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DOE OSTI2022

A Comparative Analysis of Weizmannia coagulans Genomes Unravels the Genetic Potential for Biotechnological Applications

The production of biochemicals requires the use of microbial strains with efficient substrate conversion and excellent environmental robustness, such as Weizmannia coagulans species. So far, the genomes of 47 strains have been sequenced. Herein, we report a comparative genomic analysis of nine strains on the full repertoire of Carbohydrate-Active enZymes (CAZymes), secretion systems, and resistance mechanisms to environmental challenges. Moreover, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) immune system along with CRISPR-associated (Cas) genes, was also analyzed. Overall, this study expands our understanding of the strain’s genomic diversity of W. coagulans to fully exploit its potential in biotechnological applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A structural underpinning of the lower critical solution temperature (LCST) behavior behind temperature-switchable liquids

In this work, we use state-of-the-art X-ray scattering and molecular dynamics to analyze amine-water mixtures that show the unusual lower critical solution temperature (LCST) behavior. The goal is to provide direct experimental evidence for the entropy-lowering molecular cluster formation hypothesized as necessary for LCST behavior. Differential wide-angle X-ray scattering and pair distribution analysis and small-angle X-ray scattering measurements were combined with molecular modeling and liquid-liquid equilibrium measurements, revealing direct experimental evidence for the hypothesis. However, the response of the amine phase to accommodating water is even more subtle than the simple hypothesis suggests, with the formation of robust nanoscale reverse micelles. The techniques developed in this paper can be expected to yield insights in the use of temperature-switchable liquids in solvent extraction and other separations, and the stabilization of organelles in living cells that do not have physical membranes but do require compositional gradients to operate.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Comparison of state-interaction and spinor-representation calculations of spin-orbit coupling within exact two-component coupled-cluster theories

Here a benchmark study of state-interaction and spinor-representation calculations of spin-orbit coupling using the exact two-component Hamiltonians with atomic mean-field integrals (the X2CAMF schemes) at the equation-of-motion coupled-cluster singles and doubles level is reported. We adopt a version of the X2CAMF scheme with spin-orbit integrals correct to first order for the state-interaction calculations and a version correct to infinite order for the spinor-representation calculations. The differences between the state-interaction calculations with minimum active spaces to account for (quasi-)degeneracy and the spinor-representation calculations thus correspond to higher-order spin-orbit contributions. This state-interaction approach with scalar-relativistic effects accurately included in the reference functions and in the spin-orbit integrals is shown to exhibit robust performance for elements across the periodic table. On the other hand, the more rigorous spinor representation shows more rapid convergence with respect to the number of correlated electrons and is the preferred choice for accurate calculations for heavy elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Attention Network Forecasts Time-to-Failure in Laboratory Shear Experiments

Rocks under stress deform by creep mechanisms that include formation and slip on small-scale internal cracks. Intragranular cracks and slip along grain contacts release energy as elastic waves termed acoustic emissions (AE). AEs are thought to contain predictive information that can be used for fault failure forecasting. Here, we present a method using unsupervised classification and an attention network to forecast labquakes using AE waveform features. Our data were generated in a laboratory setting using a biaxial shearing device with granular fault gouge intended to mimic the conditions of tectonic faults. Here, we analyzed the temporal evolution of AEs generated throughout several hundred laboratory earthquake cycles. We used a Conscience Self-Organizing Map (CSOM) to perform topologically ordered vector quantization based on waveform properties. The resulting map was used to interactively cluster AEs. We examined the clusters over time to identify those with predictive ability. Finally, we used a variety of LSTM and attention-based networks to test the predictive power of the AE clusters. By tracking cumulative waveform features over the seismic cycle, the network is able to forecast the time-to-failure (TTF) of lab earthquakes. Our results show that analyzing the data to isolate predictive signals and using a more sophisticated network architecture are key to robustly forecasting labquakes. In the future, this method could be applied on tectonic faults to monitor earthquakes and augment early warning systems.

