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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Surface Reconstruction in Hydrated Amphiphilic Block Copolymer Thin Films Probed by Fluid Cell Atomic Force Microscopy

In many thin film materials, nuanced interplays of interfacial energies control the surface morphology and rearrangement. This work evaluates polymer−solvent interactions and solvent-driven surface reconstructions via ex situ and in situ fluid cell Atomic Force Microscopy (fc-AFM) analysis of amphiphilic block copolymer (BCP) thin films upon exposure to deionized (DI) water. We examine the differences in surface morphology, whole-film swelling, and force response in thin films of polystyrene-block-poly(ethylene oxide) (PS-b-PEO) and polystyrene- block-poly[(allyl glycidyl ether)-co-(ethylene oxide)] (PS-b- P[AGE-co-EO]) processed into standing-up cylinder morphologies perpendicular to a silicon substrate (⊥C). Using Amplitude Modulation AFM (AM-AFM) and Amplitude-Phase Distance (APD) force spectroscopy, this work probes the mechanoresponsive nature of the dynamic surface layers of these films, unveiling surface layer stratification and surface chain rearrangement via minimal tip−sample stimulation. To help rationalize the observed reconfigurations, the energetic driving forces were estimated using the harmonic mean approximations of interfacial energies. Given the nonionizable nature of the minority P(AGE-co-EO) block and the energetic driving forces for chain mobility, this work shows how the elimination of unfavorable PS−water interfaces drives chain rearrangement and coverage of the PS surface by chains of the hydrophilic block. This work highlights considerations for increasing the heterogeneity and complexity of BCP thin films via random blocks and how those changes to local interfacial energies may drive larger scale film morphology reconstructions, with broader implications for tuning interface hydrophilicity.

Copolymers↗
DOE OSTI2019

Fast response of fungal and prokaryotic communities to climate change manipulation in two contrasting tundra soils

Climate models predict substantial changes in temperature and precipitation patterns across Arctic regions, including increased winter precipitation as snow in the near future. Soil microorganisms are considered key players in organic matter decomposition and regulation of biogeochemical cycles. However, current knowledge regarding their response to future climate changes is limited. Here, we explore the short-term effect of increased snow cover on soil fungal, bacterial and archaeal communities in two tundra sites with contrasting water regimes in Greenland. In order to assess seasonal variation of microbial communities, we collected soil samples four times during the plant-growing season. The analysis revealed that soil microbial communities from two tundra sites differed from each other due to contrasting soil chemical properties. Fungal communities showed higher richness at the dry site whereas richness of prokaryotes was higher at the wet tundra site. We demonstrated that fungal and bacterial communities at both sites were significantly affected by short-term increased snow cover manipulation. Our results showed that fungal community composition was more affected by deeper snow cover compared to prokaryotes. The fungal communities showed changes in both taxonomic and ecological groups in response to climate manipulation. However, the changes were not pronounced at all sampling times which points to the need of multiple sampling in ecosystems where environmental factors show seasonal variation. Further, we showed that effects of increased snow cover were manifested after snow had melted. We demonstrated rapid response of soil fungal and bacterial communities to short-term climate manipulation simulating increased winter precipitation at two tundra sites. In particular, we provide evidence that fungal community composition was more affected by increased snow cover compared to prokaryotes indicating fast adaptability to changing environmental conditions. Since fungi are considered the main decomposers of complex organic matter in terrestrial ecosystems, the stronger response of fungal communities may have implications for organic matter turnover in tundra soils under future climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Robust parallel iterative solvers for linear and least-squares problems (Final Technical Report)

