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The effects of alloying elements (Si, Cr, Mo) on the solution and diffusion of oxygen (O) atoms at the grain boundary of iron (Fe) Σ5(310)/[001] are investigated by the simulations of ab initio density functional theory (DFT). It is found that Si, Mo and Cr prefer to segregate to the grain boundary, and further affect the solution and diffusion of O atoms at Fe grain boundaries. The segregated Cr promotes the solution of O, while Si and Mo inhibit the solution of O at the grain boundary. Meanwhile, Cr and Si accelerate the diffusion of O, and Mo retards the diffusion of O in the grain boundary. Further analysis indicates that the effects are closely related to the interactions between the alloying elements and O atoms, which are determined by the competition between the distortion of local structure and the charge transfer between local atoms. Finally, the effects of alloying elements on the O concentration distribution near the grain boundary are explored by employing the Langmuir–McLean models. This work not only provides insights into the effects of alloying elements on the solution and diffusion of O at grain boundaries, but also provides parameters of the atomic interactions for the initial oxidation simulation on a large scale, which relates to the growth of oxide in polycrystalline systems with various grain sizes at experimental temperatures. [ABSTRACT FROM AUTHOR]

The control of segregation-induced grain boundary (GB) strengthening is a strategy for improving the ductility and intergranular fracture of metals. In this work, by first-principles calculations we study the strengthening effect of transition metals on a series of tungsten GBs to uncover its dependence on the GB structures and the radius of solute itself. The results show that the GB strengthening depends strongly on the GB structures. The solutes tend to enhance cohesion for GBs with larger GB energies, while they decrease cohesion for those with smaller GB energies. In addition, it is generally found that for all GBs the strengthening energies of elements correlate positively with their metallic radii, implying that the size effect plays a major role in the GB strengthening in tungsten. By analyzing the strengthening effect of solutes at different segregated sites, we find that the oversized solutes (Zr, Nb, Hf, Ta) act as cohesion enhancers when segregated in the GB plane, while the undersized elements (Ru, Rh, Re, Os, Ir) strengthen the GBs at the nearest neighbor positions. Experimentally, we show that the presence of Zr/Ta/Re impurity, which leads to an increase of intergranular fracture, increases the theoretical tensile strength and the GB cohesion. These results suggest that the improved fracture resistance by Re, Ta and Zr originates mainly from the GB strengthening due to their segregation. [ABSTRACT FROM AUTHOR]

• The phonons thermal resistances of tungsten grain boundaries (GBs) and the ones containing nano helium (He) bubble are systematically calculated by non-equilibrium molecular dynamics (NEMD) methods. • It is proven that the thermal resistances are positively correlated with the lattice distortion energies. • When considered the He atoms inserted in the middle of GBs with a spherical bubble, the influence of number of He atoms has increasing trend after the number reaches a certain number. • The internal pressure in He bubble is finally saturated due to the coupling of the bubble and GBs when the He atoms numbers increasing. Tungsten (W) as plasma facing material (PFM) has been used in ITER divertor. Many experiments indicate that due to helium (He) ion irradiation the thermal conductivities (TCs) of W can be significantly reduced. In this work, the lattice thermal transport property is studied based on the non-equilibrium molecular dynamics (NEMD) method. Firstly, the Kapitza resistance of grain boundaries (GBs) in W is obtained. It can be confirmed that the Kapitza resistance is positively correlated with GB energies, which reflect the lattice distortion degree in a sense. The result indicates that the distortion energy may play a key role in the thermal properties. Further simulation is performed to study the thermal resistance of GBs with nano He bubble. When the number of He atoms in bubble is less than a value, the thermal resistances are stable and change little. It implies that the effect of GBs is more significant than He bubble to block phonons diffusion. With the number of He atoms increasing, the property of heat conduction deteriorates further because the coupling of He bubble and GBs change the lattice distortion degree. [ABSTRACT FROM AUTHOR]

