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RESEARCH PAPER · The Journal of Physical Chemistry B · 2017

Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus ab Initio Methods

Fleur Legrain, Jesús Carrete, Ambroise van Roekeghem, Georg K. H. Madsen, Natalio Mingo

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Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus ab Initio MethodsOriginalDiscovery of Intermetallic Compounds from Traditional to Machine-Learning Approaches145Machine learning material properties from the periodic table using convolutional neural networks115Predictions of new AB O 3 perovskite compounds by combining machine learning and density functional theory183Applying machine learning techniques to predict the properties of energetic materials263Machine learning for molecular and materials science4884Recent Advances in Thermoelectric Performance of Half-Heusler Compounds95Survey of ab initio phonon thermal transport175Machine learning in materials design and discovery: Examples from the present and suggestions for the future198A Study of the Utility of a Machine-Learning Approach Applied to the Prediction of Site Occupancy and New Members of the Half-Heusler Family0Machine learning for renewable energy materials312Thermoelectric transport trends in group 4 half-Heusler alloys22Materials informatics: From the atomic-level to the continuum189From DFT to machine learning: recent approaches to materials science–a review848A theoretical analysis of elastic and optical properties of half Heusler MCoSb (M=Ti, Zr and Hf)73First-principles prediction of magnetically ordered half-metals above room temperature24Solving the Coloring Problem in Half-Heusler Structures: Machine-Learning Predictions and Experimental Validation29Electrical Property Dominated Promising Half-Heusler Thermoelectrics through High-Throughput Material Computations42Named Entity Recognition and Normalization Applied to Large-Scale Information Extraction from the Materials Science Literature307Half Heusler compounds: promising materials for mid-to-high temperature thermoelectric conversion89Data-Driven Discovery of Photoactive Quaternary Oxides Using First-Principles Machine Learning49Prediction of new iodine-containing apatites using machine learning and density functional theory17Machine learning in materials science1057Inverse Design of Solid-State Materials via a Continuous Representation379Thermoelectric transport trends in group 4 half-Heusler alloys28Determination of structural disorder in Heusler-type phases17Machine Learning Approaches for Thermoelectric Materials Research231Bayesian Global Optimization applied to the design of shape-memory alloys6Learning with Large Databases0Searching high spin polarization ferromagnet in Heusler alloy via machine learning19A Critical Review of Machine Learning of Energy Materials605Characterization of rattling in relation to thermal conductivity: Ordered half-Heusler semiconductors79Data-driven prediction of diamond-like infrared nonlinear optical crystals with targeting performances28Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods10Discovering Intermetallics Through Synthesis, Computation, and Data‐Driven Analysis29Investigation of structural, electronic, magnetic and lattice dynamical properties for XCoBi (X: Ti, Zr, Hf) Half-Heusler compounds52Opportunities and Challenges for Machine Learning in Materials Science522Big-Data Science in Porous Materials: Materials Genomics and Machine Learning597Experimental inspection of a computationally-designed NiCrMnSi Heusler alloy with high Curie temperature5Key Role of Defects in Thermoelectric Performance of TiMSn (M = Ni, Pd, and Pt) Half-Heusler Alloys32Adaptive machine learning for efficient materials design31Computer-Aided Design of Compounds with Crystal Structure of Melilites1Half-Heusler Structures with Full-Heusler Counterparts: Machine-Learning Predictions and Experimental Validation44Predicting Inorganic Photovoltaic Materials with Efficiencies >26% via Structure-Relevant Machine Learning and Density Functional Calculations28Prediction of the Properties of the Rare-Earth Magnets Ce2Fe17−xCoxCN : A Combined Machine-Learning and Ab Initio Study18Screening potential topological insulators in half-Heusler compounds via compressed-sensing12High-throughput design of magnetic materials52Optimization of Criteria for an Efficient Screening of New Thermoelectric Compounds: The TiNiSi Structure-Type as a Case-Study10High-throughput design of magnetic materials3A Machine-Learning Protocol for Ultraviolet Protein-Backbone Absorption Spectroscopy under Environmental Fluctuations24Machine Learning in Solid‐State Chemistry: Heusler Compounds0Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems842Some properties of LiInSi half-Heusler alloy via density functional theory24Machine learning for alloys699Recent machine learning guided material research - A review12Crystal graph attention networks