58 GEOSCIENCES↗

DOE OSTI2021

Directing reaction pathways via in situ control of active site geometries in PdAu single-atom alloy catalysts

Abstract The atomic scale structure of the active sites in heterogeneous catalysts is central to their reactivity and selectivity. Therefore, understanding active site stability and evolution under different reaction conditions is key to the design of efficient and robust catalysts. Herein we describe theoretical calculations which predict that carbon monoxide can be used to stabilize different active site geometries in bimetallic alloys and then demonstrate experimentally that the same PdAu bimetallic catalyst can be transitioned between a single-atom alloy and a Pd cluster phase. Each state of the catalyst exhibits distinct selectivity for the dehydrogenation of ethanol reaction with the single-atom alloy phase exhibiting high selectivity to acetaldehyde and hydrogen versus a range of products from Pd clusters. First-principles based Monte Carlo calculations explain the origin of this active site ensemble size tuning effect, and this work serves as a demonstration of what should be a general phenomenon that enables in situ control over catalyst selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2012

A Suzaku Study of Ejecta Structure and Origin of Hard X-ray Emission in the Supernova Remnant G156.2+5.7

We report an X-ray study of the evolved Galactic supernova remnant (SNR) G1S6.2+S.7 based on six pointing observations with Suzaku. The remnant's large extent (100' in diameter) allows us to investigate its radial structure in the northwestern and eastern directions from the apparent center. The X-ray spectra. were well fit with a two-component non-equilibrium ionization model representing the swept-up interstellar medium (ISM) and the metal-rich ejecta. We found prominent central concentrations of Si, S and Fe from the ejecta component; the lighter elements of O, Ne and Mg were distributed more uniformly. The temperature of the ISM component suggests a slow shock (610-960 km/s), hence the remnant's age is estimated to be 7,000-15,000 yr, assuming its distance to be approx. 1.1 kpc. G1S6.2+5.7 has also been thought to emit hard, non-thermal X-rays, despite being considerably older than any other such remnant. In response to a recent discovery of a background cluster of galaxies (2XMM J045637.2+522411), we carefully excluded its contribution, and reexamined the origin of the hard X-ray emission. We found that the residual hard X-ray emission is consistent with the expected level of the cosmic X-ray background. Thus, no robust evidence for the non-thermal emission was obtained from G156.2+5.7. These results are consistent with the picture of an evolved SNR.

Uchida, Hiroyuki↗

DOE OSTI2022

The Factory and the Beehive. IV. A Comprehensive Study of the Rotation X-Ray Activity Relation in Praesepe and the Hyades

X-ray observations of low-mass stars in open clusters are critical to understanding the dependence of magnetic activity on stellar properties and their evolution. Praesepe and the Hyades, two of the nearest, most-studied open clusters, are among the best available laboratories for examining the dependence of magnetic activity on rotation for stars with masses ≲1 M ⊙ . We present an updated study of the rotation–X-ray activity relation in the two clusters. We updated membership catalogs that combine pre-Gaia catalogs with new catalogs based on Gaia Data Release 2. The resulting catalogs are the most inclusive ones for both clusters: 1739 Praesepe and 1315 Hyades stars. We collected X-ray detections for cluster members, for which we analyzed, re-analyzed, or collated data from ROSAT, the Chandra X-ray Observatory, the Neil Gehrels Swift Observatory, and XMM-Newton. We have detections for 326 Praesepe and 462 Hyades members, of which 273 and 164, respectively, have rotation periods—an increase of 6× relative to what was previously available. We find that at ≈700 Myr, only M dwarfs remain saturated in X-rays, with only tentative evidence for supersaturation. We also find a tight relation between the Rossby number and fractional X-ray luminosity L X /L bol in unsaturated single members, suggesting a power-law index between –3.2 and –3.9. Lastly, we find no difference in the coronal parameters between binary and single members. These results provide essential insight into the relative efficiency of magnetic heating of the stars' atmospheres, thereby informing the development of robust age-rotation-activity relations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Efficient machine learning interatomic potentials robust for liquid and multiple solid polymorphs of NaF and KF

Achieving atomic-level understanding of crystallization of molten salts is of importance to a wide range of technological applications. Recent work [Fan et al., Proc. Natl. Acad. Sci. USA 122, e2425702122 (2025)] revealed that crystal nucleation in molten LiF salt is a multistage process according to the molecular-dynamics (MD) simulations based on an atomic cluster expansion (ACE) machine-learning interatomic potential (MLIP). In order to understand the influence of increasing cation size on nucleation pathways and nucleation rates of molten fluoride salts, here we develop two new ACE MLIPs for NaF and KF. The two ACE MLIPs feature DFT-SCAN-level accuracy for liquid and multiple solid polymorphs over a wide temperature (0–2000 K) and pressure (0–100 GPa) range, and also reproduce well a number of experimental data for solid and liquid equilibrium properties. The efficiency of the two ACE MLIPs enable million-atom-scale or microsecond-scale MD simulations. The two general-purpose ACE MLIPs are expected to be useful for atomistic simulations for different purposes, in addition to studying crystallization of molten NaF and KF salts.

