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At least 631 records · Page 35

Grain boundary segregation and chemical ordering in CoCrFeMnNi multi-principal element alloy

Owing to their far-from-dilute compositions, multi-principal element alloys (MPEAs) can exhibit unique combinations of engineering properties. As nearly all MPEAs are polycrystalline aggregates, it is necessary to understand the interactions of various elemental species with grain boundaries (GBs). This is of particular importance in extreme environments, such as radiation and elevated temperatures, where such interactions have implications on the properties of MPEAs. Herein, we employ atomistic simulations to generate a series of [001] asymmetric tilt GBs in a model CoCrFeMnNi MPEA and quantify solute interactions and segregation to these boundaries. We employ the Warren-Cowley order parameters to investigate the interplay between GB segregation and chemical short-range order (SRO). At temperatures above 800 K, simulation results reveal the segregation of Cr and Mn to CoCrFeMnNi GBs and show weak dependence of boundary solute excess on GB geometry, at least for the boundaries explored in this work. At temperatures in the range of 673–800 K, formation of domains rich in Cr is observed at GBs in agreement with experimental observations. Quantitative analysis shows that solute excess of various alloying elements decreases rapidly with the increase in temperature in the range of 1000–1200 K. Furthermore, we show that GB regions exhibit SRO characteristics that are distinct from the bulk crystals, leading to spatial variations in SRO. In broad terms, our study highlights the need to account for GB interactions with alloying elements when designing advanced MPEAs with novel chemistries.

Wang, Yitao [Lehigh University, Bethlehem, PA (Uni↗

Life-cycle analysis of soybean meal, distiller-dried grains with solubles, and synthetic amino acid-based animal feeds for swine and poultry production

Swine and poultry meat production are two important sectors in the U.S. economy. They play an important role in environmental sustainability because they contribute to the greenhouse gas (GHG) emissions as the result of agricultural and production activities. To improve the sustain ability of swine and poultry meat production, it is important to understand the environmental effects and identify the key drivers of the production activities. In this work, we presented an environmental assessment of the production of swine (i.e., pork) and poultry (i.e., broiler chicken). We conducted a life-cycle analysis of formulating animal feeds using soybean meal, corn, distiller-dried grains with solubles (DDGS), and synthetic amino acids as candidate ingredients to produce swine and poultry. We evaluated GHG emissions, fossil fuel consumption, and water consumption from formulating and utilizing a variety of animal feeds based on these ingredients for swine and poultry production, using an expanded version of the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET (R)) model. With pork and broiler chicken as the finished products, the functional unit was defined as one kg of live-weight animal at the farm gate. Feed production was the major contributor to the life-cycle GHG emissions (88 % and 91 % of the total GHG emissions for swine and poultry production, respectively) and fossil fuel consumption (79 % and 84 % of the total fossil fuel consumption for swine and poultry process, respectively). Among the four ingredient types, amino acids had the biggest GHG emission footprint; however, DDGS had the largest effect on increasing GHG emissions of swine and poultry production.

animal feed production↗

Paw-Net: Stacking ensemble deep learning for segmenting scanning electron microscopy images of fine-grained shale samples

Segmentation of scanning electron microscopy (SEM) images is critical yet time-consuming for geological analyses, as it needs to differentiate the boundaries for different mineral objects to facilitate subsequent analyses, such as porosity calculation. Recently, various machine learning methods, especially convolutional neural networks (CNNs), have been explored to segment SEM images of fine-grained shale samples. However, we found that general CNNs do not yield optimal performance due to insufficient training data and imbalanced objects in SEM images. This work has revised the U-Net architecture, a popular approach for biomedical image analyses, by incorporating a loss function that addresses the imbalance issue. Furthermore, we used the ensemble learning method to train multiple models and combined the results to improve the overall performance of segmentation. We prepared 2162 sub-images from raw SEM images in our experiments and divided them into training, validation, and testing datasets. The overall results show that our method improves the average Intersection over Union (IOU) of mineral objects from 0.49 to 0.58, compared to the original U-Net model. Our method can clearly distinguish each object from others with boundaries, even in highly imbalanced images. Training our models takes less than three minutes using a single GPU, while manual labeling can take up to three hours for each image. Furthermore, the method helps geoscientists gain insights quickly and effectively by building neural network models from a small dataset of SEM images.

