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At least 451 records · Page 25

Estimation of micro-Hall-Petch coefficients for prismatic slip system in Mg-4Al as a function of grain boundary parameters

Grain size strengthening, referred to as the Hall-Petch effect, is a common strategy to improve the yield strength of magnesium (Mg) alloys. Several experimental studies have reported that the Hall-Petch slope strongly depends on the texture of the alloy. This effect arises from altering grain boundaries (GBs) resistance to different slip systems to transfer across adjacent grains. The grain boundary barrier strength of certain grain boundaries to basal slip, referred to as basal micro-Hall-Petch, was investigated in the previous work. Here in this study, the micro-Hall-Petch coefficient values for the prismatic slip $(k^{prismatic}_{μ})$ in Mg-4Al and their correlation with the grain boundary parameters were investigated. An experimental method was developed to initiate the prismatic slip band at low-stress levels. High-resolution electron backscatter diffraction (HR-EBSD) was used to measure the residual stress tensor, from which the resolved shear stress ahead of blocked prismatic slip bands was computed for seven different grain boundaries. $(k^{prismatic}_{μ})$ values for each individual GB were calculated by coupling the stress profile information with a continuum dislocation pile-up model. The $(k^{prismatic}_{μ})$ values vary from 0.138 MPa.m 1/2 to 0.685 MPa. m 1/2 which are almost three times larger than the calculated values for the basal micro-Hall-Petch. The $(k^{prismatic}_{μ})$ values were correlated with the GB parameters, and a functional relationship depending on the two most effective angles, the angle between the traces of the slip planes on the GB plane ($\phi$) and the angle between incoming and outgoing slip directions (κ), was proposed to estimate the Hall-Petch barrier for prismatic slip system. The work provides coefficients that can be supplied as input to crystal plasticity models to couple the effect of texture and grain size effectively.

36 MATERIALS SCIENCE↗

Step-loaded creep testing of Zircaloy-4 cladding at higher temperatures in the α-phase

A refined understanding of zirconium-based cladding thermomechanical performance during rapid transients is essential for enhancing the safety and operation of light-water reactors. Traditional models for zirconium alloys under accident conditions generally assume that creep dominates fuel cladding performance. Here, these historic models have largely remained unchanged and serve as the basis for safety criteria development. As the U.S. nuclear industry pursues higher burnup levels, the increased release of fission gases during transients raises the risk of cladding failure in the low-temperature hcp α-phase, making the fidelity of these models of greater importance. Creep testing was conducted from 550–700°C with 25–120 MPa applied hoop stresses to investigate Zircaloy-4 deformation at accident-relevant temperatures in the α-phase. Step-loading was employed to capture creep behavior across a wide stress range from a single sample. The stress-strain rate data at higher temperatures (650 and 700°C) were well-described by isotropic versions of the Erbacher and Kaddour models, while the lower temperature data (550 and 600°C) were underpredicted by both anisotropic and isotropic model variants. Greater strain rates during the initial loading step at 650 and 700°C were attributed to recrystallization and grain growth of sub-micron crystallites. Yet, texture analysis revealed the basal split texture remained after testing. These observations produced results suggesting Zircaloy-4 claddings experience higher creep rates across the α-phase than previously thought, possibly related to dynamic anisotropy due to temperature dependent activation of deformation mechanisms, effects of biaxial loading, and variation in material condition between the current testing used in previous model development.

36 MATERIALS SCIENCE↗

Multi-objective surrogate-assisted calibration of CPFEM models using macroscopic response and in situ EBSD measurements of grain reorientation trajectories

Crystal plasticity finite element method (CPFEM) models are widely used to simulate the deformation behaviour of polycrystalline materials, but their calibration is often limited by their high computational cost and the non-convexity of the optimisation landscape. Here, this study develops a multi-objective surrogate-assisted calibration workflow that couples a multi-objective genetic algorithm (MOGA) with an adaptively trained deep neural network (DNN) surrogate model to efficiently identify CPFEM parameters from experimental data. The workflow is demonstrated on three crystal plasticity (CP) formulations of increasing complexity — Voce hardening (VH), two-coefficient latent hardening (LH2), and six-coefficient latent hardening (LH6) — using in situ electron backscatter diffraction (EBSD) measurements of Alloy 617 under uniaxial tensile loading. The CPFEM models are calibrated against the experimentally observed stress–strain response and reorientation trajectories of eight grains, then validated against eight additional trajectories and overall texture evolution. Across the CP formulations, the macroscopic response was reproduced reliably, while differences emerged in the robustness and accuracy of the grain-scale predictions. Including grain reorientation trajectories in the multi-objective calibration improved texture evolution predictions and filtered out physically inconsistent parameter sets that can arise from calibrating against only the stress–strain data. The workflow also demonstrates good transferability of calibrated parameters from a low- to a high-fidelity microstructural model. These results provide practical guidance for integrating in situ microstructural data into CPFEM through efficient, repeatable, and physically meaningful multi-objective calibration.