The primary goal of this project is to study and develop robust iterative methods for solving linear systems of equations and least squares systems. The focus of the Minnesota team is on algorithms development, robustness issues, and on tests and validation of the methods on realistic problems. 1. The project begun with an investigation on how to practically update a preconditioner obtained from an ILU-type factorization, when the coefficient matrix changes. 2. We investigated strategies to improve robustness in parallel preconditioners in a specific case of a PDE with discontinuous coefficients. 3. We explored ways to adapt standard preconditioners for solving linear systems arising from the Helmholtz equation. These are often difficult linear systems to solve by iterative methods. 4. We have also worked on purely theoretical issues related to the analysis of Krylov subspace methods for linear systems. 5. We developed an effective strategy for performing ILU factorizations for the case when the matrix is highly indefinite. The strategy uses shifting in some optimal way. The method was extended to the solution of Helmholtz equations by using complex shifts, yielding very good results in many cases. 6. We addressed the difficult problem of preconditioning sparse systems of equations on GPUs. 7. A by-product of the above work is a software package consisting of an iterative solver library for GPUs based on CUDA. This was made publicly available. It was the first such library that offers complete iterative solvers for GPUs. 8. We considered another form of ILU which blends coarsening techniques from Multigrid with algebraic multilevel methods. 9. We have released a new version on our parallel solver - called pARMS [new version is version 3]. As part of this we have tested the code in complex settings - including the solution of Maxwell and Helmholtz equations and for a problem of crystal growth.10. As an application of polynomial preconditioning we considered the problem of evaluating f(A)v which arises in statistical sampling. 11. As an application to the methods we developed, we tackled the problem of computing the diagonal of the inverse of a matrix. This arises in statistical applications as well as in many applications in physics. We explored probing methods as well as domain-decomposition type methods. 12. A collaboration with researchers from Toulouse, France, considered the important problem of computing the Schur complement in a domain-decomposition approach. 13. We explored new ways of preconditioning linear systems, based on low-rank approximations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Bayesian inference of nonlinear unsteady aerodynamics from aeroelastic limit cycle oscillations

A Bayesian model selection and parameter estimation algorithm is applied to investigate the influence of nonlinear and unsteady aerodynamic loads on the limit cycle oscillation (LCO) of a pitching airfoil in the transitional Reynolds number regime. At small angles of attack, laminar boundary layer trailing edge separation causes negative aerodynamic damping leading to the LCO. The fluid–structure interaction of the rigid, but elastically mounted, airfoil and nonlinear unsteady aerodynamics is represented by two coupled nonlinear stochastic ordinary differential equations containing uncertain parameters and model approximation errors. Several plausible aerodynamic models with increasing complexity are proposed to describe the aeroelastic system leading to LCO. The likelihood in the posterior parameter probability density function (pdf) is available semi-analytically using the extended Kalman filter for the state estimation of the coupled nonlinear structural and unsteady aerodynamic model. The posterior parameter pdf is sampled using a parallel and adaptive Markov Chain Monte Carlo (MCMC) algorithm. The posterior probability of each model is estimated using the Chib–Jeliazkov method that directly uses the posterior MCMC samples for evidence (marginal likelihood) computation. The Bayesian algorithm is validated through a numerical study and then applied to model the nonlinear unsteady aerodynamic loads using wind-tunnel test data at various Reynolds numbers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

M DWARF ACTIVITY IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY: FIRST CATALOG AND ROTATION PERIODS

We report on an ongoing project to investigate activity in the M dwarf stellar population observed by the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). Using a custom-built pipeline, we refine an initial sample of ∼4 million sources in PS1-MDS to a sample of 184,148 candidate cool stars using color cuts. Motivated by the well-known relationship between rotation and stellar activity, we use a multiband periodogram analysis and visual vetting to identify 270 sources that are likely rotating M dwarfs. We derive a new set of polynomials relating M dwarf PS1 colors to fundamental stellar parameters and use them to estimate the masses, distances, effective temperatures, and bolometric luminosities of our sample. We present a catalog containing these values, our measured rotation periods, and cross-matches to other surveys. Our final sample spans periods of ≲1–130 days in stars with estimated effective temperatures of ∼2700–4000 K. Twenty-two of our sources have X-ray cross-matches, and they are found to be relatively X-ray bright as would be expected from selection effects. Our data set provides evidence that Kepler -based searches have not been sensitive to very slowly rotating stars ( P {sub rot} ≳ 70 day), implying that the observed emergence of very slow rotators in studies of low-mass stars may be a systematic effect. We also see a lack of low-amplitude (<2%) variability in objects with intermediate (10–40 day) rotation periods, which, considered in conjunction with other observational results, may be a signpost of a loss of magnetic complexity associated with a phase of rapid spin-down in intermediate-age M dwarfs. This work represents just a first step in exploring stellar variability in data from the PS1-MDS and, in the farther future, Large Synoptic Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

An Uncertainty Analysis of the Hydrogen Source Term for a Station Blackout Accident in Sequoyah Using MELCOR 1.8.5

