Boundary Interactions Research Articles

Slip-twin Boundary Interactions for Oxygen-segregated Twin Boundary in α-Ti

Slip-twin Boundary Interactions for Oxygen-segregated Twin Boundary in α-Ti

The influence of online host–guest interaction on listing popularity in peer-to-peer accommodation: the role of listing price and reputation

PurposeTo promote the success of peer-to-peer accommodation, this study examines the effects of online host–guest interaction as well as the interaction's boundary conditions of listing price and reputation on listing popularity.Design/methodology/approachUsing 330,686 data collected from Airbnb in the United States of America, the authors provide empirical evidence to answer whether social-oriented self-presentation and response rate influence listing popularity from the perspective of social exchange theory (SET). In addition, the authors investigate how these two kinds of online host–guest interactions work with listing price and reputation to influence listing popularity.FindingsThe results reveal the positive association between online host–guest interaction and listing popularity. Notably, the authors find that listing price strengthens but listing reputation weakens the positive effects of online host–guest interactions on listing popularity in peer-to-peer accommodation.Originality/valueThis study is the first attempt to adopt SET to explain the importance of online host–guest interactions in influencing listing popularity as well as examine the moderating role of listing price and reputation on the above relationship.

Segregation-enhanced grain boundary embrittlement of recrystallised tungsten evidenced by site-specific microcantilever fracture

Tungsten stands a prime candidate for plasma-facing applications in fusion reactors, attributed to its capacity to withstand high temperatures and intensive particle fluxes. The operational heat flux, however, can induce recrystallisation of the initial microstructure, increasing the brittle-to-ductile transition temperature. Although such a phenomenon is thought to result from impurity segregation to grain boundaries, direct evidence of impurity-induced grain boundary embrittlement has not yet been reported. Addressing this, our study employs microcantilever testing, coupled with local chemical analysis via atom probe tomography, to unveil the impact of impurity segregation on the fracture toughness of recrystallised tungsten with a purity of 99.98 at.%. The in situ fracture toughness measurements were performed with the notch placed directly at random high-angle grain boundaries, revealing brittle failure regardless of grain boundary misorientation or grain orientation. Notably, both single-crystalline microcantilevers and the as-received material exhibited significant plasticity before failure, with instances without crack propagation. In contrast, recrystallised grain boundaries displayed a fracture toughness of 4.7 ± 0.4 MPa·√m, determined using a linear elastic approach - notably lower than for cleavage plane fracture in tungsten microcantilevers. Local atom probe analysis of the high-angle grain boundaries exposed phosphorous segregation exceeding 2 at.% at the recrystallised interfaces, stemming from recrystallisation. Atomistic simulations confirmed the role of phosphorous in embrittling high-angle grain boundaries in tungsten, while additionally revealing mechanisms of crack-grain boundary interactions and their dependence on phosphorous segregation.

Prediction of dislocation - grain boundary interactions in FCC aluminum bicrystals using a modified continuum criterion and machine learning methods

Mechanical properties of metals such as strength and toughness are strongly correlated to complex interactions between various defects in the crystalline structure. While elementary interactions between these defects have been investigated using recent micro- and nano-characterization techniques, understanding of the detailed interaction mechanisms has hardly been obtained. To understand defect-driven plasticity at various time and length scales, it is necessary to formulate a general guideline to predict both the interaction type (transmission or reflection) and the dislocation's subsequent slip system after the interaction. Many criteria based on the geometric alignment of the defects have been developed to predict this phenomenon, but these have yet to be found to be accurate when applied to general data sets of grain boundaries (GBs). With this motivation, we conduct a systematic study using molecular dynamics (MD) models of bicrystals to analyze defect interaction process between a prismatic dislocation loop and eleven different grain boundaries of the following character: three tilt, three twist, and five mixed. Based on the MD observations, two new prediction methods are developed: the first is a new data-driven parametric score function based on the classical geometric criteria, and the second is by applying Gaussian process machine learning methods to find the probability distribution of a hidden function. The proposed data-driven prediction methods could pave a new way to predict the unit interaction of dislocations with various GBs, which could show much higher accuracy compared to pre-existing geometric criteria.