58 GEOSCIENCES↗

Polycarboxylate ester adsorption on cement grains: Influence of polydispersity

Although in academic and industrial practice polymers are typically described by their average molecular parameters, most often they display a polydispersity both in size and in properties. In this paper, we focus on the influence of polydispersity on the adsorption of polycarboxylate ester on cement grains and on its influence on the definition of a so-called affinity of the polymer to the surface. We first show that a constant fraction of a polydisperse polycarboxylate ester always adsorbs no matter the availability of adsorption sites. We moreover suggest from our measurements and from scaling laws from literature that the degree of polydispersity in the structure of polycarboxylate ester should affect adsorption at both low and intermediate dosages and hydrodynamic radii in solution. However, it shall not have a major influence on polymer layer thickness or saturation dosage.

36 MATERIALS SCIENCE↗

Dissolution of periodic arrays of grains: Upscaling of pore-scale simulations with fast reactions

Upscaling methods are frequently used to derive transport equations at the macroscopic scale from more fundamental equations formulated at the pore scale. These methods typically give a suitable structure for the macroscopic equations and can also provide explicit expressions for the constitutive parameters, such as permeability and dispersion coefficients. Introducing chemical reactions complicates upscaling in at least two important ways. First, the interplay between chemical reactions and transport processes introduces a new length scale, which can be much smaller than the convective or dispersive length scales. A small reactive length scale breaks one of the key assumptions in upscaling; that there is a significant separation in length between the pore-scale and macro-scale processes. The second complication is that if reactions take place at mineral surfaces (dissolution or precipitation) then the pore space itself is evolving in time. In this paper we suggest ways in which these difficulties can be approached, based on analysis of pore-scale simulation data. First, we noticed that the concentration field in successive unit cells has an almost identical spatial variation, with a single scaling factor for each unit cell that is proportional to the incoming reactant flux. Using pore-scale simulations to determine the mass transfer coefficient in a few unit cells, we can calculate the concentration field in the whole domain, even when dissolution is entirely transport limited. Second, we have noticed a time-dependent mapping of the grain shapes from different unit cells. From these observations, we can deduce constitutive relations where the only time-varying parameter is the porosity. Here, we show that a model based on these ideas can quantitatively account for the pore-scale simulation data.

58 GEOSCIENCES↗

DECA: Discrete Event inspired Cellular Automata for grain structure prediction in additive manufacturing

Microstructure largely dictates macroscopic material properties and is strongly affected by processing. Therefore, the simulation of microstructure evolution in response to thermal fields during processing is of significant interest within the computational materials science community. Additive manufacturing (AM) has emerged as a technique for producing complex geometries and unique microstructures. Yet, complex and rapid thermal cycles in AM pose computational challenges for existing microstructure models. This work proposes a discrete event inspired cellular automata (CA) approach, titled DECA, to accelerate simulation of grain structure evolution in AM. In contrast to conventional time-stepped CA models, this model directly solves the times capture events would take place allowing for stepping in events rather than time (a technique also found in the field of discrete-event simulation). In comparison to purely serial discrete-event models, DECA allows for temporary violation of the causality constraint, but detects and corrects these violations, leading to an emergent phenomenon dubbed causality rippling, in which previously calculated capture events are overwritten. The amount of repeated calculations, defined by the capture ratio, is taken as a measure of computational inefficiency, and the model parameters that affect this ratio are evaluated. The new DECA approach was found to be more computationally efficient than conventional time-stepped CA models while guaranteeing an accurate solution, which can only be achieved in the conventional models for vanishingly small time steps. Finally, opportunities for parallelization and scaling of the new approach are discussed.

36 MATERIALS SCIENCE↗

Dolomites in hydrated fine-grained Antarctic micrometeorites: Effective tools for analyzing secondary processes

We report detailed transmission electron microscope (TEM) observations of carbonates from one hydrated fine-grained Antarctic micrometeorite (H-FgMM). These carbonates show the occurrence of complex chemical variations and microstructures that provide important evidence regarding the formation and evolution of rarely analyzed H-FgMMs. The chemical variations were identified at both micrometer and nanometer scales, indicating that these carbonates formed under localized fluid conditions that suggest a variable chemical microenvironment. Individual carbonates grew from isolated reservoirs of fluid. Moreover, these carbonates contain manganese amounts almost twice as high as those measured in CM chondrites but similar to those identified in CI chondrites. Their particular compositions indicate reducing and progressively evolving conditions in the fluid from which these carbonates precipitated, probably due to water consumption during phyllosilicates formation. In addition to the compositional variability, microstructural features are pervasive in these carbonates, similar to those described in heavily shocked meteorites indicating that these carbonates were probably modified during shock processes after their formation. Since carbonates are highly susceptible to shock metamorphism, we suggest that it is essential to investigate their structure in detail before interpreting the isotopic measurements related to the time of their formation. Additionally, associated with carbonates, ubiquitous phosphates were identified in the micrometeorite analyzed. Future studies of these mineral associations will provide us further insight into the formation and evolution of asteroids, especially since they were both identified in the surface materials of Ryugu and Bennu.

