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Two-Layer High-Throughput:Effective Mass Calculations Including Warping

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Engineering 2022年第3期8卷 74-80页

作者： Andrew Supka Nicholas A.Mecholsky Marco Buongiorno Nardelli stefano curtarolo Marco Fornari Department of Physics&Science of Advanced Materials Program Central Michigan UniversityMount PleasantMI 48859USA Department of Physics&Vitreous State Laboratory The Catholic University of AmericaWashingtonDC 20064USA Department of Physics&Department of Chemistry University of North TexasDentonTX 76203USA Center for Autonomous Materials Design Duke UniversityDurhamNC 27708USA Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA

In this paper,we perform two-layer high-throughput *** the first layer,which involves changing the crystal structure and/or chemical composition,we analyze selected Ⅲ-Ⅴ semiconductors,filled and unfilled skutterudites,as well as rock salt and layered *** second layer searches the full Brillouin zone(BZ)for critical points within 1.5 eV(1 eV=1.602176×10^(-19)J)of the Fermi level and characterizes those points by computing the effective *** introduce several methods to compute the effective masses from first principles and compare them to each *** approach also includes the calculation of the density-of-states effective masses for warped critical points,where traditional approaches fail to give consistent results due to an underlying non-analytic behavior of the critical *** demonstrate the need to consider the band structure in its full complexity and the value of complementary approaches to compute the effective *** also provide computational evidence that warping occurs only in the presence of degeneracies.

关键词： High-throughput Electronic structure Band warping Effective mass

Parametrically constrained geometry relaxations for high-throughput materials science

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npj Computational Materials 2019年第1期5卷 63-72页

作者： Maja-Olivia Lenz Thomas A.R.Purcell David Hicks stefano curtarolo Matthias Scheffler Christian Carbogno Fritz-Haber-Institut der Max-Planck-Gesellschaft Faradayweg 4–6D-14195 BerlinGermany Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA

Reducing parameter spaces via exploiting symmetries has greatly accelerated and increased the quality of electronic-structure ***,many of the traditional methods fail when the global crystal symmetry is broken,even when the distortion is only a slight perturbation(e.g.,Jahn-Teller like distortions).Here we introduce a flexible and generalizable parametric relaxation scheme and implement it in the all-electron code *** approach utilizes parametric constraints to maintain symmetry at any *** demonstrating the method’s ability to relax metastable structures,we highlight its adaptability and performance over a test set of 359 materials,across 13 lattice *** we show how these constraints can reduce the number of steps needed to relax local lattice distortions by an order of *** flexibility of these constraints enables a significant acceleration of high-throughput searches for novel materials for numerous applications.

关键词： relaxation constraints distortion

Thermodynamic analysis of metal segregation in dual phase high entropy ceramics

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Journal of Materiomics 2024年第4期10卷 889-895页

作者： Steven M.Smith II William G.Fahrenholtz Gregory E.Hilmas stefano curtarolo Missouri University of Science and Technology Materials Science and Engineering DepartmentRollaMO65409USA Duke University Department of Mechanical Engineering and Materials ScienceDurhamNC27708USA Duke University Center of Autonomous Materials DesignDurhamNC27708USA

Equilibrium Gibbs'free energy calculations were used to determine metal segregation trends between boride and carbide solid solutions containing two metals that are relevant to dual phase high entropy *** model predicted that Ti had the strongest tendency to segregate to the boride phase followed by Zr,Nb,Mo,V,Hf,and Ta,which matches experimental results of measured *** ratio of a metal in the carbide phase to the content of the same metal in the corresponding metal boride had a linear trend with the change in standard Gibbs'free energy of reaction for a metal carbide reacting with B_(4)C to produce its corresponding metal boride and *** proposed model was used to predict the changes in standard Gibbs'free energy for CrC→CrB_(2) to be−260 kJ and WC→WB_(2) to be 148 kJ,which indicates that Cr has the strongest segregation to the boride and W has the strongest segregation to the *** proposed model can be used to estimate the segregation of metals in dual phase high entropy boride-carbide ceramics of any boride/carbide ratio or metal content.