Pre-Smectic Ordering and the Unwinding Helix in Monte Carlo Simulations of Cholesteric Liquid-Crystals.

In this paper, molecular chirality is studied for liquid-crystal fluids represented by hard rods with the addition of an attractive chiral dispersion term. Chiral forces between molecular pairs are assumed to be long-ranged and are described in terms of the pseudotensor of Goossens [W. J. A. Goossens, Mol. Cryst. Liq. Cryst. 1971, 12, 237-244]. Following Varga and Jackson [S. Varga and G. Jackson, Chem. Phys. Lett. 2003, 377, 6-12], this is combined with a hard-spherocylinder core. We investigate the relationship between molecular chirality and the helical pitch of the system, which occurs in the absence of full three-dimensional periodic boundary conditions. The dependence of the wavenumber of this pitch on the thermodynamic variables, temperature, and density is measured. We also explore the use of a novel surface boundary interaction model. As a result of this approach, we are able to lower the temperature of the system without the occurrence of nematic droplets, which would interfere with the formation of a uniaxial pitch. Regarding the theoretical predictions of Wensink and Jackson [H. H. Wensink and G. Jackson, J. Chem. Phys. 2009, 130, 234911], on the one hand, we have qualitative agreement with the observed non-monotonic density dependence of the wavenumber. Initially increasing with density, the wavenumber reaches a maximum, before falling as the density moves toward the point of phase transition from cholesteric to smectic. However, further analysis for shorter rods, in the presence of novel boundary conditions, reveals some disagreement with the theory, at least in this case; the unwinding of the cholesteric helix in the cholesteric phase occurs simultaneously with subtle increases in smectic ordering. These pre-smectic fluctuations have not been accounted for so far in theories on cholesterics but turn out to play a key role in controlling the pitch of cholesteric phases of rod-shaped mesogens with a small to moderate aspect ratio.

Modeling solute-grain boundary interactions in a bcc Ti-Mo alloy using density functional theory

Solute segregation in alloys is a key phenomenon which affects various material characteristics such as embrittlement, grain growth and precipitation kinetics. In this work, the segregation energies of Y, Zr, and Nb to a Σ5 grain boundary in a bcc Ti-25 at % Mo alloy are determined using density functional theory (DFT) calculations. A systematic approach is laid out by computing the solution energy distributions in the bulk alloy using Warren-Cowley short-range order parameters to find a representative bulk-solute reference energy. Additionally, different scenarios are considered when a solute atom replaces different sites in terms of their local Ti-Mo chemistry at the GB plane to calculate the distribution of segregation energies. The solute segregation to a Mo site at the GB plane is preferred rather than to a Ti site. Further analysis shows that these segregation energy trends can be rationalized based on a primarily elastic interaction. Thus the segregation energies scale with the solute size such that Y has the largest segregation energies followed by Zr and Nb.

Phase-field modeling of interaction between void and grain boundaries and its swelling effect

The interaction of irradiated voids and grain boundaries in zirconium is systematically studied by using a composite multiphase-field model that couples the evolution of irradiated voids and grain boundaries. In phase-field modeling, the polycrystalline evolution phase-field governing equation and void evolution phase-field governing equation are coupled together for modeling. In the numerical solution, the aforementioned two sets of equations are coupled to solve the absorption of vacancies and interstitial atoms by grain boundaries. First, we studied the influence of the existence of voids on the evolution of polycrystalline grains when the voids did not evolve. Thereafter, we examined the influence of the grain boundaries on the evolution of the voids when the grain boundaries did not evolve. Finally, we analyzed the interaction process between the grain boundaries and voids at the same time. The preceding simulation research can reproduce the pinning effect of the void on the grain boundary and the phenomenon that the grain boundary acts on the void evolution process to form a “void-denuded zone” near the grain boundary. The interaction mechanism between grain boundaries and voids is revealed through systematic simulation research. On this basis, the influence of the interaction process between the grain boundary and the void on the swelling behavior is further discussed.

