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At least 1,009 records · Page 56

Bifunctional nanoprecipitates strengthen and ductilize a medium-entropy alloy

Single-phase high- and medium-entropy alloys with face-centred cubic (fcc) structure can exhibit high tensile ductility and excellent toughness, but their room-temperature strengths are low. Dislocation obstacles such as grain boundaries, twin boundaries, solute atoms and precipitates can increase strength. However, with few exceptions, such obstacles tend to decrease ductility. Interestingly, precipitates can also hinder phase transformations. Here, using a model, precipitate-strengthened, Fe–Ni–Al–Ti medium-entropy alloy, we demonstrate a strategy that combines these dual functions in a single alloy. The nanoprecipitates in our alloy, in addition to providing conventional strengthening of the matrix, also modulate its transformation from fcc-austenite to body-centred cubic (bcc) martensite, constraining it to remain as metastable fcc after quenching through the transformation temperature. During subsequent tensile testing, the matrix progressively transforms to bcc-martensite, enabling substantial increases in strength, work hardening and ductility. This use of nanoprecipitates exploits synergies between precipitation strengthening and transformation-induced plasticity, resulting in simultaneous enhancement of tensile strength and uniform elongation. Further, our findings demonstrate how synergistic deformation mechanisms can be deliberately activated, exactly when needed, by altering precipitate characteristics (such as size, spacing, and so on), along with the chemical driving force for phase transformation, to optimize strength and ductility.

36 MATERIALS SCIENCE↗

X-ray linear dichroic tomography of crystallographic and topological defects

Abstract The functionality of materials is determined by their composition 1–4 and microstructure, that is, the distribution and orientation of crystalline grains, grain boundaries and the defects within them 5,6 . Until now, characterization techniques that map the distribution of grains, their orientation and the presence of defects have been limited to surface investigations, to spatial resolutions of a few hundred nanometres or to systems of thickness around 100 nm, thus requiring destructive sample preparation for measurements and preventing the study of system-representative volumes or the investigation of materials under operational conditions 7–15 . Here we present X-ray linear dichroic orientation tomography (XL-DOT), a quantitative, non-invasive technique that allows for an intragranular and intergranular characterization of extended polycrystalline and non-crystalline 16 materials in three dimensions. We present the detailed characterization of a polycrystalline sample of vanadium pentoxide (V 2 O 5 ), a key catalyst in the production of sulfuric acid 17 . We determine the nanoscale composition, microstructure and crystal orientation throughout the polycrystalline sample with 73 nm spatial resolution. We identify and characterize grains, as well as twist, tilt and twin grain boundaries. We further observe the creation and annihilation of topological defects promoted by the presence of volume crystallographic defects. The non-destructive and spectroscopic nature of our method opens the door to operando combined chemical and microstructural investigations 11,18 of functional materials, including energy, mechanical and quantum materials.

Science & Technology - Other Topics↗

Interfacial stabilization for epitaxial CuCrO 2 delafossites

AB O 2 delafossites are fascinating materials that exhibit a wide range of physical properties, including giant Rashba spin splitting and anomalous Hall effects, because of their characteristic layered structures composed of noble metal A and strongly correlated B O 2 sublayers. However, thin film synthesis is known to be extremely challenging owing to their low symmetry rhombohedral structures, which limit the selection of substrates for thin film epitaxy. Hexagonal lattices, such as those provided by Al 2 O 3 (0001) and (111) oriented cubic perovskites, are promising candidates for epitaxy of delafossites. However, the formation of twin domains and impurity phases is hard to suppress, and the nucleation and growth mechanisms thereon have not been studied for the growth of epitaxial delafossites. In this study, we report the epitaxial stabilization of a new interfacial phase formed during pulsed-laser epitaxy of (0001)-oriented CuCrO 2 epitaxial thin films on Al 2 O 3 substrates. Through a combined study using scanning transmission electron microscopy/electron-energy loss spectroscopy and density functional theory calculations, we report that the nucleation of a thermodynamically stable, atomically thick CuCr 1-x Al x O 2 interfacial layer is the critical element for the epitaxy of CuCrO 2 delafossites on Al 2 O 3 substrates. This finding provides key insights into the thermodynamic mechanism for the nucleation of intermixing-induced buffer layers that can be used for the growth of other noble-metal-based delafossites, which are known to be challenging due to the difficulty in initial nucleation.

