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Refractory high-entropy alloys (HEAs) have attracted considerable attention due to their stable phase structure and excellent high-temperature properties. In this work, we performed first-principles calculations, coupled with experiments, to explore HEAs with high corrosion resistance. The results revealed that TiNbTa-based HEAs exhibited a lower tendency for corrosion. However, the appearance of local chemical fluctuations (LCFs) increased the corrosion tendency of TiNbTa-based HEAs. Comprehensive SHapley Additive exPlanations analyses uncovered that in a sample with configurational LCFs, the atomic order near the surface was altered. Therefore, corrosion behavior was affected. Based on experiments, the annealed samples exhibited typical chemical segregation and declined corrosion resistance. [ABSTRACT FROM AUTHOR]

A scalable, reusable, and broad-coverage unified material knowledge representation shows its importance and will bring great benefits to data sharing among materials communities. A knowledge graph (KG) for materials terminology, which is a formal collection of term entities and relationships, is conceptually important to achieve this goal. In this work, we propose a KG for materials terminology, named Materials Genome Engineering Database Knowledge Graph (MGED-KG), which is automatically constructed from text corpus via natural language processing. MGED-KG is the most comprehensive KG for materials terminology in both Chinese and English languages, consisting of 8,660 terms and their explanations. It encompasses 11 principal categories, such as Metals, Composites, Nanomaterials, each with two or three levels of subcategories, resulting in a total of 235 distinct category labels. For further application, a knowledge web system based on MGED-KG is developed and shows its great power in improving data sharing efficiency from the aspects of query expansion, term, and data recommendation. [ABSTRACT FROM AUTHOR]

Optimizing several properties simultaneously based on small data-driven machine learning in complex black-box scenarios can present difficulties and challenges. Here we employ a triple-objective optimization algorithm deduced from probability density functions of multivariate Gaussian distributions to optimize the γ′ volume fraction, size, and morphology in CoNiAlCr-based superalloys. The effectiveness of the algorithm is demonstrated by synthesizing alloys with desired γ/γ′ microstructure and optimizing γ′ microstructural parameters. In addition, the method leads to incorporating refractory elements to improve γ/γ′ microstructure in superalloys. After four iterations of experiments guided by the algorithm, we synthesize sixteen alloys of relatively high creep strength from ~120,000 candidates of which three possess high γ′ volume fraction (>54%), small γ′ size (<480 nm), and high cuboidal γ′ fraction (>77%). [ABSTRACT FROM AUTHOR]

The wide range of alloy composition controllability for multi-principal element alloys (MPEAs) may provide a great opportunity for discovering special forms of surface oxides to improve the corrosion and oxidation resistance in extreme environments. Changing the type and content of promoting passivation elements would not only change the microstructure of the alloy but also significantly affect the composition and structure of the surface passive film, resulting in a strong impact on the corrosion and oxidation resistance of the alloy. This article reviews recent research on the effects of alloying elements on the passivation properties, the contribution of each alloying element, and the synergistic effect between the elements on the passivation mechanisms and electrochemical dissolution characteristics of surface passive films that form on some MPEAs. In addition, the composition and structural characteristics of surface oxides relevant to the selective oxidation of elements are elaborated upon. Finally, several open questions and recommendations for research directions regarding the passivation and selective oxidation of MPEAs were provided to guide future exploration. [ABSTRACT FROM AUTHOR]

Alloy synthesis and processing determine the design of alloys with desired microstructure and properties. However, using data science to identify optimal synthesis-design routes from a specified set of starting materials has been limited by large-scale data acquisition. Text mining has made it possible to convert scientific text into structured data collections. Still, the complexity, diversity, and flexibility of synthesis and processing expressions, and the lack of annotated corpora with a gold standard severely hinder accurate and efficient extraction. Here we introduce a semi-supervised text mining method to extract the parameters corresponding to the sequence of actions of synthesis and processing. We automatically extract a total of 9853 superalloy synthesis and processing actions with chemical compositions from a corpus of 16,604 superalloy articles published up to 2022. These have then been used to capture an explicitly expressed synthesis factor for predicting γ′ phase coarsening. The synthesis factor derived from text mining significantly improves the performance of the data-driven γ′ size prediction model. The method thus complements the use of data-driven approaches in the search for relationships between synthesis and structures. [ABSTRACT FROM AUTHOR]

