA deletion strain but not in the other deletion strains. Therefore, the cadA deletion strain is a novel microorganism host for production of aconitic acid and other value-added chemicals from lignocellulosic biomass.

Deng, Shuang↗

DOE OSTI2026

Kinetic control of phase evolution and defect-mediated recombination in AACVD-grown copper antimony sulphide thin films

Copper antimony sulphide (CAS) is a multinary chalcogenide semiconductor in which small deviations from stoichiometry can drive phase competition and strong defect-mediated modulation of optoelectronic properties. However, the systematic roles of copper precursor fraction and deposition time in governing phase evolution, off-stoichiometry, and recombination dynamics in aerosol-assisted chemical vapour deposition (AACVD)-grown undoped CAS thin films remain insufficiently understood. In this work, undoped CAS thin films were deposited by AACVD using Cu(dedtc)2 and Sb(dedtc)3 single-source precursors at 550 °C and a carrier gas flow rate of 150 sccm, while the Cu(dedtc)2 mole fraction (x = 0.15 – 0.55) and deposition time (1 – 2 hours) were systematically varied to probe how growth kinetics influence phase composition, microstructure, and defect-mediated optical properties without post-deposition annealing or extrinsic doping. Increasing copper precursor content drives phase evolution toward tetrahedrite-dominant CAS films at intermediate Cu(dedtc)2 mole fractions, with the film deposited at x = 0.35 exhibiting the strongest tetrahedrite character within the parameter space examined. The films are also copper-rich, antimony-poor, and sulphur-deficient, consistent with off-stoichiometric growth and intrinsic defect formation, plausibly including copper interstitials, Cu-on-Sb antisites, and sulphur vacancies. These growth-dependent compositional deviations are accompanied by tunable indirect optical bandgaps of approximately 1.60 – 2.18 eV and weak visible photoluminescence governed by defect-mediated recombination. Time-resolved photoluminescence reveals bi-exponential decay behaviour with lifetimes of approximately 0.1 – 3.6 ns, with emission dominated by slower donor–acceptor pair recombination and a smaller contribution from faster trap-assisted pathways. Collectively, these results establish an explicit kinetic process–structure–defect–property relationship for AACVD-grown CAS thin films and provide a growth–structure–property framework relevant to future optimization of CAS-based optoelectronic and energy materials.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Decoding the dynamics of poleward shifting climate zones using aqua-planet model simulations

Growing evidence indicates that the atmospheric and oceanic circulation experiences a systematic poleward shift in a warming climate. However, the complexity of the climate system, including the coupling between the ocean and the atmosphere, natural climate variability and land-sea distribution, tends to obfuscate the causal mechanism underlying the circulation shift. Here, using an idealised coupled aqua-planet model, we explore the mechanism of the shifting circulation, by isolating the contributing factors from the direct CO 2 forcing, the indirect ocean surface warming, and the wind-stress feedback from the ocean dynamics. We find that, in contrast to the direct CO 2 forcing, ocean surface warming, in particular an enhanced subtropical ocean warming, plays an important role in driving the circulation shift. This enhanced subtropical ocean warming emerges from the background Ekman convergence of surface anomalous heat in the absence of the ocean dynamical change. Additionally, it expands the tropical warm water zone, causes a poleward shift of the mid-latitude temperature gradient, hence forces a corresponding shift in the atmospheric circulation and the associated wind pattern. The shift in wind, in turn drives a shift in the ocean circulation. Our simulations, despite being idealised, capture the main features of the observed climate changes, for example, the enhanced subtropical ocean warming, poleward shift of the patterns of near-surface wind, sea level pressure, storm tracks, precipitation and large-scale ocean circulation, implying that increase in greenhouse gas concentrations not only raises the temperature, but can also systematically shift the climate zones poleward.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Optical Characterization of the Keck Array and BICEP3 CMB Polarimeters from 2016 to 2019

