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Critical to the growth of digital manufacturing is the development of rapid yet accurate quality control technologies to assess the microstructure of each metal part produced. Typical surface analysis methods are limited in measurement throughput and impose constraints on maximum area size and surface quality, which enforce the tedious practice of extracting and preparing flat, small-scale samples for microstructure analysis. Here, we propose a new approach based on directional reflectance microscopy (DRM) which can yield part-scale microstructure information nondestructively and on curved, complex surfaces. We demonstrate our approach on the airfoil of a turbine blade and carry out a rigorous error analysis using other samples with variable surface geometry. Our results highlight the potential for part-specific quality control in the context of digital manufacturing. [ABSTRACT FROM AUTHOR]

Energy absorption by matter is fundamental to natural and man-made processes. However, despite this ubiquity, developing materials capable of withstanding severe energy fluxes without degradation is a significant challenge in materials science and engineering. Despite recent advances in creating alloys resistant to energy fluxes, mitigating the damage caused by the absorption and transfer of mechanical energy remains a critical obstacle in both fundamental science and technological applications. This challenge is especially prominent when the mechanical energy is transferred to the material by shock loading. This study demonstrates a phenomenon in which microstructurally stabilized nanocrystalline Cu-Ta alloys can undergo reversal or nearly complete recovery of the dislocation structure after multiple shock-loading impacts, unlike any other known metallic material. The microstructure of these alloys can withstand repeated shock-wave interactions at pressures up to 12 GPa without any significant microstructural damage or deterioration, demonstrating an extraordinary capacity to be virtually immune to the detrimental effects of shock loading. This study reveals that under 12 GPa shock loading, stabilized nanocrystalline Cu-3Ta can generate and reabsorb dislocations, enabling near-complete recovery without microstructural deterioration. This behavior contrasts with other known metals. [ABSTRACT FROM AUTHOR]

While large language models learn sound statistical representations of the language and information therein, ontologies are symbolic knowledge representations that can complement the former ideally. Research at this critical intersection relies on datasets that intertwine ontologies and text corpora to enable training and comprehensive benchmarking of neurosymbolic models. We present the MaterioMiner dataset and the linked materials mechanics ontology where ontological concepts from the mechanics of materials domain are associated with textual entities within the literature corpus. Another distinctive feature of the dataset is its eminently fine-grained annotation. Specifically, 179 distinct classes are manually annotated by three raters within four publications, amounting to 2191 entities that were annotated and curated. Conceptual work is presented for the symbolic representation of causal composition-process-microstructure-property relationships. We explore the annotation consistency between the three raters and perform fine-tuning of pre-trained language models to showcase the feasibility of training named entity recognition models. Reusing the dataset can foster training and benchmarking of materials language models, automated ontology construction, and knowledge graph generation from textual data. [ABSTRACT FROM AUTHOR]

High-energy irradiation significantly increases the optical losses and noise coefficients of laser materials, leading to a substantial decrease in the slope efficiency or gain performance of laser output. To address this issue, we propose a strategy to enhance the radiation resistance of glasses/fibers by introducing phase interfaces. Based on the sol–gel method, through phase-separation techniques and high-temperature annealing treatments, silica-rich and phosphorus-rich phases were formed in erbium-ytterbium co-doped high-phosphorus silica glass, and nanoscale phase interfaces with specific densities, stability levels, and homogeneous distributions of doped elements were constructed between the phases. Using high-resolution transmission electron microscopy, nuclear magnetic resonance, and spectroscopic analyses, we tracked the evolution of the internal microstructure of the glasses at the atomic level. The findings confirmed that annealing effectively controlled the density of the phase interfaces formed. Under 1 kGy X-ray irradiation, glasses with effective phase interfaces exhibited significant reduction in radiation-induced attenuation (RIA) and improvement in photoluminescence intensity compared to pristine glasses. This indicated that effective phase interfaces could act as complex centers for irradiation-induced point defects, absorbing radiant energy and trapping these defects, thus mitigating high-energy radiation-induced damages. Furthermore, online irradiation tests on the Er3+/Yb3+ co-doped silica fibers supported this result. Compared to pristine fiber, fibers annealed for 3 h and annealed for 20 h with different phase interfacial densities showed 45% and 73% lower RIA at 1080 nm, respectively. Highlights: Erbium-ytterbium co-doped high-phosphorus silica glasses/fibers were synthesized via a modified sol–gel method, incorporating nanoscale phase-interface structures. Annealing treatment was utilized to increase the density of phase interfaces in the glasses/fibers. Strengthening the phase interfaces resulted in reduced radiation-induced attenuation and improved radiation resistance of glasses/fibers. [ABSTRACT FROM AUTHOR]

Phase-field modeling offers a powerful tool for investigating the electrical control of the domain structure in ferroelectrics. However, its broad application is constrained by demanding computational requirements, limiting its utility in inverse design scenarios. Here, we introduce a machine-learning surrogate to accelerate 3D phase-field modeling of tip-induced electrical switching. By dynamically handling the boundary conditions, the surrogate achieves accurate reproduction of switching trajectories under various tip locations and applied voltages. With stable predictions throughout entire morphological evolution pathways and a relative error inferior to 10% compared to direct solvers, the model efficiently emulates intricate switching sequences. By successfully replicating the boundary conditions, the presented framework strides towards a holistic surrogate for the ferroelectric phase field. With up to 2500-fold speed-ups over classical methods, our approach opens the path for the tractable design of the domain structure and the resolution of realistic inverse problems. [ABSTRACT FROM AUTHOR]

