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13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Materials Data on AgAs(SeF2)3 by Materials Project

AgAs(SeF2)3 crystallizes in the monoclinic C2/m space group. The structure is two-dimensional and consists of two AgAs(SeF2)3 sheets oriented in the (0, 1, 0) direction. there are two inequivalent Ag1+ sites. In the first Ag1+ site, Ag1+ is bonded in a distorted octahedral geometry to six Se atoms. There are four shorter (2.98 Å) and two longer (3.04 Å) Ag–Se bond lengths. In the second Ag1+ site, Ag1+ is bonded in a 10-coordinate geometry to two equivalent Se and eight F1- atoms. Both Ag–Se bond lengths are 2.74 Å. There are four shorter (2.74 Å) and four longer (3.15 Å) Ag–F bond lengths. As5+ is bonded in an octahedral geometry to six F1- atoms. There are a spread of As–F bond distances ranging from 1.76–1.80 Å. There are two inequivalent Se sites. In the first Se site, Se is bonded in a distorted rectangular see-saw-like geometry to two Ag1+ and two equivalent Se atoms. Both Se–Se bond lengths are 2.40 Å. In the second Se site, Se is bonded in a distorted rectangular see-saw-like geometry to one Ag1+, two Se, and one F1- atom. The Se–Se bond length is 2.36 Å. The Se–F bond length is 3.15 Å. There are three inequivalent F1- sites. In the first F1- site, F1- is bonded in a distorted single-bond geometry to one Ag1+, one As5+, and one Se atom. In the second F1- site, F1- is bonded in a single-bond geometry to one Ag1+ and one As5+ atom. In the third F1- site, F1- is bonded in a single-bond geometry to one As5+ atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on AgAs(S8F3)2 by Materials Project

AgS16AsF6 crystallizes in the monoclinic C2/c space group. The structure is zero-dimensional and consists of four AgS16 clusters and four AsF6 clusters. In each AgS16 cluster, Ag1+ is bonded in a 4-coordinate geometry to four S atoms. There are two shorter (2.72 Å) and two longer (2.81 Å) Ag–S bond lengths. There are eight inequivalent S sites. In the first S site, S is bonded in a water-like geometry to two S atoms. There are one shorter (2.05 Å) and one longer (2.06 Å) S–S bond lengths. In the second S site, S is bonded in a trigonal non-coplanar geometry to one Ag1+ and two S atoms. There are one shorter (2.06 Å) and one longer (2.08 Å) S–S bond lengths. In the third S site, S is bonded in a water-like geometry to two S atoms. The S–S bond length is 2.07 Å. In the fourth S site, S is bonded in a water-like geometry to two S atoms. The S–S bond length is 2.07 Å. In the fifth S site, S is bonded in a water-like geometry to two S atoms. There are one shorter (2.05 Å) and one longer (2.07 Å) S–S bond lengths. In the sixth S site, S is bonded in a water-like geometry to two S atoms. In the seventh S site, S is bonded in a water-like geometry to two S atoms. In the eighth S site, S is bonded in a trigonal non-coplanar geometry to one Ag1+ and two S atoms. In each AsF6 cluster, As5+ is bonded in an octahedral geometry to six F1- atoms. There are a spread of As–F bond distances ranging from 1.77–1.79 Å. There are three inequivalent F1- sites. In the first F1- site, F1- is bonded in a single-bond geometry to one As5+ atom. In the second F1- site, F1- is bonded in a single-bond geometry to one As5+ atom. In the third F1- site, F1- is bonded in a single-bond geometry to one As5+ atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on AgAs(XeF5)2 by Materials Project

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on AgAs by Materials Project