A Lie-algebra-based description of disclination densities and the quantification of partial disclinations in deformed polycrystalline metals

Crystalline defects (e.g., dislocations, disclinations and grain boundaries) play a critical role in determining the mechanical and functional properties of metallic materials. From a physical point of view, dislocations and disclinations are the two fundamental types of topological defects in crystals, which originate from the breaking of translational symmetry and rotational symmetry, respectively. In spite of extensive studies on dislocations in the literature, the effects of disclinations on mechanical properties of metals have not been well recognized, partially due to the lack of an appropriate description for the rotational nature of disclinations. Here we suggest a Lie-algebra-based method to quantify the rotational properties of disclinations, which leads to a convenient way to determine disclination density distribution directly from Electron Backscatter Diffraction data. Through quasi-in-situ Electron Backscatter Diffraction characterizations, three major formation mechanisms of disclinations have been identified in deformed polycrystalline Mg alloys, i.e., dislocation-grain boundary interaction, dislocation redistribution and twin-twin reaction, all of which can be treated as topological reactions among various types of defects under a general framework. Our work not only suggests a new mathematical tool to investigate the interactions and reactions among multiple types of crystalline defects, but also provides a new insight to understand the deformation behaviors of metals and alloys based on dislocation/disclination theory.

Investigating the effect of polydispersity on the dynamics of multiphase flows using computational fluid dynamics tools

Granular flows consist of discrete macroscopic particles. If they are non-cohesive, their status is determined by the interaction of particle-particle frictional forces, external boundaries and gravity. In particular, the understanding of the transport mechanisms of granular materials is of paramount importance for the characterization of volcanic granular flows and for hazard assessments associated with these flows. In order to investigate dynamics of these kinds of flows, we replicated large-scale experiments with multiphase computational fluid dynamic (CFD) simulations using the Two-Fluid Model approach, with an emphasis on the polydispersity effect on the flow behaviour. The CFD simulations were run using the software MFIX. The present work consists of: 1) investigations on the drag force relationships implemented in MFIX; 2) applications of MFIX to replicate large-scale experiments on volcanic dry granular flows sliding on an inclined channel; 3) comparisons between experimental and simulated data with particular emphasis on the velocity of the granular flow front. Simulations on polydisperse granular flows demonstrated the simulated flows capability to replicate segregation dynamics active in real granular flows, and the polydispersity effects on velocities and shapes of granular flows. The non-uniformity of solid phases highly affects the dynamic of the whole flow and results in a better agreement between simulated and experimental flow velocities than the simplest monodisperse particles systems. In particular, the greater the number of the solid phases, the lower the velocity of granular flows and the mean square error, which decreases by ca. 50%.

Feature interaction network based on hierarchical decoupled convolution for 3D medical image segmentation.

Manual image segmentation consumes time. An automatic and accurate method to segment multimodal brain tumors using context information rich three-dimensional medical images that can be used for clinical treatment decisions and surgical planning is required. However, it is a challenge to use deep learning to achieve accurate segmentation of medical images due to the diversity of tumors and the complex boundary interactions between sub-regions while limited computing resources hinder the construction of efficient neural networks. We propose a feature fusion module based on a hierarchical decoupling convolution network and an attention mechanism to improve the performance of network segmentation. We replaced the skip connections of U-shaped networks with a feature fusion module to solve the category imbalance problem, thus contributing to the segmentation of more complicated medical images. We introduced a global attention mechanism to further integrate the features learned by the encoder and explore the context information. The proposed method was evaluated for enhance tumor, whole tumor, and tumor core, achieving Dice similarity coefficient metrics of 0.775, 0.900, and 0.827, respectively, on the BraTS 2019 dataset and 0.800, 0.902, and 0.841, respectively on the BraTS 2018 dataset. The results show that our proposed method is inherently general and is a powerful tool for brain tumor image studies. Our code is available at: https://github.com/WSake/Feature-interaction-network-based-on-Hierarchical-Decoupled-Convolution.

