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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59

SPRUCE Compositional Stability of Peat in Ecosystem-Scale Warming Mesocosms, 2014 and 2019

This dataset contains measurements of carbohydrate and aromatic compounds in peat samples subjected to various levels of deep peat heating (DPE) and whole ecosystem warming (WEW). Samples were collected in August 2014 and August 2019 at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. These data serve to identify chemical changes occurring within peatland soils following five years of warming. Samples were analyzed in the uppermost 2m of peat using Fourier Transform Infrared Spectroscopy (FT-IR) to quantify the relative abundance of carbohydrate and aromatic compounds in the peat. The peat soils were subjected to DPH beginning in June of 2014 followed by WEW in August of 2015. This dataset contains one data file in comma-separated values (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separated values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

SRF cavity instability detection with machine learning at CEBAF

During the operation of the Continuous Electron Beam Accelerator Facility (CEBAF), one or more unstable superconducting radio-frequency (SRF) cavities often cause beam loss trips while the unstable cavities themselves do not necessarily trip off. The present RF controls for the legacy cavities report at only 1 Hz, which is too slow to detectfast transient instabilities during these trip events. These challenges make the identification of an unstable cavity out of the hundreds installed at CEBAF a difficult and time-consuming task. To tackle these issues, a fast data acquisition system (DAQ) for the legacy SRF cavities has been developed, which records the sample at 5 kHz. An unsupervised learning framework has been developed to identify anomalous SRF cavity behavior. We will discuss the present status of the DAQ system and our framework, along with recent successes in detecting anomalous cavity behavior. Overall, our method offers a practical solution for identifying unstable SRF cavities, contributing to increased beam availability and machine reliability.

Accelerator Physics↗

Canadian MSAT field trial program user requirements

A wide range of mobile satellite service offerings will be available in late 1993 with the launch of Canada's first satellite devoted almost exclusively to mobile and transportable services. During the last seven years, the Dept. of Communications has been meeting with potential MSAT users in government and the private sector as part of a $20M Communications Trials Program. User trials will be conducted using leased capacity as well as capacity on Canada's MSAT satellite. User requirements are discussed which were identified under the Communications Trials Program. Land, marine, aeronautical, and fixed applications are described from the perspective of the end users. Emphasis is placed on field trials being accomplished using leased capacity such as the marine data trial being implemented by Ultimateast Data Communications, trials using transportable briefcase terminals and additional field trials being considered for implementation with the TMI Mobile Data Service. The pre-MSAT trials that will be conducted using leased capacity are only a limited sample of the overall end user requirements that have been identified to date. Additional end user applications are discussed, along with a summary of user benefits.

Pedersen, Allister↗

Wildfire Smoke Particle Properties and Evolution, From Space-Based Multi-Angle Imaging II: The Williams Flats Fire during the FIREX-AQ Campaign

Although the characteristics of biomass burning events and the ambient ecosystem determine emitted smoke composition, the conditions that modulate the partitioning of black carbon (BC) and brown carbon (BrC) formation are not well understood, nor are the spatial or temporal frequency of factors driving smoke particle evolution, such as hydration, coagulation, and oxidation, all of which impact smoke radiative forcing. In situ data from surface observation sites and aircraft field campaigns offer deep insight into the optical, chemical, and microphysical traits of biomass burning (BB) smoke aerosols, such as single scattering albedo (SSA) and size distribution, but cannot by themselves provide robust statistical characterization of both emitted and evolved particles. Data from the NASA Earth Observing System’s Multi-Angle Imaging SpectroRadiometer (MISR) instrument can provide at least a partial picture of BB particle properties and their evolution downwind, once properly validated. Here we use in situ data from the joint NOAA/NASA 2019 Fire Influence on Regional to Global Environments Experiment-Air Quality (FIREX-AQ) field campaign to assess the strengths and limitations of MISR-derived constraints on particle size, shape, light-absorption, and its spectral slope, as well as plume height and associated wind vectors. Based on the satellite observations, we also offer inferences about aging mechanisms effecting downwind particle evolution, such as gravitational settling, oxidation, secondary particle formation, and the combination of particle aggregation and condensational growth. This work builds upon our previous study, adding confidence to our interpretation of the remote-sensing data based on an expanded suite of in situ measurements for validation. The satellite and in situ measurements offer similar characterizations of particle property evolution as a function of smoke age for the 06 August Williams Flats Fire, and most of the key differences in particle size and absorption can be attributed to differences in sampling and changes in the plume geometry between sampling times. Whereas the aircraft data provide validation for the MISR retrievals, the satellite data offer a spatially continuous mapping of particle properties over the plume, which helps identify trends in particle property downwind evolution that are ambiguous in the sparsely sampled aircraft transects. The MISR data record is more than two decades long, offering future opportunities to study regional wildfire plume behavior statistically, where aircraft data are limited or entirely lacking.