36 MATERIALS SCIENCE↗

Developing of nano sized fibrous eutectic silicon in hypereutectic Al–Si alloy by laser remelting

Laser surface melting followed by rapid solidification is an effective means to produce very fine microstructures with desirable surface properties because of the high rates of cooling associated with it. In the present study, the effect of rapid cooling on the silicon particle size, distribution, and morphology of hypereutectic Al–17wt.%Si and Al–20wt.%Si alloys have been investigated. A continuous-wave CO2 laser of wavelength 10.6 μm and a Trumpf Yb-YAG disk laser of wavelength 1.030 μm were used with a beam diameter of 1 mm and scanning speeds ranging from 5 to 100 mm/s. Rapid solidification increased the solubility of silicon in aluminum to approximately 5wt% and induced non-equilibrium hypoeutectic microstructures comprising large volume fractions of primary α-Al dendrites and ultrafine Al–Si eutectic of lamellar morphology. Both α-Al dendrites and the silicon particle sizes were significantly reduced from micron to nanoscale level. The morphology of silicon particles is modified from massive polygonal and plate-like to a mixture of fine fakes with round corners, feathery and fibrous, or a coral-like and thread-like structure. The eutectic silicon size and the interlamellar spacing were reduced to 30 and 10 nm, respectively. Furthermore, most of the silicon crystals in the eutectic region and the aluminum dendrites contained a significant number of twins which were considered as an essential contributor to the mechanism of growth and branching. Microhardness values increased two to threefold due to the refinement of the microstructural constituent.

42 ENGINEERING↗

Tensile deformation behavior of twist grain boundaries in CoCrFeMnNi high entropy alloy bicrystals

High entropy alloys (HEA) are a class of materials that consist of multiple elemental species in similar concentrations. The use of elements in far from dilute concentrations introduces a multi-dimensional composition design space by which the properties of metallic systems can be tailored. While the mechanical behavior of HEAs has been the subject of active research recently, the role of grain boundaries (GBs) in their deformation behavior remains poorly understood. Motivated by recent experiments on HEAs demonstrating that GBs act as nucleation sites for deformation twins, herein, we leverage atomistic simulations to construct a series of equiatomic CoCrFeMnNi HEA bicrystals with $\langle 110 \rangle$ and $\langle 111 \rangle$ symmetric twist GBs and examine their tensile behavior and underlying deformation mechanisms at 77 K. Simulation results reveal that plastic deformation proceeds by the nucleation of partial dislocations from GBs, which then grow with further loading by bowing into the bulk crystals leaving behind stacking faults. Variations in the nucleation stress exist as function of GB character, defined in this work by the twist angle. Our results provide future avenues to explore GBs as a microstructure design tool to develop HEAs with tailored properties.

36 MATERIALS SCIENCE↗

Correlating work hardening with co-activation of stacking fault strengthening and transformation in a high entropy alloy using in-situ neutron diffraction

Transformation induced plasticity (TRIP) leads to enhancements in ductility in low stacking fault energy (SFE) alloys, however to achieve an unconventional increase in strength simultaneously, there must be barriers to dislocation motion. While stacking faults (SFs) contribute to strengthening by impeding dislocation motion, the contribution of SF strengthening to work hardening during deformation is not well understood; as compared to dislocation slip, twinning induced plasticity (TWIP) and TRIP. Thus, we used in-situ neutron diffraction to correlate SF strengthening to work hardening behavior in a low SFE Fe 40 Mn 20 Cr 15 Co 20 Si 5 (at%) high entropy alloy, SFE ~ 6.31 mJ m –2 . Cooperative activation of multiple mechanisms was indicated by increases in SF strengthening and γ-f.c.c. → ε-h.c.p. transformation leading to a simultaneous increase in strength and ductility. The present study demonstrates the application of in-situ, neutron or X-ray, diffraction techniques to correlating SF strengthening to work hardening.

36 MATERIALS SCIENCE↗

Excellent ballistic impact resistance of Al 0.3 CoCrFeNi multi-principal element alloy with unique bimodal microstructure

Multi-principal element alloys represent a new paradigm in structural alloy design with superior mechanical properties and promising ballistic performance. Here, the mechanical response of Al 0.3 CoCrFeNi alloy, with unique bimodal microstructure, was evaluated at quasistatic, dynamic, and ballistic strain rates. The microstructure after quasistatic deformation was dominated by highly deformed grains. High density of deformation bands was observed at dynamic strain rates but there was no indication of adiabatic shear bands, cracks, or twinning. The ballistic response was evaluated by impacting a 12 mm thick plate with 6.35 mm WC projectiles at velocities ranging from 1066 to 1465 m/s. The deformed microstructure after ballistic impact was dominated by adiabatic shear bands, shear band induced cracks, microbands, and dynamic recrystallization. The superior ballistic response of this alloy compared with similar Al x CoCrFeNi alloys was attributed to its bimodal microstructure, nano-scale L1 2 precipitation, and grain boundary B2 precipitates. Deformation mechanisms at quasistatic and dynamic strain rates were primarily characterized by extensive dislocation slip and low density of stacking faults. Deformation mechanisms at ballistic strain rates were characterized by grain rotation, disordering of the L1 2 phase, and high density of stacking faults.