Under a severe neutron irradiation environment, helium behaviour has become a significant concern due to helium-induced degradation of mechanical properties in SiC structural materials. Experimental observations showed that helium prefers to aggregate at grain boundaries (GBs) in SiC ceramics. However, the interaction mechanisms between helium and GBs have remained unclear. By performing first-principles calculations, we studied helium segregation at six symmetric tilt GBs and helium diffusion along and across the GBs. The solution energies of helium at the GBs are much lower than that of helium in grains, indicating preferential helium segregation at the GBs. The negative segregation energies of helium decrease linearly with the excess volume of GBs and the relative charge densities of the interstitial sites, which reveals that helium easily segregates at the GBs having open structures and low charge density interstitial sites. The interstitial helium atoms at GBs are difficult to form clusters due to weak interactions. The diffusion energy barriers of helium along the GBs Σ9(221)[1 1 ¯ 0] and Σ27(552)[1 1 ¯ 0] in the direction of tilt axis [1 1 ¯ 0] are much lower than that of helium in the grains. The two GBs can significantly enhance the helium diffusivity, serving as fast diffusion channels for helium. The calculation results are analysed and compared with our experimental data. [ABSTRACT FROM AUTHOR]

The strengthening energy or embrittling potency of an alloying element is a fundamental energetics of the grain boundary (GB) embrittlement that control the mechanical properties of metallic materials. A data-driven machine learning approach has recently been used to develop prediction models to uncover the physical mechanisms and design novel materials with enhanced properties. In this work, to accurately predict and uncover the key features in determining the strengthening energies, three machine learning methods were used to model and predict strengthening energies of solutes in different metallic GBs. In addition, 142 strengthening energies from previous density functional theory calculations served as our dataset to train three machine learning models: support vector machine (SVM) with linear kernel, SVM with radial basis function (RBF) kernel, and artificial neural network (ANN). Considering both the bond-breaking effect and atomic size effect, the nonlinear kernel based SVR model was found to perform the best with a correlation of r2 ~ 0.889. The size effect feature shows a significant improvement to prediction performance with respect to using bond-breaking effect only. Moreover, the mean impact value analysis was conducted to quantitatively explore the relative significance of each input feature for improving the effective prediction. [ABSTRACT FROM AUTHOR]

• A ML framework was developed to predict the formation energies of stable SIAs at GBs by combining the SVM model suitable for handling small samples with the DE algorithm designed for global optimization. • Atomic volumes of GB sites were calculated to capture the structural relation of the stable SIA with its surrounding environments and further construct the descriptors. • The results from 7-fold and LOO CV showed a promising prediction capability for GB systems beyond the training set based on the currently constructed descriptors and DE-SVM model, with MAPE lower than 6.3 % and R2 close to 0.9. • A decrease in the site stability induced by the SIA loading was revealed, which further led to the transformation of the GB's role from trapping Vs to annihilating Vs. The stable sites of self-interstitial atoms (SIAs) at grain boundaries (GBs) and corresponding energetics are fundamental to explore both the SIA–GB interaction and the effects of SIA segregation on the role of GBs in microstructural evolution under irradiation. In this study, by combing the support vector machine (SVM) model suitable for handling small samples with the differential evolution (DE) algorithm designed for global optimization, a machine learning (ML) framework for modeling and predicting the formation energies of stable SIAs (E S I A min f) at tungsten GBs was established. The stable SIA site was related to the atomic site with maximum atomic volume in the pure GB, and the feature variables for constructing descriptors were thus extracted. Meanwhile, three GB characteristics of tilt angle, GB energy and interplanar spacing were also selected to construct the descriptors. The optimal descriptors consisting of both the local structure information and the GB characteristics were determined by the property-feature correlation analysis, wrapper and enumeration methods. The model from 7-fold and leave-one-out cross validation has mean absolute percentage error (MAPE) close to 6.0 % and square correlation coefficient (R2) close to 0.9, showing a promising prediction capability for E S I A min f out of the training set based on the currently constructed descriptors. The performance comparison with other ML methods reflects the effectiveness of our constructed descriptors and the high efficiency of SVM in dealing with small-size datasets. The model transferability was further verified by its application to α -iron and molybdenum based systems. The present work establishes the relationship between the energetics of the stable SIA and the GB structure via ML, and shows great prospect in the application of ML methods on modeling GB-relevant defect properties. [Display omitted] [ABSTRACT FROM AUTHOR]