biomass burning↗

Identification of the molecular-weight growth reaction network in counterflow flames of the C 3 H 4 isomers allene and propyne

The reaction networks responsible for aromatics formation in counterflow flames of the C 3 H 4 isomers allene and propyne are identified through a combined experimental and modeling study. Mole fraction profiles of near-atmospheric pressure (933 mbar) diffusion flames fueled by the C 3 H 4 isomers are analyzed by means of a newly assembled, chemically detailed kinetic mechanism. The experiment consists of a counterflow burner system that is coupled to a high-resolution time-of-flight molecular-beam mass spectrometer with single-photon ionization via synchrotron-generated vacuum-ultraviolet photons. Flame-sampled, mass-specific photoionization efficiency curves are used to identify the presence of aliphatically substituted aromatic species in addition to the commonly considered pericondensed ring structures. The new mechanism describes the formation and growth of aromatics through repetitive sequences of radical–radical and radical–molecule reactions that include C 1 6 intermediates. Higher concentrations of aromatic species are observed in the allene flame and the new mechanism captures the observed experimental trends very accurately. The results indicate the importance of the aliphatically substituted aromatics and of ring-enlargement reactions for the growth reactions. According to the model simulations, radical+radical recombination and PAH-radical+molecule reactions play an important role in PAH growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long-term Accumulation, Depth Distribution, and Speciation of Silver Nanoparticles in Biosolids-Amended Soils

Biosolids, when applied to soil, can be a source of metals and metal nanoparticles. One of the metals that forms nanoparticles is silver (Ag), which is commonly used in elemental (Ag(0)) form as an engineered nanomaterial in industrial or consumer products. The objective of this study was to quantify and characterize the accumulation and transport of Ag in a natural soil that has received agronomically-recommended rates of biosolids as fertilizer for the past 23 years (1994{2017). Total Ag concentrations were measured in biosolids and soil samples collected from 0 to 10 cm between 1996 and 2017. In addition, the depth distribution of Ag in the soil down to 60-cm depth was measured in 2017. Electron microscopy, in combination with X-ray spectroscopy, and X-ray absorption spectroscopy were used to identify the elemental association and oxidation state of the Ag in the samples. The Ag concentrations in the biosolids-amended soil increased steadily from 1996 until 2007, after which the concentrations leveled off at about 1.25 mg Ag kg-1 soil. This corresponded with a decrease of Ag concentrations in the biosolids over time. The majority of the Ag (82%) was confined to the top 10 cm of the soil, small amounts (14%) were detected in 10 to 20-cm depth, and trace amounts (4%) in 30 to 40-cm depth. The Ag in the biosolids and soil was identified as Ag-containing nanoparticles with a diameter of 10 to 12 nm. Ag was associated with S suggest that these 19 nanoparticles are Ag2S. This could be corroborated in biosolids with X-ray absorption spectroscopy (XANES); however, the Ag concentrations in the soil samples were too low to allow identification with XANES. Biosolids, when applied at agronomic rates in dryland cropping systems, represent an economically viable source of crop nutrients. In our study, long-term application of biosolids did not increase the concentration of total Ag in soil above a maximum of 1.5 mg Ag kg-1, and the Ag is present in the sulfide form. This concentration is below ecotoxicity limits for Ag2S in soil.