Corrosion initiation and propagation are a time-series problem, evolving continuously with corrosion time, and future pitting behavior depends closely on the past. Predicting localized corrosion for corrosion-resistant alloys remains a great challenge, as macroscopic experiments and microscopic theoretical simulations cannot couple internal and external factors to describe the pitting evolution from a time dimension. In this work, a data-driven method based on time-series analysis was explored. Taking cobalt-based alloys and duplex stainless steels as the case scenario, a corrosion propagation model was built to predict the free corrosion potential (Ecorr) using a long short-term memory neural network (LSTM) based on 150 days of immersion testing in saline solution. Compared to traditional machine learning methods, the time-series analysis method was more consistent with the evolution of ground truth in the Ecorr prediction of the subsequent 70 days' immersion, illustrating that time-series dependency of pitting propagation could be captured and utilized. [ABSTRACT FROM AUTHOR]

Information Extraction (IE) in Natural Language Processing (NLP) aims to extract structured information from unstructured text to assist a computer in understanding natural language. Machine learning-based IE methods bring more intelligence and possibilities but require an extensive and accurate labeled corpus. In the materials science domain, giving reliable labels is a laborious task that requires the efforts of many professionals. To reduce manual intervention and automatically generate materials corpus during IE, in this work, we propose a semi-supervised IE framework for materials via automatically generated corpus. Taking the superalloy data extraction in our previous work as an example, the proposed framework using Snorkel automatically labels the corpus containing property values. Then Ordered Neurons-Long Short-Term Memory (ON-LSTM) network is adopted to train an information extraction model on the generated corpus. The experimental results show that the F1-score of γ' solvus temperature, density and solidus temperature of superalloys are 83.90%, 94.02%, 89.27%, respectively. Furthermore, we conduct similar experiments on other materials, the experimental results show that the proposed framework is universal in the field of materials. [ABSTRACT FROM AUTHOR]

A new high-precision angular-dependent potential of the Ni–Pd system was obtained by fitting the experimental data and first-principles calculations. Then, the element segregation characteristics and thermal stability of Ni–Pd bimetallic nanoparticles were investigated by Monte Carlo method and molecular dynamics method. The results show that the chemical ordering pattern of PdxNi1 − x nanoparticle is the result of the competition of surface energy, strain energy, bond energy and interface energy. When a small amount of Pd atoms are substitutionally doped into the Ni nanoparticle, all the Pd atoms will be segregated on the surface and dispersed. The synergistic effect of Ni atoms and Pd atoms in the surface will improve the catalytic activity and carbon deposition resistance of PdxNi1 − x nanoparticle catalyst in methane dry reforming reaction. Increasing the doping amount of Pd atoms will gradually reduce the melting point of PdxNi1 − x nanoparticle, thereby reducing its sintering resistance. [ABSTRACT FROM AUTHOR]

Data provides a foundation for machine learning, which has accelerated data-driven materials design. The scientific literature contains a large amount of high-quality, reliable data, and automatically extracting data from the literature continues to be a challenge. We propose a natural language processing pipeline to capture both chemical composition and property data that allows analysis and prediction of superalloys. Within 3 h, 2531 records with both composition and property are extracted from 14,425 articles, covering γ′ solvus temperature, density, solidus, and liquidus temperatures. A data-driven model for γ′ solvus temperature is built to predict unexplored Co-based superalloys with high γ′ solvus temperatures within a relative error of 0.81%. We test the predictions via synthesis and characterization of three alloys. A web-based toolkit as an online open-source platform is provided and expected to serve as the basis for a general method to search for targeted materials using data extracted from the literature. [ABSTRACT FROM AUTHOR]

With scientific research in materials science becoming more data intensive and collaborative after the announcement of the Materials Genome Initiative, the need for modern data infrastructures that facilitate the sharing of materials data and analysis tools is compelling in the materials community. In this paper, we describe the challenges of developing such infrastructure and introduce an emerging architecture with high usability. We call this architecture the Materials Genome Engineering Databases (MGED). MGED provides cloud-hosted services with features to simplify the process of collecting datasets from diverse data providers, unify data representation forms with user-centered presentation data model, and accelerate data discovery with advanced search capabilities. MGED also provides a standard service management framework to enable finding and sharing of tools for analyzing and processing data. We describe MGED's design, current status, and how MGED supports integrated management of shared data and services. [ABSTRACT FROM AUTHOR]

