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At least 181 records · Page 10

Model Parameter Development for Complex Materials: Species-Specific Diffusion Barriers in 316 Stainless Steel from Systematic DFT Calculations

Vacancy-mediated diffusion barriers in 316 stainless steel have been systematically calculated using density functional theory to provide essential parameters for mesoscale microstructure evolution models. A statistical sampling approach employing 210 nudged elastic band calculations across multiple special quasi-random structures captures the effects of local chemical environments in this concentrated alloy. The computational methodology addresses challenges specific to chemically disordered systems, including proper magnetic treatment throughout multi-step calculations and validation against experimental structural properties. The calculated activation barriers reveal clear species-dependent diffusion behavior with the hierarchy Ni >> Fe ˜ Cr >> Mo. Nickel exhibits the highest barriers (0.74–1.31 eV, mean 1.045 eV), confirming its role as the slowest-diffusing major component. Iron and chromium show similar moderate barriers averaging 0.587 eV and 0.522 eV, respectively. Remarkably, molybdenum demonstrates exceptionally low barriers (0.12–0.28 eV, mean 0.194 eV), suggesting much higher mobility than previously recognized and potentially significant implications for precipitation kinetics and microstructure evolution. The barrier ranges remain consistent across different 316 SS compositions, supporting parameter transferability for modeling applications. The overall mean barrier of 0.64 eV provides a practical approximation for phase field simulations, while species-specific values enable detailed treatments of diffusion-controlled processes. This systematic approach establishes a validated framework for generating diffusion parameters in other concentrated alloys where experimental data are limited, while providing the first systematic set of species-specific barriers for predictive modeling of 316 stainless steel microstructure evolution.

36 MATERIALS SCIENCE↗

Controlling Magnetization Vector Depth Profiles of La 0.7 Sr 0.3 CoO 3 /La 0.7 Sr 0.3 MnO 3 Exchange Spring Bilayers via Interface Reconstruction

The La 0.7 Sr 0.3 CoO 3–δ /La 0.7 Sr 0.3 MnO 3–δ (LSCO/LSMO) bilayer system is an ideal perovskite oxide platform for investigating interface reconstruction and its effect on their magnetic properties. Previous studies have shown that LSCO can separate into magnetic sublayers, which possess distinct trends as the total LSCO thickness increases. Here, we used polarized neutron reflectometry to quantify changes in the magnetic and chemical depth profiles, and it confirms the formation of ~12 Å-thick interfacial LSCO and LSMO layers, characterized by a decreased nuclear scattering length density compared to the bulk of the layers. This decrease is attributed to the combined effects of oxygen vacancy formation and interfacial charge transfer, which lead to magnetically active Co 2+ ions with ionic radii larger than the Co 3+ /Co 4+ ions typically found in bulk LSCO or single-layer films. The interfacial magnetization values, as well as Co 2+ ion and oxygen vacancy concentrations, depend strongly on the LSCO layer thickness. These results highlight the sensitive interplay of the cation valence states, oxygen vacancy concentration, and magnetization at interfaces in perovskite oxide multilayers, demonstrating the potential to tune their functional properties via careful design of their structure.

36 MATERIALS SCIENCE↗

A reaction–diffusion model for grayscale digital light processing 3D printing

We report that digital light processing (DLP) 3D printing is an additive manufacturing process that utilizes light patterns to photopolymerize a liquid resin into a solid. Due to the accuracy of modern digital micromirror devices (DMD) and recent advances in resin chemistry, it is now possible to create functionally graded structures using different light intensity values, also known as grayscale DLP (g-DLP). Different intensities of light lead to differences in the polymer crosslinking density after curing, which ultimately produces a part with gradients of material properties. However, g-DLP is a complicated process. First, the DLP printing is a highly coupled chemical and physical process that involves light propagation, chemical reactions, species diffusion, heat transfer, volume shrinkage, and changes in mechanical behaviors of the curing resin. Second, in g-DLP, light gradients create strong in plane gradients of chemical species concentrations in the curing liquid resin due to the strong dependence of light intensity on the rate of monomer crosslinking. Furthermore, light gradients through the depth create concentration gradients due to the degree of cure dependent light absorption and the use of photoabsorbers. These complex physical features of the printing process must be understood in order to properly control printing parameters such as light exposure time, printing speed, and grayscale variations to achieve accurate mechanical properties. In this paper, a photopolymerization reaction–diffusion model is developed and used in conjunction with experiments to investigate the coupled effects of light propagation, chemical reaction rates, and species diffusion during g-DLP 3D printing. The model is implemented numerically utilizing the finite difference method and simulation results are compared to experimental findings of simple printed structures. The agreement between experimental and model predictions of simple quantities of interest, such as geometric feature sizes, shows that the model can capture the overcure due to free-radical and other species diffusion during printing when grayscale patterns are employed. This model lays the groundwork for future extensions that can incorporate more complex coupled physics such as heat transfer, volume shrinkage, and material property evolution, which are critically important in utilizing g-DLP 3D printing for the fabrication of high-performance parts which excellent geometric and material property tolerances.