Taylor, Stephen E.↗

Oligodeoxynucleotide Probes for Detecting Intact Cells

A rapid, sensitive test using chemiluminescent oligodeoxynucleotide probes has been developed for detecting, identifying, and enumerating intact cells. The test is intended especially for use in detecting and enumerating bacteria and yeasts in potable water. As in related tests that have been developed recently for similar purposes, the oligodeoxynucleotide probes used in this test are typically targeted at either singlecopy deoxyribonucleic acid (DNA) genes (such as virulence genes) or the multiple copies (10,000 to 50,000 copies per cell) of 16S ribosomal ribonucleic acids (rRNAs). Some of those tests involve radioisotope or fluorescent labeling of the probes for reporting hybridization of probes to target nucleic acids. Others of those tests involve labeling with enzymes plus the use of chemiluminescent or chromogenic substrates to report hybridization via color or the emission of light, respectively. The present test is of the last-mentioned type. The chemiluminescence in the present test can be detected easily with relatively simple instrumentation. In developing the present test, the hybridization approach was chosen because hybridization techniques are very specific. Hybridization detects stable, inheritable genetic targets within microorganisms. These targets are not dependent on products of gene expression that can vary with growth conditions or physiological states of organisms in test samples. Therefore, unique probes can be designed to detect and identify specific genera or species of bacteria or yeast (in terms of rRNA target sequences) or can be designed to detect and identify virulence genes (genomic target sequences). Because of the inherent specificity of this system, there are few problems of cross-reactivity. Hybridization tests are rapid, but hybridization tests now available commercially lack sensitivity; typically, between 10(exp 6) and 10(exp 7) cells of the target organism are needed to ensure a reliable test. Consequently, the numbers of target bacteria in samples are usually amplified by overnight pre-enrichment growth. These tests are usually performed in laboratories by skilled technicians. The present test was designed to overcome the shortcomings of the commercial hybridization tests. The figure summarizes the major steps of the test. It is important to emphasize that the hybridization process used in this test differs from that of other hybridization tests in that it does not extract target nucleic acids. This process is based on intact-cell hybridization (so-called in situ hybridization ), wherein the intact cells act as immobilizing agents. The cells are identified and enumerated by measuring the chemiluminescence emitted from alkaline phosphatase-probe (AP-probe) hybridization; the chemiluminescence is detected or measured by use of photographic film or a luminometer, respectively.

Rosson, Reinhardt A.↗

DESI Survey Validation Spectra Reveal an Increasing Fraction of Recently Quenched Galaxies at z ∼ 1

Abstract We utilize ∼17,000 bright luminous red galaxies (LRGs) from the novel Dark Energy Spectroscopic Instrument Survey Validation spectroscopic sample, leveraging its deep (∼2.5 hr galaxy −1 exposure time) spectra to characterize the contribution of recently quenched galaxies to the massive galaxy population at 0.4 < z < 1.3. We use Prospector to infer nonparametric star formation histories and identify a significant population of recently quenched galaxies that have joined the quiescent population within the past ∼1 Gyr. The highest-redshift subset (277 at z > 1) of our sample of recently quenched galaxies represents the largest spectroscopic sample of post-starburst galaxies at that epoch. At 0.4 < z < 0.8, we measure the number density of quiescent LRGs, finding that recently quenched galaxies constitute a growing fraction of the massive galaxy population with increasing look-back time. Finally, we quantify the importance of this population among massive ( log ( M ⋆ / M ⊙ ) > 11.2) LRGs by measuring the fraction of stellar mass each galaxy formed in the gigayear before observation, f 1 Gyr . Although galaxies with f 1 Gyr > 0.1 are rare at z ∼ 0.4 (≲0.5% of the population), by z ∼ 0.8, they constitute ∼3% of massive galaxies. Relaxing this threshold, we find that galaxies with f 1 Gyr > 5% constitute ∼10% of the massive galaxy population at z ∼ 0.8. We also identify a small but significant sample of galaxies at z = 1.1–1.3 that formed with f 1 Gyr > 50%, implying that they may be analogs to high-redshift quiescent galaxies that formed on similar timescales. Future analysis of this unprecedented sample promises to illuminate the physical mechanisms that drive the quenching of massive galaxies after cosmic noon.