A methodology for using the MELCOR code with the Latin Hypercube Sampling method was developed to estimate uncertainty in various predicted quantities such as hydrogen generation or release of fission products under severe accident conditions. In this case, the emphasis was on estimating the range of hydrogen sources in station blackout conditions in the Sequoyah Ice Condenser plant, taking into account uncertainties in the modeled physics known to affect hydrogen generation. The method uses user-specified likelihood distributions for uncertain model parameters, which may include uncertainties of a stochastic nature, to produce a collection of code calculations, or realizations, characterizing the range of possible outcomes. Forty MELCOR code realizations of Sequoyah were conducted that included 10 uncertain parameters, producing a range of in-vessel hydrogen quantities. The range of total hydrogen produced was approximately 583kg ± 131kg. Sensitivity analyses revealed expected trends with respected to the parameters of greatest importance, however, considerable scatter in results when plotted against any of the uncertain parameters was observed, with no parameter manifesting dominant effects on hydrogen generation. It is concluded that, with respect to the physics parameters investigated, in order to further reduce predicted hydrogen uncertainty, it would be necessary to reduce all physics parameter uncertainties similarly, bearing in mind that some parameters are inherently uncertain within a range. It is suspected that some residual uncertainty associated with modeling complex, coupled and synergistic phenomena, is an inherent aspect of complex systems and cannot be reduced to point value estimates. The probabilistic analyses such as the one demonstrated in this work are important to properly characterize response of complex systems such as severe accident progression in nuclear power plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.

3D electron microscopy↗
DOE OSTI2026

Search for light pseudoscalar boson pairs produced from Higgs boson decays using the 4τ and 2μ2τ final states in proton-proton collisions at $\sqrt{s}=13$ TeV

A search for a pair of light pseudoscalar bosons (a 1 ) produced in the decay of the 125 GeV Higgs boson is presented. The analysis examines decay modes where one a 1 decays into a pair of tau leptons and the other decays into either another pair of tau leptons or a pair of muons. The a1 boson mass probed in this study ranges from 4 to 15 GeV. The data sample was recorded by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponds to an integrated luminosity of 138 fb −1 . No excess above standard model (SM) expectations is observed. The study combines the 4τ and 2μ2τ channels to set upper limits at 95% confidence level (CL) on the product of the Higgs boson production cross section and the branching fraction to the 4τ final state, relative to the Higgs boson production cross section predicted by the SM. In this interpretation, the a 1 boson is assumed to have Yukawa-like couplings to fermions, with coupling strengths proportional to the respective fermion masses. The observed (expected) upper limits range between 0.007 (0.011) and 0.079 (0.066) across the mass range considered. The results are also interpreted in the context of models with two Higgs doublets and an additional complex singlet field (2HD+S). The tightest constraints are obtained for the Type III 2HD+S model. In this case, assuming the Higgs boson production cross section equals the SM prediction, values of the branching ratio for the Higgs boson decay into a pair of a1 bosons exceeding 16% are excluded at 95% CL for a1 boson masses between 5 and 15 GeV and tan β > 2, with the exception of scenarios in which the a1 boson mixes with charm or bottom quark-antiquark bound states.

Higgs physics↗
DOE OSTI2022

Survey of Surveys: I. The largest compilation of radial velocities for the Galaxy

