A machine learning approach to predict the structural and magnetic properties of Heusler alloy families

Mitra, Srimanta; Ahmad, Aquil; Biswas, Sajib; Das, A. K.

doi:10.1016/j.commatsci.2022.111836

Cited by 8 publications

(6 citation statements)

References 125 publications

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“…where n is the total number of samples; RSS and TSS represent the residual sum of squares and the total sum of squares, respectively; ŷi denotes the predicted value of the ith sample; and y i , y are the measured values of the ith sample and the mean of the measured values, respectively. However, a higher value of positive R 2 does not necessarily imply a better goodness of fit, as the degree of freedom also affects the R 2 value, which will increase if more parameters are introduced, but this does not imply a better goodness of fit [36]. Thus, we used the adjusted R 2 as a modified version of R 2 accounting for the degrees of freedom to compare the goodness of fit of the different PSD functions in this study.…”

Section: Shape or Locationmentioning

confidence: 99%

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Particle Size Distributions and Extinction Coefficients of Aerosol Particles in Land Battlefield Environments

Gao,

Chen,

Chen

et al. 2023

Remote Sensing

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In land battlefield environments, aerosol particles can cause laser beams to undergo attenuation, thus deteriorating the operational performance of military laser devices. The particle size distribution (PSD) and extinction coefficient are key optical properties for assessing the attenuation characteristics of laser beams caused by aerosol particles. In this study, we employed the laser diffraction method to measure the PSDs of graphite smoke screen, copper powder smoke screen, iron powder smoke screen, ground dust, and soil explosion dust. We evaluated the goodness of fit of six common unimodal PSD functions and a bimodal lognormal PSD function employed for fitting these aerosol particles using the root mean square error (RMSE) and adjusted R2, and selected the optimal PSD function to evaluate their extinction coefficients in the laser wavelength range of 0.249~12 μm. The results showed that smoke screens, ground dust, and soil explosion dust exhibited particle size ranges of 0.7~50 µm, 1~400 µm, and 1.7~800 μm, respectively. The lognormal distribution had the best goodness of fit for fitting the PSDs of these aerosol particles in the six unimodal PSD functions, followed by the gamma and Rosin–Rammler distributions. For the bimodal aerosol particles with a lower span, the bimodal lognormal PSD functions exhibited the best goodness of fit. The graphite smoke screen exhibited the highest extinction coefficient, followed by the copper and iron powder smoke screens. In contrast, the ground dust and soil explosion dust exhibited the lowest extinction coefficients, reaching their minimum values at a wavelength of approximately 8.2 μm. This study provides a basis for analyzing and improving the detection and recognition performance of lasers in land battlefield environments.

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Section: Shape or Locationmentioning

confidence: 99%

“…Thus, we used the adjusted R 2 as a modified version of R 2 accounting for the degrees of freedom to compare the goodness of fit of the different PSD functions in this study. The adjusted R 2 can be expressed as follows [36]:…”

Section: Shape or Locationmentioning

confidence: 99%

Particle Size Distributions and Extinction Coefficients of Aerosol Particles in Land Battlefield Environments

Gao,

Chen,

Chen

et al. 2023

Remote Sensing

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“…Giant Magnetoresistance (GMR) and Tunnel Magnetoresistance are the first manifestations of spintronics [1–3]. A systematic process is followed to predict the structural and magnetic properties of different types of quaternary Heusler alloys, using an automatic computer learning technique, these robust algorithms simulate the evolution of grain microstructure under thermomechanical loads [4, 5]. These alloys are based on a quaternary system of stoichiometric composition with a general formula X 2 YZ.…”

Section: Introductionmentioning

confidence: 99%

A comparative study of physical and thermoelectrical characteristics of the new full‐Heusler alloys Ag₂TiGa and Ag₂VGa with ab initio calculations