36 MATERIALS SCIENCE↗

Shape-preserving amorphous-to-crystalline transformation of CaCO3 revealed by in situ TEM

Organisms use inorganic ions and macromolecules to regulate crystallization from amorphous- precursors, endowing natural biominerals with complex morphologies and enhanced properties. The mechanisms by which modifiers enable these shape preserving transformations are poorly understood. We used in situ liquid-phase transmission electron microscopy to follow the evolution from amorphous calcium carbonate to calcite in the presence of additives. A combination of contrast analysis and infrared spectroscopy shows that Mg ions, which are widely present in seawater and biological fluids, alter the transformation pathway in a concentration-dependent manner. The ions bring excess (structural) water into the amorphous bulk so that a direct transformation is triggered by dehydration in the absence of morphological changes. Molecular dynamics simulations suggest Mg-incorporated water induces structural fluctuations, allowing transformation without the need to nucleate a separate crystal. Thus, the obtained calcite retains the original morphology of the amorphous state, biomimetically achieving the morphological control of crystals seen in biominerals

crystallization, biomineralization, calcium carbon↗

Grain boundary segregation beyond the dilute limit: Separating the two contributions of site spectrality and solute interactions

Solute segregation at grain boundaries (GBs) is known to have a profound impact on material properties, and as such is becoming routinely used as an element in alloy design. Beyond the dilute limit, the extent of solute GB segregation is known to be concentration dependent. Using hybrid Monte Carlo/Molecular Statics simulations of Mg segregation in Al, in this work we decouple the two contributions to this composition dependence: (i) spectrality of atomic environments at the boundary and (ii) solute-solute interactions. Although only contribution (ii) is typically considered in the literature, we argue that both contributions are equally important to understand concentration dependence and correctly quantify GB solute segregation in a binary alloy. Finally, a thermodynamic segregation isotherm is outlined that accounts for both the spectrality of grain boundary sites and solute-solute interactions. Unlike classical isotherms like those of McLean or Fowler-Guggenheim, which can be successfully fitted to GB segregation data only over a limited range of composition and temperature, our proposed model is shown to be accurate across the composition-temperature space.

36 MATERIALS SCIENCE↗

Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties

The chemical properties of oils are vital in the design of microemulsion systems. The hydrophilic–lipophilic difference equation used to predict microemulsions’ phase behavior expresses the oils’ physiochemical properties as the equivalent alkane carbon number (EACN). The experimental determination of EACN requires knowledge of the temperature dependence of the microemulsion system and the effects of different surfactant concentrations. Thus, the experimental determination is time-intensive and tedious, requiring days to months for proper separations. Furthermore, the experiments require high purity of chemicals because microemulsions are sensitive to impurities. Our work focuses on the quick and reliable predictions of the EACN with machine learning (ML) models. Due to the immaturity of ML chemical predictions, we compare three graph neural networks (GNNs) and a gradient-boosted tree algorithm, known as XGBoost. The GNNs use the molecular structures represented as simplified molecular-input line-entry system (SMILES) codes for the initial input, which allows us to assess whether geometry optimization is necessary for reliable results. The XGBoost model also begins with the SMILES representations of the molecules but uses molecular descriptors instead of geometry optimizations. As a result, the best model tested (crystal graph convolutional neural network with Merck molecular force field-94) has an error of 1.15 EACN units of the true EACN for unknown data with the errors skewed toward zero and an R² score of 0.9

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Illustrating galaxy–halo connection in the DESI era with illustrisTNG