36 MATERIALS SCIENCE↗

Co-introduction of precipitate hardening and TRIP in a TWIP high-entropy alloy using friction stir alloying

Tuning deformation mechanisms is imperative to overcome the well-known strength-ductility paradigm. Twinning-induced plasticity (TWIP), transformation-induced plasticity (TRIP) and precipitate hardening have been investigated separately and have been altered to achieve exceptional strength or ductility in several alloy systems. In this study, we use a novel solid-state alloying method—friction stir alloying (FSA)—to tune the microstructure, and a composition of a TWIP high-entropy alloy by adding Ti, and thus activating site-specific deformation mechanisms that occur concomitantly in a single alloy. During the FSA process, grains of the as-cast face-centered cubic matrix were refined by high-temperature severe plastic deformation and, subsequently, a new alloy composition was obtained by dissolving Ti into the matrix. After annealing the FSA specimen at 900 °C, hard Ni–Ti rich precipitates formed to strengthen the alloy. An additional result was a Ni-depleted region in the vicinity of newly-formed precipitates. The reduction in Ni locally reduced the stacking fault energy, thus inducing TRIP-based deformation while the remaining matrix still deformed as a result of TWIP. Our current approach presents a novel microstructural architecture to design alloys, an approach that combines and optimizes local compositions such that multiple deformation mechanisms can be activated to enhance engineering properties.

36 MATERIALS SCIENCE↗

Fingerprinting shock-induced deformations via diffraction

Abstract During the various stages of shock loading, many transient modes of deformation can activate and deactivate to affect the final state of a material. In order to fundamentally understand and optimize a shock response, researchers seek the ability to probe these modes in real-time and measure the microstructural evolutions with nanoscale resolution. Neither post-mortem analysis on recovered samples nor continuum-based methods during shock testing meet both requirements. High-speed diffraction offers a solution, but the interpretation of diffractograms suffers numerous debates and uncertainties. By atomistically simulating the shock, X-ray diffraction, and electron diffraction of three representative BCC and FCC metallic systems, we systematically isolated the characteristic fingerprints of salient deformation modes, such as dislocation slip (stacking faults), deformation twinning, and phase transformation as observed in experimental diffractograms. This study demonstrates how to use simulated diffractograms to connect the contributions from concurrent deformation modes to the evolutions of both 1D line profiles and 2D patterns for diffractograms from single crystals. Harnessing these fingerprints alongside information on local pressures and plasticity contributions facilitate the interpretation of shock experiments with cutting-edge resolution in both space and time.

36 MATERIALS SCIENCE↗

Tailoring plasticity mechanisms in compositionally graded hierarchical steels fabricated using additive manufacturing

Abstract While there exists in nature abundant examples of materials with site-specific gradients in microstructures and properties, engineers and designers have traditionally used monolithic materials with discrete properties. Now, however, additive manufacturing (AM) offers the possibility of creating structures that mimic some aspects of nature. One example that has attracted attention in the recent years is the hierarchical structure in bamboo. The hierarchical architecture in bamboo is characterized by spatial gradients in properties and microstructures and is well suited to accommodate and survive complex stress states, severe mechanical forces, and large deformations. While AM has been used routinely to fabricate functionally graded materials, this study distinguishes itself by leveraging AM and physical metallurgy concepts to trigger cascading deformation in a single sample. Specifically, we have been successful in using AM to fabricate steel with unique spatial hierarchies in structure and property to emulate the structure and deformation mechanisms in natural materials. This study shows an improvement in the strength and ductility of the nature-inspired “hierarchical steel” compared with conventional cast stainless steels. In situ characterization proves that this improvement is due to the sequential activation of multiple deformation mechanisms namely twinning, transformation-induced plasticity, and dislocation-based plasticity. While significantly higher strengths can be achieved by refining the chemical and processing technique, this study sets the stage to achieve the paradigm of using AM to fabricate structures which emulate the flexibility in mechanical properties of natural materials and are able to adapt to in-service conditions.