In the present-day panorama of large spectroscopic surveys, the amount, diversity, and complexity of the available data continuously increase. The overarching goal of studying the formation and evolution of our Galaxy is hampered by the heterogeneity of instruments, selection functions, analysis methods, and measured quantities. Here, we present a comprehensive catalogue, the Survey of Surveys (SoS), built by homogeneously merging the radial velocity (RV) determinations of the largest ground-based spectroscopic surveys to date, such as APOGEE, GALAH, Gaia-ESO, RAVE, and LAMOST, using Gaia as a reference. This pilot study serves to prove the concept and to test the methodology that we plan to apply in the future to the stellar parameters and abundance ratios as well. We have devised a multi-staged procedure that includes: (i) the cross match between Gaia and the spectroscopic surveys using the official Gaia cross-match algorithm, (ii) the normalisation of uncertainties using repeated measurements or the three-cornered hat method, (iii) the cross calibration of the RVs as a function of the main parameters on which depend (magnitude, effective temperature, surface gravity, metallicity, and signal-to-noise ratio) to remove trends and zero point offsets, and (iv) the comparison with external high-resolution samples, such as the Gaia RV standards and the Geneva-Copenhagen survey, to validate the homogenisation procedure and to calibrate the RV zero-point of the SoS catalogue. We provide the largest homogenised RV catalogue to date, containing almost 11 million stars, of which about half come exclusively from Gaia and half in combination with the ground-based surveys. We estimate the accuracy of the RV zero-point to be about 0.16–0.31 km s –1 and the RV precision to be in the range 0.05–1.50 km s –1 depending on the type of star and on its survey provenance. We validate the SoS RVs with open clusters from a high resolution homogeneous samples and provide the systemic velocity of 55 individual open clusters. Additionally, we provide median RVs for 532 clusters recently discovered by Gaia data. The SoS is publicly available and ready to be applied to various research projects, such as the study of star clusters, Galactic archaeology, stellar streams, or the characterisation of planet-hosting stars, to name a few. We also plan to include survey updates and more data sources in future versions of the SoS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Toward the origins of binding energy shifts and “satellites” formation during plasma-XPS measurements

In-plasma x-ray photoelectron spectroscopy (plasma-XPS) emerges as a powerful platform for real-time, in situ chemical analysis under conditions relevant to semiconductor processing and other plasma-enabled technologies. This study investigates the origins of binding energy (BE) shifts and the formation of “satellite” peaks observed during plasma-XPS measurements across conductive, dielectric, and gas-phase systems. Using a standard laboratory-based ambient pressure XPS apparatus coupled with an alternating current (AC)-driven capacitively coupled plasma source, we demonstrate that metastable surface species, such as transient Au oxides, can be detected during plasma exposure, revealing chemical states that are hardly accessible using conventional ultrahigh vacuum (UHV) XPS. In dielectric samples (e.g., undoped diamond, sapphire), we observe pressure- and plasma-type-dependent BE shifts of more than 50 eV, attributed to x-ray-induced and plasma-mediated surface charging. These shifts are mitigated at higher pressures/plasmas or in electronegative plasmas (e.g., O 2 ), the latter due to enhanced charge compensation mechanisms involving slow negative ions. For gas-phase species, AC-plasma excitation leads to spectral broadening and the emergence of “satellite” peaks with energy separations of a few electron volts, linked to oscillating local plasma potentials in the probing volume. Furthermore, these findings highlight the complex and important interplay between plasma parameters, surface charging, and local electric fields in shaping XPS spectra. Overall, plasma-XPS emerges as a critical metrological tool for probing transient surface chemistry, with implications for semiconductor processing, material synthesis, and plasma diagnostics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