ABSTRACT We employ the hydrodynamical simulation illustrisTNG to inform the galaxy–halo connection of the Luminous Red Galaxy (LRG) and Emission Line Galaxy (ELG) samples of the Dark Energy Spectroscopic Instrument (DESI) survey at redshift z ∼ 0.8. Specifically, we model the galaxy colours of illustrisTNG and apply sliding DESI colour–magnitude cuts, matching the DESI target densities. We study the halo occupation distribution (HOD) model of the selected samples by matching them to their corresponding dark matter haloes in the illustrisTNG dark matter run. We find the HOD of both the LRG and ELG samples to be consistent with their respective baseline models, but also we find important deviations from common assumptions about the satellite distribution, velocity bias, and galaxy secondary biases. We identify strong evidence for concentration-based and environment-based occupational variance in both samples, an effect known as ‘galaxy assembly bias’. The central and satellite galaxies have distinct dependencies on secondary halo properties, showing that centrals and satellites have distinct evolutionary trajectories and should be modelled separately. These results serve to inform the necessary complexities in modelling galaxy–halo connection for DESI analyses and also prepare for building high-fidelity mock galaxies. Finally, we present a shuffling-based clustering analysis that reveals a 10–15 ${{\ \rm per\ cent}}$ excess in the LRG clustering of modest statistical significance due to secondary galaxy biases. We also find a similar excess signature for the ELGs, but with much lower statistical significance. When a larger hydrodynamical simulation volume becomes available, we expect our analysis pipeline to pinpoint the exact sources of such excess clustering signatures.

79 ASTRONOMY AND ASTROPHYSICS↗

A study of the properties of beryllium doped silicon with particular emphasis on diffusion mechanisms: Profiles of depth dependent conductivity as determined by electrical surface probes

Very large diffusion coefficients were encountered and required the determination of impurity profiles for samples approximately 1 cm thick. Since conductivity values are readily converted into concentrations of electrically active impurities, the major problem became that of accurately determining the conductivity profiles of beryllium diffused silicon samples. Four-point probe measurements on samples having depth conductivities are interpreted in terms of conductivity profiles, based on an exact solution of the problem of exponentially depth dependent conductivity. Applications include surface conductivity determination where the form of the conductivity profile is known, and conductivity profile determination from probe measurements taken as the sample surface is progressively lapped away. The application is limited to samples having conductivity monotonically decreasing with depth from the probed surface.

Franks, R. K.↗

Band Energy Dependence of Defect Formation in the Topological Semimetal Cd3As2

Cadmium Arsenide (Cd3As2) is a prototypical Dirac semimetal that manifests topological properties in a 3D bulk material. In defect-free Cd3As2, the Fermi level lies at a minimum in the density of states at the Dirac point, but experimentally it forms with excess electron carriers and an elevated EF, thereby masking the topological features. To computationally study the self-doping of Cd3As2, we combine density functional theory (DFT) calculations for defect formation energies with quasi-particle self-consistent GW (QSGW) electronic structure calculations. We demonstrate an innate dependence of the point defect formation energies on carrier concentrations and use the QSGW calculated density of states to extrapolate formation energies to arbitrary electron concentrations. This approach allows the quantitative modeling of thermodynamic defect equilibria in topological semimetals and is used to predict how Cd3As2 growth conditions affect the position of EF relative to the Dirac point.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

How exudates production along a phosphorus gradient influences mineral dissolution across contrasting soil development stages

Harnessing rhizosphere processes offers a valuable opportunity to optimize nutrient use efficiency in agroecosystems. In nutrient-limited soils, plants discharge part of photosynthate surplus via root exudation, including carboxylates, which may enhance mineral dissolution and nutrient mobilization. We aimed to assess how plant responses to nutrient limitation translated into changes in exudate profiles, and how these exudates, in turn, drive bioweathering processes across soils of contrasting mineralogy and weathering degree. We conducted a hydroponic experiment with Lupinus albus grown under five phosphorus (P) concentrations (5, 10, 20, 30, and 50 µM) over seven weeks. We measured plant biomass and root traits, performed a metabolomics analysis and quantified seven carboxylates in root exudates using gas chromatography-mass spectrometry. To assess bioweathering processes across contrasted soil domains, we conducted batch dissolution tests with exudates using three soil horizons—35 each with distinct physicochemical properties: enriched in organic matter, iron oxides, or primary silicates. At the intermediate level of P supply, shoot biomass was comparable to that under high P, but plants produced more root biomass and a higher total carboxylate exudation rate. Despite low carboxylate concentrations (<100 ppb), exudates promoted the dissolution of Ca, Mg, Si, Fe, P and K in all horizons. Yet, the degree of element released varied among horizons. These findings highlight the importance of root exudates in enhancing mineral dissolution, with effects dependent on soil physicochemical properties. The results suggest that managing agroecosystems under moderate nutrient limitation could be a sustainable strategy to increase root-to-shoot ratios, enhance bioweathering processes and nutrient release in soil solution.