Molecular statics/dynamics (MS/MD) based on empirical interatomic potentials (IAPs) is an effective means for conducting grain boundary (GB) related studies. The accuracy of these MS/MD simulations, however, can be greatly affected by the IAP used. Unfortunately, the large discrepancies between the ab-initio values make it difficult to evaluate, improve and further develop IAPs. Motivated by this issue, in the present work we perform a systematic investigation of 〈100〉 and 〈110〉 symmetric tilt GBs in tungsten (W) via atomistic simulations, including the stable structure, GB energy, work of separation, excess volume, and vacancy formation energy. We here use a two-step relaxation process, initially obtaining the candidate structures from MS and then performing DFT validation of these structures to determine the ground state structure, where six empirical IAPs and four exchange–correlation (xc) functionals are used. And the step-like feature is revealed that can be used to reduce the cost of time-consuming optimization processes. Taking the results yielded by PBEsol xc-functional as a benchmark, it is shown that for the same xc-functional, the relative errors of GB energy and work of separation are almost identical, independent of the GB character. The performance of six typical empirical IAPs considered for W is also evaluated by comparing it with the DFT data. The quantities chosen for the comparison include the structure and energetic properties of GBs, as mentioned before. We demonstrate that these empirical IAPs tend to better describe only part of the properties of GBs; for example, some IAPs can predict the energetic properties well, while others can better describe the structure. This suggests that a fully reliable description of GBs remains an elusive objective, requiring further efforts in the development and optimization of the IAP. [ABSTRACT FROM AUTHOR]

Based on the first-principles calculations, we studied the He n V clusters (n = 1–9) in α-Fe bulk, and comparatively studied three orthogonal orientations of He 2 V clusters in the grain boundary (GB) plane of five symmetrical tilt grain boundaries (STGBs). The results of He n V clusters in bulk showed that He n V clusters with larger binding energy (He 4 V and He 6 V in this work) are more likely to exhibit a highly symmetrical configuration. Moreover, it is also indicated that the Fe He interatomic potential using an s-band model is more accurate than other potentials to describe the system. The grain boundary region (He n V (0 ≤ n ≤ 2) in a Σ5(3 1 0) GB as an example) was effectively used by constructing two simplified GB models (free surface GB model and reconstructed GB model) and the results proved that the free surface GB model is a good approximation by maintaining high precision (−0.09 eV to +0.03 eV binding energy error) and reducing resources consumption (24–90% computational time of the original GB model) as well. He 2 V residing in parallel to GB plane with relatively higher binding energies are more stable than the ones that perpendicular to it. He 2 V perpendicular to GB plane shows shorter He He separation distances than in bulk or tend to deviate from the orientation more easily to bind with GBs. [ABSTRACT FROM AUTHOR]

The interaction between the radiation defects of vacancies (Vs) and grain boundaries (GBs) is critical to the understanding of the radiation response of polycrystalline materials. In this work, by combing atomistic calculations with kinetic Monte Carlo methods, multiscale simulations of Vs behavior near different iron GBs were carried out to reveal the Vs accumulation mechanisms at GBs. On the one hand, the dependence of Vs accumulation on the GB character was clarified. At high temperature, new V escaping processes were revealed, including the emission from twin boundary and special coincidence site lattice (CSL) GB with a low V–GB binding strength and the leakage from the extremely low-angle GB with a bulk-like region between dislocation cores. These processes weaken the trapping efficiency of such GBs for Vs. Enhanced Vs trapping could be obtained for the general low-angle GB because of the large strain field. Due to the large V–GB binding energy and trapping site density, the general high-angle GB was found to capture Vs efficiently. On the other hand, the coupling of grain size with GB character via the combination of grain size, V formation energy at the GB and migration energy barrier within the GB was proposed, which leads to the competition between the V emission from the GB and its cruise along the GB. This accounts for the experimentally observed scattered relation of the radiation-performance to defect–GB binding strength. The present work provides some theoretical guidance for optimizing the radiation resistance of polycrystalline materials based on GB engineering. [Display omitted] [ABSTRACT FROM AUTHOR]

