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At least 307 records · Page 17

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DOE OSTI2022

Refining perovskite structures to pair distribution function data using collective Glazer modes as a basis

Structural modelling of octahedral tilts in perovskites is typically carried out using the symmetry constraints of the resulting space group. In most cases, this introduces more degrees of freedom than those strictly necessary to describe only the octahedral tilts. It can therefore be a challenge to disentangle the octahedral tilts from other structural distortions such as cation displacements and octahedral distortions. This paper reports the development of constraints for modelling pure octahedral tilts and implementation of the constraints in diffpy-CMI, a powerful package to analyse pair distribution function (PDF) data. The model in the program allows features in the PDF that come from rigid tilts to be separated from non-rigid relaxations, providing an intuitive picture of the tilting. The model has many fewer refinable variables than the unconstrained space group fits and provides robust and stable refinements of the tilt components. It further demonstrates the use of the model on the canonical tilted perovskite CaTiO 3 which has the known Glazer tilt system α + β – β – . The Glazer model fits comparably to the corresponding space-group model Pnma below r = 14 Å and becomes progressively worse than the space-group model at higher r due to non-rigid distortions in the real material.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗

DOE OSTI2023

Synthesis, crystal and electronic structure of the Zintl phase Ba 16 Sb 11 . A case study uncovering greater structural complexity via monoclinic distortion of the tetragonal Ca 16 Sb 11 structure type

The binary Zintl phase Ba 16 Sb 11 has been synthesized and structurally characterized. Detailed studies via single-crystal X-ray diffraction methods indicate that although Ba 16 Sb 11 appears to crystallize in the tetragonal Ca 16 Sb 11 structure type (space group $P\bar{4}2_1$m with a=13.5647(9) Å, c=12.4124(12)Å, Z=2, R 1 = 3.14%; wR 2 = 4.77%), there exists an extensive structural disorder. Some Ba 16 Sb 11 crystals were found to be monoclinic and the structure was solved and refined in space group P2 1 (a=18.3929(12) Å, b=13.5233(8) Å, c=18.3978(12) Å, β=94.6600(10)°; Z=4, R 1 =5.84 %; wR 2 =9.58 %). The latter corresponds to a 2-fold superstructure of the tetragonal one, which provides a disorder-free structural model. In both descriptions, the disordered tetragonal and the ordered monoclinic superstructure, the basic building units that make up the structure of this Ba-rich compound are pairs of face-shared square antiprisms of Ba atoms, which are centered by Sb atoms. The dimerized antiprisms are linked into parallel chains via square prisms of Ba atoms, which are also centered by Sb atoms. The Zintl concept can be applied in a straightforward manner and as result, the structure of Ba 32 Sb 22 (=2×Ba 16 Sb 11 ) can be rationalized as (Ba 2+ ) 32 (Sb 3– ) 20 [Sb 2 ] 4– . Notably, the partitioning of the valence electrons is done taking into an account the homoatomic Sb–Sb contacts (d=3.01 Å), which can be clearly distinguished in the lower symmetry space group. Electronic structure calculations of Ba 16 Sb 11 are in good accordance with the Zintl rationalization and predict a semiconductor with a band gap of 0.77 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Equity implications of net-zero emissions: A multi-model analysis of energy expenditures across income classes under economy-wide deep decarbonization policies

With companies, states, and countries targeting net-zero emissions around midcentury, there are questions about how these targets alter household welfare and finances, including distributional effects across income groups. This paper examines the distributional dimensions of technology transitions and net-zero policies with a focus on welfare impacts across household incomes. The analysis uses a model intercomparison with a range of energy-economy models using harmonized policy scenarios reaching economy-wide, net-zero CO 2 emissions across the United States in 2050. Here we employ a novel linking approach that connects output from detailed energy system models with survey microdata on energy expenditures across income classes to provide distributional analysis of net-zero policies. Although there are differences in model structure and input assumptions, we find broad agreement in qualitative trends in policy incidence and energy burdens across income groups. Models generally agree that direct energy expenditures for many households will likely decline over time with reference and net-zero policies. However, there is variation in the extent of changes relative to current levels, energy burdens relative to reference levels, and electricity expenditures. Policy design, primarily how climate policy revenues are used, has first-order impacts on distributional outcomes. Net-zero policy costs, in both absolute and relative terms, are unevenly distributed across households, and relative increases in energy expenditures are higher for lowest-income households. However, we also find that recycled revenues from climate policies have countervailing effects when rebated on a per-capita basis, offsetting higher energy burdens and potentially even leading to net progressive outcomes. Model results also show carbon Laffer curves, where revenues from net-zero policies increase but then decline with higher stringencies, which can diminish the progressive effects of climate policies. We also illustrate how using annual income deciles for distributional analysis instead of expenditure deciles can overstate the progressivity of emissions policies by overweighting revenue impacts on the lowest-income deciles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Folded network and structural transition in molten tin