Pollet, Sasha L.↗

Ferroelectric and Charge Transport Properties in Strain-Engineered Two-Dimensional Lead Iodide Perovskites

Transitions from three-dimensional (3D) hybrid organic–inorganic perovskite (HOIP) structures to lower dimensions including 2D and quasi-2D structures open a new range of functional properties in these materials systems. Yet, the performance of solar cells made from 2D HOIP is below that of the 3D compositions due to the higher band-gap energy, low carrier concentration, and anisotropy in charge transport. Controlling ferroelectricity in 2D HOIPs is considered to be a powerful strategy to drive the spatial separation of photogenerated charge carriers to improve the photovoltaic action in this class of HOIPs. Here, we explore the strain-dependent ferroelectricity and charge carrier properties in strain-engineered 2D-layered HOIPs utilizing advanced scanning probe microscopy (SPM) techniques. Band excitation-piezoresponse force microscopy (BE-PFM) and contact Kelvin probe force microscopy (cKPFM) reveal ferroelectric domains and switchable dynamics with significantly low switching voltages in the low-strain film. Photoluminescence (PL) spectroscopy shows strain-dependent optical properties and a noncentrosymmetric structure with strong second-harmonic generation (SHG) peaks in the low-strain film. In addition, KPFM results demonstrate a higher surface potential in the low-strain films, while the photovoltage and local current are the highest on the high-strain film. Furthermore, our study demonstrates the critical role of strain engineering on the electromechanical and charge carrier dynamics in 2D HOIPs, which is important for development of 2D HOIP devices.

36 MATERIALS SCIENCE↗

The red edge of plant leaf reflectance

A detailed study of the red edge spectral feature of green vegetation based on laboratory reflectance spectrophotometry is presented. A parameter lambda is defined as the wavelength is defined as the wavelength of maximum slope and found to be dependent on chlorophyll concentration. Species, development stage, leaf layering, and leaf water content of vegetation also influences lambda. The maximum slope parameter is found to be independent of simulated ground area coverage. The results are interpreted in terms of Beer's Law and Kubelka-Munk theory. The chlorophyll concentration dependence of lambda seems to be explained in terms of a pure absorption effect, and it is suggested that the existence of two lambda components arises from leaf scattering properties. The results indicate that red edge measurements will be valuable for assessment of vegetative chlorophyll status and leaf area index independently of ground cover variations, and will be particularly suitable for early stress detection.

Horler, D. N. H.↗

Studies of light noble gases in mineral grains from lunar soils: A status report

Among the lunar soil constituents, monomineralic grains deserve special attention. Noble gases of carefully prepared mineral separates from lunar bulk soils were studied. The major results and conclusions of these investigations are summarized, in the context of both the regolith evolution and the history of the solar corpuscular radiation. With regard to the most abundant noble gas component in the regolith samples (the solar gases) the mineral grains have mainly two properties giving these particles among all soil constituents the best characteristics as sensors for solar gases, despite the fact, that the noble gas concentrations in a mineral separate are 10 to 60 times lower that those in a bulk sample of the same grain size. The first of these properties is the mineral dependent retentivity of the light gases He and Ne, the second property concerns the relatively short time during which a mineral grain acquires it solar gases. These two points are briefly discussed.

Wieler, R.↗

Weld stresses beyond elastic limit: Materials discontinuity

When welded structures depend on properties beyond the elastic limit to qualify their ultimate safety factor, and weld-parent materials abruptly change at the interface, then stress discontinuity is inevitable. The stress concentration is mildly sensitive to material relative strain hardening and acutely sensitive to applied stress fields. Peak stresses occur on the weld surface, at the interface, and dissipate within a 0.01-inch band. When the stress is intense, the weld will always fracture at the interface. The analysis incorporates a classical mechanics model to more sharply define stress spikes within the bandwidth, and suggests a relative material index and Poisson's ratio related to strain hardening. Implications are discussed which are applicable to industries of high performance structures.

Verderaime, V.↗

Multi-band automatic sun and sky scanning radiometer system for measurement of aerosols

A weather resistant automatic scanning Sun photometer system is assessed and demonstrated as practical for measurements of aerosol concentrations and properties at remote sites. Interfaced with a transmitter using the Geostationary Data Collection System (GDCS), the data are processed in near real time. The processing allows a time dependence of the aerosols and water vapor and an ongoing assessment of the health and calibration of the instruments. The system's automatic data acquisition, transmission, and processing offer immediate application to atmospheric monitoring and modeling on a regional to global scale and validation of satellite retrievals. It is estimated that under normal circumstances the retrieved aerosol optical thickness has a network wide accuracy of +/- 0.02 from 340 nm to 1020 nm, water vapor +/- 0.2 cm and size distribution from 0.1 to 3 micrometers.