58 GEOSCIENCES↗

Grain reorientation and stress-state evolution during cyclic loading of an α -Ti alloy below the elastic limit

Here, high-energy synchrotron x-rays are used to track grain-averaged lattice reorientation and stress-state evolution in Ti–7Al as it is cyclically loaded to 90% of its macroscopic yield stress. This evolution provides clear indication of accumulating plastic strain even though the sample never exceeded the elastic limit. The largest changes in lattice orientation and stress state are observed following the first cycle then evolution continues at a lower rate with subsequent cycles. Variation of the axes about which lattice reorientation occurs is found to be highly dependent on the maximum resolved shear stress and corresponding activation of various families of slip systems.

36 MATERIALS SCIENCE↗

A coarse-grained model of clay colloidal aggregation and consolidation with explicit representation of the electrical double layer

The aggregation of clay minerals in liquid water exemplifies colloidal self-assembly in nature. These negatively charged aluminosilicate platelets interact through multiple mechanisms with different sensitivities to particle shape, surface charge, aqueous chemistry, and interparticle distance and exhibit complex aggregation structures. Experiments have difficulty resolving the associated colloidal assemblages at the scale of individual particles. Conversely, all-atom molecular dynamics (MD) simulations provide detailed insight on clay colloidal interaction mechanisms, but they are limited to systems containing a few particles. We develop a new coarse-grained (CG) model capable of representing assemblages of hundreds of clay particles with accuracy approaching that of MD simulations, at a fraction of the computational cost. Our CG model is parameterized based on MD simulations of a pair of smectite clay particles in liquid water. A distinctive feature of our model is that it explicitly represents the electrical double layer (EDL), i.e., the cloud of charge-compensating cations that surrounds the clay particles. Our model captures the simultaneous importance of long-range colloidal interactions (i.e., interactions consistent with simplified analytical models, already included in extant clay CG models) and short-range interactions such as ion correlation and surface and ion hydration effects. The resulting simulations correctly predict, at low solid-water ratios, the existence of ordered arrangements of parallel particles separated by water films with a thickness up to ~10 nm and, at high solid-water ratios, the coexistence of crystalline and osmotic swelling states, in agreement with experimental observations.

54 ENVIRONMENTAL SCIENCES↗

Investigation of nonlinear mechanical behavior of two superfine-grained graphites with DIC assisted disc splitting test

Using standardized uniaxial tensile test specimens is not practical due to the limited volumes in irradiation capsules, molten salt degradation facilities, or oxidation apparatus. The ASTM International Standard Test Method for Tensile Strength Estimate by Disc Compression of Manufactured Graphite (ASTM D8289) was developed to provide a convenient way for estimating tensile strength. Unlike the traditional uniaxial tensile test in ASTM C749 (International Standard Test Method for Tensile Stress–Strain of Carbon and Graphite), which uses dog-bone shaped specimens larger than 12.95 mm × 120.65 mm, the ASTM D8289 standard uses smaller discs with diameters of 6–12.7 mm. A digital image correlation (DIC) system, which uses a full-field noncontact surface displacement measurement technique, was applied along with the ASTM D8289 disc splitting test on IG-110 samples and compared with previous measurements from Mersen 2114 samples. Results confirmed that the DIC technique can measure the surface displacement/strain on these small (Ø6 mm × 3 mm) graphite specimens with good repeatability. However, Mersen 2114 and IG-110 samples exhibited strain discrepancies when DIC measurements were compared with analytical and finite element simulation values. The loading history and strain results also indicated different mechanical behaviors between Mersen 2114 and IG-110, particularly the nonlinear behavior of the IG-110 samples. Good agreement was observed by comparing the splitting tensile strengths of two superfine-grained grades with results from other work. The specimen size effect is discussed when comparing the splitting tensile strength with corresponding uniaxial tensile strength of these two graphite grades.

