Related papers: Grain Boundary Segregation Spectra from a Generali…
Thermodynamics is fundamental for understanding and synthesizing multi-component materials, while efficient and accurate prediction of it still remain urgent and challenging. As a demonstration of the "Divide and conquer" strategy…
This study presents a machine learning approach to predict the Curie temperature in binary alloys, specifically focusing on the Fe-Pt, Fe-Ni, Fe-Pd, and Co-Pt compounds within a concentration range of 10 to 90 atomic percent. The optimal…
The space of possible grain boundary structures is vast, with 5 macroscopic, crystallographic degrees of freedom that define the character of a grain boundary. While numerous datasets of grain boundaries have examined this space in part or…
Over the past decade inter-atomic potentials based on machine-learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure…
Models of grain boundary energy are essential for predicting the behavior of polycrystalline materials. Typical models represent the minimum boundary energy as a function of macroscopic boundary parameters. An energy model may allow for…
There are still debates regarding the mechanisms that lead to hot cracking in parts build by additive manufacturing (AM) of non-weldable Ni-based superalloys. This lack of in-depth understanding of the root causes of hot cracking is an…
Local chemical ordering strongly influences the behavior of complex concentrated alloys, yet its characterization remains challenging due to the nanoscale dimensions and scattered spatial distribution of the ordered domains. Here, we study…
Grain growth simulation is crucial for predicting metallic material microstructure evolution during annealing and resulting final mechanical properties, but traditional partial differential equation-based methods are computationally…
Density functional theory and its optimization algorithm are the main methods to calculate the properties in the field of materials. Although the calculation results are accurate, it costs a lot of time and money. In order to alleviate this…
Segregated impurities at grain boundaries can dramatically change the mechanical behavior of metals, while the mechanism is still obscure in some cases. Here, we suggest an unified approach to investigate segregation and its effects on the…
A set of Modified Embedded Atom Method (MEAM) potentials for the interactions between Al, Si, Mg, Cu, and Fe was developed from a combination of each element's MEAM potential in order to study metal alloying. Previously published MEAM…
This study advances our understanding of how chemical binding and solute distribution impact grain boundary segregation behavior and subsequent annealing texture modification in lean Mg-X-Zn alloys (X = RE or Ca). Notably, differences in Ca…
Materials properties depend strongly on chemical composition, i.e., the relative amounts of each chemical element. Changes in composition lead to entirely different chemical arrangements, which vary in complexity from perfectly ordered…
We investigate the structural and dynamical properties of binary aluminum-titanium liquid metallic alloys, as a function of temperature and composition. We make use of MD-simulations, using a transferable machine-learning potential…
The use of machine learning (ML) algorithms in molecular simulations has become commonplace in recent years. There now exists, for instance, a multitude of ML force field algorithms that have enabled simulations approaching ab initio level…
Grain boundary (GB) energy is a fundamental property that affects the form of grain boundary and plays an important role to unveil the behavior of polycrystalline materials. With a better understanding of grain boundary energy distribution…
Nanoparticle superlattices consisting of ordered arrangements of nanoparticles exhibit unique optical, magnetic, and electronic properties arising from nanoparticle characteristics as well as their collective behaviors. Understanding how…
With the high-resolution spectroscopy now available in the optical and satellite UV, it is possible to determine the neutral/ionized column density ratios for several different elements in a single cloud. Assuming ionization equilibrium for…
Calibration models have been developed for determination of trace elements, silver for instance, in soil using laser-induced breakdown spectroscopy (LIBS). The major concern is the matrix effect. Although it affects the accuracy of LIBS…
We present a multiscale modelling framework that integrates density functional theory (DFT) with a phase-field model (PFM) to explore the intricate dynamics of grain growth in nanocrystalline {\alpha}-Fe single-phase alloy in the presence…