Ag(As) is beta-prime cadmium gold structured and crystallizes in the orthorhombic Pmma space group. The structure is three-dimensional. Ag1+ is bonded to four equivalent Ag1+ and eight equivalent As1- atoms to form AgAg4As8 cuboctahedra that share corners with eight equivalent AsAg8As4 cuboctahedra, corners with ten equivalent AgAg4As8 cuboctahedra, edges with six equivalent AgAg4As8 cuboctahedra, edges with twelve equivalent AsAg8As4 cuboctahedra, faces with eight equivalent AsAg8As4 cuboctahedra, and faces with twelve equivalent AgAg4As8 cuboctahedra. There are two shorter (2.96 Å) and two longer (3.02 Å) Ag–Ag bond lengths. There are four shorter (2.98 Å) and four longer (3.03 Å) Ag–As bond lengths. As1- is bonded to eight equivalent Ag1+ and four equivalent As1- atoms to form distorted AsAg8As4 cuboctahedra that share corners with eight equivalent AgAg4As8 cuboctahedra, corners with ten equivalent AsAg8As4 cuboctahedra, edges with six equivalent AsAg8As4 cuboctahedra, edges with twelve equivalent AgAg4As8 cuboctahedra, faces with eight equivalent AgAg4As8 cuboctahedra, and faces with twelve equivalent AsAg8As4 cuboctahedra. There are two shorter (2.96 Å) and two longer (3.03 Å) As–As bond lengths.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Transcription factor FOXC1 positively regulates SFRP1 expression in androgenetic alopecia

Androgenetic alopecia (AGA) is the most common type of hair loss dysfunction. Secreted frizzled related protein 1 (SFRP1) is found to be associated with hair loss, but its role in AGA and the regulation mechanism of its transcription level is unclear. The aim of our study is to explore the expression of SFRP1 in AGA samples and its transcriptional mechanism. Male frontal and occipital scalp hair follicles from AGA patients were collected, and human dermal papilla cells (DPCs) were isolated and cultured. SFRP1 gene was cloned and constructed into recombinant plasmids to perform dual-luciferase reporter assay. Transcription factor binding sites were predicted through the Jaspar website and further confirmed by the chromatin immunoprecipitation (ChIP) assay. Expression of genes in DPCs was determined by immunofluorescence (IF) staining, quantitative real-time PCR (qRT-PCR) and western blotting. Our findings showed that SFRP1 was highly expressed in DPCs of AGA patients. The core promoter region of SFRP1 was from −100 to +50 bp and was found to be positively regulated by forkhead box C1 (FOXC1), a transcription factor related to hair growth, both at mRNA and protein level in DPCs. Our study suggests that FOXC1 plays an important role in regulating SFRP1 transcription, which may provide new insights into the development of therapeutic strategies for the treatment of AGA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Prediction of crystal structures and motifs in the Fe–Mg–O system at Earth’s core pressures

Abstract Fe, Mg, and O are among the most abundant elements in terrestrial planets. While the behavior of the Fe–O, Mg–O, and Fe–Mg binary systems under pressure have been investigated, there are still very few studies of the Fe–Mg–O ternary system at relevant Earth’s core and super-Earth’s mantle pressures. Here, we use the adaptive genetic algorithm (AGA) to study ternary Fe x Mg y O z phases in a wide range of stoichiometries at 200 GPa and 350 GPa. We discovered three dynamically stable phases with stoichiometries FeMg 2 O 4 , Fe 2 MgO 4, and FeMg 3 O 4 with lower enthalpy than any known combination of Fe–Mg–O high-pressure compounds at 350 GPa. With the discovery of these phases, we construct the Fe–Mg–O ternary convex hull. We further clarify the composition- and pressure-dependence of structural motifs with the analysis of the AGA-found stable and metastable structures. Analysis of binary and ternary stable phases suggest that O, Mg, or both could stabilize a BCC iron alloy at inner core pressures.