Crystal plasticity finite element method↗

Ultrafine-grained Fe-TiB 2 high-modulus nanocomposite steel with high strength and isotropic mechanical properties by laser powder bed fusion

Fe-TiB 2 metal matrix composite, also called high-modulus steels (HMSs), are of great interest for applications in fuel-efficient transportation infrastructure, aerospace, and wear industries due to their high specific stiffness and yield strength. However, conventional cast Fe-TiB 2 HMSs often contain coarse and sharp-edged TiB 2 particles which easily trigger premature cracking during loading. Here, we synthesized a Fe-TiB 2 nanocomposite HMS via laser powder bed fusion (LPBF) additive manufacturing of mixed micro-sized powders of Fe, Ti, and Fe 2 B. We investigated the microstructure formation and mechanical behavior of the Fe-TiB 2 HMS. We found that in situ chemical reaction of Ti and Fe 2 B enables the formation of TiB 2 particles at nanoscale during rapid solidification of LPBF. These nanoscale TiB 2 particles can serve as heterogeneous nucleation sites and promote the formation of ultrafine and equiaxed α-Fe grains with random crystallographic textures, which differ from many other additively manufactured (AM) metal alloys characteristic of strong crystallographic textures. As such, isotropic mechanical properties were achieved in the AM Fe-TiB 2 nanocomposite HMS with a high elastic modulus of ~ 240 GPa, an exceptional yield strength of ~ 1450 MPa, and a large plasticity of ~ 20% under compression. Quantitative analysis reveals that the high yield strength primarily originates from strengthening contributions of the ultrafine grains with an average grain size of ~450 nm, the nanoscale TiB 2 reinforcing particles of 20–180 nm, and a high density of printing-induced dislocations of the order of 10 15 m –2 . In situ synchrotron high-energy X-ray diffraction unveils the load partitioning from the softer α-Fe matrix to the stiffer and stronger TiB 2 nanoparticles, contributing to the sustained strain hardening during compression. Our work not only provides a general pathway for achieving high-performance metal matrix nanocomposites by in situ chemical reaction and precipitation of ceramic nanoparticles during additive manufacturing, but also offers mechanistic insights into the deformation mechanism of nanoparticle-reinforced HMS composites.

36 MATERIALS SCIENCE↗

Effects of size, geometry, and testing temperature on additively manufactured Ti-6Al-4V titanium alloy

This article presents a comprehensive study concerning size and geometry effect on the ambient and high-temperature mechanical behavior of additively manufactured laser powder bed fusion Ti-6Al-4V alloy. Key mechanical property metrics are presented, including strain hardening rate, yield strength, and Young’s modulus as a function of thickness and testing temperature (ambient, 250 °C, and 450 °C). Here, the effect of specimen size on manufacturing-induced microstructural feature formation is demonstrated and discussed. A detailed analysis regarding Young’s modulus, yield strength, and strain hardening rate variation at elevated temperatures is also presented. Size effect and temperature-sensitive deformation mechanisms are linked to the underlying microstructural deformation mechanisms activated at respective temperatures. Counter-intuitively, this study determined that irrespective of the geometry, strain hardening rates increased as temperature increased. An in-depth microstructural examination is presented to explain the stated observation. The texture of Interrupted tensile test samples examined for ambient, 250 °C, and 450 °C post-yield was observed to be unchanged, indicating the strain hardening behavior was not texture dependent. Schmid factor analysis, coupled with experimental findings from previous work, was implemented to generate a hypothesis. This hypothesis suggests that the drop in critical resolved shear stress for basal and pyramidal slip systems, as temperature increases, paired with the high dislocation density of laser powder bed fusion Ti-6Al-4V, leads to dislocation entanglement and results in increased strain hardening at elevated temperatures.

