scholarly journals A Ternary Map of Ni–Mn–Ga Heusler Alloys from Ab Initio Calculations

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 973
Author(s):  
Yulia Sokolovskaya ◽  
Olga Miroshkina ◽  
Danil Baigutlin ◽  
Vladimir Sokolovskiy ◽  
Mikhail Zagrebin ◽  
...  

In the search for new magnetic functional materials, non-stoichiometric compounds remain a relatively unexplored territory. While experimentalists create new compositions looking for improved functional properties, their work is not guided by systematic theoretical predictions. Being designed for perfect periodic crystals, the majority of first-principles approaches struggle with the concept of a non-stoichiometric system. In this work, we attempt a systematic computational study of magnetic and structural properties of Ni–Mn–Ga, mapped onto ternary composition diagrams. Compositional stability was examined using the convex hull analysis. We show that the cubic austenite has its stability region close to the stoichiometric Ni2MnGa, in agreement with experimental data, while the tetragonal martensite spreads its stability over a wider range of Mn and Ni contents. The unstable compositions in both austenite and martensite states are located in the Ga-rich corner of the ternary diagram. We note that simultaneous stability of the austenite and martensite should be considered for potentially stable compounds suitable for synthesis. The majority of compounds are predicted to be ferrimagnetically ordered in both austenitic and martensitic states. The methodology used in this work is computationally tractable, yet it delivers some predictive power. For experimentalists who plan to synthesize stable Ni–Mn–Ga compounds with ferromagnetic order, we narrow the target compositional range substantially.

Author(s):  
Levan Chkhartishvili

Materials atomic structure, ground-state and physical properties as well as their chemical reactivity mainly are determined by electronic structure. When first-principles methods of studying the electronic structure acquire good predictive power, the best approach would be to design new functional materials theoretically and then check experimentally only most perspective ones. In the paper, the semi-classical model of multi-electron atom is constructed, which makes it possible to calculate analytically (in special functions) the electronic structure of atomic particles themselves and materials as their associated systems. Expected relative accuracy makes a few percent, what is quite acceptable for materials science purposes.


2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>


2021 ◽  
Vol 26 ◽  
pp. e00539
Author(s):  
Jonah Nagura ◽  
Timothy M. Ashani ◽  
Paul O. Adebambo ◽  
F. Ayedun ◽  
Gboyega A. Adebayo

2020 ◽  
Vol 8 ◽  
Author(s):  
Christopher Sutton ◽  
Sergey V. Levchenko

In most applications, functional materials operate at finite temperatures and are in contact with a reservoir of atoms or molecules (gas, liquid, or solid). In order to understand the properties of materials at realistic conditions, statistical effects associated with configurational sampling and particle exchange at finite temperatures must consequently be taken into account. In this contribution, we discuss the main concepts behind equilibrium statistical mechanics. We demonstrate how these concepts can be used to predict the behavior of materials at realistic temperatures and pressures within the framework of atomistic thermodynamics. We also introduce and discuss methods for calculating phase diagrams of bulk materials and surfaces as well as point defect concentrations. In particular, we describe approaches for calculating the configurational density of states, which requires the evaluation of the energies of a large number of configurations. The cluster expansion method is therefore also discussed as a numerically efficient approach for evaluating these energies.


Author(s):  
S. Ghosh ◽  
Suraj N. Mali ◽  
D.N. Bhowmick ◽  
Amit P. Pratap

2017 ◽  
Vol 121 (8) ◽  
pp. 4139-4145 ◽  
Author(s):  
Rohit Batra ◽  
Tran Doan Huan ◽  
Jacob L. Jones ◽  
George Rossetti ◽  
Rampi Ramprasad

Sign in / Sign up

Export Citation Format

Share Document