相关论文: Surface segregation in high-entropy alloys from al…
High-entropy alloys (HEAs) are promising materials for high-temperature structural applications such as nuclear reactors due to their outstanding mechanical properties and thermal stability. Instead of the trial-and-error method, it is…
High-entropy alloys (HEAs) are complex alloys containing multiple elements in high concentrations. Plasticity in HEAs is carried by dislocations, but the random nature of their composition pins dislocations, effectively hindering their…
In this paper we investigate by means of first-principles density functional theory calculations the (111) surface of the Ag-Cu alloy under varying conditions of pressure of the surrounding oxygen atmosphere and temperature. This alloy has…
High-entropy alloys (HEAs) are attracting attention due to their exceptional properties, such as enhanced mechanical toughness, superconducting robustness, and thermoelectric performance. Numerous HEAs have been developed for diverse…
High entropy alloys (HEAs) have attracted substantial interest in recent years. Thus far, most investigations have focused on their applications as structural materials rather than functional materials. In this paper, we show that…
High-entropy alloys (HEAs) and their two-dimensional counterparts (2D-HEAs) have recently attracted attention due to their tunable properties and catalytic potential, yet their chemical complexity makes direct density functional theory…
Machine learning (ML) can facilitate efficient thermoelectric (TE) material discovery essential to address the environmental crisis. However, ML models often suffer from poor experimental generalizability despite high metrics. This study…
The design of corrosion-resistant high entropy alloys (CR-HEAs) is challenging due to the alloys' virtually astrological composition space. To facilitate this, efficient and reliable high-throughput exploratory approaches are needed. Toward…
Engineering liquid metal alloys offers a transformative pathway for plasma-facing components (PFC) by enabling chemically tailored surfaces that can simultaneously optimize plasma-material interactions, reduce divertor heat flux, and…
High-entropy materials have emerged as a promising class of catalysts, driven by their high configurational entropy originating from structural disorder in single-phase multicomponent systems. Despite their potential, the catalytic…
We show that the magnetic properties of high-entropy alloys (HEAs) can be captured by \textit{ab initio} calculations within the coherent potential approximation, where the atomic details of the high-entropy mixing are considered as an…
We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning approaches in rare-earth intermetallic design have been…
High-entropy alloys (HEAs), as multi-component materials with high configurational entropy, have garnered significant attention as new biomaterials; still, their low yield stress and high elastic modulus need to be overcome for future…
Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen…
The development of machine learning sheds new light on the problem of statistical thermodynamics in multicomponent alloys. However, a data-driven approach to construct the effective Hamiltonian requires sufficiently large data sets, which…
Do high-entropy alloys and ceramics have their grain boundary (GB) counterparts? As the concept of high-entropy grain boundaries (HEGBs) was initially proposed in 2016, this article provides the first complete and rigorous discussion of the…
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,…
Refractory multi-principal element alloys (RMPEAs) represent a novel class of alloys characterized by an extensive compositional design space and the potential for exceptional mechanical performance under extreme conditions. While accurate…
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…
Segregation and dissolution behavior of Mg alloyed with Ca and Al are studied by performing density functional theory calculations considering an extensive set of surface structures and compositions. Combining ab initio surface science…