Related papers: Composition Design of Shape Memory Ceramics based …
Developing high-entropy ceramics (HECs) with ultra-high melting points (Tm) is crucial for their applications in ultra-high-temperature environments. However, related research has seldom been reported. Here, taking high-entropy diborides…
With the advent of powerful computer simulation techniques, it is time to move from the widely used knowledge-guided empirical methods to approaches driven by data science, mainly machine learning algorithms. We investigated the predictive…
The expansiveness of compositional phase space is too vast to fully search using current theoretical tools for many emergent problems in condensed matter physics. The reliance on a deep chemical understanding is one method to identify local…
Numerical simulations of high energy-density experiments require equation of state (EOS) models that relate a material's thermodynamic state variables -- specifically pressure, volume/density, energy, and temperature. EOS models are…
We use a random forest model to predict the critical cooling rate (RC) for glass formation of various alloys from features of their constituent elements. The random forest model was trained on a database that integrates multiple sources of…
The martensitic start temperature ($M_{\text{s}}$) is a technologically fundamental characteristic of high-temperature shape memory alloys. We have recently shown [Phys. Rev. B 94, 224104 (2016)] that the two key features in describing the…
The identification and use of reversible Martensitic transformations, typically described as shape memory transformations, as a new class of solid-solid phase change material is experimentally demonstrated here for the first time. To prove…
The paper is devoted to the study of a mathematical model for the thermomechanical evolution of metallic shape memory alloys. The main novelty of our approach consists in the fact that we include the possibility for these materials to…
Magnetic shape memory alloys are characterized by the coupling between a structural phase transition and magnetic one. This permits to control the shape change via an external magnetic field, at least in single crystals. Composite materials…
Accurate and fast prediction of materials properties is central to the digital transformation of materials design. However, the vast design space and diverse operating conditions pose significant challenges for accurately modeling arbitrary…
The thermal memory effect, TME, has been studied in Ni55Fe19Ga26 shape memory alloys, fabricated as ribbons via melt-spinning and as pellets via arc-melting, to evaluate its dependence on the martensitic structure and the macrostructure of…
Using a modified Lennard-Jones model for elliptic particles and spherical impurities, we present results of molecular dynamics simulation in two dimensions. In one-component systems of elliptic particles, we find an orientation phase…
We construct a holographic QCD model based on the Einstein--dilaton--flavor framework with 2+1 flavors and investigate its phase structure using machine-learning techniques. At zero chemical potential, the model reproduces the equation of…
We present thermodynamic crystallization and melting models and calculate phase change velocities in $Ge_2 Sb_2 Te_5$ based on kinetic and thermodynamic parameters. The calculated phase change velocities are strong functions of grain size,…
Predicting solid-solid phase transitions remains a long-standing challenge in materials science. Solid-solid transformations underpin a wide range of functional properties critical to energy conversion, information storage, and thermal…
The athermal quasistatic (AQS) method is a powerful technique to study the mechanical behavior of disordered systems. However, its applicability is limited to temperatures near zero, where thermal activation is unlikely. In this work, we…
The lattice thermal conductivity ($\kappa$) of two ceramic materials, cerium dioxide (CeO$_2$) and magnesium oxide (MgO), is computed up to 1500 K using first principles and the phonon Boltzmann Transport Equation (PBTE) and compared to…
The magnetic properties of a material are determined by a subtle balance between the various interactions at play, a fact that makes the design of new magnets a daunting task. High-throughput electronic structure theory may help to explore…
Achieving desired mechanical properties in additive manufacturing requires many experiments and a well-defined design framework becomes crucial in reducing trials and conserving resources. Here, we propose a methodology embracing the…
In this paper we introduce a 3D phenomenological model for shape memory behavior, accounting for: martensite reorientation, asymmetric response of the material to tension/compression, different kinetics between forward and reverse phase…