Crystal melting↗

DOE OSTI2021

Effects of fluorinated solvents on electrolyte solvation structures and electrode/electrolyte interphases for lithium metal batteries

Electrolyte is very critical to the performance of the high-voltage lithium (Li) metal battery (LMB), which is one of the most attractive candidates for the next generation high-density energy storage systems. Electrolyte formulation and structure determine the physical properties of the electrolytes and their interfacial chemistries on the electrode surfaces. Localized high-concentration electrolytes (LHCEs) outperform state-of-the-art carbonate electrolytes in many aspects in LMBs due to their unique solvation structure. Types of fluorinated co-solvents used in LHCEs are investigated here in searching for the most suitable diluent for high concentration electrolytes (HCEs). Non-solvating solvents (including fluorinated ethers, fluorinated borate and fluorinated orthoformate) added in HCEs enable the formation of LHCEs with high-concentration solvation structures. However, low solvating fluorinated carbonate will coordinate with Li+ ions and form a second solvation shell or a pseudo-LHCE which diminishes the benefits of LHCE. In addition, it is evident that the diluent has significant influence on the electrode/electrolyte interphases (EEIs) beyond retaining the high-concentration solvation structures. Diluent molecules surrounding the high-concentration clusters could accelerate or decelerate the anion decomposition through co-participation of diluent decomposition in the EEI formation. The varied interphase features lead to significantly different battery-performance. This study points out the importance of diluents and their synergetic effects with the conductive salt and the solvating solvent in designing LHCEs. These systematic comparisons and fundamental insights into LHCEs using different types of fluorinated solvents can guide further development of advanced electrolytes for high-voltage LMBs.

Cao, Xia↗

DOE OSTI2022

Multiple spillovers from humans and onward transmission of SARS-CoV-2 in white-tailed deer

Many animal species are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and could act as reservoirs; however, transmission in free-living animals has not been documented. White-tailed deer, the predominant cervid in North America, are susceptible to SARS-CoV-2 infection, and experimentally infected fawns can transmit the virus. To test the hypothesis that SARS-CoV-2 is circulating in deer, 283 retropharyngeal lymph node (RPLN) samples collected from 151 free-living and 132 captive deer in Iowa from April 2020 through January of 2021 were assayed for the presence of SARS-CoV-2 RNA. Ninety-four of the 283 (33.2%) deer samples were positive for SARS-CoV-2 RNA as assessed by RT-PCR. Notably, following the November 2020 peak of human cases in Iowa, and coinciding with the onset of winter and the peak deer hunting season, SARS-CoV-2 RNA was detected in 80 of 97 (82.5%) RPLN samples collected over a 7-wk period. Whole genome sequencing of all 94 positive RPLN samples identified 12 SARS-CoV-2 lineages, with B.1.2 (n = 51; 54.5%) and B.1.311 (n = 19; 20%) accounting for ~75% of all samples. The geographic distribution and nesting of clusters of deer and human lineages strongly suggest multiple human-to-deer transmission events followed by subsequent deer-to-deer spread. These discoveries have important implications for the long-term persistence of the SARS-CoV-2 pandemic. Our findings highlight an urgent need for a robust and proactive “One Health” approach to obtain enhanced understanding of the ecology, molecular evolution, and dissemination of SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2023

The optimization of model ensemble composition and size can enhance the robustness of crop yield projections

Linked climate and crop simulation models are widely used to assess the impact of climate change on agriculture. However, it is unclear how ensemble configurations (model composition and size) influence crop yield projections and uncertainty. Here, we investigate the influences of ensemble configurations on crop yield projections and modeling uncertainty from Global Gridded Crop Models and Global Climate Models under future climate change. We performed a cluster analysis to identify distinct groups of ensemble members based on their projected outcomes, revealing unique patterns in crop yield projections and corresponding uncertainty levels, particularly for wheat and soybean. Furthermore, our findings suggest that approximately six Global Gridded Crop Models and 10 Global Climate Models are sufficient to capture modeling uncertainty, while a cluster-based selection of 3-4 Global Gridded Crop Models effectively represents the full ensemble. The contribution of individual Global Gridded Crop Models to overall uncertainty varies depending on region and crop type, emphasizing the importance of considering the impact of specific models when selecting models for local-scale applications. Our results emphasize the importance of model composition and ensemble size in identifying the primary sources of uncertainty in crop yield projections, offering valuable guidance for optimizing ensemble configurations in climate-crop modeling studies tailored to specific applications.