Holben, B. N.↗

The development of concentration gradients in a suspension of chemotactic bacteria

When a suspension of bacterial cells of the species Bacillus subtilis is placed in a chamber with its upper surface open to the atmosphere complex bioconvection patterns are observed. These arise because the cells: (1) are denser than water; and (2) usually swim upwards, so that the density of an initially uniform suspension becomes greater at the top than the bottom. When the vertical density gradient becomes large enough, an overturning instability occurs which ultimately evolves into the observed patterns. The reason that the cells swim upwards is that they are aerotactic, i.e., they swim up gradients of oxygen, and they consume oxygen. These properties are incorporated in conservation equations for the cell (N) and oxygen (C) concentrations, and these are solved in the pre-instability phase of development when N and C depend only on the vertical coordinate and time. Numerical results are obtained for both shallow- and deep-layer chambers, which are intrinsically different and require different mathematical and numerical treatments. It is found that, for both shallow and deep chambers, a thin boundary layer, densely packed with cells, forms near the surface. Beneath this layer the suspension becomes severely depleted of cells. Furthermore, in the deep chamber cases, a discontinuity in the cell concentration arises between this cell-depleted region and a cell-rich region further below, where no significant oxygen concentration gradients develop before the oxygen is fully consumed. The results obtained from the model are in good qualitative agreement with the experimental observations.

NASA Discipline Cell Biology↗

Preferrential Concentration of Particles in Protoplanetary Nebula Turbulence

Preferential concentration in turbulence is a process that causes inertial particles to cluster in regions of high strain (in-between high vorticity regions), with specifics depending on their stopping time or Stokes number. This process is thought to be of importance in various problems including cloud droplet formation and aerosol transport in the atmosphere, sprays, and also in the formation of asteroids and comets in protoplanetary nebulae. In protoplanetary nebulae, the initial accretion of primitive bodies from freely-floating particles remains a problematic subject. Traditional growth-by-sticking models encounter a formidable "meter-size barrier" [1] in turbulent nebulae. One scenario that can lead directly from independent nebula particulates to large objects, avoiding the problematic m-km size range, involves formation of dense clumps of aerodynamically selected, typically mm-size particles in protoplanetary turbulence. There is evidence that at least the ordinary chondrite parent bodies were initially composed entirely of a homogeneous mix of such particles generally known as "chondrules" [2]. Thus, while it is arcane, turbulent preferential concentration acting directly on chondrule size particles are worthy of deeper study. Here, we present the statistical determination of particle multiplier distributions from numerical simulations of particle-laden isotopic turbulence, and a cascade model for modeling turbulent concentration at lengthscales and Reynolds numbers not accessible by numerical simulations. We find that the multiplier distributions are scale dependent at the very largest scales but have scale-invariant properties under a particular variable normalization at smaller scales.

protoplanetary nebulae↗

Cirrus Susceptibility to Changes in Ice Nuclei: Physical Processes, Model Uncertainties, and Measurement Needs

One of the proposed concepts for mitigating the warming effect of increasing greenhouse gases is seeding cirrus cloud with ice nuclei (IN) in order to reduce the lifetime and coverage of cold cirrus that have a net warming impact on the earth's surface. Global model simulations of the net impact of changing upper tropospheric IN have given widely disparate results, partly as a result of poor understanding of ice nucleation processes in the current atmosphere, and partly as a result of poor representation of these processes in global models. Here, we present detailed process-model simulations of tropical tropopause layer (TTL) transport and cirrus formation with ice nuclei properties based on recent laboratory nucleation experiments and field measurements of aerosol composition. The model is used to assess the sensitivity of TTL cirrus occurrence frequency and microphysical properties to the abundance and efficacy of ice nuclei. The simulated cloud properties compared with recent high-altitude aircraft measurements of TTL cirrus and ice supersaturation. We find that abundant effective IN (either from glassy organic aerosols or crystalline ammonium sulfate with concentrations greater than about 100/L) prevent the occurrences of large ice concentration and large ice supersaturations, both of which are clearly indicated by the in situ observations. We find that concentrations of effective ice nuclei larger than about 50/L can drive significant changes in cirrus microphysical properties and occurrence frequency. However, the cloud occurrence frequency can either increase or decrease, depending on the efficacy and abundance of IN added to the TTL. We suggest that our lack of information about ice nuclei properties in the current atmosphere, as well as uncertainties in ice nucleation processes and their representations in global models, preclude meaningful estimates of climate impacts associated with addition of ice nuclei in the upper troposphere. We will briefly discuss the key field measurements needed to constrain ice nucleation processes.

Jensen, Eric↗