79 ASTRONOMY AND ASTROPHYSICS↗

Development of Computational Environmental Microbiome Workflows for the Laboratory and the International Space Station

Identification of microorganisms in the spaceflight environment is critical for crew health risk assessment on the International Space Station (ISS). Since 2017, nanopore sequencing technology has been used to support thein situ identification of microbial species during spaceflight. Beginning in 2018, a culture-independent, swab-to-sequencer method was implemented onboard the ISS to provide a more thorough insight of the ISS microbiome. Eliminating microbial culture enables identification of difficult-to-culture organisms, reduces risks associated with potentially pathogenic cultures, and could significantly reduce the time from sample-to-answer. However, this molecular-based approach generates large metagenomic datasets that require substantial computational resources for analysis. To process nanopore-generated sequencing data, the JSC Microbiology Laboratory established a bioinformatics workflow on Amazon EC2 under the security guidance of the NASA Science Managed Cloud Environment (SMCE).This resource allows for the development, testing, and accessing of computational tools for processing large and complex datasets. The work described here will address the downlinking of data from the ISS, the automated pipeline developed to identify targeted bacterial and fungal organisms, and the time from sampling onboard to microbial identification. The pipelines have been enhanced to address high and low biomass samples using optimization based on sample source (air, water, or surface) and type of collection (filter, colony, or swab).The resulting microbiome data can be assessed beyond microbial identifications to gain understanding toward population changes over time, potential selective environmental pressures, and evaluating correlations with a wide range of additional data sets. Metagenome analysis pipelines in development could allow for simultaneous identification of microbial species, gene function, and gene pathways present in the environment. Beyond the ground processing, the developed analysis pipeline is currently deployed onboard the ISS to allow for near real-time assessments of the ISS microbiome. This study serves as a critical foundation for exploration missions, where rapid microbiome analyses will be required.

G. Marie Sharp↗

Calculations of the moon's heat history at different concentrations of radioactive elements taking account of the material differentiation with melting

A mathematical procedure for analyzing the heat conductivity of the lunar surface is discussed. The solution is based on homogeneous and laminated moon models and considers the effects of radioactive elements conveyed to the lunar surface by melting. The various parameters which introduce uncertainties into the numerical analysis are identified. The application of data obtained from radio astronomy and from analyses of lunar samples returned by the Apollo flights is explained. Tables of data are included to show the types and amounts of radioactive materials which have been identified.

Arnatskaya, O. I.↗

Repetitive diacetyl vapor exposure promotes ubiquitin proteasome stress and precedes bronchiolitis obliterans pathology

Bronchiolitis obliterans (BO) is a devastating lung disease seen commonly after lung transplant but also seen following severe respiratory tract infection or chemical inhalation exposure. Diacetyl (DA; 2,3-butanedione), highly reactive alpha-diketone is known to cause BO when inhaled, however, the mechanisms of how inhalation exposure leads to BO development remains poorly understood. In the current work, we combined two clinically relevant models for studying the pathogenesis of DA-induced BO: (1) an in vivo rat model of repetitive DA vapor exposures with recovery and (2) an in vitro model of primary human airway epithelial cells exposed to pure DA vapors. Rats exposed to 5 consecutive days 200 parts-per-million DA 6 hrs per day had worsening survival, persistent hypoxemia, poor weight gain, and histologic evidence of BO 14 days after DA exposure cessation. At the end of exposure, increased expression of the ubiquitin stress protein, ubiquitin-C, accumulated within DA-exposed rat lung homogenates, localized primarily to the airway epithelium, the primary site of BO development, and did not occur in air-exposed controls. Lung proteasome activity increased concurrently after DA exposure. In primary human airway cultures, global proteomics analysis identified 519 significantly modified proteins in DA-exposed samples relative to controls with the ubiquitin proteasome system, endosomal reticulum transport, and the response to unfolded protein pathways being upregulated while cell-cell adhesion and oxidation-reduction pathways being downregulated in DA-exposed samples. Altogether, repetitive DA vapor exposure resulted in abundant protein damage, accumulation of polyubiquinated proteins, and ubiquitin proteasome stress prior to the development of chemical-induced BO pathology.