NORTH DAKOTA CARBONSAFE PHASE III: SITE CHARACTERIZATION AND PERMITTING OF GEOLOGIC STORAGE OF CARBON DIOXIDE

The Energy & Environmental Research Center (EERC), in partnership with Minnkota Power Cooperative Inc. (Minnkota), SLB, and Computer Modelling Group Ltd. (CMG), supported wide-scale deployment of carbon capture and storage (CCS) as part of the U.S. Department of Energy (DOE) National Energy Technology Laboratory Carbon Storage Assurance Facility Enterprise (CarbonSAFE) Initiative Phase III. This phase included the acquisition, analysis, and development of information to fully characterize two storage complexes to demonstrate viable storage resources for commercial volumes of CO2 (defined by DOE as a minimum of 50 million tonnes [MMt] of CO2 within a 30-year period) (National Energy Technology Laboratory, 2024). Phase III also involved the preparation, submission, and approval of North Dakota underground injection control (UIC) Class VI storage facility permits (SFPs)—required precursors to applications for Class VI injection well permits. The presumed viability of commercial-scale CCS, situated adjacent to Minnkota’s Milton R. Young Station (MRYS), is validated by Minnkota’s continued pursuit of Project Tundra—an initiative to build the world’s largest lignite-based CCS project in central North Dakota (www.projecttundrand.com). Project Tundra comprises two scopes of work, Tundra Capture (installation of postcombustion CO2 capture at MRYS) and Tundra SGS (secure geologic storage). The efforts of North Dakota CarbonSAFE Phase III, Site Characterization and Permitting, supported Tundra SGS. Extensive site-specific characterization activities included a successful multimeasurement geophysical approach and drilling a stratigraphic test well (J-ROC 1, subsequently renamed Liberty-1) adjacent to MRYS. Core collection and analyses, downhole testing and fluid sampling, and geophysical logging were performed on J-ROC 1 and on a nearby stratigraphic test well (known as J-LOC 1), which was drilled, cored, and tested under a complementary project funded by the North Dakota Lignite Research Program. The injection tests performed on J-LOC 1 positively impacted the CarbonSAFE project, resulting in fewer proposed injection wells and significant construction, operations, and monitoring cost savings. The characterization data collected and analyses performed were integrated into geologic models, and successive numerical simulations were run to determine CO2 plume extent and subsurface pressure buildup associated with the planned CO2 injection rate of nearly 4 MMt per year. The latter doubles the CarbonSAFE Initiative goal with an estimated 100 MMt of CO2 stored in 20 years. Application of the U.S. Environmental Protection Agency’s (EPA’s) method for estimating the Class VI Rule area of review (AOR) to the overpressurized Broom Creek Formation inspired an alternative method of calculation, called risk-based AOR delineation. This peer-reviewed method was applied for the first time during the storage facility-permitting process. The two SFP applications submitted in 2021 successfully resulted in North Dakota Industrial Commission (NDIC) orders in 2022 authorizing the creation of the storage facility areas and amalgamation of pore space as well as establishing financial responsibility requirements. After approval of the SFPs, Minnkota filed in 2022 applications for permits to reenter the J-ROC 1 well and to drill two new wells—all with the intended purpose to become Class VI injection wells. To establish eligibility under the Internal Revenue Code for Section 45Q tax incentives, a monitoring, reporting, and verification (MRV) plan was prepared and submitted by Minnkota to EPA in 2022, resulting in the first such plan approved in North Dakota. Also in 2022, under the National Environmental Policy Act (NEPA), Minnkota prepared and submitted an environmental information volume (EIV) describing the proposed CCS project and associated potential environmental impacts. Based on the EIV, DOE determined that the proposed construction project required an environmental assessment, and Minnkota submitted the first draft in 2023 and a revised draft in 2024. Both submissions were followed by a public comment period. Subsequently, DOE issued a finding of no significant impact (FONSI) on September 13, 2024. A successful outreach program, strongly based in the production, presentation, and dissemination of informational material, fostered an environment to aid stakeholders in making informed decisions regarding the planned project. Opportunities for public input were provided at various steps along the way, including at county planning and zoning meetings, before and during the SFP administrative hearing, and during environmental assessment public comment periods. In addition, land/pore space owners and mineral owners had various points of contact, including granting access rights, securing pore space leasing, and mineral owner notifications. Based upon the successful storage facility permitting issued by NDIC, approval of the MRV plan by EPA, and receipt of a FONSI under the NEPA, Minnkota is continuing its pursuit of Project Tundra. In December 2023, the Office of Clean Energy Demonstrations under its Carbon Capture Demonstrations Projects Program announced funding for the capture system (Office of Clean Energy Demonstrations, 2023) and a proposal for CarbonSAFE Phase IV: Construction funding was submitted in March 2024 for the storage project. A go/no-go decision to proceed with construction and operations in the Broom Creek Formation is anticipated in 2024. References National Energy Technology Laboratory, CarbonSafe Initiative, https://netl.doe.gov/carbon-management/carbon-storage/carbonsafe (accessed August 2024). Office of Clean Energy Demonstrations, 2023, OCED selects three projects in CA, ND, and TX to reduce harmful carbon pollution, create new economic opportunities, and advance carbon reducing technologies, December, www.energy.gov/oced/articles/oced-selects-three-projects-ca-nd-and-tx-reduce-harmful-carbon-pollution-create-new (accessed August 2024).