Wang, Renhai↗
DOE OSTI2025

Bridging Experiment and Theory to Reveal Compounds in K–Zn(Cd)–Bi Systems

This study investigates the facile hydride synthesis method guided by theoretical predictions to explore the K–T–Bi (T = Zn, Cd) phase spaces. Using an adaptive genetic algorithm (AGA) and density functional theory (DFT), candidate compositions are identified for experimental validation via a facile hydrides route, permitting experimental screening of K–Zn–Bi and “empty” K–Cd–Bi systems. The previously reported KZnBi and KZn 2 Bi 2 are synthesized alongside newly discovered KCdBi and KCd 2 Bi 2 . While the AGA and DFT predict the stability of these compounds, structural predictions align with the experiment only for KZnBi and KZn 2 Bi 2 . Single-crystal X-ray structure refinements confirm that KZnBi and KZn 2 Bi 2 adopt the hexagonal ZrBeSi- and tetragonal ThCr 2 Si 2 -structure types, respectively. KCdBi has tetragonal PbClF-structure type and KCd 2 Bi 2 belongs to the ThCr 2 Si 2 -structure type. A trend based on the ratio of the metal ionic radii allows to rationalize variation in the structure types within the ATBi family (A = Li–Cs), correctly identifying KCdBi as isostructural to NaZnBi. Thermal stability studied by high-temperature powder X-ray diffraction reveals that Zn-containing compounds melt at higher temperatures (821 K for KZn 2 Bi 2 ) than Cd-containing KCd 2 Bi 2 (635 K). This study highlights the efficacy of combining rapid synthesis techniques with predictive modeling, though structural predictions show some limitations in accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Enhanced purification coupled with biophysical analyses shows cross-β structure as a core building block for Streptococcus mutans functional amyloids

Streptococcus mutans is an etiologic agent of human dental caries that forms dental plaque biofilms containing functional amyloids. Three amyloidogenic proteins, P1, WapA, and Smu_63c were previously identified. C123 and AgA are naturally occurring amyloid-forming fragments of P1 and WapA, respectively. We determined that four amyloidophilic dyes, ThT, CDy11, BD-oligo, and MK-H4, differentiate C123, AgA, and Smu_63c amyloid from monomers, but non-specific binding to bacterial cells in the absence of amyloid precludes their utility for identifying amyloid in biofilms. Congo redinduced birefringence is a more specific indicator of amyloid formation and differentiates biofilms formed by wild-type S. mutans from a triple ΔP1/WapA/Smu_63c mutant with reduced bioiflm forming capabilities. Amyloid accumulation is a late event, appearing in older S. mutans biofilms after 60hours of growth. Amyloid derived from pure preparations of all three proteins is visualized by electron microscopy as mat-like structures. Typical amyloid fibers become evident following protease digestion to eliminate non-specific aggregates and monomers. Amyloid mats, similar in appearance to those reported in S. mutans biofilm extracellular matrices, are reconstituted by co-incubation of monomers and amyloid fibers. X-ray fiber diffraction of amyloid mats and fibers from all three proteins demonstrate patterns reflective of a cross-β amyloid structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The microwave spectra of the conformers of $\mathcal{n}$-butyl nitrate

We report the microwave spectrum of n-butyl nitrate was recorded in the 5 to 20 GHz frequency range using broadband chirp and narrowband pulse excitation molecular jet Fourier transform microwave spectrometers. A quantum chemistry structural analysis yielded thirteen stable conformers. Among them, the five most energetically stable conformers were observed in the experimental spectra. The most stable conformer features a butyl chain with an anti-gauche-anti conformation (AGA) where the γ-carbon atom is about 64° out of the nitrate plane. For this conformer, spectra of all 13 C and 15 N minor isotopologues could be measured. The conformer with a straight butyl chain (AAA), and three other conformers (GAA, GGA, and AGG) were also observed. Accurate rotational constants, centrifugal distortion constants, and 14 N nuclear quadrupole coupling constants could be deduced and compared to the theoretical values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Cubit v.16.X

SAND2021-3051 O CUBIT is a full-featured software toolkit for robust generation of two- and three-dimensional finite element meshes (grids) and geometry preparation. Its main goal is to reduce the time required to generate meshes - particularly large hex meshes of complicated, interlocking assemblies. It is a solid-modeler-based preprocessor that meshes volumes and surfaces for finite element analysis. CUBIT also includes state-of-the-art smoothing algorithms and provides an extensive suite of tools for geometry decomposition and mesh generation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Stimpson, Clint↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