36 MATERIALS SCIENCE↗

Soybean fallow and nitrification inhibitors: Strategies to reduce N 2 O emission intensities and N losses in Australian sugarcane cropping systems

The Australian sugar industry is facing mounting pressure to reduce the nitrogen (N) losses and nitrous oxide (N 2 O) emissions associated with N fertiliser use. Research has shown that N 2 O emissions from sugarcane (Saccharum officinarum L.) cropping systems can be reduced with the use of fertilisers coated with nitrification inhibitors, or by sowing legume crops in the fallows between sugarcane crop cycles. However, the efficacy of these two N management strategies across different climatic zones is still unclear, as results from field studies have been contradictory. The objectives of this study were therefore to use the DayCent model to assess the long-term effects of the two strategies (separately or in combination) on N 2 O emissions, N losses and yields. The model was parameterised using data from eight field experiments (39 treatments) conducted across four of the five main districts of the Australian sugarcane industry. A series of long-term scenarios embracing a range of N fertiliser rates (0- 160 kg N ha -1 applied as urea), climatic regions (Tropics and Subtropics), soil textures (fine- and coarse-textured soils) and N-loss risk scenarios (crop fertilised well before or close to the on-set of the wet season) were tested for both N management strategies. Simulations identified that the combined use of soybean (Glycine max L.) fallows and N fertiliser coated with the 3,4-dimethylpyrazole phosphate (DMPP) nitrification inhibitor was the most effective strategy to maintain or even increase current yields while significantly reducing N 2 O and cumulative N (mainly due to nitrate) losses. When used alone, the soybean fallow strategy on average reduced N losses over the entire crop cycle by 29 % compared with current industry best practice. However, this strategy showed a limited capacity to reduce N 2 O emissions over the entire cane crop cycle (median: -3% compared with current industry best practice), or even increased them in scenarios at high-risk of N losses in the Tropics. The use of urea coated with DMPP alone allowed current fertiliser N rates to be reduced by 30 % without any substantial yield penalty. In environments prone to high N losses, DMPP urea abated overall N losses and N 2 O emissions by 41 % and 30 %, respectively. This was the first study to use such an extensive dataset to parameterise a biogeochemical model for yields, N 2 O emissions and N losses in sugarcane cropping systems. Finally, the findings will be instrumental in guiding future research and policies designed to improve the profitability and environmental sustainability of this industry.

54 ENVIRONMENTAL SCIENCES↗

Simulation of radiation damage via alpha decay in BFS:PC grouts using 4 He 2+ ion acceleration

The impact of alpha radiation on cements used to encapsulate intermediate-level waste (ILW) is not well understood. ILW wastes can contain high levels of alpha-emitting radionuclides, meaning that the grouts used to encapsulate them are exposed to significant ionising radiation. Thus, a damaged region could develop in the grout adjacent to the alpha-emitting species. This work attempted to recreate this behaviour through nonradioactive 4 He 2+ ion-accelerator experiments, which have not previously been applied to common encapsulation grouts. The influence of this irradiation on a slag-Portland cement was investigated at different ages via transmission electron microscopy energy-dispersive x-ray spectroscopy (TEM-EDX) and supporting techniques, to assess whether 4 He 2+ irradiation caused textural or chemical zonation. No significant changes in hydrate phases or textures were observed, other than minor variations associated with carbonation. This paper provides a proof of concept for using ion acceleration techniques on cements and furthers knowledge on their radiation response.

36 MATERIALS SCIENCE↗

Shifting modes of iron sulfidization at the onset of OAE-2 drive regional shifts in pyrite δ 34 S records