The fundamental relationships between the structure and properties of liquids are far from being well understood. For instance, the structural origins of many liquid anomalies still remain unclear, but liquid-liquid transitions (LLT) are believed to hold a key. However, experimental demonstrations of LLTs have been rather challenging. Here, we report experimental and theoretical evidence of a second-order-like LLT in molten tin, one which favors a percolating covalent bond network at high temperatures. The observed structural transition originates from the fluctuating metallic/covalent behavior of atomic bonding, and consequently a new paradigm of liquid structure emerges. The liquid structure, described in the form of a folded network, bridges two well-established structural models for disordered systems, i.e., the random packing of hard-spheres and a continuous random network, offering a large structural midground for liquids and glasses. Our findings provide an unparalleled physical picture of the atomic arrangement for a plethora of liquids, shedding light on the thermodynamic and dynamic anomalies of liquids but also entailing far-reaching implications for studying liquid polyamorphism and dynamical transitions in liquids.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Rapid and robust antibody Fab fragment crystallization utilizing edge-to-edge beta-sheet packing

Antibody therapeutics are one of the most important classes of drugs. Antibody structures have become an integral part of predicting the behavior of potential therapeutics, either directly or as the basis of modeling. Structures of Fab:antigen complexes have even greater value. While the crystallization and structure determination of Fabs is easy relative to many other protein classes, especially membrane proteins, broad screening and optimization of crystalline hits is still necessary. Through a comprehensive review of rabbit Fab crystal contacts and their incompatibility with human Fabs, we identified a small secondary structural element from the rabbit light chain constant domain potentially responsible for hindering the crystallization of human Fabs. Upon replacing the human kappa constant domain FG loop (HQGLSSP) with the two residue shorter rabbit loop (QGTTS), we dramatically improved the crystallization of human Fabs and Fab:antigen complexes. Our design, which we call “Crystal Kappa”, enables rapid crystallization of human fabs and fab complexes in a broad range of conditions, with less material in smaller screens or from dilute solutions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Sierra/SD – User’s Guide for NasGen – 5.20

NasGen provides a path for migration of structural models from Nastran bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Adagio). Many tools at Sandia National Labs (SNL) use the Exodus format. This document describes capabilities and limitations of the NasGen translation software.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Sierra/SD – User’s Guide for NasGen – 5.18

NasGen provides a path for migration of structural models from NASTRAN bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Presto). Many tools at Sandia National Labs (SNL) use the Exodus format. NasGen was written specifically for Salinas and Presto but should be usable with a number of these packages.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Sierra/SD – User’s Guide for NasGen (V.5.16)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Sierra/SD – User’s Guide for NasGen – 5.22

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Sierra/SD – User’s Guide for NasGen (V.5.24)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Sierra/SD – User’s Guide for NasGen – 5.28

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Sierra/SD– User’s Guide for NasGen - 5.30

NasGen provides a path for migration of structural models from NASTRAN bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Presto). Many tools at Sandia National Labs use the Exodus format. NasGen was written specifically for Salinas and Presto but should be usable with a number of these packages.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Atomically Dispersed Platinum in Surface and Subsurface Sites on MgO Have Contrasting Catalytic Properties for CO Oxidation