关键词： Dual phase High entropy ceramic Boride Carbide Thermodynamics

Theoretical prediction of high melting temperature for a Mo–Ru–Ta–W HCP multiprincipal element alloy

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npj Computational Materials 2021年第1期7卷 49-52页

作者： Qi-Jun Hong Jan Schroers Douglas Hofmann stefano curtarolo Mark Asta Axel van de Walle School of Engineering Brown UniversityProvidenceRI 02912USA Department of Mechanical Engineering and Materials Science Yale UniversityNew HavenCT 06511USA NASA Jet Propulsion Laboratory California Institute of Technology4800 Oak Grove Dr.PasadenaCA 91109USA Department of Mechanical Engineering and Materials Science and Center for Autonomous Materials Design Duke UniversityDurhamNC 27708USA Department of Materials Science and Engineering University of CaliforniaBerkeleyCA 94720USA Materials Sciences Division Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA

While rhenium is an ideal material for rapid thermal cycling applications under high temperatures,such as rocket engine nozzles,its high cost limits its widespread use and prompts an exploration of viable cost-effective *** prior work,we identified a promising pool of candidate substitute alloys consisting of Mo,Ru,Ta,and *** this work we demonstrate,based on density functional theory melting temperature calculations,that one of the candidates,Mo_(0.292)Ru_(0.555)Ta_(0.031)W_(0.122),exhibits a high melting temperature(around 2626 K),thus supporting its use in high-temperature applications.

关键词： alloy cycling high

Spin Hall effect in prototype Rashba ferroelectrics GeTe and SnTe

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npj Computational Materials 2020年第1期6卷 1607-1613页

作者： Haihang Wang Priya Gopal Silvia Picozzi stefano curtarolo Marco Buongiorno Nardelli Jagoda Sławińska Department of Physics University of North TexasDentonTX 76203USA Consiglio Nazionale delle Ricerche Istituto SPINUOS L’AquilaSede di lavoro CNR-SPIN c/o Univ.G.D’Annunzio66100 ChietiItaly Center for Autonomous Materials Design Duke UniversityDurhamNC 27708USA Materials Science Electrical EngineeringPhysics and ChemistryDuke UniversityDurhamNC 27708USA

Ferroelectric Rashba semiconductors(FERSCs)have recently emerged as a promising class of spintronics *** peculiar coupling between spin and polar degrees of freedom responsible for several exceptional properties,including ferroelectric switching of Rashba spin texture,suggests that the electron’s spin could be controlled by using only electric *** this regard,recent experimental studies revealing charge-to-spin interconversion phenomena in two prototypical FERSCs,GeTe and SnTe,appear extremely ***,by employing density functional theory calculations,we investigate spin Hall effect(SHE)in these materials and show that it can be large either in ferroelectric or paraelectric *** further explore the compatibility between doping required for the practical realization of SHE in semiconductors and polar distortions which determine Rashba-related phenomena in FERSCs,but which could be suppressed by free charge carriers.

关键词： structure Rashba ferroelectric

AFLOW-XtalFinder:a reliable choice to identify crystalline prototypes

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npj Computational Materials 2021年第1期7卷 264-283页

作者： David Hicks Cormac Toher Denise CFord Frisco Rose Carlo De Santo Ohad Levy Michael J.Mehl stefano curtarolo Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA Center for Autonomous Materials Design Duke UniversityDurhamNC 27708USA Department of Physics NRCNP.O.Box 9001Beer-Sheva 84190Israel

The accelerated growth rate of repository entries in crystallographic databases makes it arduous to identify and classify their prototype *** open-source AFLOW-XtalFinder package was developed to solve this *** symbolically maps structures into standard designations following the AFLOW Prototype Encyclopedia and calculates the internal degrees of freedom consistent with the International Tables for *** ensure uniqueness,structures are analyzed and compared via symmetry,local atomic geometries,and crystal mapping techniques,simultaneously grouping them by *** software(i)distinguishes distinct crystal prototypes and atom decorations,(ii)determines equivalent spin configurations,(iii)reveals compounds with similar properties,and(iv)guides the discovery of unexplored *** operations are accessible through a Python module ready for workflows,and through command line *** the 4+million compounds in the *** repositories are mapped to their ideal prototype,allowing users to search database entries via symbolic ***,15,000 unique structures—sorted by prevalence—are extracted from the AFLOW-ICSD catalog to serve as future prototypes in the Encyclopedia.

关键词： Python symbolic crystalline

Machine learning modeling of superconducting critical temperature

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npj Computational Materials 2018年第1期4卷 405-418页

作者： Valentin Stanev Corey Oses A.Gilad Kusne Efrain Rodriguez Johnpierre Paglione stefano curtarolo Ichiro Takeuchi Department of Materials Science and Engineering University of MarylandCollege ParkMD 20742-4111USA Center for Nanophysics and Advanced Materials University of MarylandCollege ParkMD 20742USA Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA Center for Materials Genomics Duke UniversityDurhamNC 27708USA National Institute of Standards and Technology GaithersburgMD 20899USA Department of Chemistry and Biochemistry University of MarylandCollege ParkMD 20742USA Department of Physics University of MarylandCollege ParkMD 20742USA Fritz-Haber-Institut der Max-Planck-Gesellschaft 14195 Berlin-DahlemGermany