Lin, Lianshan [ORNL] (ORCID:0000000203399219)↗

Effect of subfreezing testing temperature on tensile mechanical behavior of fine-grained magnesium

Here, the effect of testing temperature on mechanical properties and deformation mechanisms was investigated by tensile testing of fine-grained magnesium samples under a range of temperatures (i.e. room temperature 20°C, subfreezing temperatures 0°C, -30°C, and - 60°C) and microstructural observations of both untested and tested samples using electron backscatter diffraction. The results suggest that mechanical properties and deformation mechanisms were significantly affected by lowering testing temperature. Strength increased linearly and ductility decreased linearly with the decrease of testing temperature. Although twinning is generally known to be athermal, this experimental study shows that tensile twinning is the dominating deformation mechanism at room temperature, and that twinning is negligible and dislocation operation is the primary deformation mechanism at 0°C, -30°C, and -60°C

36 MATERIALS SCIENCE↗

Effects of applied stress and grain size on creep-rupture lifetime prediction for Haynes 282 alloy

A multiple-heat set of tensile and creep-rupture data generated from a single laboratory was used to establish and evaluate predictive equations for the average creep-limited lifetime of an aged wrought Haynes 282 alloy using two different time- and temperature-compensated parametric models (those of Larson and Miller and Wilshire et al.). The range of temperatures and stresses used to produce the creep-rupture data used in the analyses revealed that two distinct regimes, above and below the proportional limit, were necessary for more accurate predictions of creep lifetimes over the range of conditions studied. Furthermore, a 2x difference in grain size amongst the three heats revealed a breakdown in the relationship between ultimate tensile strength and creep-rupture time, thus impacting the predictive ability of the Wilshire model. Finally, lifetime predictions based on the formulations from the respective models were compared to other available Haynes 282 datasets and found to reasonably replicate the experimental trends established in other studies.

36 MATERIALS SCIENCE↗

Elucidating texture and grain morphology contributions to the micromechanical response of additively manufactured Inconel 625

Microstructural variation of additively manufactured (AM) metal components in comparison to wrought counterparts makes certification for critical applications a challenge. Microscale simulations leveraging modern computational tools may be used to supplement testing of AM microstructures, thus accelerating certification by reducing the number of experiments needed. However, as micromechanical response is closely tied to critical properties like fatigue-life and fracture, utilization of these simulations with macroscale experimental data alone is insufficient. One means to attain microscale experimental data is in situ diffraction data collected from synchrotron X-ray sources. In this work, such data were collected during in situ compression of AM Inconel 625 superalloy. Interpretation of experimental results was assisted by massive (8M element) complementary micromechanical simulations performed on sets of virtual microstructures generated using cellular automata. Together, micromechanical data from diffraction experiments and simulations were used to probe the effects of textured “track” microstructures generated during laser powder bed fusion and directional strength-to-stiffness on micromechanical response. Though fiber-averaged directional strength-to-stiffness ratios were expected to dominate given the high elastic anisotropy of the material, the combination of small variations in texture and specific grain configurations unique to AM microstructures lead to significant variability in micromechanical response after yield. The findings emphasize the importance of high-fidelity microstructural representation that captures key texture components and AM-specific morphology for property prediction of AM metals.

36 MATERIALS SCIENCE↗

Phase-field modeling of diffusion bonding in 316H stainless steel: Impact of processing conditions on grain morphology and bonding quality

A novel multi-phase, multi-component phase‐field model is presented to study the diffusion bonding of 316H stainless steel. Combined with targeted experimental investigations, this model simulates the bond-growth process and predicts the bonding quality. Unlike previous models, our approach captures the simultaneous evolution of voids and grain structures, while quantifying bonding quality using defined bonding ratio. A comprehensive analysis of bond process control is performed by changing temperature, pressure and surface roughness observing the resulting bond structure, which is consistent with experimental observations and analytical predictions. Temperature is determined to be the dominant factor, with the transition from a flat to a robust bond occurring between 1000 °C and 1050 °C. At the ideal bonding temperature of 1050 °C, a surface roughness exceeding 0.6 μm or an applied stress below 4 MPa results in poor bonding quality. Beyond this, higher pressures and smoother surfaces reduce void size, accelerate void shrinkage, and lead to improved bond integrity. This diffuse-interface model can be extended to other material systems if supplied with appropriate thermodynamic and kinetic data. In conclusion, this makes it an effective modeling platform for optimizing high-temperature diffusion bonding and developing reliable bonded components such as compact heat exchangers.