for the prediction of stable materials153Preparation and In‐Situ High‐Throughput Screening of Bi Thixotropic Ink3Machine learning guided microwave-assisted quantum dot synthesis and an indication of residual H 2 O 2 in human teeth35Mysteriöse Materialien0Random projections and kernelised leave one cluster out cross validation: universal baselines and evaluation tools for supervised machine learning of material properties27Effect of (Na, Si, Al, K or Ca) doping on the electronic structure and optoelectronic properties of half-Heusler LiMgN alloy: Ab initio framework27Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validation16Structural, elastic, mechanical, electronic, magnetic and optical properties of half-Heusler compounds CoFeZ (Z = P, As, Sb): A GGA+U approximation19Machine Learning in Materials Chemistry: An Invitation46Machine learning assisted discovering of new M 2 X 3 ‐type thermoelectric materials35First-principles study of optoelectronic and thermoelectric properties of LiCaX (X=N, P and As) half-Heusler semiconductors53Heusler alloys for metal spintronics74Machine-learning-assisted discovery of empirical rule for inherent brittleness of full Heusler alloys15Orbital angular momentum optical communications enhanced by artificial intelligence33Computational study of structural, electronic, elastic and vibrational properties of LiAlSi, NaAlSi, and KAlSi Half-Heusler alloys9Machine learned synthesizability predictions aided by density functional theory30Machine‐Learning‐Assisted Determination of the Global Zero‐Temperature Phase Diagram of Materials109Roadmap on thermoelectricity30Influence of pressure on structural stability and physical properties of NaCaZ (Z=N, P and As) half-Heusler semiconductor materials42Machine learning prediction of thermal and elastic properties of double half-Heusler alloys22Principles of Machine Learning and Its Application to Thermal Barrier Coatings23Machine learning framework to predict instantaneous heat release rate of polymer nanocomposites in cone calorimetry20Structural, Electronic, and Magnetic Characteristics of Co1-xFexMnSb: Insight from DFT Computation3Machine Learning-Based Predictions for Half-Heusler Phases11Machine-learning guided prediction of thermoelectric properties of topological insulator Bi 2 Te 3− x Se x25Predictive analysis of a new FeVTe alloy from first principles: An excellent choice for thermoelectric applications7Bibliometric Analysis: Collaboration Networks In Discovery Learning Research0Alloys innovation through machine learning: a statistical literature review14Iridium's influence on the structural, electronic and mechanical characteristics of ZrCo1-xIrxSb half-heusler alloys6Classification enhanced machine learning model for energetic stability of binary compounds3Highly Refractive Transparent Half‐Heuslers for Near Infrared Optics and Their Material Design1Phase Prediction via Crystal Structure Similarity in the Periodic Number Representation3Predicting and Enhancing Ductility in X2YZ-type Heusler Alloys Using Machine Learning and Abinitio Calculations0Comprehensive DFT study on the physical properties of the CsNaICl quaternary Heusler compound13Bridging current and future innovations to unlock the potential of multifunctional materials for sustainable energy applications28SynCoTrain: a dual classifier PU-learning framework for synthesizability prediction9Typical thermoelectric materials: Progress and prospects16A Comprehensive Analysis of CoHfX (X = As, Bi) Half Heusler Alloys: Implications for High-Performance Thermoelectric and Photovoltaic Devices8TiNiSi-type EuPdBi0Many-body ab initio study of quasiparticles, optical excitations, and excitonic properties in Li Zn As and Sc Ag C for photovoltaic applications5Machine learning investigation of chemical disorder effects in 24-valence-electron full-Heusler alloys with single magnetic element3Exploring Phase Stability and Transport Properties of Emerging Thermoelectric Materials: Machine Learning and Experimental Insights6Machine Learning in Flocculant Research and Application: Toward Smart and Sustainable Water Treatment8A physics-informed machine learning framework for accelerated discovery of single-phase B2 multi-principal element intermetallics17Prediction of ABX Compounds (X = As, Sn, Sb, Pb, or Bi) with the MgAgAs Structure Type and Their Crystal Lattice Parameters0Polymers and the eco-design transformation. A cosmetic perspective3Unlocking Thermoelectric Potential: A Machine Learning Stacking Approach for Half-Heusler Alloys3First-principles prediction of ferromagnetic half-Heusler LiMnTe for spintronic applications0Enhancement of the Thermoelectricity in Half‐Heusler TaRuAs by Substitutional Doping0Beyond predicted zT: Machine learning strategies for the experimental discovery of thermoelectric materials4PNcsp+: A Periodic Number-Based Crystal Structure Prediction Method Enhanced by Machine Learning2

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