Magnetic field control of high-enthalpy shock wave/boundary-layer interactions using a fully implicit thermochemical non-equilibrium solver

Magnetohydrodynamic (MHD) heat shield systems have been proven to be highly effective in hypersonic blunt-nosed bodies. Thus, it is natural to consider the application of MHD to more complex geometries that induce shock wave/boundary-layer interactions associated with locally high heat load, which is a lack of deep research, especially for the large-size model in high-enthalpy conditions. To investigate the possibility and mechanism of the control of shock wave/boundary-layer interactions using local magnetic fields, the partially ionized flow of the hollow cylinder/flare coupling of these fields was numerically analyzed using a hypersonic thermochemical nonequilibrium solver. It consisted of an 11-species reaction model and a Park two-temperature model based on the low magneto-Reynolds assumption. To address the numerical stiffness introduced by the large difference in the characteristic time of the thermochemical non-equilibrium and grid refinement in the boundary layer and interaction zone, a fully implicit block lower–upper symmetric Gauss–Seidel algorithm was developed. This algorithm improved the accelerating rate and the solver was validated using cases involving MHD control of flow around a typical reentry vehicle, and the measured double cone and hollow cylinder/flare data for a high-enthalpy wind tunnel. After that, a parametric study of high-enthalpy flow over the hollow cylinder/flare model was conducted and MHD control was divided into three categories. Among these, N-type control led to the largest reduction in the peak value of the total wall heat flux near the neck region, which was obtained using a uniform magnetic field. Specifically, the peak heat flux and the peak skin friction coefficient were reduced by 20.0% and 48.0%, respectively. Then, two local MHD interaction parameters were newly proposed for mechanism analysis and can serve as an effective indicator for MHD controllability. The numerical results demonstrated that the Lorentz force in the counter-streamlined direction induced by the external magnetic field and ionized flow were key factors that influenced the control of the local heat flux. The results of this study lay the foundation for the design of MHD experiments in a high-enthalpy wind tunnel.

The Origin and Evolution of DMM-Like Lithospheric Mantle Beneath Continents: Mantle Xenoliths from the Oku Volcanic Group in the Cameroon Volcanic Line, West Africa

Abstract The lithospheric mantle as sampled by peridotite xenoliths in some continental settings resembles the source of mid-ocean ridge basalts (MORB). Whether this resemblance is a primary feature or the result of post-formation secondary processes remains controversial. Here, the age, origin and thermochemical evolution of fertile continental mantle are constrained based on the chemical composition of minerals in spinel-facies lherzolite and websterite xenoliths from the Wum maar and Befang cinder cone of the Oku Volcanic Group (Cameroon Volcanic Line, West Africa), combined with in-situ Sr isotope compositions of clinopyroxene and fabric investigation by Electron Backscatter Diffraction (EBSD). The majority of lherzolites (here assigned to Group I) consist of minerals with fertile composition (olivine Fo89, Al-rich pyroxenes, spinel Cr# 0.08–0.10). Clinopyroxene is LREE-depleted and has depleted 87Sr/86Sr (0.7017–0.7020). Crystal-preferred orientation determined by EBSD reveals that clinopyroxene, and sporadically both clino- and orthopyroxene, post-date the olivine framework. Subordinate Group II lherzolites also contain secondary clinopyroxene which is LREE-enriched and has higher 87Sr/86Sr (0.7033). In contrast, the scarce lherzolites of Group III are more refractory: they contain 72–78 vol.% olivine, Al-poor pyroxenes, and spinel with Cr# 0.18. Clinopyroxene (87Sr/86Sr 0.7021) is texturally coeval with olivine and orthopyroxene. Few lherzolites contain amphibole (87Sr/86Sr 0.7031) which post-dates the nominally anhydrous minerals. Most of the websterites (Group A) are aluminous (spinel Cr# 0.04–0.06) with LREE-depleted clinopyroxene having depleted 87Sr/86Sr ratios (0.7017–0.7020) similar to Group I lherzolites. Chemical characteristics of minerals coupled with the crystal-preferred orientation data suggests that Group I lherzolites originated in the spinel stability field by reactive intergranular percolation of an incompatible element-depleted MORB-like melt. Group A websterites likely formed as cumulates from that melt. The Group II lherzolites supposedly occur close to lithosphere-asthenosphere boundary and record interaction with lavas of the Cameroon Volcanic Line, whereas Group III lherzolites occur in the shallow part of the mantle profile and represent the protolith from which the Group I lherzolites were formed. Local crystallization of amphibole and concomitant recrystallization of the host lherzolite were driven by supply of water in an event post-dating the formation of LREE-depleted rejuvenated rocks. Migration of alkaline melts of the CVL apparently did not significantly affect the mineral and chemical composition of the lithospheric mantle, which allowed Group I lherzolites and Group A websterites to retain very low 87Rb/86Sr (average 0.002) and depleted 87Sr/86Sr ratios in clinopyroxene. This not only indicates their formation in the Paleoproterozoic (~2.0–2.25 Ga), possibly during the Eburnean orogeny at the margin of the Congo craton, but also indicates surprisingly little influence of the regionally recognized Pan-African event.