Peck, Wesley↗
DOE OSTI2020

Defect suppression in wet-treated etched-and-regrown nonpolar m-plane GaN vertical Schottky diodes: A deep-level optical spectroscopy analysis

In this work, steady-state photocapacitance (SSPC) was conducted on nonpolar m-plane GaN n-type Schottky diodes to evaluate the defects induced by inductively coupled plasma (ICP) dry etching in etched-and-regrown unipolar structures. An ~10× increase in the near-midgap Ec – 1.9 eV level compared to an as-grown material was observed. Defect levels associated with regrowth without an etch were also investigated. The defects in the regrown structure (without an etch) are highly spatially localized to the regrowth interface. Subsequently, by depth profiling an etched-and-regrown sample, we show that the intensities of the defect-related SSPC features associated with dry etching depend strongly on the depth away from the regrowth interface, which is also reported previously. A photoelectrochemical etching (PEC) method and a wet AZ400K treatment are also introduced to reduce the etch-induced deep levels. A significant reduction in the density of deep levels is observed in the sample that was treated with PEC etching after dry etching and prior to regrowth. An ~2× reduction in the density of Ec – 1.9 eV level compared to a reference etched-and-regrown structure was observed upon the application of PEC etching treatment prior to the regrowth. The PEC etching method is promising for reducing defects in selective-area doping for vertical power switching structures with complex geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures

Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently became a topic of intensive research due their unique combination of low density, impressive mechanical properties, and stress dissipation capabilities. Conventional methods for fabricating foams rely on complex and stochastic processes, making it challenging to achieve precise architectural control of structured porosity. In contrast, AM provides access to a wide range of printable materials, where precise spatial control over structured porosity can be modulated during the fabrication process enabling the production of foam replacement structures (FRS). Current approaches for designing FRS are based on intuitive understanding of their properties or an extensive number of finite element method (FEM) simulations. These approaches, however, are computationally expensive and time consuming. As such, in this work, we present a novel methodology for determining the mechanical compression response of direct ink write (DIW) 3D printed FRS using a simple cross-sectional image. By obtaining measurement data for a relatively small number of samples, an artificial neural network (ANN) was trained, and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image. Finally, a genetic algorithm (GA) was used to solve the inverse design problem, generating the AM printing parameters that an engineer should use to achieve a desired compression response from a DIW printed FRS. The methods developed herein present an avenue for entirely autonomous design and analysis of additively manufactured structures using artificial intelligence.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The Impact of Galactic Winds on the Angular Momentum of Disk Galaxies in the Illustris Simulation

Observed galactic disks have specific angular momenta similar to expectations for typical dark matter halos in ΛCDM. Cosmological hydrodynamical simulations have recently reproduced this similarity in large galaxy samples by including strong galactic winds, but the exact mechanism that achieves this is not yet clear. Here we present an analysis of key aspects contributing to this relation: angular momentum selection and evolution of Lagrangian mass elements as they accrete onto dark matter halos, condense into Milky-Way-scale galaxies, and join the z = 0 stellar phase. We contrast this evolution in the Illustris simulation with that in a simulation without galactic winds, where the z = 0 angular momentum is ≈0.6 dex lower. We find that winds induce differences between these simulations in several ways: increasing angular momentum, preventing angular momentum loss, and causing z = 0 stars to sample the accretion-time angular momentum distribution of baryons in a biased way. In both simulations, gas loses on average ≈0.4 dex between accreting onto halos and first accreting onto central galaxies. In Illustris, this is followed by ≈0.2 dex gains in the “galactic wind fountain” and no further net evolution past the final accretion onto the galaxy. Without feedback, further losses of ≈0.2 dex occur in the gas phase inside the galaxies. An additional ≈0.15 dex difference arises from feedback preferentially selecting higher angular momentum gas at accretion by expelling gas that is poorly aligned. These and additional effects of similar magnitude are discussed, suggesting a complex origin of the similarity between the specific angular momenta of galactic disks and typical halos.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Formation and transformation of iron oxy-hydroxide precursor clusters to ferrihydrite