36 MATERIALS SCIENCE↗

Multi-fidelity information fusion with concatenated neural networks

Recently, computational modeling has shifted towards the use of statistical inference, deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many applications like design optimization and real-time control by lowering the computational burden, training deep learning models needs a huge amount of data. This big data is not always available for scientific problems and leads to poorly generalizable data-driven models. This gap can be furnished by leveraging information from physics-based models. Exploiting prior knowledge about the problem at hand, this study puts forth a physics-guided machine learning (PGML) approach to build more tailored, effective, and efficient surrogate models. For our analysis, without losing its generalizability and modularity, we focus on the development of predictive models for laminar and turbulent boundary layer flows. In particular, we combine the self-similarity solution and power-law velocity profile (low-fidelity models) with the noisy data obtained either from experiments or computational fluid dynamics simulations (high-fidelity models) through a concatenated neural network. We illustrate how the knowledge from these simplified models results in reducing uncertainties associated with deep learning models applied to boundary layer flow prediction problems. The proposed multi-fidelity information fusion framework produces physically consistent models that attempt to achieve better generalization than data-driven models obtained purely based on data. While we demonstrate our framework for a problem relevant to fluid mechanics, its workflow and principles can be adopted for many scientific problems where empirical, analytical, or simplified models are prevalent. In line with grand demands in novel PGML principles, this work builds a bridge between extensive physics-based theories and data-driven modeling paradigms and paves the way for using hybrid physics and machine learning modeling approaches for next-generation digital twin technologies.

42 ENGINEERING↗

Texture evolution during processing and post-processing of maraging steel fabricated by laser powder bed fusion

Abstract In this study, the evolution of solidification texture during LPBF of Ti-free grade 300 maraging steel, and its effect on texture development during subsequent post-fabrication heat treatments was characterized using Electron Backscatter Diffraction (EBSD). It was found that in the as-fabricated state, no texture was observed in the room temperature martensitic phase. However, the reconstructed parent austenite phase displayed a Cube texture with a minor fraction of Rotated Goss texture. During subsequent aging treatments involving two different routes, namely direct aging of the as-fabricated samples, and conventional solution treatment + aging of the as-fabricated samples, significant changes in the texture components of parent austenite were observed, whereas no changes in texture were observed in the room temperature martensitic phase. During direct aging, it was found that with an increase in the aging temperature up to 520 °C, the texture components of the parent austenite changed from Cube/Rotated Goss to Brass, whereas during the conventional solution treatment and aging cycle, interestingly a change in texture component to rotated copper was observed. The transitions in texture components have been discussed using the concepts of recrystallization and twinning in austenite during annealing and/or aging, and strain energy release maximization (SERM) theory. Furthermore, the importance of these preferred orientations on the mechanical properties was quantified using transformation potential diagrams.

36 MATERIALS SCIENCE↗

Progressive transfer learning for advancing machine learning-based reduced-order modeling

Abstract To maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for reduced-order modeling (p-ROM) framework is proposed. A key concept of p-ROM is to selectively transfer knowledge from previously trained ML models and effectively develop a new ML model(s) for unseen tasks by optimizing information gates in hidden layers. The p-ROM framework is designed to work with any type of data-driven ROMs. For demonstration purposes, we evaluate the p-ROM with specific Barlow Twins ROMs (p-BT-ROMs) to highlight how progress learning can apply to multiple topological and physical problems with an emphasis on a small training set regime. The proposed p-BT-ROM framework has been tested using multiple examples, including transport, flow, and solid mechanics, to illustrate the importance of progressive knowledge transfer and its impact on model accuracy with reduced training samples. In both similar and different topologies, p-BT-ROM achieves improved model accuracy with much less training data. For instance, p-BT-ROM with four-parent (i.e., pre-trained models) outperforms the no-parent counterpart trained on data nine times larger. The p-ROM framework is poised to significantly enhance the capabilities of ML-based ROM approaches for scientific and engineering applications by mitigating data scarcity through progressively transferring knowledge.

97 MATHEMATICS AND COMPUTING↗

Mixed polytype/polymorph formation in InSe films grown by molecular beam epitaxy on GaAs(111)B

Abstract We report the growth of InSe films on semi-insulating GaAs(111)B substrates by molecular beam epitaxy (MBE). Excellent nucleation behavior resulted in the growth of smooth, single-phase InSe films. The dominant polytype was the targeted γ-InSe. Transmission electron microscopy revealed the presence of three bulk polytypes β, γ, and ε-InSe arranged in nanosized domains, which can be interpreted as sequences of stacking faults and rotational twin boundaries of γ-InSe. Additionally, a centrosymmetric Se-In-In-Se layer polymorph with $P\bar{3}m$ symmetry was identified as typically not present in bulk. Sizeable differences in their electronic properties were found, which resulted in sizeable electronic disorder arising from the nanoscale polytype arrangement that dominated the electronic transport properties. While MBE is a viable synthesis route towards stabilization of InSe polytypes not present in the bulk, an improved understanding to form the targeted polymorph is required to ultimately inscribe a layer sequence on demand utilizing bottom-up synthesis approaches.