Grain boundaries (GBs) profoundly influence the properties and performance of materials, emphasizing the importance of understanding the GB structure and phase behavior. As recent computational studies have demonstrated the existence of multiple GB phases associated with varying the atomic density at the interface, we introduce a validated, open-source GRand canonical Interface Predictor (GRIP) tool that automates high-throughput, grand canonical optimization of GB structures. While previous studies of GB phases have almost exclusively focused on cubic systems, we demonstrate the utility of GRIP in an application to hexagonal close-packed titanium. We perform a systematic high-throughput exploration of tilt GBs in titanium and discover previously unreported structures and phase transitions. In low-angle boundaries, we demonstrate a coupling between point defect absorption and the change in the GB dislocation network topology due to GB phase transformations, which has important implications for the accommodation of radiation-induced defects. Grain boundaries strongly influence the properties of crystalline materials, but identifying their multiple phases remains difficult. Here, authors show a new tool for automated grain boundary structure prediction with an application to Ti. [ABSTRACT FROM AUTHOR]

Interdiffusion-based macromolecular transport across glassy interfaces is reportedly achieved at high temperatures in accordance with the classical model of reptation. Here, for the first time, we report a new mechanistic pathway for achieving solid-state glassy joining by triggering rapid macromolecular acceleration through mechanical deformation. Large-scale molecular simulations reveal that active plastic deformation in glassy polymers, at temperatures well below the bulk (and surface) glass transition temperatures T g b (and T g s ), causes segmental translations of macromolecules leading to interfacial interpenetrations, and the formation of new entanglements. The mechanistic basis for this new type of bonding is identified as molecular-scale dilatations and densifications during deformation-induced mobility. The reported insights open promising avenues for achieving quick, strong, and energetically less-intensive joining of polymeric glasses across various sectors. [ABSTRACT FROM AUTHOR]

Unraveling the effects of continuous dislocation interactions with interfaces, particularly at the nanometer length scales, is key to a broader understanding of plasticity, to material design and to material certification. To this end, this work proposes a novel discrete dislocation dynamics-based model for dislocation interface interactions tracking the fate of residual dislocation on interfaces. This new approach is used to predict the impact of dislocation/interface reactions on the overall mechanical behavior of accumulative roll bonded nanometallic laminates. The framework considers the dynamic evolution of the interface concurrent with a large network of dislocations, thus, accounting for the local short and long range effects of the dislocations under the external boundary conditions. Specifically, this study focuses on two-phase Fe/Cu nanometallic laminates, and investigates the role of the underlying elastic and plastic contrast of the Fe and the Cu layers on the composite response of the material. Moreover, the role of initial microstructures, resulting from processing is also investigated. Subsequently, the model is used to examine the effect of layer thickness and interface orientation relationship on the residual stresses of the relaxed microstructure. The associated mechanical response of these laminates are compared when loaded under normal direction compression, as well as shear compression. Finally, this work predicts a dominant effect of the layer thickness, as compared to the interface orientation relationship, on the macroscopic response and on the residual stresses of these nanolaminates, while the local dislocation transmission propensity through the interface is significantly influenced by the corresponding orientation relationship. [ABSTRACT FROM AUTHOR]

Some low-coordination materials, including water, silica, and silicon, exhibit polyamorphism, having multiple amorphous forms. However, the microscopic mechanism and kinetic pathway of amorphous-amorphous transition (AAT) remain largely unknown. Here, we use a state-of-the-art machine-learning potential and local structural analysis to investigate the microscopic kinetics of AAT in silicon after a rapid pressure change. We find that the transition from low-density-amorphous (LDA) to high-density-amorphous (HDA) occurs through nucleation and growth, resulting in non-spherical interfaces that underscore the mechanical nature of AAT. In contrast, the reverse transition occurs through spinodal decomposition. Further pressurisation transforms LDA into very-high-density amorphous (VHDA), with HDA serving as an intermediate state. Notably, the final amorphous states are inherently unstable, transitioning into crystals. Our findings demonstrate that AAT and crystallisation are driven by joint thermodynamic and mechanical instabilities, assisted by preordering, occurring without diffusion. This unique mechanical and diffusion-less nature distinguishes AAT from liquid-liquid transitions. The mechanism of amorphous-amorphous transitions is highly debated. Here, the authors use molecular dynamics simulations to reveal transitions via nucleation-growth or spinodal decomposition, resembling a thermodynamic phase transition but influenced by mechanics. [ABSTRACT FROM AUTHOR]

We use micro-computed tomography (µ-CT) to characterize the sizes, shapes, and locations of layer perforation (LP) defects in laminates of copper (Cu) and tantalum (Ta) processed by accumulative roll bonding (ARB). One—termed Cu/Ta—was processed from an initial stacking of seven alternating Cu and Ta sheets, with the exterior sheets being Cu. In the other—termed Ta/Cu—the exterior sheets are Ta. Cu/Ta remained intact during processing and exhibits an approximately uniform spatial distribution of LPs. By contrast, Ta/Cu fractured by longitudinal splitting. LPs in this latter sample are concentrated near the sample surfaces. Moreover, their density increases with decreasing distance to the fracture surface. These findings show that materials undergoing ARB may remain intact, despite profuse formation of LPs, provided that the LPs are uniformly distributed. However, a non-uniform distribution of LPs is correlated with longitudinal splitting. [ABSTRACT FROM AUTHOR]