Thermodynamic properties of binary HCP solution phases from special quasirandom structures

Three different special quasirandom structures (SQS) of the substitutional hcp $A_{1-x}B_x$ binary random solutions ($x=0.25$, 0.5, and 0.75) are presented. These structures are able to mimic the most important pair and multi-site correlation functions corresponding to perfectly random hcp solutions at those compositions. Due to the relatively small size of the generated structures, they can be used to calculate the properties of random hcp alloys via first-principles methods. The structures are relaxed in order to find their lowest energy configurations at each composition. In some cases, it was found that full relaxation resulted in complete loss of their parental symmetry as hcp so geometry optimizations in which no local relaxations are allowed were also performed. In general, the first-principles results for the seven binary systems (Cd-Mg, Mg-Zr, Al-Mg, Mo-Ru, Hf-Ti, Hf-Zr, and Ti-Zr) show good agreement with both formation enthalpy and lattice parameters measurements from experiments. It is concluded that the SQS's presented in this work can be widely used to study the behavior of random hcp solutions.Comment: 15 pages, 8 figure

First-principles calculation of the instability leading to giant inverse magnetocaloric effects

The structural and magnetic properties of functional Ni-Mn-Z (Z=Ga, In, Sn) Heusler alloys are studied by first-principles and Monte Carlo methods. The ab initio calculations give a basic understanding of the underlying physics which is associated with the strong competition of ferro- and antiferromagnetic interactions with increasing chemical disorder. The resulting d-electron orbital dependent magnetic ordering is the driving mechanism of magnetostructural instability which is accompanied by a drop of magnetization governing the size of the magnetocaloric effect. The thermodynamic properties are calculated by using the ab initio magnetic exchange coupling constants in finite-temperature Monte Carlo simulations, which are used to accurately reproduce the experimental entropy and adiabatic temperature changes across the magnetostructural transition

Experiment Design Frameworks for Accelerated Discovery of Targeted Materials Across Scales

Over the last decade, there has been a paradigm shift away from labor-intensive and time-consuming materials discovery methods, and materials exploration through informatics approaches is gaining traction at present. Current approaches are typically centered around the idea of achieving this exploration through high-throughput (HT) experimentation/computation. Such approaches, however, do not account for the practicalities of resource constraints which eventually result in bottlenecks at various stage of the workflow. Regardless of how many bottlenecks are eliminated, the fact that ultimately a human must make decisions about what to do with the acquired information implies that HT frameworks face hard limits that will be extremely difficult to overcome. Recently, this problem has been addressed by framing the materials discovery process as an optimal experiment design problem. In this article, we discuss the need for optimal experiment design, the challenges in it's implementation and finally discuss some successful examples of materials discovery via experiment design

A deep neural network regressor for phase constitution estimation in the high entropy alloy system Al-Co-Cr-Fe-Mn-Nb-Ni

Abstract High Entropy Alloys (HEAs) are composed of more than one principal element and constitute a major paradigm in metals research. The HEA space is vast and an exhaustive exploration is improbable. Therefore, a thorough estimation of the phases present in the HEA is of paramount importance for alloy design. Machine Learning presents a feasible and non-expensive method for predicting possible new HEAs on-the-fly. A deep neural network (DNN) model for the elemental system of: Mn, Ni, Fe, Al, Cr, Nb, and Co is developed using a dataset generated by high-throughput computational thermodynamic calculations using Thermo-Calc. The features list used for the neural network is developed based on literature and freely available databases. A feature significance analysis matches the reported HEAs phase constitution trends on elemental properties and further expands it by providing so far-overlooked features. The final regressor has a coefficient of determination (r 2) greater than 0.96 for identifying the most recurrent phases and the functionality is tested by running optimization tasks that simulate those required in alloy design. The DNN developed constitutes an example of an emulator that can be used in fast, real-time materials discovery/design tasks