We report total reduced inorganic S isotope ratios (δ 34 S CRS ) shift toward more negative values across much of the southern North Atlantic just before the onset of the Cenomanian-Turonian Ocean Anoxic Event (OAE-2). At the same time, there is no parallel isotopic change in the significantly larger pool of kerogen (organic) S, which indicates that the distribution and S-isotope composition of sulfide in the environment likely did not drive the change in δ 34 S CRS . Here, we investigate possible explanations for the negative shift in δ 34 S CRS values and their divergence from organic S by isolating iron sulfides for morphological identification and grain-specific isotopic analysis using secondary ion mass spectrometry (SIMS). In pre- and syn-OAE-2 sedimentary rocks from Demerara Rise, we find four distinct morphologies of iron sulfides: pyrite framboids (1–20 μm diameter), irregular pyrite aggregates (1–38 μm diameter), large cemented pyrite aggregates (~60 μm diameter), and irregular and cemented aggregates of the pyrite polymorph marcasite (1–45 μm diameter). These different textural groups have distinct S-isotopic compositions that are largely consistent through the onset of OAE-2. As such, the secular change in bulk δ 34 S CRS values likely reflects the changing proportions of these phases stratigraphically across OAE-2. All textural groups feature resolvable intra-grain δ 34 S variability, suggesting that the environments in which they formed were characterized by dynamic sulfide δ 34 S values and/or by partial closed-system distillation. We use grain-specific δ 34 S distributions to rule out shoaling of the chemocline within the sediments as a mechanism for the observed decrease in δ 34 S CRS . Instead, we propose that changes in the reactivity of the iron species delivered to Demerara Rise over the ~200 kyr leading up to the onset of OAE-2 impacted the relative contributions of pyrite with S-isotope signatures reflecting the water column, shallow sediments, and deeper sediments to the bulk sedimentary δ 34 S CRS value. Specifically, the change in iron reactivity at the onset of OAE-2 favored the production of 34 S-depleted large, cemented aggregates and framboids at the expense of more 34 S-enriched irregular aggregates. Our results underscore that bulk δ 34 S CRS measurements integrate multiple reduced phases that form via distinct reaction mechanisms and potentially in different parts of the depositional environment. Grain-specific SIMS analyses dramatically enrich our ability to interpret pyrite isotopic patterns in the geologic record.

58 GEOSCIENCES↗

Effect of grain structure and strain rate on dynamic recrystallization and deformation behavior: A phase field-crystal plasticity model

Herein, a phase field (PF)-crystal plasticity (CP) model has been developed to study the effects of initial grain structures, recrystallized grain orientation, and strain rates on dynamic recrystallization and deformation behavior under stress states typical of the Shear Assisted Processing and Extrusion (ShAPE) process. The model takes the geometrically necessary dislocation density as the nucleation criterion for recrystallization and minimizes the deformation energy as the driving force of recrystallized grain growth. Using this model, the effects of grain orientations and strain rates on dynamic recrystallization and deformation behavior were simulated. The results demonstrate that (1) a polycrystalline structure with the texture observed in ShAPE process has the lowest yield stress under the ShAPE stress conditions, (2) the recrystallized grains with the texture observed in ShAPE process largely soften the materials, and (3) higher shear strain rate or rotation speed results in larger magnitude of material softening.

36 MATERIALS SCIENCE↗

On the numerical sensitivity of cellular automata grain structure predictions to large thermal gradients and cooling rates

Cellular automata (CA) models of as-solidified grain structure, originally developed and applied to casting, have become a common means of predicting grain structure resulting from Additive Manufacturing (AM) processes. The majority of these models are based on the decentered octahedron approach, which attempts to correct for the effect of grid anisotropy on the prediction of competitive solidification of dendritic grains. However, AM solidification occurs under cooling rates ($\dot{T}$) and thermal gradients (G) that are orders of magnitude larger than those encountered in casting, and no systematic investigation on the effect of the CA model cell size (Δx) and time step (Δt) on AM microstructure predictions has been performed. Here, in this study, such an investigation is first performed via simulation of individual grains of various crystallographic orientations with a fixed, unidirectional G, showing that CA prediction of the steady-state undercooling matched the expected values based on the interfacial response function at small G and deviated from the expected values at large G. Simulation of competitive growth of multiple grains showed a weakening of the predicted texture as G and Δx became large. Simulation of solidification under AM conditions, where G and $\dot{T}$ vary spatially across the melt pools, showed that not only does grain selection weaken and deviate from expectations at large Δx, but grains with crystallographic $\langle$100$\rangle$ aligned with the grid directions are more adversely affected by the temperature field discontinuities than grains with other crystallographic orientations. Despite the fact that the exact grain competition results depended on Δt, the overall texture development was notably less sensitive to Δt than Δx, provided that a reasonable value of Δt is selected based on the ratio of Δx to the maximum local solidification velocity in the simulation domain. Finally, from the directional solidification and AM simulation results, an analysis of computational cost compared to simulation resolution is performed based on an equation derived to quantify the relatively inaccuracy in grain selection based on the model and temperature field inputs. From this analysis, it is concluded that there is a need for algorithmic improvements to improve CA grain competition accuracy for large G processing conditions as sufficiently small Δx to resolve the necessary competition is intractable for many AM processing conditions.

