Related papers: Linking Order to Strength in Metals
Steels, and in particular stainless steels, play a crucial role in the construction of large particle accelerators and high-energy physics experiments, of fusion reactors and their superconducting magnet structures. Such projects face…
We describe a first-principles statistical mechanics method to calculate the free energies of crystalline alloys that depend on temperature, composition, and strain. The approach relies on an extension of the alloy cluster expansion to…
As pointed out by Linus Pauling in his classic work on the relationship between crystal packing and ionic radius ratio, a difference in atomic size can be accommodated more readily by an ordered structure than by a disordered one. Because…
High-entropy materials shift the traditional materials discovery paradigm to one that leverages disorder, enabling access to unique chemistries unreachable through enthalpy alone. We present a self-consistent approach integrating…
A recent paper by Juntao Huo et al [Chin. Phys. Lett. 39 (2022) 0464011] reported a correlation between the entropy of mixing (and the corresponding energy state) and the thermal stability and mechanical parameters, for three Zr-Ti-Cu-Ni-Be…
Phase diagrams exhibiting extended solid-solution and lens-like melting are often reproduced using ideal solutions, where ideal mixing considers a fully random configurational entropy of mixing. In the field of irreversible thermodynamics,…
High-order harmonic generation (HHG) is a powerful tool for probing electronic structure and ultrafast dynamics in matter. Traditionally studied in atomic and molecular gases, HHG has recently been extended to condensed matter, enabling…
Disordered systems like liquids, gels, glasses, or granular materials are not only ubiquitous in daily life and in industrial applications but they are also crucial for the mechanical stability of cells or the transport of chemical and…
The development of high-entropy alloys (HEAs) has marked a paradigm shift in alloy design, moving away from traditional methods that prioritize a dominant base metal enhanced by minor elements. HEAs instead incorporate multiple alloying…
To describe chemical ordering in solid solutions systems Warren-Cowley short-range parameters are ordinarily used. However, they are not directly suited for application to long-range ordered systems, as they do not converge to zero for…
Disorder can have a dominating influence on correlated and quantum materials leading to novel behaviors which have no clean limit counterparts. In magnetic systems, spin and exchange disorder can provide access to quantum criticality,…
Porous metallic structures are regularly used in electrochemical energy storage devices as supports, current collectors or active electrode materials. Bulk metal porosification, dealloying, welding or chemical synthesis routes involving…
The reason behind the remarkable properties of High-Entropy Alloys (HEAs) is rooted in the diverse phases and the crystal structures they contain. In the realm of material informatics, employing machine learning (ML) techniques to classify…
We report results of non-equilibrium molecular dynamics simulations of a one-component glassy system under the influence of a shear flow, with the aim of investigating shear induced ordering of this system. In spite of the very low…
We introduce highly optimized tolerance (HOT), a mechanism that connects evolving structure and power laws in interconnected systems. HOT systems arise, e.g., in biology and engineering, where design and evolution create complex systems…
Traditionally, increasing compositional complexity and chemical diversity of high entropy alloy ceramics whilst maintaining a stable single-phase solid solution has been a primary design strategy for the development of new ceramics.…
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…
Self-organization is frequently observed in active collectives, from ant rafts to molecular motor assemblies. General principles describing self-organization away from equilibrium have been challenging to identify. We offer a unifying…
The complicated mesoscopic configurations of composite plate and shell structures requires a huge amount of computational overhead for directly simulating their mechanical problems. In this paper, a unified high-order multi-scale method,…
Machine learning (ML) is shown to predict new alloys and their performances in a high dimensional, multiple-target-property design space that considers chemistry, multi-step processing routes, and characterization methodology variations. A…