Understanding the interaction of hydrogen (H) with defects has been recognized as a central aspect in hydrogen-induced damages in metals. In this work, the role of coherent and semi-coherent interfaces between W and ZrC on H trapping, desorption and clustering in nanostructured W alloys was investigated by density functional theory calculations. It is found that, the trapping ability of pure interface is comparable with the intrinsic defects (grain boundary, dislocations) in bulk W, with segregation energies of H ranging from -1.37 to -0.98 eV. While the interfaces with W/C vacancy show stronger trapping capabilities, especially for the semi-coherent interfaces. This leads to low peak temperatures of 390–567 K for H desorption from the pure interfaces and high peak temperatures of 470–836 K from the vacancy-containing interfaces. As the number of H atoms increases, they preferentially segregate to the interfacial W vacancy and divacancy, and then stay at the interface and interface-like zones discretely until the adsorption rate reaches 3/8. The strong traps of vacancy-containing phase interfaces could effectively absorb H from the screw dislocation cores and bulk vacancies in W, hence preventing H-induced damage. This work advances atomic-level understanding of the role of phase interfaces in H trapping and clustering, not only offering direct explanations for experimental H desorption observations, but also pointing to a feasible route towards interface engineering against H-induced damage in structural metals. [Display omitted] [ABSTRACT FROM AUTHOR]

Nano-crystalline metals (NCs) exhibit radiation-tolerance due to the sink of grain boundaries (GBs) for radiation-induced defects such as self-interstitial atoms (SIAs) and vacancies (Vs). However, the relevant mechanisms for the radiation damage accumulation and GB structural relaxation under high radiation field in NCs are still not well understood. By combining coarse-grained and atomistic simulations, we proposed an iterative method to investigate the evolution of the microstructure and SIA/V-GB interaction under cumulative irradiation in NC iron. The SIA overloaded effect was revealed in iron GBs when subjected to irradiation at a high radiation dose rate and/or low temperature. With the SIAs accumulated at the GB, the new GB phase was formed and then a critical concentration of the SIAs at the GB transited to a small quantity of the Vs during the GB structural recovery, accompanied by the local GB motion. Consequently, the GB's role for Vs nearby alternated between the trapping and annihilation center with radiation dose. Alternatively, the GB with relatively low defect formation energy developed to a disordered structure after trapping abundant SIAs. The GB response pattern to cumulative irradiation is related to the SIA formation energy at the GB or the GB thermal stability, which is well manifested in the cumulative distribution function of the defects formation energy and its energy level density. At a high temperature, the SIA was found to be clustered at the GB in the form of planar configurations with unique energetics that cannot be described by the capillary law. The present work reveals a dynamic healing picture for radiation damage near the GB under cumulative irradiation. [Display omitted] [ABSTRACT FROM AUTHOR]

• The effectiveness of refining grains and tailoring grain boundary types in enhancing the radiation resistance of tungsten was evaluated by molecular statics and steady-state rate theory calculations. • Nanocrystalline tugnsten was found to exhibit better radiation tolerance than coarse-grained tungsten under the conditions of a relatively high temperature and low dose rate. • Some high-angle and high-energy grain boundaries with a large vacancy (V) segregation energy and a small V–V binding energy were expected to improve the radiation resistance of nanocrystalline tugnsten. Grain boundary (GB) character and radiation conditions restrict the in-depth understanding of the effectiveness of tailoring grain size in controlling the radiation damage and promoting the radiation resistance of materials. Here, we constructed 46 [0 0 1] W symmetric tilt GBs with tilt angle varying from 6.73° to 82.37° Then, molecular statics (MS) was used to investigate the impact of GB character (tilt angle, GB energy, Σ) on the defect energetics. The present results suggested that it is energetically favorable for Vs/SIAs to segregate into the GB and GBs have the biased absorption of SIAs over Vs. Some high-angle and high-energy GBs could provide larger energetic driving force for the V/SIA to segregate. Multiple Vs/SIAs tended to be bound together inside the GB, with a varying binding strength. Using steady-state rate theory (RT) calculations, we explored the Vs accumulation in the W systems with different grain sizes (50–1000 nm) under the typical radiation conditions of temperature (300–1800 K) and dose rate (10−8–102 dpa/s). In particular, based on the results of MS calculations, the effect of GB character on the Vs accumulation was examined by varying V segregation energies (0.99–2.04 eV). In the process, two extreme values (2.04 and 0.99 eV) of V segregation energy were extracted to investigate its impact, with other values being in this range. The results suggested that nanocrystalline (NC) W would exhibit better radiation tolerance than coarse-grained (CG) W under the conditions of a relatively high temperature and low dose rate. A high V segregation energy led to a low damage accumulation in the grain interior. Some high-angle and high-energy GBs with a large V segregation energy and a small V–V binding energy were expected to improve the radiation resistance of NC. [Display omitted] [ABSTRACT FROM AUTHOR]