Imparted benefits on mechanical properties by achieving grain boundary migration across voids

Understanding the interaction of micro-voids and grain boundaries is critical to achieving superior mechanical properties for safety-critical parts. Micro-voids and grain boundaries may interact during advanced manufacturing processes such as sintering, additive manufacturing and diffusion bonding. Here, we show imparted benefits on mechanical properties by achieving grain boundary migration across voids. The micro-mechanisms and quantitative analysis of grain boundary migration on local deformation were studied by integrated in-situ EBSD/FSE and crystal plasticity finite element modelling. It is revealed that a migrated grain boundary does not alter the activated slip systems but precludes grain boundary-multislip interaction around interfacial voids to alleviate stress concentrations. The stress mitigation caused by grain boundary migration is almost the same as that caused by void closure under the example diffusion bonding thermal-mechanical process used in this study. This new understanding sheds light on the mechanistic link between GND hardening, grain boundary migration and the corresponding material tensile behaviour. It opens a new avenue for achieving superior mechanical properties for metallic parts with micro-defects such as those generated in diffusion-bonded, sintered and additive manufactured components.

Role of Ag segregation on microscale strengthening and slip transmission in an asymmetric Σ5 copper grain boundary

Micropillar compression was used to investigate whether Ag segregation to an asymmetric Σ5[001] grain boundary will lead to measurable strength differences compared to the pure copper bicrystal. Ag segregation was accomplished by deposition and subsequent annealing of an Ag thin-film applied on the surface of the Cu bicrystal. Atom probe tomography analysis indicated Ag segregation at the grain boundary with a peak concentration of 2.3 at.%. While the pristine Σ5 grain boundary shows a yield strength of 288 ± 18 MPa when compressing 1 µm diameter pillars along 〈001〉, micropillars containing an Ag-segregated Σ5 grain boundary demonstrated an increased yield strength of 318 ± 17 MPa. In addition, post-deformation electron microscopy was carried out to examine the active slip systems and slip transmission across Ag-free and Ag-containing bicrystals. The results are compared to reference measurements of the adjacent single crystal grains. The 1 µm pillar diameter promoted deformation governed by dislocation-grain boundary interactions for the bicrystalline pillars. This is the first time that changes in flow stress associated with grain boundary segregation have been quantified locally without interference from other mechanisms such as solid solution strengthening, formation of precipitates or changes in stacking fault energy. The results clearly indicate that purely geometrical models for slip transmission are not sufficient as the local atomic structure and composition influence dislocation transmission through grain boundaries.