Superconductivity has been the focus of enormous research effort since its discovery more than a century ***,some features of this unique phenomenon remain poorly understood;prime among these is the connection between superconductivity and chemical/structural properties of *** bridge the gap,several machine learning schemes are developed herein to model the critical temperatures(T_(c))of the 12,000+known superconductors available via the SuperCon *** are first divided into two classes based on their T_(c) values,above and below 10 K,and a classification model predicting this label is *** model uses coarse-grained features based only on the chemical *** shows strong predictive power,with out-of-sample accuracy of about 92%.Separate regression models are developed to predict the values of T_(c) for cuprate,iron-based,and low-T_(c) *** models also demonstrate good performance,with learned predictors offering potential insights into the mechanisms behind superconductivity in different families of *** improve the accuracy and interpretability of these models,new features are incorporated using materials data from the AFLOW Online ***,the classification and regression models are combined into a single-integrated pipeline and employed to search the entire Inorganic Crystallographic Structure Database(ICSD)for potential new *** identify>30 non-cuprate and non-iron-based oxides as candidate materials.

关键词： learning critical offering

Coordination corrected ab initio formation enthalpies

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npj Computational Materials 2019年第1期5卷 633-644页

作者： Rico Friedrich Demet Usanmaz Corey Oses Andrew Supka Marco Fornari Marco Buongiorno Nardelli Cormac Toher stefano curtarolo Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA Center for Materials Genomics Duke UniversityDurhamNC 27708USA Department of Physics and Science of Advanced Materials Program Central Michigan UniversityMount PleasantMI 48859USA Department of Physics and Department of Chemistry University of North TexasDentonTX 76203USA Materials Science Electrical EngineeringPhysics and ChemistryDuke UniversityDurhamNC 27708USA Fritz-Haber-Institut der Max-Planck-Gesellschaft 14195 Berlin-DahlemGermany

The correct calculation of formation enthalpy is one of the enablers of ab-initio computational materials *** several classes of systems(***)standard density functional theory produces incorrect *** we propose the“coordination corrected enthalpies”method(CCE),based on the number of nearest neighbor cation–anion bonds,and also capable of correcting relative stability of *** uses calculations employing the Perdew,Burke and Ernzerhof(PBE),local density approximation(LDA)and strongly constrained and appropriately normed(SCAN)exchange correlation functionals,in conjunction with a quasiharmonic Debye model to treat zero-point vibrational and thermal *** benchmark,performed on binary and ternary oxides(halides),shows very accurate room temperature results for all functionals,with the smallest mean absolute error of 27(24)meV/atom obtained with *** zero-point vibrational and thermal contributions to the formation enthalpies are small and with different signs—largely canceling each other.

关键词： corrected vibrational oxides

Predicting superhard materials via a machine learning informed evolutionary structure search

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npj Computational Materials 2019年第1期5卷 352-362页

作者： Patrick Avery Xiaoyu Wang Corey Oses Eric Gossett Davide M.Proserpio Cormac Toher stefano curtarolo Eva Zurek Department of Chemistry State University of New York at BuffaloBuffaloNY 14260-3000USA Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA Dipartimento di Chimica Universitàdegli Studi di MilanoVia Golgi 1920133 MilanoItaly Samara Center for Theoretical Materials Science(SCTMS) Samara State Technical UniversityMolodogvardeyskaya St.244443100 SamaraRussia Center for Autonomous Materials Design Department of Mechanical Engineering and Materials ScienceDuke UniversityDurhamNC 27708USA

The computational prediction of superhard materials would enable the in silico design of compounds that could be used in a wide variety of technological ***,good agreement was found between experimental Vickers hardnesses,Hv,of a wide range of materials and those calculated by three macroscopic hardness models that employ the shear and/or bulk moduli obtained from:(i)first principles via AFLOW-AEL(AFLOW Automatic Elastic Library),and(ii)a machine learning(ML)model trained on materials within the AFLOW *** H^(ML)_(v) values can be quickly estimated,they can be used in conjunction with an evolutionary search to predict stable,superhard *** methodology is implemented in the XTALOPT evolutionary *** crystal is minimized to the nearest local minimum,and its Vickers hardness is computed via a linear relationship with the shear modulus discovered by *** the energy/enthalpy and H^(ML)_(v),Teter are employed to determine a structure’s *** implementation is applied towards the carbon system,and 43 new superhard phases are found.A topological analysis reveals that phases estimated to be slightly harder than diamond contain a substantial fraction of diamond and/or lonsdaleite.

关键词： structure modulus Elastic