Atomically dispersed metals on metal oxide supports are a rapidly growing class of catalysts. Developing an understanding of where and how the metals are bonded to the supports is challenging because support surfaces are heterogeneous, and most reports lack a detailed consideration of these points. In this work, we report two atomically dispersed CO oxidation catalysts having markedly different metal–support interactions: platinum in the first layer of crystalline MgO powder and platinum in the second layer of this support. Structural models have been determined on the basis of data and computations, including those determined by extended X-ray absorption fine structure and X-ray absorption near edge structure spectroscopies, infrared spectroscopy of adsorbed CO, and scanning transmission electron microscopy. The data demonstrate the transformation of surface to subsurface platinum as the temperature of sample calcination increased. Catalyst performance data demonstrate the lower activity but greater stability of the subsurface platinum than of the surface platinum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Orthorhombic cerium(III) carbonate hydroxide studied by synchrotron powder X-ray diffraction

Cerium(III) carbonate is a precursor material for the synthesis of various Ce-containing compounds. In this work, a synchrotron powder X-ray diffraction study of commercially obtained ‘cerium(III) carbonate hydrate' indicates that multiple Ce-containing phases are present. The majority phase CeCO 3 OH (52.49% wt ) was refined using an orthorhombic Pmcn structure model with a = 5.01019 (2) Å, b = 8.55011 (4) Å and c = 7.31940 (4) Å, which is based on a reported structure for the lanthanoid carbonate mineral ancylite. Additionally, a substantial portion of the precursor material is cubic cerium(IV) oxide (47.12% wt ).

08 HYDROGEN↗

DOE OSTI2021

Can Simple Machine Learning Tools Extend and Improve Temperature-Based Methods to Infer Streambed Flux?

Temperature-based methods have been developed to infer 1D vertical exchange flux between a stream and the subsurface. Current analyses rely on fitting physically based analytical and numerical models to temperature time series measured at multiple depths to infer daily average flux. These methods have seen wide use in hydrologic science despite strong simplifying assumptions including a lack of consideration of model structural error or the impacts of multidimensional flow or the impacts of transient streambed hydraulic properties. We performed a “perfect-model experiment” investigation to examine whether regression trees, with and without gradient boosting, can extract sufficient information from model-generated subsurface temperature time series, with and without added measurement error, to infer the corresponding exchange flux time series at the streambed surface. Using model-generated, synthetic data allowed us to assess the basic limitations to the use of machine learning; further examination of real data is only warranted if the method can be shown to perform well under these ideal conditions. We also examined whether the inherent feature importance analyses of tree-based machine learning methods can be used to optimize monitoring networks for exchange flux inference.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Transmission Spectroscopy for the Warm Sub-Neptune HD 3167c: Evidence for Molecular Absorption and a Possible High-metallicity Atmosphere

We present a transmission spectrum for the warm (500−600 K) sub-Neptune HD 3167c obtained using the Hubble Space Telescope Wide Field Camera 3 infrared spectrograph. We combine these data, which span the 1.125–1.643 μm wavelength range, with broadband transit measurements made using Kepler/K2 (0.6–0.9 μm) and Spitzer/IRAC (4–5 μm). We find evidence for absorption by at least one of H{sub 2}O, HCN, CO{sub 2}, and CH{sub 4} (Bayes factor 7.4; 2.5σ significance), although the data precision does not allow us to unambiguously discriminate between these molecules. The transmission spectrum rules out cloud-free hydrogen-dominated atmospheres with metallicities ≤100× solar at >5.8σ confidence. In contrast, good agreement with the data is obtained for cloud-free models assuming metallicities >700× solar. However, for retrieval analyses that include the effect of clouds, a much broader range of metallicities (including subsolar) is consistent with the data, due to the degeneracy with cloud-top pressure. Self-consistent chemistry models that account for photochemistry and vertical mixing are presented for the atmosphere of HD 3167c. The predictions of these models are broadly consistent with our abundance constraints, although this is primarily due to the large uncertainties on the latter. Interior structure models suggest that the core mass fraction is >40%, independent of a rock or water core composition, and independent of atmospheric envelope metallicity up to 1000× solar. We also report abundance measurements for 15 elements in the host star, showing that it has a very nearly solar composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