Attention-induced semantic and boundary interaction network for camouflaged object detection

The high intrinsic similarity between camouflaged objects and the background makes camouflaged object detection (COD) more challenging than traditional salient object detection (SOD). Existing deep-learning methods often fall into the following shortcomings: (1) When dealing with high-level features, it is difficult to fully and accurately extract semantic information, which is crucial for locating camouflaged targets. (2) The camouflaged targets identified by existing methods in complex scenes have rough boundaries and incomplete spatial information. (3) Existing methods cannot effectively exert the uniqueness and complementarity of multiple features when integrating multiple features. To this end, we propose an attention-induced semantic and boundary interaction network for accurately identifying camouflaged objects. Specifically, we propose a contrastive positioning module (CPM), which adopts a contrastive learning way to separate the camouflaged object from the background, thereby obtaining the exact location of the camouflaged target and retaining more semantic information. Then, we design a boundary exploration module (BEM), which can reduce background noise interference, focus on the structural details of camouflaged targets, and explore rich fine-grained spatial information. Finally, we propose an attention-induced interaction module (AIM) to fuse multivariate information (i.e., semantic location information, boundary information, and the side output information of the backbone), and multivariate information is complementarily fused under attention guidance to generate more powerful camouflaged target features. Extensive experiments show that the proposed method on the different backbones (i.e., ResNet-50, Res2Net-50, PVTv2-B2, EfficientNet-B1) produces state-of-the-art results on several camouflaged benchmarks. The code is available https://github.com/zhangqiao970914/ASBI.

A deep learning empowered smart representative volume element method for long fiber woven composites

In response to the global trend of carbon reduction over the last few years, various industries, including the aviation and automobile industries, have gradually begun research, design, and production of carbon fiber composite materials. These have excellent mechanical properties, such as being lightweight, high strength, and of high rigidity, which provide weight reduction and energy savings in applications across many fields. When used as a load-beam structure, the weave pattern determines the primary mechanical properties of the composite material. Therefore, the production of diverse products and components can be carried out using different patterns of weaving and manufacturing according to an application’s requirements. The mechanical properties of woven fiber composites can be obtained by using simulation analysis software, which can reduce unnecessary waste during design and manufacturing. However, difficulties arise in the simulation analysis due to the complexity of the weaving method. With the continuous improvement of computer technology in recent years and the enormous amount of training data available, many research teams have begun to implement artificial intelligence (AI) technology, which has been widely used to overcome long-standing obstacles in many different fields. For example, the problems involved in the prediction of protein folding sequences and the prediction of the physics of structural materials have all been resolved by AI. We implement a convolutional neural network (CNN), a deep learning method, to establish a model that utilizes a representative volume element for the prediction of the mechanical properties of a woven fiber composite material. The predictive model significantly streamlines the computational complexity involved in analyzing woven composite materials, resulting in a substantial reduction in processing time compared to conventional methods. Unlike traditional finite element simulations, which necessitate intricate boundary conditions and interactions on a case-by-case basis, our research simplifies these complex procedures and accommodates a wide range of scenarios. This research offers substantial advantages for industrial manufacturing, particularly in the design and mass production of woven fiber composite materials.

Analytical investigation of a grain boundary model that accounts for slip system coupling in gradient crystal plasticity frameworks

In this work, a physically based dislocation theory of plasticity is derived within an extended continuum mechanical context. An orientation-dependent grain boundary flow rule is introduced for the modelling of dislocation pile-up at grain boundaries and dislocation transmission through grain boundaries. With the conventional grain boundary modelling approach according to Gurtin (Gurtin. 2008 J. Mech. Phys. Solids 56 , 640–662. ( doi:10.1016/j.jmps.2007.05. 002 )) the single-crystal consistency check for the limit case of adjacent grains that hold no misorientation is not satisfied. In order to overcome this modelling shortcoming, a slip system coupling based on a geometric measure of slip system compatibility is introduced. In order to investigate the grain boundary modelling approaches, the analytical solution of a three-phase periodic laminate is used to study the interactions of dislocations and grain boundaries within the gradient crystal plasticity framework. With the developed grain boundary model two grain boundary states, i.e. microhard and microcontrolled, are observed for misaligned grains. This allows the modelling of slip activation at grain boundaries based on the dislocation pile-up stress.