Elkoua,

Masrour

2023

Int J of Quantum Chemistry

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This paper will focus on the comparative study of the structural, electronic, magnetic, optical, and thermoelectric properties of the two Heusler systems Ag2TiGa and Ag2VGa in the inverse L21 Hg2CuTi structure. Using the density functional theory‐based wien2k code, which implements the computational methods used in this study, namely GGA, GGA‐mBJ, GGA + U, and GGA + SOC (spin‐orbit coupling). The band structures show that all two structures studied are metallic. The spin density of states of Ag2VGa has evident spin splitting near the Fermi level, and the total magnetic moment of the Ag2VGa structure is 2.19 μB, which indicates that Ag2VGa is magnetic. The full‐Heusler Ag2VGa material can be used as spintronic materials due to their high spin polarization (about 50%). While Ag2TiGa has low polarization so it is bad electronically, but better thermoelectrically than Ag2VGa. So, the full‐Heusler Ag2TiGa material may also be considered as a potential candidate for thermoelectric applications at room temperature. Studies of the two new Heusler alloys may provide a theoretical reference for subsequent theoretical research and experimental synthesis of Ag‐based Heusler alloys.

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“…In addition, machine-learning methods could be used to overcome the number of combinations to be calculated, as shown by Bartel et al For the prediction of Heusler stability, compounds have been screened by Gzyl et al and, more rarely, on quaternary Heuslers learned from a large DFT database that is not consistently calculated on a single phase. Other predictions of properties such as magnetic moment, lattice parameters, and phonon force have been made on quaternary Heusler materials. However, to the best of our knowledge, the combined stability with the prediction of electronic properties of Heusler materials, such as semiconducting properties, has never been fully investigated.…”

Section: Introductionmentioning

confidence: 99%

Screening New Quaternary Semiconductor Heusler Compounds By Machine-Learning Methods

Xie,

Crivello,

Barreteau

2023

Chem. Mater.

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The following work presents a theoretical workflow to accelerate the discovery of new quaternary Heusler compounds for thermoelectric applications. The process consists of several steps: (i) construction of a consistent home-made DFT learning database with a limited set of compounds mainly involving unary, binary, and ternary configurations; (ii) machine-learning regression to estimate the heat of formation for all possible arrangements of atoms in the 4 crystallographic sites of the Heusler phase; (iii) classification learning to predict the semiconductor (SC) feature; (iv) verification of stable SC compounds through a convex hull analysis of the ground state for each quaternary system; and (v) phonon calculation to check the mechanical stabilities of the final candidates. From a selection of 24 chemical elements, 13 272 unique DFT calculations were performed among all 244 = 331 776 configurations. The learning and screening process led to predict the properties of all quaternaries (24 × 23 × 22 × 21 = 255 024) along with the discovery of 8 new stable semiconducting compounds (TaAlCoMn, TaSiFeMn, NbAlCoMn, NbSiFeMn, ···), promising potential interest in thermoelectric properties.

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A machine learning approach to predict the structural and magnetic properties of Heusler alloy families

Cited by 8 publications

References 125 publications

Particle Size Distributions and Extinction Coefficients of Aerosol Particles in Land Battlefield Environments

Particle Size Distributions and Extinction Coefficients of Aerosol Particles in Land Battlefield Environments

A comparative study of physical and thermoelectrical characteristics of the new full‐Heusler alloys Ag₂TiGa and Ag₂VGa with ab initio calculations

Screening New Quaternary Semiconductor Heusler Compounds By Machine-Learning Methods

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A machine learning approach to predict the structural and magnetic properties of Heusler alloy families

Cited by 8 publications

References 125 publications

Particle Size Distributions and Extinction Coefficients of Aerosol Particles in Land Battlefield Environments

Particle Size Distributions and Extinction Coefficients of Aerosol Particles in Land Battlefield Environments

A comparative study of physical and thermoelectrical characteristics of the new full‐Heusler alloys Ag2TiGa and Ag2VGa with ab initio calculations

Screening New Quaternary Semiconductor Heusler Compounds By Machine-Learning Methods

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A comparative study of physical and thermoelectrical characteristics of the new full‐Heusler alloys Ag₂TiGa and Ag₂VGa with ab initio calculations