Iron (Fe) oxy-hydroxide minerals such as ferrihydrite (Fh) are ubiquitous in Earth-surface environments and important in biogeochemical element cycling. Recent research has suggested that their formation is preceded by the precipitation of ultrasmall (~1 nm) Keggin-like Fe oxy-hydroxide clusters. However, relatively little is understood about the structure of the precursor clusters and the impacts of pH and time on their growth and transformation to more stable phases. Here, we used a new method that involves mixed flow reactors (MFR) to synthesize these Fe oxy-hydroxide precursor clusters at pH 1.0, 1.5, 2.5, and 4.5. In situ and ex situ synchrotron scattering measurements and laboratory small-angle X-ray scattering (SAXS) were used to study the structure and size of Fe oxy-hydroxide clusters and their transformation products, respectively. Results show that with increasing pH, the particle size and structural order of samples increase, forming solids that resemble 2-line Fh at pH 4.5. The experimental data were compared with X-ray pair distribution functions (PDF) calculated for a range of Fe(III) oxyhydroxide clusters, including Fe 13 Keggin isomers computed previously using density functional theory (DFT), which yielded at best only partial agreement at short range (<5 Å). Aging of the clusters synthesized at pH 1.5 and 2.5 results in growth and transformation via Ostwald ripening to mixtures of goethite (Gt) and lepidocrocite (Lp). This process was inhibited by immediately reacting the early-formed clusters with phosphate (PO 4 3– ), suggesting that oxyanion surface complexes can stabilize the initial clusters by preventing growth and crystallization to more stable phases.

58 GEOSCIENCES↗
DOE OSTI2024

Microstructural stability and mechanical properties of the as-cast and heat-treated newly developed TiNbCrTa refractory complex concentrated alloy

In this study, a TiNbCrTa refractory complex concentrated alloy (RCCA) was prepared using vacuum arc remelting. The microstructural evolution and mechanical properties of both as-cast and heat-treated RCCA samples were analyzed. Heat treatment (HT) was performed at 800–1200 °C for 1 h in a vacuum-sealed environment. These samples exhibited a formation of Cr 2 Nb and Cr 2 Ti Laves phases. A variation in elemental distribution was observed, with interdendritic (ID) regions showing higher fractions of Ti and Cr, while the dendritic regions had a greater concentration of Ta and Nb. Micro-segregation at the IDs was confirmed through energy dispersive x-ray spectroscopy mapping, which inferred the formation of Cr- and Ti-rich phases during HT at 800–1200 °C. High-temperature HT at 1200 °C for 1 h led to the evolution of the hcp omega phase. Prolonged HT at 1200 °C for 96 h resulted in the evolution of a Cr-rich Laves phase (Cr 2 Ta), which was homogeneously distributed within the microstructure, indicating an unstable microstructure. Furthermore, despite prolonged HT, a variation in the elemental distribution persisted due to the presence of dendritic and ID regions. Electron backscattered diffraction analysis revealed the presence of bcc and hcp phases in the dendritic and ID regions, respectively, of the as-cast and HTed samples. The as-cast samples demonstrated a high compressive strength of approximately 2 GPa. Micro-hardness values increased with the HT temperature up to 1000 °C. Further increases under HT conditions did not significantly reduce the microhardness value, whereas prolonged HT at 1200 °C led to an increase in the microhardness value. Overall, the newly developed TiNbCrTa RCCA exhibited high-strength behavior even after the phase transformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

IDAES-PSE 2.4.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.. Deprecations • Convergence Analysis tool (idaes/core/util/convergence): deprecated in favor of new Parameter Sweep tools. To be removed in v3.0.0. New Beta Capabilities • Parameter Sweep Tool (idaes.core.util.parameter_sweep) o A new API for defining and performing parameter sweep studies on IDAES models has been developed • Diagnostics Tools (idaes.core.util.model_diagnostics) o New methods for identifying duplicate variables and constraints have been added to the diagnostics toolbox o New tools for detecting ill conditioning in Jacobians have been developed and are available in the model_diagnostics module. These provide alternatives to the existing DegeneracyHunter toolbox, and will eventually be merged with this capability, but initial working versions have been provided as beta capabilities for interested users o IpoptConvergenceAnalysis (replaces deprecated Convergence Analysis tool):  A new tool for performing convergence analysis studies that leverages the new Parameter Sweep tools has been developed. This tool allows users to define the input parameters to their model and sampling methods for these (leveraging Pysmo's sampling tools) and to then solve their model across the sampled domains and return a summary of the solver performance (IPOPT only) Improved Models • Thickener model (idaes.models.unit_models.solid_liquid.thickener) o Improved model to include predictive correlations for unit sizing based on settling velocity measurements (steady-state only) • Modular Property Packages o Added general support for calculating critical properties of mixtures using defined Equation of State modules. New API defined for Equation of State modules in order to define the necessary constraints for calculating critical properties (most EoS modules DO NOT support calculation of critical properties (yet)) o Added new methods to Cubic Equation of State module to support calculation of critical properties

DiagnosticsToolbox↗