36 MATERIALS SCIENCE↗

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗

Quantifying cover crop effects on soil health and productivity

The dataset presented here supports the research paper entitled “A calculator to quantify cover crop effects on soil health and productivity”. Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters – erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity – to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

54 ENVIRONMENTAL SCIENCES↗

Soft matter approach for creating novel protein hydrogels using fractal whey protein assemblies as building blocks

In this study, mesoscopic sized fractal assembly (FA) particles were prepared using whey protein isolate; the coldset gelation properties of FA particles were investigated in-depth. Two types of FA particles (FA -62 and FA -90) with different mean sizes were synthesized through controlled thermal treatment of whey protein solutions at two concentrations (62 g/L and 90 g/L). Particle characteristics e.g. hydrodynamic radius, ζ-potential and surface hydrophobicity were dependent on pH and structure of FA. Transmission electron microscopy (TEM) observation confirmed the fractal morphology and small-angle X-ray scattering (SAXS) analysis suggested an internal fractal structure for the obtained FA particles. Eight cold-set FA protein gels (2 % w/v) were manufactured by controlling two gelling factors at two levels: pH (5.8 and 7.0) and Ca 2+ content (5 mM and 10 mM). Rheological characteristics in the large amplitude oscillatory shear regime revealed that pH 7.0 gels were softer and elastic while pH 5.8 gels were harder and brittle. Rheology Pipkin diagrams demonstrated that the strain softening/stiffening and the shear-thinning/thickening behaviors may be fine-tuned by manipulating the key gelation factors: e.g. FA structure, pH, and Ca 2+ . The entrainment speed-dependent friction coefficient curves showed that at an intermediate velocity regime (6-250 mm s -1 ), FA -90 particles induced hydrogels had superior lubrication effect compared to FA -62 gels. Further, this work demonstrated a food structure design approach regarding tuning texture and lubrication properties of protein gels without changing protein content and protein composition. The optimized protein hydrogels may be used as texturizer for "cleaner label" food formulas and/or as delivery system for carrying micronutrients.

60 APPLIED LIFE SCIENCES↗

Machine learning assisted rediscovery of methane storage and separation in porous carbon from material literature

Porous carbon (PC) has been widely regarded as one of the most promising absorbents for methane storage. Studies show that its uptake capacity and selectivity highly depend on textural structures. Although much effort has been made, unveiling their detailed structure-performance relationship remains a challenge. Here, we propose an innovative study where, with the assistance of machine learning, the hidden relationship of the textural structures of PC with the methane uptake and separation can be derived from existing data in material literature. Machine learning models were trained by the data, including specific surface area, micropore volume, mesopore volume, temperature, and pressure as the input variables and methane uptake as the output variable for prediction. Among the tested models, the multilayer perceptron (MLP) shows the highest accuracy in predicting the methane uptake. In addition, the model enables to automatically construct a uptake performance map in terms of micropore volume and mesopore volume. The obtained MLP model was also extended to explore the CO 2 /CH 4 selectivity by retraining it with the data collected from literature of PC for the CO 2 uptake. Finally, the constructed 2D selectivity map shows that the high selectivity can be achieved in the low CH 4 uptake region.

42 ENGINEERING↗

Effect of amine type on acidic toxic gas adsorption at ambient conditions on modified CuBTC

We report two amine-modified copper-based Metal Organic Frameworks (MOF (CuBTC)) of different surface chemical and textural features were synthesized and used as adsorbents of acidic toxic gases (NO 2 and H 2 S) in both moist (71% relative humidity (R.H.)) and dry conditions. The initial and exhausted samples were characterized by nitrogen adsorption, powder X-ray diffraction, scanning electron microscopy, thermal gravimetric analysis and Fourier transform infrared spectroscopy. The addition of melamine prevented full growth of CuBTC crystals and resulted in amorphous-like particles with sizes less than 200 nm. The material was non-porous with a small surface area. When urea was used as an amine source, the resulting particles maintained the overall octahedral shape of the parent CuBTC MOF and the material was more porous than the parent MOF. While the urea-modified CuBTC sample performed well as an NO 2 adsorbent in the presence of moisture, the reactivity of the melamine-modified sample and its physical properties provided a favorable environment for the removal of H 2 S. The incorporation of amines into the MOF structure also resulted in surface defects /open copper sites that favored the removal of toxic gases in dry conditions. The reactivity of the adsorbents with toxic gases was demonstrated by the changes in the adsorbent colors, in texture, and in surface chemistry (organic salts, complexes, sulfides and nitrates were formed).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MnBi-based magnets prepared from melt-spun alloys: Effect of $α → β$ phase transformation during field annealing