59 BASIC BIOLOGICAL SCIENCES↗

A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions

We develop an Evolutionary Markov Chain Monte Carlo (EMCMC) algorithm for sampling spatial partitions that lie within a large, complex, and constrained spatial state space. Our algorithm combines the advantages of evolutionary algorithms (EAs) as optimization heuristics for state space traversal and the theoretical convergence properties of Markov Chain Monte Carlo algorithms for sampling from unknown distributions. Local optimality information that is identified via a directed search by our optimization heuristic is used to adaptively update a Markov chain in a promising direction within the framework of a Multiple-Try Metropolis Markov Chain model that incorporates a generalized Metropolis-Hastings ratio. We further expand the reach of our EMCMC algorithm by harnessing the computational power afforded by massively parallel computing architecture through the integration of a parallel EA framework that guides Markov chains running in parallel.

97 MATHEMATICS AND COMPUTING↗

Unraveling compacted graphite evolution during solidification of cast iron using in-situ synchrotron X-ray tomography

In spite of many years of research, the physical phenomena leading to the evolution of compacted graphite (CG) during solidification is still not fully understood. In particular, it is unknown how highly branched CG aggregates form and evolve in the semi-solid, and how local microstructural variations at micrometer length scale affect this growth process. We present here the first time-resolved synchrotron tomography combined with a bespoke high-temperature environmental cell that allows direct observation of the evolution of CG and relates this dynamic process to the local surrounding microstructures in a cast iron sample during repeated melting and solidification. Distinct processes are identified for the formation of CG involving the nucleation, growth, development of branches and interconnection of graphite particles, ultimately evolving into highly branched graphite aggregates with large sizes and low sphericities. CG is found to nucleate with a spheroidal or a plate-like shape, developing branches induced by high carbon concentration, e.g. thin melt channels. Additionally, CG grows much faster than spheroidal graphite during subsequent cooling in solid state. The direct visualization of the dynamic solidification process provides unprecedented new insights into formation mechanisms of CG and correlating factors such as local microstructural variations, and guides the development of CG iron solidification models.

36 MATERIALS SCIENCE↗

Generative learning for slow manifolds and bifurcation diagrams

In dynamical systems characterized by separation of time scales, the approximation of so called “slow manifolds”, on which the long term dynamics lie, is a useful step for model reduction. Initializing on such slow manifolds is a useful step in modeling, since it circumvents fast transients, and is crucial in multiscale algorithms (like the equation-free approach) alternating between fine scale (fast) and coarser scale (slow) simulations. In a similar spirit, when one studies the infinite time dynamics of systems depending on parameters, the system attractors (e.g., its steady states) lie on bifurcation diagrams (curves for one-parameter continuation, and more generally, on manifolds in state parameter space. Sampling these manifolds gives us representative attractors (here, steady states of ODEs or PDEs) at different parameter values. Algorithms for the systematic construction of these manifolds (slow manifolds, bifurcation diagrams) are required parts of the “traditional” numerical nonlinear dynamics toolkit. In more recent years, as the field of Machine Learning develops, conditional score-based generative models (cSGMs) have been demonstrated to exhibit remarkable capabilities in generating plausible data from target distributions that are conditioned on some given label. It is tempting to exploit such generative models to produce samples of data distributions (points on a slow manifold, steady states on a bifurcation surface) conditioned on (consistent with) some quantity of interest (QoI, observable). In this work, we present a framework for using cSGMs to quickly (a) initialize on a low-dimensional (reduced-order) slow manifold of a multi-time-scale system consistent with desired value(s) of a QoI (a “label”) on the manifold, and (b) approximate steady states in a bifurcation diagram consistent with a (new, out-of-sample) parameter value. This conditional sampling can help uncover the geometry of the reduced slow-manifold and/or approximately “fill in” missing segments of steady states in a bifurcation diagram. Finally, the quantity of interest, which determines how the sampling is conditioned, is either known a priori or identified using manifold learning-based dimensionality reduction techniques applied to the training data.