ferroelectrics and multiferroics↗

Patchy nuclear chain reactions

Stochastic fluctuations of the neutron population within a nuclear reactor are typically prevented by operating the core at a sufficient power, since a deterministic (i.e., exactly predictable) behavior of the neutron population is required by automatic safety systems to detect unwanted power excursions. In order to characterize the reactor operating conditions at which the fluctuations vanish, an experiment was designed and took place in 2017 at the Rensselaer Polytechnic Institute Reactor Critical Facility. This experiment however revealed persisting fluctuations and striking patchy spatial patterns in neutron spatial distributions. Here we report these experimental findings, interpret them by a stochastic modeling based on branching random walks, and extend them using a “numerical twin” of the reactor core. Consequences on nuclear safety will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dark-field X-ray microscopy with structured illumination for three-dimensional imaging

Dark-field X-ray microscopy is a lens-based technique that enables real-space imaging of heterogeneous micro- and meso-scale ordered materials. However, achieving accurate three-dimensional (3D) reconstruction often requires meticulous sample alignment or rastering, requiring complex rotational setups and extended acquisition times. To address these challenges, we introduce a structured illumination technique optimized for 3D imaging of ordered materials at sub-micrometer length scales. Our approach employs a coded aperture to spatially modulate the incident X-ray beam, enabling 3D structural reconstruction from images captured at various aperture positions. Unlike current 3D imaging approaches, which often rely on rotational or rastering methods, our technique uses scanning X-ray silhouettes of the coded aperture for depth resolution along the diffraction axis. This eliminates the need for sample rotation or rastering, resulting in a highly stable and efficient imaging modality. We validated the efficacy of this approach through experimental imaging of an isolated twin domain within a bulk single crystal of an iron pnictide using a dark-field X-ray microscope. This advancement aligns with the enhanced brightness upgrades of modern synchrotron radiation facilities, unlocking new possibilities for high-resolution imaging of ordered materials.

47 OTHER INSTRUMENTATION↗

Natural deep eutectic solvent mediated extrusion for continuous high-solid pretreatment of lignocellulosic biomass

Several deep eutectic solvents (DESs) have been demonstrated to be highly effective for lignocellulosic biomass pretreatment, combining the advantages of simple synthesis, relatively low chemical cost and better biocompatibility. However, low biomass loading that is usually involved with DES pretreatment hinders its practical use. Here, a twin-screw extruder was used for pretreating biomass sorghum bagasse at solid loadings up to 50%, mediated by a neutral-pH DES, choline chloride : glycerol (ChCl : Gly). This continuous extrusion process led to high glucose and xylose yields of >85% from enzymatic saccharification of the pretreated sorghum. A combination of microscopic, spectroscopic, and X-ray diffraction analyses demonstrate a high degree of defibration and disruption of the biomass cell wall structures; however, little or no change in chemical compositions. Further results from gel permeation chromatographic (GPC) and nuclear magnetic resonance (NMR) spectroscopic analyses indicate that ChCl : Gly-mediated extrusion preserved the basic lignin structural characteristics with no significant differences between extruded biomass at a solid loading of 30% and 50%. This study demonstrates the potential of DES-mediated extrusion as a highly effective continuous high-solid biomass pretreatment technology for industrially relevant applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of super-strong and thermally stable nanotwinned Al alloys via solute synergy

Al alloys have widespread industrial applications. However, their mechanical strength is often much lower than steels. Here, we investigate the influence of solutes on achieving ultrahigh strength and thermal stability of nanotwinned Al alloys. In situ micropillar compression tests show the addition of a small amount of Ti can significantly increase the mechanical strength of Al–Ni alloys to 2 GPa. Deformation induced detwinning, Ni segregation and grain coarsening as discovered in binary Al–Ni alloys are mostly absent in the ternary Al–Ni–Ti alloys. Moreover, the ternary Al–Ni–Ti alloys have outstanding thermal stability. Density function theory calculations reveal the synergetic pinning effect of Ni–Ti solute pairs on incoherent twin boundaries. This study demonstrates that the proper selection of synergistic solute pairs is critical to improve the thermal stability and mechanical properties of nanotwinned Al alloys.

36 MATERIALS SCIENCE↗