Thermal and Radiation Stability in Nanocrystalline Cu

Nanocrystalline metals have presented intriguing possibilities for use in radiation environments due to their high grain boundary volume, serving as enhanced irradiation-induced defect sinks. Their promise has been lessened due to the propensity for nanocrystalline metals to suffer deleterious grain growth from combinations of irradiation and/or elevated homologous temperature. While approaches for stabilizing such materials against grain growth are the subject of current research, there is still a lack of central knowledge on the irradiation-grain boundary interactions in pure metals despite many studies on the same. Due to the breadth of available reports, we have critically reviewed studies on irradiation and thermal stability in pure, nanocrystalline copper (Cu) as a model FCC material, and on a few dilute Cu-based alloys. Our study has shown that, viewed collectively, there are large differences in interpretation of irradiation-grain boundary interactions, primarily due to a wide range of irradiation environments and variability in materials processing. We discuss the sources of these differences and analyses herein. Then, with the goal of gaining a more overarching mechanistic understanding of grain size stability in pure materials under irradiation, we provide several key recommendations for making meaningful evaluations across materials with different processing and under variable irradiation conditions.

The correlation between the dislocation slip/grain boundary interaction mode and the resistance to SCC initiation of Alloy 690 in simulated PWR primary water

Recurring step straining was applied on Alloy 690 to establish a correlation between the dislocation slip/grain boundary (GB) interaction mode and the resistance to stress corrosion crack (SCC) initiation in high temperature hydrogenated water. The intergranular carbides can suppress the dislocation transmission across GB in thermally treated Alloy 690. GBs that block dislocation slip show higher resistance to SCC initiation than those that transmit slip. Such correlation reveals that the local normal strain near GB is the primary driving force for breaching the surface oxide film over GB which is a critical prerequisite in the SCC initiation of Alloy 690.

Dissimilar cavitation dynamics and damage patterns produced by parallel fiber alignment to the stone surface in holmium:yttrium aluminum garnet laser lithotripsy.

Recent studies indicate that cavitation may play a vital role in laser lithotripsy. However, the underlying bubble dynamics and associated damage mechanisms are largely unknown. In this study, we use ultra-high-speed shadowgraph imaging, hydrophone measurements, three-dimensional passive cavitation mapping (3D-PCM), and phantom test to investigate the transient dynamics of vapor bubbles induced by a holmium:yttrium aluminum garnet laser and their correlation with solid damage. We vary the standoff distance (SD) between the fiber tip and solid boundary under parallel fiber alignment and observe several distinctive features in bubble dynamics. First, long pulsed laser irradiation and solid boundary interaction create an elongated "pear-shaped" bubble that collapses asymmetrically and forms multiple jets in sequence. Second, unlike nanosecond laser-induced cavitation bubbles, jet impact on solid boundary generates negligible pressure transients and causes no direct damage. A non-circular toroidal bubble forms, particularly following the primary and secondary bubble collapses at SD = 1.0 and 3.0 mm, respectively. We observe three intensified bubble collapses with strong shock wave emissions: the intensified bubble collapse by shock wave, the ensuing reflected shock wave from the solid boundary, and self-intensified collapse of an inverted "triangle-shaped" or "horseshoe-shaped" bubble. Third, high-speed shadowgraph imaging and 3D-PCM confirm that the shock origins from the distinctive bubble collapse form either two discrete spots or a "smiling-face" shape. The spatial collapse pattern is consistent with the similar BegoStone surface damage, suggesting that the shockwave emissions during the intensified asymmetric collapse of the pear-shaped bubble are decisive for the solid damage.