Out-of-plane ordering in quaternary MAX alloys: an alloy theoretic perspective

This letter is motivated by an apparent paradox, in that some quaternary systems (particularly in the Ti–Zr–Al–C system) have been shown to exhibit M-site out-of-plane ordering, while prior work and calculations by the present authors suggest endothermic interactions between Zr and Ti. In this letter we provide a resolution to this issue and provide a more extended analysis on the out-of-plane and in-plane ordering in the M sites of quaternary MAX alloys. The results provide further insights to develop criteria to predict potential out-of-plane ordering tendencies in other MAX systems.fx

High throughput exploration of the oxidation landscape in high entropy alloys

High entropy alloys (HEAs) have gained interest for structural applications in extreme environments. With a potentially vast chemical and phase space, there are significant opportunities to discover superior performing alloys. Crucial for most high-temperature applications is understanding and mitigating the oxidation behavior of these chemically complex alloys. Most experimental and computational HEA studies have focused on a limited set of compositions and only a fraction of these compositions have been characterized for oxidation. We present a high-throughput framework that utilizes density-functional theory (DFT) in concert with a combined machine-learning model and grand-canonical linear programming for assessing phase stability, phase-fraction, chemical activity and high-temperature survivability of arbitrary HEAs. This framework considers temperature dependent contributions to the Gibbs energy of the competing phases arising from short-range order and vibrational entropy. We demonstrate the effectiveness of the framework by assessing the thermodynamic stability, oxidation behavior, chemical activity, and phase decomposition of body-centered cubic Mo–W–Ta–Ti–Zr refractory HEAs. A total of 51 compositions were analyzed and ranked in order of their survivability based on the Pareto-front analysis. Oxidation was performed at 1373 K on four samples in air showing the difference in oxidation behavior determined experimentally through scale thickness and their mass changes. The insights on oxidation behavior presented in this work will enable the fast assessment of technologically useful HEAs needed for future structural application in extreme conditions.This is a manuscript of an article published as Sauceda, D., P. Singh, G. Ouyang, O. Palasyuk, M. J. Kramer, and R. Arróyave. "High throughput exploration of the oxidation landscape in high entropy alloys." Materials Horizons 9, no. 10 (2022): 2644-2663. DOI: 10.1039/D2MH00729K. Copyright 2022 The Royal Society of Chemistry. Posted with permission. DOE Contract Number(s): AR0001427; AC02-07CH11358; DGE-1545403

Describing the deformation behaviour of TRIP and dual phase steels employing an irreversible thermodynamics formulation

The plastic deformation of multiphase steels is described employing an irreversible thermodynamics formulation. Transformation induced plasticity and dual phase grades are described within a single theoretical framework. The approach describes the plastic deformation of each individual phase in terms of the evolution of dislocation density, subject to dissipative mechanisms associated to dislocation generation, glide and annihilation. The collective behaviour of the ensemble of phases into a single microstructure is ensured through a self-consistent approach based on the iso-work approximation. The parameterised model shows very good agreement with several alloys studied experimentally and available in the literature

Does aluminum play well with others? Intrinsic Al-A alloying behavior in 211/312 MAX phases

<p>The search for further control over the properties of MAX phases as well as the promise of discovering compounds with new functionalities has resulted in an increased interest in MAX solid solutions resulting from mixing in either the M, A, or X sublattices. The possibility of alloying MAX compounds not only enables finer tuning of their properties but can also be used to stabilize compounds that may otherwise be metastable in their pure state. In this letter, we present an <i>ab initio</i>-based investigation of the intrinsic alloying behavior in the A sublattice of Ti(Al,A)C, Zr(Al,A)C and Ti(Al,A)C MAX compounds.</p> <p><b>IMPACT STATEMENT</b></p> <p>In this work, we present for the first time a comprehensive study of the intrinsic alloying tendencies in MAX solid solutions with (Al,A) mixing in the A sublattice.</p