This study was conducted to assess the link of miRNA expressions in cow's mammary gland undergoing heat stress. Twelve Holstein cows were allocated either to undergo heat stress (HS) or remain in a thermoneutral environment (non-heat stress, NS), respectively. The experiment with HS cows was carried out in August, and the experiment with NS cows was done in November. After a month, three cows from each group were slaughtered, and mammary gland samples were obtained, and then miRNA were extracted from the samples for later sequencing. From the miRNA-seq, we obtained a total of 124 differentially expressed miRNAs in HS and NS cows' mammary gland. The differentially expressed miRNA could be predicted to influence multiple target genes. The target interleukin-1 (IL-1), which play a role in regulating the function of mammary gland in dairy cows, could be affected by bta-let-7c, bta-let-7e, bta-miR-181d, bta-miR-452, and bta-miR-31. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that mitogen-activated protein kinase (MAPK) pathway plays an important role in the mammary glands of dairy cows and bta-miR-25 and bta-miR-382 may influence MAPK pathway through c-Jun N-terminal kinase (JNK) gene to affect the function of mammary gland in HS cows. In conclusion, this study characterized expression profile of miRNAs in the Holstein cows' mammary gland under summer heat stress or not. We observed miRNA expression during heat stress, which was significantly different from non-heat stress states. A comprehensive analysis of the miRNA's expression will be helpful to further study the link of miRNAs with mechanisms regulating heat stress in the cow mammary gland. [ABSTRACT FROM AUTHOR]

Designing a material with multiple desired properties is a great challenge, especially in a complex material system. Here, we propose a material design strategy to simultaneously optimize multiple targeted properties of multi-component Co-base superalloys via machine learning. The microstructural stability, γ′ solvus temperature, γ′ volume fraction, density, processing window, freezing range, and oxidation resistance were simultaneously optimized. A series of novel Co-base superalloys were successfully selected and experimentally synthesized from >210,000 candidates. The best performer, Co-36Ni-12Al-2Ti-4Ta-1W-2Cr, possesses the highest γ′ solvus temperature of 1266.5 °C without the precipitation of any deleterious phases, a γ′ volume fraction of 74.5% after aging for 1000 h at 1000 °C, a density of 8.68 g cm−3 and good high-temperature oxidation resistance at 1000 °C due to the formation of a protective alumina layer. Our approach paves a new way to rapidly design multi-component materials with desired multi-performance functionality. [ABSTRACT FROM AUTHOR]

The nucleating, growing and cracking of hydrogen blister have been investigated experimentally and theoretically. The results show that atomic hydrogen induces superabundant vacancies in metals. The superabundant vacancies and hydrogen aggregate into a hydrogen-vacancy cluster (microcavity). The hydrogen atoms in the microcavity become hydrogen molecules which can stabilize the cluster. And the hydrogen blister nucleates. With the entry of vacancies and hydrogen atoms, the blister nucleus grows and the pressure in the cavity increases. When the stress induced by hydrogen pressure on the blister is up to the cohesive strength, cracks will initiate from the wall of the blister. [ABSTRACT FROM AUTHOR]

Propagation process of electrically induced fatigue cracking in BaTiO3 single crystal has been studied using atomic force microscope (AFM). The results show that alternating electric field generates a random domain switching around indentation cracks instead of a cyclic domain switching and an arrest indentation crack can be re-initiated by applying either positive or negative alternating electric field. [ABSTRACT FROM AUTHOR]

The growing process of a hydrogen blister in a wheel steel was observed in situ with an optical microscope, and the fracture surfaces formed from broken blisters on a wheel steel and bulk metallic glass were investigated. The initiating, growing, cracking and breaking of hydrogen blisters are as follows. Supersaturated vacancies can increase greatly during charging and gather together into a vacancy cluster (small cavity). Hydrogen atoms become hydrogen molecules in the vacancy cluster and hydrogen molecules can stabilize the vacancy cluster. The small cavity becomes the nucleus of hydrogen blister. The blister will grow with entering of vacancies and hydrogen atoms. With increasing hydrogen pressure, plastic deformation occurs first, the hydrogen blister near the surface extrudes, and then cracks initiate along the wall of the blister with further increasing hydrogen pressure. A cracked blister can grow further through propagating of cracks until it breaks. [ABSTRACT FROM AUTHOR]

The combined effect of electric and mechanical loading on fracture of a PZT-5 ferroelectric ceramic in silicone oil has been investigated using a single edge notched specimen. The results show that the fracture toughness and the threshold stress intensity factor of delayed fracture in silicone oil, i.e. stress corrosion cracking, decrease linearly with the increasing applied electric field, either positive or negative. For the PZT-5 ferroelectric ceramics, delayed fracture in silicone oil under sustained positive or negative field can occur, and the threshold field for delayed fracture under sustained positive or negative field decreases linearly with applied stress intensity factor. The combined effect of electric and mechanical loading on delayed fracture in silicone oil includes fieldenhancing delayed fracture under sustained load and stress-enhancing delayed fracture in silicone oil under sustained field. [ABSTRACT FROM AUTHOR]

Investigates stress corrosion cracking of a lead zirconate titanate (PZT) ferroelectric ceramics in various media at a constant load test using a single-edge notched tensile specimen. Poling direction parallel to the crack plane; Stress-induced 90 degrees domain switching causing the anisotropy of the PZT.