Dynamical systems↗

Stable isotope equilibria in the dihydrogen-water-methane-ethane-propane system. Part 2: Experimental determination of hydrogen isotopic equilibrium for ethane-H2 from 30 to 200 °C and propane-H2 from 75 to 200 °C

The stable isotopic compositions of light n-alkanes, including methane, ethane, and propane, are often used to identify the sources and thermal maturity of natural gas samples. Though stable isotopic compositions of these molecules are commonly assumed to be controlled by kinetic isotope effects, recent studies have proposed both carbon and hydrogen isotopic equilibrium may also occur in some samples. Assessing whether samples are in isotopic equilibrium requires knowledge of light alkane equilibrium fractionation factors over geologically relevant temperatures for formation and storage (up to ∼300 °C). In this study, we report experimental results of hydrogen isotopic equilibrium between ethane and H2 from 30 to 200 °C and propane and H2 from 75 to 200 °C. We compare these results with high-level theoretical calculations and provide a preferred polynomial fit to describe equilibrium fractionation factors. Comparison of these fractionation factors with a compilation of ∼500 compiled environmental gas samples supports the proposal that many (∼50%) of these natural gas samples exhibit hydrogen isotopic compositions consistent with having formed in or attained methane-ethane-propane hydrogen isotopic equilibrium over geologically relevant temperatures for formation and storage (50–300 °C).

Turner, Andrew C↗

Densification of the entropy stabilized oxide (Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )O

The first entropy-stabilized oxide, (Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )O, was reported in 2015. Initial studies synthesized this material using solid state processing and were limited to densities < 80%. Here, we report a straightforward solid state route to sinter samples to densities up to 98% of the theoretical by identifying the role of oxygen and promoting the resulting mechanisms in densification. Previous works have studied effects of cation stoichiometry on the entropy-driven reaction to form a single phase, but few have explored the associated effects of anion stoichiometry and/or redox chemistry on both phase stability and densification. We demonstrate here that tuning heating rate and pO 2 during heating of initially-homogeneous calcined powders can enhance densifying diffusion processes and enable reliable sintering of dense (Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )O samples.

MATERIALS SCIENCE↗

Age hardening response of Cu-30Ni alloys: The role of Si microalloying additions

Cu-30Ni alloys offer high strength and excellent corrosion resistance for maritime applications. While primarily a solid solution system, industrial alloys typically include microalloying additions of Fe, Mn, Nb and/or Si to enable age hardening. However, an understanding of the microstructural evolution during age hardening remains incomplete. Here, we conduct systematic ageing treatments and report the resulting hardness and microstructures. The Cu-30Ni alloy with Si aged at 650 °C for 6 h demonstrates significantly enhanced Vickers hardness, reaching ∼201 HV 1 compared to 103 HV 1 for the as-homogenised sample. Si-rich clusters and γ′ precipitates are identified, with their composition, size, and volume fraction quantified to determine their strengthening contributions. First-principles atomistic simulations elucidate the underlying formation mechanisms of these clusters and precipitates, highlighting the critical role of Si in driving their nucleation and growth. This study advances the design of high-strength, Cu alloys with the potential for corrosion resistance in demanding maritime environments.

Age hardening↗

Diffusion Quantum Monte Carlo Benchmarking of Magnetic Moments in MnBi 2 Te 4

The intrinsically antiferromagnetic topological insulator, MnBi 2 Te 4 (MBT), has garnered significant attention recently due to its potential to host numerous exotic topological quantum states. Unfortunately, their consistent realization has been hindered by intrinsic antisite defects among the Mn and Bi sublattices. In this work, we establish Mn magnetization of pristine MBT through high level diffusion Monte Carlo calculations, which can serve as a precise starting point for various models to estimate antisite defect concentrations in actual MBT samples. The benchmark quality of DMC calculations is further identified from out model estimating antisite defect concentrations, which combines the benchmarked Mn magnetization with data from magnetic susceptibility and intermediate field magnetization measurements. This reproduces well Bi Mn and Mn Bi concentrations measured in the experiments. Here, we anticipate these theoretically based magnetic purity measures may be used as minimization targets in cycles of refinement to synthesize MBT with low antisite defect concentrations and more reproducible topological properties.

Defects↗