The BICEP/Keck experiment (BK) is a series of small-aperture refracting telescopes observing degree-scale cosmic microwave background (CMB) polarization from the South Pole in search of a primordial B-mode signature. This B-mode signal arises from primordial gravitational waves interacting with the CMB and has amplitude parametrized by the tensor-to-scalar ratio r. Since 2016, BICEP3 and the Keck Array have been observing with 4800 total antenna-coupled transition-edge sensor detectors, with frequency bands spanning 95, 150, 220, and 270 GHz. Here we present the optical performance of these receivers from 2016 to 2019, including far-field beams measured in situ with an improved chopped thermal source and instrument spectral response measured with a field-deployable Fourier transform spectrometer. As a pair differencing experiment, an important systematic that must be controlled is the differential beam response between the co-located, orthogonally polarized detectors. We generate per-detector far-field beam maps and the corresponding differential beam mismatch that is used to estimate the temperature-to-polarization leakage in our CMB maps and to give feedback on detector and optics fabrication. The differential beam parameters presented here were estimated using improved low-level beam map analysis techniques, including efficient removal of non-Gaussian noise as well as improved spatial masking. These techniques help minimize systematic uncertainty in the beam analysis, with the goal of constraining the bias on r induced by temperature-to-polarization leakage to be subdominant to the statistical uncertainty. This is essential as we progress to higher detector counts in the next generation of CMB experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

A Geo-Data Science Method for Assessing Unconventional Rare-Earth Element Resources in Sedimentary Systems

Abstract Rare-earth elements (REEs) supply raw materials that constitute many of our modern critical infrastructure, defense, technology, and electrification needs. Despite REE accumulations occurring in conventional bedrock and ion-adsorption deposits sourced from weathering of igneous rocks, unconventional host materials such as coal and related sedimentary strata have been identified as promising sources of REEs to meet growing demand. To maximize the potential of unconventional resources such as REE-coal systems, new approaches are needed overcome challenges from mineral systems with no known deposits and areas with sparse geochemical data. This article presents a systematic knowledge-data resource assessment method for predicting and identifying REE resource potential and occurrence in these unconventional systems. The method utilizes a geologic and geospatial knowledge-data approach informed and guided by REE accumulation mechanisms to systematically assess and identify areas of higher enrichment. An assessment of the Powder River Basin is presented as a test case to demonstrate the method workflow and results. The key output is a potential enrichment score map reported with varying confidence levels based on the amount of supporting evidence. Results from the test case indicate several locations with promising potential for different types of coal-REE deposits, demonstrating the viability of the method for exploration and assessment of unconventional REE resources. The method is flexible by design and, with sufficient applicable knowledge and data, can be adapted for assessing critical mineral systems in other sedimentary systems as well.

58 GEOSCIENCES↗

DOE OSTI2025

Metasomatic Alteration of Type 3 Ordinary and Carbonaceous Chondrites

Metasomatism refers to the process during which a pre-existing rock undergoes compositional and mineralogical transformations associated with chemical reactions triggered by the reaction of fluids which invade the protolith. It changes chemical compositions of minerals, promotes their dissolution and precipitation of new minerals. In this paper, we review metasomatic alteration of type 3 ordinary (H, L, LL) and carbonaceous (CV, CO, CK) chondrites, including (i) secondary mineralization, (ii) physicochemical conditions, (iii) chronology ( 53 Mn- 53 Cr, 26 Al- 26 Mg, 129 I- 129 Xe) of metasomatic alteration, (iv) records of metasomatic alteration in H, O, N, C, S, and Cl isotopic systematics, (v) effects of metasomatic alteration on O- and Al-Mg-isotope systematics of primary minerals in chondrules and refractory inclusions, and (vi) sources of water ices in metasomatically altered CV, CO, and ordinary chondrites, and outline future studies.

129I-129Xe chronology↗

DOE OSTI2025

Evaluation of normalization strategies for mass spectrometry-based multi-omics datasets

