相关论文: Grain Boundary Segregation Spectra from a Generali…
High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development…
Achieving a combination of high mechanical strength and high electrical conductivity in low-weight Al alloys requires a full understanding of the relationships between nanoscaled features and physical properties. Grain boundary…
Refractory multi-principal element alloys exhibiting promising mechanical properties such as excellent strength retention at elevated temperatures have been attracting increasing attention. Although their inherent chemical complexity is…
Grain boundaries (GBs) govern critical properties of polycrystals. Although significant advancements have been made in characterizing minimum energy GBs, real GBs are seldom found in such states, making it challenging to establish…
Grain boundary diffusion in severely deformed Al-based AA5024 alloy is investigated. Different states are prepared by combination of equal channel angular processing and heat treatments, with the radioisotope $^{57}$Co being employed as a…
It is believed that grain boundary segregation of light interstitials can serve as possible mechanism of thermal stability in commercially pure nanostructured titanium alloys. In this paper, using first-principles calculations, we show that…
An age-hardenable Al-Cu-Mg alloy (A2024) was processed by high-pressure torsion (HPT) for producing an ultrafine-grained structure. The alloy was further aged for extra strengthening. The tensile strength then reached a value as high as ~1…
Grain size engineering, particularly reducing grain size into the nanocrystalline regime, offers a promising pathway to further improve the strength-to-weight ratio of Al alloys. Unfortunately, the fabrication of nanocrystalline metals…
The segregation of solutes to grain boundaries can significantly influence material behavior. Most previous computational studies have concentrated on substitutional solute segregation, neglecting interstitial segregation due to its…
Segregation-induced structural transitions in metallic grain boundaries are studied with hybrid atomistic Monte Carlo/molecular dynamics simulations using Cu-Zr as a model system, with a specific emphasis on understanding the effect of…
Solute segregation plays an important role in formation of long-period stacking ordered (LPSO) structure in Mg-M-RE (M: Zn, Ni etc., RE: Y, Gd, etc.) alloy systems. In this work, the planar segregation in Mg-Al-Gd alloy is characterized by…
We propose machine learning (ML) models to predict the electron density -- the fundamental unknown of a material's ground state -- across the composition space of concentrated alloys. From this, other physical properties can be inferred,…
Grain boundaries (GBs) and interfaces in polycrystalline materials are significant research subjects in the field of materials science. Despite a more than 50-year history of their study, there are still many open questions. The main…
Resorbable magnesium (Mg) alloys are promising candidates for temporary medical devices due to their biodegradability and favorable mechanical properties. To accelerate the design of diluted Mg alloys for implants, we developed a…
Machine learning potentials (MLPs) have become indispensable for performing accurate large-scale atomistic simulations and predicting crystal structures. This study introduces the development of a polynomial MLP specifically for the ternary…
With the rapid development of artificial intelligence, the combination of material database and machine learning has driven the progress of material informatics. Because aluminum alloy is widely used in many fields, so it is significant to…
Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicability. Here, we present a feasible approach for constructing a…
New refractory alloys are being continuously designed and characterised for applications requiring good high-temperature mechanical properties and stability. Computational design from atomistic simulations is limited by interatomic…
Grain boundaries control a wide variety of bulk properties in polycrystalline materials, so simulation methods like density functional theory are routinely used to study their structure-property relationships. A standard practice for such…
Active learning (AL) can drastically accelerate materials discovery; its power has been shown in various classes of materials and target properties. Prior efforts have used machine learning models for the optimal selection of physical…