Agriculture↗

DOE OSTI2020

Modeling regional precipitation over the Indus River basin of Pakistan using statistical downscaling

Complex processes govern spatiotemporal distribution of precipitation within the high-mountainous headwater regions (commonly known as the upper Indus basin (UIB)), of the Indus River basin of Pakistan. Reliable precipitation simulations particularly over the UIB present a major scientific challenge due to regional complexity and inadequate observational coverage. Here, we present a statistical downscaling approach to model observed precipitation of the entire Indus basin, with a focus on UIB within available data constraints. Taking advantage of recent high altitude (HA) observatories, we perform precipitation regionalization using K-means cluster analysis to demonstrate effectiveness of low-altitude stations to provide useful precipitation inferences over more uncertain and hydrologically important HA of the UIB. We further employ generalized linear models (GLM) with gamma and Tweedie distributions to identify major dynamic and thermodynamic drivers from a reanalysis dataset within a robust cross-validation framework that explain observed spatiotemporal precipitation patterns across the Indus basin. Final statistical models demonstrate higher predictability to resolve precipitation variability over wetter southern Himalayans and different lower Indus regions, by mainly using different dynamic predictors. The modeling framework also shows an adequate performance over more complex and uncertain trans-Himalayans and the northwestern regions of the UIB, particularly during the seasons dominated by the westerly circulations. However, the cryosphere-dominated trans-Himalayan regions, which largely govern the basin hydrology, require relatively complex models that contain dynamic and thermodynamic circulations. Furthermore, we also analyzed relevant atmospheric circulations during precipitation anomalies over the UIB, to evaluate physical consistency of the statistical models, as an additional measure of reliability. Overall, our results suggest that such circulation-based statistical downscaling has the potential to improve our understanding towards distinct features of the regional-scale precipitation across the upper and lower Indus basin. Additionally, such understanding should help to assess the response of this complex, data-scarce, and climate-sensitive river basin amid future climatic changes, to serve communal and scientific interests.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Baryon acoustic oscillation theory and modelling systematics for the DESI 2024 results

This paper provides a comprehensive overview of how fitting of baryon acoustic oscillations (BAO) is carried out within the upcoming Dark Energy Spectroscopic Instrument’s (DESI) 2024 results using its DR1 data set, and the associated systematic error budget from theory and modelling of the BAO. We derive new results showing how non-linearities in the clustering of galaxies can cause potential biases in measurements of the isotropic (⁠α iso ⁠) and anisotropic (⁠α ap ) BAO distance scales, and how these can be effectively removed with an appropriate choice of reconstruction algorithm. We then demonstrate how theory leads to a clear choice for how to model the BAO and develop, implement, and validate a new model for the remaining smooth-broad-band (i.e. without BAO) component of the galaxy clustering. Finally, we explore the impact of all remaining modelling choices on the BAO constraints from DESI using a suite of high-precision simulations, arriving at a set of best practices for DESI BAO fits, and an associated theory and modelling systematic error. Overall, our results demonstrate the remarkable robustness of the BAO to all our modelling choices and motivate a combined theory and modelling systematic error contribution to the post-reconstruction DESI BAO measurements of no more than 0.1 per cent (0.2 per cent) for its isotropic (anisotropic) distance measurements. We expect the theory and best practices laid out to here to be applicable to other BAO experiments in the era of DESI and beyond.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Robust calibration of non-perturbative models with history matching

We apply, for the first time, Bayes Linear Emulation and History Matching to the calibration of non-perturbative models in Monte Carlo event generators. In contrast to the usual approach of "Monte Carlo tuning", History Matching does not result in best-fit plus ellipsoidal parameter uncertainty estimates but instead identifies all parameter space regions that are consistent with data. This approach leads to a systematic and robust quantification of parametric uncertainties in the models, especially in those challenging cases where different, possibly disjoint, regions of parameter space deliver similar results, which are usually not properly treated with current methodology. We highlight the power of this method with the hadronisation models available through Sherpa : the built-in cluster fragmentation Ahadic and string fragmentation through an interface to Pythia .

Iskauskas, Andrew [Durham U. (main)] (ORCID:000000↗

NASA NTRS2004

Proceedings from the 2nd International Symposium on Formation Flying Missions and Technologies