Damage behaviors of ITER grade tungsten (W) induced by repetitive thermal loads have been investigated using an electron beam device EBMP-30. The metallographic observation, backscattered electron scanning electron microscopy, electron backscattered diffraction, atomic force microscopy analysis and tensile tests were carried out after the repetitive heat loads. Results indicate that there are negligible effects on the microstructures, surface morphologies and mechanical properties with the absorbed power densities (APD) lower than 10 MW/m2. While serious damages including the severe surface roughness with protruding structures along grain boundaries, and significant grains coarsening with the evolution of the grain shape occur undesirably due to the full recrystallization during the repetitive 30 MW/m2 heat loads. Furthermore, after exposed to an APD of 30 MW/m2 with 50 heat loads, the tensile properties deteriorate dramatically, resulting in a limited ultimate tensile strength of only 328 MPa and even a zero total elongation at 300 °C. The relationships between the thermal loads, microstructures evolution and degradation of mechanical properties have been analyzed. [ABSTRACT FROM AUTHOR]

• A framework for predicting vacancy formation energy (E V f) near symmetry tilt grain boundaries in tungsten (W) by machine learning technique was presented. • The geometrical factors, such as spatial size characteristic, density and location, were determined as descriptors for the machine learning analysis. • Three separate cross validation (CV) predictions for high angle, low angle-I and low angle-II STGBs have obvious improvement in accuracies compared to all-data CV. • The present method is robust and general to other materials such as α-Fe, and beneficial to predict and understand the vacancy formation near interfaces. Grain boundary (GB) plays a crucial role in the mechanical properties and irradiation resistance of nuclear materials. It is thus essential to understand and predict the defect properties near GBs. Here, we present a framework for predicting vacancy formation energy (E V f) near GBs in tungsten (W) by machine learning (ML) technique. The E V f values of 4496 atomic sites near 46 types of [001] symmetry tilt GB (STGB) in W are calculated as database and eight appropriate variables are selected to characterizing the surrounding atomic configuration and location of atomic sites. Via the support vector machine with the radial basis kernel function (RBF-SVM), the good predicted results of cross validation (CV) and generalized verification prove the suitability and effectiveness of the selected variables and RBF-SVM method. Beside, due to their big differences in dislocation arrangement and atomic configuration, the STGBs need to be divided into three types, high angle, low angle-I and low angle-II STGBs, for adopting the Separate CV, and their predicted accuracies were found to have big improvements. Because the present method adopts geometrical factors, such as spatial size characteristic, density and location, as descriptors for the ML analysis, it is robust and general to other materials such as α-Fe, and beneficial to predict and understand the vacancy formation near interfaces. [ABSTRACT FROM AUTHOR]

The defect relaxation behavior of AlCrTiV x (x = 0, 0.5, and 1) high entropy alloys was reported in this paper. A pronounced internal friction (IF) peak superimposing on a monotonously increasing high-temperature background (HTBG) was observed in all samples, which was ascribed to grain boundary peak. The activation energy of grain boundary relaxation increases with the increasing V content, implying an increasing complexity and difficulty of atomic diffusion with the increasing mixing entropy. After annealing at 1100 °C for 5 h, the HTBG of AlCrTiV alloy abnormally increases, which was attributed to the appearance of misfit dislocations induced by precipitation of nano-sized Ti-rich phases as confirmed by microstructure analysis. These findings may provide a new degree of freedom for evaluating and designing high entropy alloys with high thermal stability. [Display omitted] [ABSTRACT FROM AUTHOR]