Introduction Data normalization is crucial for multi-omics integration, reducing systematic errors and maximizing the likelihood of discovering true biological variation. Most studies assess normalization for a single omics type or use datasets from separate experiments. Few address time-course data, where normalization might bias temporal differentiation. In this study, we compared common normalization methods and a machine learning approach, Systematical Error Removal using Random Forest (SERRF), using multi-omics datasets generated from the same experiment—even from the same cell lysate. Objectives To develop a straightforward process to assess normalization effects and identify the most robust methods across multi-omics datasets. Methods We analyzed metabolomics, lipidomics, and proteomics datasets from primary human cardiomyocytes and motor neurons exposed to acetylcholine-active compounds over time. Normalization effectiveness was evaluated based on improvement in QC features consistency and observing the change in treatment and time-related variance. Results Probabilistic Quotient Normalization (PQN) and Locally Estimated Scatterplot Smoothing (LOESS) QC were identified as optimal for metabolomics and lipidomics, while PQN, Median, and LOESS normalization excelled for proteomics. These methods consistently enhanced QC feature consistency in metabolomics and lipidomics, and preserved time-related variance or treatment-related variance in proteomics, demonstrating their effectiveness and robustness. SERRF normalization, applied only to metabolomics in this study, outperformed other methods in some datasets but inadvertently masked treatment-related variance in others. Conclusion Our evaluation identified PQN and LoessQC as the top methods for metabolomics and lipidomics, and PQN, Median, and Loess normalization for proteomics, in multi-omics integration in a temporal study.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Challenges and opportunities of machine learning control in building operations

Machine learning control (MLC) is a highly flexible and adaptable method that enables the design, modeling, tuning, and maintenance of building controllers to be more accurate, automated, flexible, and adaptable. The research topic of MLC in building energy systems is developing rapidly, but to our knowledge, no review has been published that specifically and systematically focuses on MLC for building energy systems. Here this paper provides a systematic review of MLC in building energy systems. We review technical papers in two major categories of applications of machine learning in building control: (1) building system and component modeling for control, and (2) control process learning. We identify MLC topics that have been well-studied and those that need further research in the field of building operation control. We also identify the gaps between the present and future application of MLC and predict future trends and opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

A comprehensive diffusion mobility database comprising 23 elements for magnesium alloys

We report that reliable experimental diffusion coefficients of 10 key alloying elements in Mg obtained by the present authors together with experimental data in the literature enabled us to perform a systematic test of the reliability of diffusion coefficients obtained from DFT calculations. The computed activation energy values were found to be quite accurate (mostly within 0.2 eV) but the computed pre-factors were less reliable. Such insights allowed us to develop a practical and yet robust strategy to perform diffusion mobility assessments by adopting the computed activation energy while fitting only the pre-factor when available experimental data are limited to a narrow temperature range. The overall good agreement between the DFT data and experimental data also gave us the confidence to employ the computed data for those that were still missing or inaccessible from experimental measurements. A systematic assessment of both the measured and computed diffusion data in hcp Mg was performed using the above holistic approach to yield the most comprehensive open Mg mobility database to date, comprising 23 elements (Mg, Ag, Al, Be, Ca, Cd, Ce, Cu, Fe, Ga, Gd, In, La, Li, Mn, Nd, Ni, Pu, Sb, Sn, U, Y, Zn). This more reliable mobility database will contribute to future development of advanced Mg alloys. The holistic approach developed in this study will be very beneficial to the future establishment of reliable mobility databases for other alloy systems as well.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Sensor impact evaluation and verification for fault detection and diagnostics in building energy systems: A review

Sensors are the key information source for fault detection and diagnostics (FDD) in buildings. However, sensors are often not properly designed, installed, calibrated, located, and maintained, which negatively impacts FDD performance. Several sensor-related FDD topics have been widely studied, covering a wide range of fault types and applications. However, it is difficult to get a clear picture of the technical development of sensor-related topics in FDD. A systematic review of sensor topics is needed to summarize the existing research in a logical way, draw conclusions on the current development, and predict the future development of sensors in building FDD. To address this gap, we conducted a comprehensive literature review of more than 100 FDD-sensor-related papers. In this article, we subdivide the FDD tasks into building-level, system-level, and component-level FDD, and review sensor-related topics in each category. Our major conclusions are: (a) current data-driven FDD research focuses more on FDD algorithms than sensors, (b) sensor “hardware” research topics are less studied than sensor “software” topics, (c) very few papers focus on sensor engineering as an integral aspect of FDD development, and (d) some important sensor topics, such as sensor cost-effectiveness and sensor schema/layout/location, are not well studied. Finally, we discuss the need for a systematic framework of FDD sensors and models to integrate sensor design/selection, sensor data analysis/mining, feature selection, physics-based or data-driven algorithm development, sensor fault detection, sensor calibration, and sensor maintenance. Finally, expert interviews are conducted to validate the above findings and conclusions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Remote sensing of seasonal variation of LAI and fAPAR in a deciduous broadleaf forest