The temperature of the annealing treatment applied to the MnBi alloys with the intention to stabilize the α -MnBi “low-temperature” phase – a promising material for the rare-earth-free permanent magnets – is usually kept below the range of the β -Mn 1.08 Bi “high-temperature” phase. This work is focused on the investigation of the effects of partial and complete α → β phase transformation in bulk magnetic-field-annealed magnets on their structure and magnetic properties. MnBi alloys modified with In, Mg and Sb were melt-spun, compacted to their full density and then heated in a magnetic field of 30 kOe to temperatures sufficiently high for the beginning of the α → β transformation. A heating of 15 °C/min was used which was immediately followed by cooling at the rate of 7.5 °C/min; the degree of the phase transformation was measured by in situ monitoring of changes in the sample magnetization. In all the studied alloys, the α → β transformation was found to improve the [0 0 1] fiber texture induced by the applied magnetic field, although it simultaneously decreased the coercivity. A partial transformation has resulted in a 11% increase of the maximum energy product for the Mn 50 Bi 49 Sb 0.5 In 0.5 magnet, to 8.3 MGOe, and a 3% increase for the Mn 50 Bi 46 Mg 3 Sb 0.5 In 0.5 magnet, to 12.8 MGOe. In the latter alloy, the α → β and reverse transformations were found to initially occur in well-defined pockets leading to clusters of large, highly textured α crystallites. In the Mn 50 Bi 48.5 Sb 1.5 magnet, only part of the α phase could be recovered after the transformation, which instead promoted the paramagnetic MnBi 0.9 Sb 0.1 phase.

36 MATERIALS SCIENCE↗

Spin-dependent Seebeck and Nernst effects in an ideal skyrmion gas

In this work, we theoretically and numerically study spin-dependent Seebeck and Nernst effects in 2D ferromagnetic materials with the topological spin texture (skyrmion and vortex) ideal gas. From the numerical solution of the matrix Boltzmann equation for a nonequilibrium distribution function and the Lippmann–Schwinger equation for a T-matrix we find the strong nonlinear behaviors in the thermoelectric coefficients depending on skyrmion/vortex diameters and electron concentrations. In particular, the dramatic dependences in the Seebeck and Nernst coefficients take place at larger magnetic texture sizes where the abrupt sign flip in the vortex Seebeck and Nernst coefficients occurs in the narrow region of electron concentrations. In this case the normalized Nernst coefficient changes from +5 to -7. The spin-dependent thermoelectric coefficients are proportional to T at low temperatures for all skyrmion/vortex sizes.

36 MATERIALS SCIENCE↗

Origins of high ductility exhibited by an extruded magnesium alloy Mg-1.8Zn-0.2Ca: Experiments and crystal plasticity modeling

Low ductility and strength are major bottlenecks against Mg alloys' wide applications. In this work, we systematically design the composition and fabrication process for a low-alloyed Mg-Zn-Ca alloy, showing that it can be extruded at low temperatures (~ 250 degrees C) and high speeds (~2 mm/s). After the extrusion, this alloy exhibits a substantially weakened basal texture, relatively small grain size, very high tensile elongation (~ 30%), and good strength. The origin of the considerably improved ductility was studied using a combination of three-dimensional atom probe tomography (3D-APT), transmission electron microscopy (TEM), electron backscattered diffraction (EBSD) in conjunction with surface slip trace analysis, in-situ synchrotron X-ray diffraction, and elasto-plastic self-consistent (EPSC) modeling. Co-segregation of Zn and Ca atoms at a grain boundary is observed and associated with texture weakening and grain boundary mediated plasticity, both improving the ductility. While basal slip and prismatic slip are identified as the dominant deformation systems in the alloy, the ratio between their slip resistances is substantially reduced relative to pure Mg and most other Mg alloys, significantly contributing to the improved ductility of the alloy. This Mg-Zn-Ca alloy exhibiting excellent mechanical properties and low fabrication cost is a promising candidate for industrial productions.

36 MATERIALS SCIENCE↗