Topics discussed include: The Stellar Imager (SI) "Vision Mission"; First Formation Flying Demonstration Mission Including on Flight Nulling; Formation Flying X-ray Telescope in L2 Orbit; SPECS: The Kilometer-baseline Far-IR Interferometer in NASA's Space Science Roadmap Presentation; A Tight Formation for Along-track SAR Interferometry; Realization of the Solar Power Satellite using the Formation Flying Solar Reflector; SIMBOL-X : Formation Flying for High-Energy Astrophysics; High Precision Optical Metrology for DARWIN; Close Formation Flight of Micro-Satellites for SAR Interferometry; Station-Keeping Requirements for Astronomical Imaging with Constellations of Free-Flying Collectors; Closed-Loop Control of Formation Flying Satellites; Formation Control for the MAXIM Mission; Precision Formation Keeping at L2 Using the Autonomous Formation Flying Sensor; Robust Control of Multiple Spacecraft Formation Flying; Virtual Rigid Body (VRB) Satellite Formation Control: Stable Mode-Switching and Cross-Coupling; Electromagnetic Formation Flight (EMFF) System Design, Mission Capabilities, and Testbed Development; Navigation Algorithms for Formation Flying Missions; Use of Formation Flying Small Satellites Incorporating OISL's in a Tandem Cluster Mission; Semimajor Axis Estimation Strategies; Relative Attitude Determination of Earth Orbiting Formations Using GPS Receivers; Analysis of Formation Flying in Eccentric Orbits Using Linearized Equations of Relative Motion; Conservative Analytical Collision Probabilities for Orbital Formation Flying; Equations of Motion and Stability of Two Spacecraft in Formation at the Earth/Moon Triangular Libration Points; Formations Near the Libration Points: Design Strategies Using Natural and Non-Natural Ares; An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer; GVE-Based Dynamics and Control for Formation Flying Spacecraft; GNC System Design for a New Concept of X-Ray Distributed Telescope; GNC System for the Deployment and Fine Control of the DARWIN Free-Flying Interferometer; Formation Algorithm and Simulation Testbed; and PLATFORM: A Formation Flying, RvD and Robotic Validation Test-bench.

Source record↗

DOE OSTI2024

Clustering Interval Load with Weather to Create Scenarios of Behind-the-Meter Solar Penetration

Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation is only visible to the utility as aggregated net-load. This work proposes a methodology for creation of scenarios of solar penetration at the feeder level for use by forecasters to test the robustness of their algorithm to progressively higher penetrations of solar. The algorithm draws on publicly available observations of weather condition (e.g., rainy/cloudy/fair) for use as proxies to sky clearness. These observations are used to mask and weight the interval deviations of similar native usage profiles from which average interval usage is calculated and subsequently added to interval net generation to reconstruct interval total generation. This approach improves the estimate of annual energy generation by 23%; where the net generation signal currently reflects 52% of total annual gener- ation, now 75% is captured. This methodology for creation of forecast testing scenarios is data driven and extensible to service territories which lack information on irradiance measurements and geocoordinates.

solar, load↗

DOE OSTI2026

Assembly bias and local Primordial non-Gaussianity from DESI DR1 quasars

The analysis of the large-scale clustering of quasars (QSO) observed by the Dark Energy Spectroscopic Instrument (DESI) represents a promising avenue for constraining local Primordial non-Gaussianity (PNG), parameterized by f NL . The signal to be constrained is the scale-dependent bias induced in the 2-point clustering of the considered tracer sample. The resulting constraints on f NL , however, are fully degenerate with the local PNG bias parameter b ϕ , dependent on the assembly bias parameter p. Using IllustrisTNG hydrodynamical simulations, we select a QSO sample reflecting the selection criteria and properties of DESI QSOs, and provide a robust prior for p, and thus for b ϕ , building on the findings of Fondi et al. 2024. We find a distribution with mean p̅ ≃ 1.4 with weak redshift dependence, stable to selection noise and consistent with the expected recent merger history typical of quasar-hosting halos. By comparing with the CAMELS simulations we demonstrate that this prior is robust to astrophysical assumptions and cosmic variance. Finally, applying this prior to the DESI DR1 dataset, we derive updated constraints on local PNG, obtaining f NL = -3.3±9.2.

cosmological parameters from LSS↗

DOE OSTI2024

Was There a 3.5 keV Line?

Abstract The 3.5 keV line is a purported emission line observed in galaxies, galaxy clusters, and the Milky Way whose origin is inconsistent with known atomic transitions and has previously been suggested to arise from dark matter decay. We systematically reexamine the bulk of the evidence for the 3.5 keV line, attempting to reproduce six previous analyses that found evidence for the line. We only reproduce one of the analyses; in the other five, we find no significant evidence for a 3.5 keV line when following the described analysis procedures on the original data sets. For example, previous results claimed 4 σ evidence for a 3.5 keV line from the Perseus cluster; we dispute this claim, finding no evidence for a 3.5 keV line. We find evidence for background mismodeling in multiple analyses. We show that analyzing these data in narrower energy windows diminishes the effects of mismodeling but returns no evidence for a 3.5 keV line. We conclude that there is little robust evidence for the existence of the 3.5 keV line. Some of the discrepancy of our results from those of the original works may be due to the earlier reliance on local optimizers, which we demonstrate can lead to incorrect results. For ease of reproducibility, all code and data are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