Climate change is affecting the phenology of terrestrial ecosystems. In deciduous forests, phenology in leaf area index (LAI) is the primary driver of seasonal variation in the fraction of absorbed photosynthetically active radiation (fAPAR), which drives photosynthesis. Remote sensing has been widely used to estimate LAI and fAPAR. However, while many studies have examined both empirical and model-based relationships among LAI, fAPAR, and spectral vegetation indices (SVI) from remote sensing, few studies have systematically and empirically examined how relationships among these variables change over the growing season. In this study, we examine how and why seasonal-scale covariation differs among time series of remotely sensed SVIs and both LAI and fAPAR based on current understanding and theory. To do this we use newly available remote sensing data sets in combination with time series of in-situ measurements and a canopy radiative transfer model to analyze how seasonal variation in canopy and environmental conditions affect relationships among remotely sensed SVIs, LAI, and fAPAR at a temperate deciduous forest site in central Massachusetts. Our results show that accounting for seasonal variation in canopy shadowing, which is driven by variation in solar zenith angle, improved remote sensing-based estimates of LAI, fAPAR, and daily total APAR. Specifically, we show that the phenology of SVIs is strongly influenced by seasonal variation in near infrared (NIR) reflectance arising from systematic variation in the canopy shadow fraction that is independent of changes in LAI or fAPAR. Therefore, results of this work provide a refined basis for understanding how remote sensing can be used to monitor and model the phenology of LAI, fAPAR, APAR, and gross primary productivity in temperate deciduous forests.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Effective field theory for two-body systems with shallow S -wave resonances

Resonances are of particular importance to the scattering of composite particles in quantum mechanics. We build an effective field theory for two-body scattering which includes a low-energy S-wave resonance. Our starting point is the most general Lagrangian with short-range interactions. We demonstrate that these interactions can be organized into various orders so as to generate a systematic expansion for an S matrix with two low-energy poles. The pole positions are restricted by renormalization at leading order, where the common feature is a non-positive effective range. We carry out the expansion explicitly to next-to-leading order and illustrate how it systematically accounts for the results of a toy model — a spherical well with a delta shell at its border.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Non-local corrections to the typical medium theory of Anderson localization

We use the recently developed finite cluster typical medium approach to study the Anderson localization transition in three dimensions. Applying our method to the box and binary alloy disorder distributions, we find a fast convergence with the cluster size. We demonstrate the importance of the typical medium environment and the non-local spatial correlations for the proper characterization of the localization transition. As the cluster size increases, our typical medium cluster method recovers the correct critical disorder strength for the transition. Our findings highlight the importance of the non-local cluster corrections for capturing the localization behavior of the mobility edge trajectories. Our results demonstrate that the typical medium cluster approach developed here provides a consistent and systematic description of the Anderson localization transition in the framework of the effective medium embedding schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Quantum kinetics of anomalous and nonlinear Hall effects in topological semimetals

Highlights: • Linear and photogalvanic anomalous Hall responses are systematically derived. • Extrinsic mechanisms of AHE include Gaussian, diffractive, hybrid skew scattering. • Diagrammatic calculations are matched to semiclassical picture of AHE. • The Pancharatnam phase of multifold fermions determines the skew scattering amplitude. • Photon-induced interband scattering are accompanied by coordinate shifts. We present a systematic microscopic derivation of the semiclassical Boltzmann equation for band structures with the finite Berry curvature based on Keldysh technique of nonequilibrium systems. In the analysis, an AC electrical driving field is kept up to quadratic order, and both cases of small and large frequencies corresponding to intra- and interband transitions are considered. In particular, this formulation is suitable for the study of nonlinear Hall effect and photogalvanic phenomena. The role of impurity scattering is carefully addressed. Specifically, in addition to previously studied side-jump and skew-scattering processes, quantum interference diffractive contributions are now explicitly incorporated within the developed framework. This theory is applied to multifold fermions in topological semimetals, for which the generic formula for the skew scattering rate from the Pancharatnam phase is obtained along with the corresponding anomalous Hall conductivity.

36 MATERIALS SCIENCE↗