Diffusion bonding↗

Ultrafine-grained Al-Mg-Zr Alloy Processed by Shear-Assisted Extrusion with High Thermal Stability

Shear-assisted processing and extrusion (ShAPE) is used to consolidate Al-4.2Mg-1.6Zr-0.25Si-0.1Fe (wt.%) powders. The extruded alloy exhibits: (i) near-zero porosity; (ii) an attractive combination of tensile yield strength (~220 MPa), ultimate strength (330 MPa) and elongation (>20%); and (iii) excellent thermal stability at 400 ºC. The ultra-fine grain size in the gas-atomized powders – created and stabilized by primary L12-Al3Zr submicron precipitates - is maintained after consolidation and subsequent exposure at 400 ºC, contributing twice as much to strength as Mg in solid-solution. Electron microscopy reveals the microstructure of the L12-Al3Zr precipitates, and other precipitates (Mg2Si and Al3Fe) and dispersoids (oxides).

ShAPE, Friction Extrusion, aluminum powder, Shear ↗

Response to the comments on creep-induced elemental redistribution at grain boundaries of 304L stainless steel – An experimental evidence for diffusional creep mechanisms

Sandström and He reanalyzed our 304L creep data (Acta Materialia 121137, 2025) at 10 MPa/750 °C and proposed that: (i) primary dislocation creep dominates based on the ϕ -model; (ii) measured creep rates deviate from published 304H data and Coble creep predictions using literature grain boundary (GB) diffusivity; and (iii) creep-induced elemental redistribution (CIER) could be explained by dislocation emission/absorption (DEAA) and GB creep (GBC), as opposed to diffusional creep. Here, in this response, we propose that: (i) the creep behavior at 15 MPa/750 °C—for which we demonstrated CIER—is only partially captured by the ϕ -model; (ii) direct comparison between 304L and 304H creep data is inappropriate due to carbides in 304H, and Coble creep predictions estimated from CALPHAD-based bulk diffusivity span experimental rates; and (iii) CIER exhibits distinct fingerprint for diffusional creep characterized by anisotropy and stress orientation dependence whereas neither DEAA nor GBC have been mechanistically substantiated.

36 - MATERIALS SCIENCE↗

Enhancing Chemical Stability and Suppressing Ion Migration in CH 3 NH 3 PbI 3 Perovskite Solar Cells via Direct Backbone Attachment of Polyesters on Grain Boundaries

Organic–inorganic halide perovskites feature excellent optoelectronic properties but poor chemical stability. While passivating perovskite grain boundary (GB) by polymers shows prospects on long-term performance of perovskite solar cells (PSCs), its detailed impact on the ion migration phenomenon, which largely deteriorates the PSC stability, remains less probed. In this work, we introduce a new polar polymer, polycaprolactone (PCL), to passivate GBs of methylammonium lead triiodide (MAPbI 3 ) perovskite with only 1–2 polymer monolayers via direct backbone attachment. The PSCs with passivated MAPbI 3 , using a classic but less stable Spiro-OMeTAD (2,2',7,7'-tetrakis[N,N-di(4-methoxyphenyl)amino]-9,9'-spirobifluorene) hole transport layer (HTL), exhibit improved power conversion efficiencies up to 20.1%, with 90% of the initial PCE being preserved after 400 h ambient storage, and 80% even after 100 h, 85 °C aging. The improved PSC stability indicates critical roles of PCL GB passivation in retarding moisture-induced decomposition and suppressing ion migration within the perovskite. Furthermore, time-of-flight secondary ion mass spectrometry reveals that I– ions can actively migrate into the electrode, HTL, and their interface in nonpassivated PSCs, even without an externally applied electric field, while such migration is significantly mitigated in PCL-passivated PSCs. This effective GB passivation by PCL suggests an important potential of polymer additives toward the development of stable high-performance PSCs.

36 MATERIALS SCIENCE↗

Learning Coarse-Grained Potentials for Binary Fluids

Even though atomistic and CG models have been used to simulate liquid nanodroplets in vapor, very few rigorous studies of the liquid-liquid interface structure are available, and most of them are limited to planar interfaces. In this work, we evaluate several existing force fields (FF)s, including two atomistic and three CG FFs, with respect to modeling the interface structure and thermodynamic properties of the water-hexane interface. Both atomistic FFs are able to quantitatively reproduce the interfacial tension and the coexisting densities of the experimentally-observed planar interface. We use the atomistic FFs to model water droplets in hexane and use these simulations to test the CG FFs. We found that the tested CG FFs cannot reproduce the interfacial tensions of planar and/or curved interfaces. Finally, we propose a new approach for learning coarse-grained (CG) potentials within the CG SDK (Shinoda-DeVane- Klein) FF framework from atomistic simulation data. We demonstrate that the new potential significantly improves the prediction of both the interfacial tension and structure of water-hexane planar and curved interfaces.

Gao, Peiyuan↗