Threshold stress intensity factor of hydrogen-induced cracking (HIC), K IH, of a lead zirconate titanate ferroelectric ceramics (PZT-5) has been measured during dynamic charging with various current densities at constant load using notched tensile specimens with poling direction parallel or perpendicular to the crack plane. The results show that K IH reveals anisotropy, and the threshold stress intensity factor for the specimen with poling direction parallel to the crack plane, K , is greater than that perpendicular to the crack plane, K , similar to the anisotropy of fracture toughness, K IC. The normalized threshold stress intensity factor of HIC, however, does not reveal anisotropy, and decreass linearly with logarithm of hydrogen concentration, C o, i.e. K / K = K / K =0.4−0.15 In C o. Therefore, the anisotropy of HIC is the same as that of the fracture toughness, and is due to the anisotropy of the stress-induced 90° domain switching. [ABSTRACT FROM AUTHOR]

Using a special TEM constant deflection device, the change in dislocation configuration ahead of a loaded crack tip before and after adsorption of Hg atoms and the initiation of liquid metal-induced nanocracks (LMIC) have been observed. The results show that chemisorption of Hg atoms can facilitate dislocation emission, multiplication and motion. Nanocracks will be initiated in the dislocation-free zone (DFZ) or at the crack tip when chemisorption-facilitated dislocation emission, multiplication and motion reach a critical condition. On the basis of the available experimental evidence concerning liquid metal embrittlement (LME), a new mechanism for this phenomenon is considered. This involves the fact that the decrease in surface energy induced by chemisorption of Hg atoms results in a reduction in the critical stress intensity factors for dislocation emission and the resistance for dislocation motion. On the other hand, the plastic work and K IC will decrease with the decrease in the surface energy. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Recent progress in material data mining has been driven by high-capacity models trained on large datasets. However, collecting experimental data (real data) has been extremely costly owing to the amount of human effort and expertise required. Here, we develop a novel transfer learning strategy to address problems of small or insufficient data. This strategy realizes the fusion of real and simulated data and the augmentation of training data in a data mining procedure. For a specific task of grain instance image segmentation, this strategy aims to generate synthetic data by fusing the images obtained from simulating the physical mechanism of grain formation and the "image style" information in real images. The results show that the model trained with the acquired synthetic data and only 35% of the real data can already achieve competitive segmentation performance of a model trained on all of the real data. Because the time required to perform grain simulation and to generate synthetic data are almost negligible as compared to the effort for obtaining real data, our proposed strategy is able to exploit the strong prediction power of deep learning without significantly increasing the experimental burden of training data preparation. [ABSTRACT FROM AUTHOR]

Metastable ω phase is common in body-centred cubic (bcc) metals and alloys, including high-alloying steels. Recent theoretical calculations also suggest that the ω structure may act as an intermediate phase for face-centred cubic (fcc)-to-bcc transformation. Thus far, the role of the ω phase played in fcc-bcc martensitic transformation in carbon steels has not been reported. In previous investigations on martensitic carbon steels, extra electron diffraction spots were frequently observed by transmission electron microscopy (TEM), and these spots were historically ascribed to the diffraction arising from either internal twins or carbides. In this paper, an intensive TEM investigation revealed that the extra spots are in fact attributed to the metastable ω phase in particle-like morphology with an overall size of several or dozens of nanometres. The strict orientation relationships between the ω phase and the ferrite matrix are in good agreement with those of the hexagonal (P6/mmm) ω phase in other bcc metals and alloys. The identification of the ω phase as well as the extra diffraction spots might provide a clue to help understand the physical mechanism of martensitic transformation in steels. [ABSTRACT FROM AUTHOR]

Finite element analyses were conducted to clarify the role of corrosion product films (CPFs) in stress corrosion cracking (SCC). Flat and U-shaped edge-notched specimens were investigated in terms of the CPF-induced stress in the metallic substrate and the stress in the CPF. For a U-shaped edge-notched specimen, the stress field in front of the notch tip is affected by the Young's modulus of the CPF and the CPF thickness and notch geometry. The CPF-induced tensile stress in the metallic substrate is superimposed on the applied load to increase the crack tip strain and facilitate localized plasticity deformation. In addition, the stress in the CPF surface contributes to the rupture of the CPFs. The results provide physical insights into the role of CPFs in SCC. [ABSTRACT FROM AUTHOR]