Corey Oses

Materials Science and Engineering, Johns Hopkins University
(W) +1 (410) 516 5779
pdf
link · citations: 3255 (YTD 977) · h-index: 22

Work Experience

Assistant Professor
Johns Hopkins University
Postdoctoral Fellow
Duke University
Supervisor: S. Curtarolo
Internship
Cornell High Energy Synchrotron Source (BioSAXS on F2 and G Beamlines)
Supervisors: R. E. Gillilan & E. Fontes
Internship
Cornell High Energy Synchrotron Source (Capillary Optics Group)
Supervisors: R. Huang & E. Fontes

Education

Ph.D.
Duke University

Department: Mechanical Engineering and Materials Science

Thesis: Machine learning, phase stability, and disorder with the Automatic Flow Framework for Materials Discovery

DukeSpace: link

Advisor: S. Curtarolo

B.Sc.
Cornell University

Department: Applied and Engineering Physics

Thesis: Plume Propagation Simulation for Pulsed Laser Deposition

Advisor: J. Brock

Journal Publications

2022

Under Review

aflow++: a C++ framework for autonomous materials design

Authors: C. Oses, M. Esters, D. Hicks, S. Divilov, H. Eckert, R. Friedrich, M. J. Mehl, A. Smolyanyuk, X. Campilongo, A. van de Walle, J. Schroers, A. G. Kusne, I. Takeuchi, E. Zurek, M. Buongiorno Nardelli, M. Fornari, Y. Lederer, O. Levy, C. Toher & S. Curtarolo

arXiv: 2208.03052. [PDF]

Computational Materials Science

aflow.org: a web ecosystem of databases, software and tools

Comput. Mater. Sci. in press (2022)

Authors: M. Esters, C. Oses, S. Divilov, H. Eckert, R. Friedrich, D. Hicks, M. J. Mehl, F. Rose, A. Smolyanyuk, A. Calzolari, X. Campilongo, C. Toher & S. Curtarolo

arXiv: 2207.09842. [PDF]

Angewandte Chemie

The Microscopic Diamond Anvil Cell: Stabilization of Superhard, Superconducting Carbon Allotropes at Ambient Pressure

Angew. Chem. in press (2022)

Authors: X. Wang, D. M. Proserpio, C. Oses, C. Toher, S. Curtarolo & E. Zurek

DOI: 10.1002/anie.202205129. [PDF]

Electronic Structure

Roadmap on Machine Learning in Electronic Structure

Electron. Struct. 4(2), 023004 (2022)

Authors: H. J. Kulik, T. Hammerschmidt, J. Schmidt, S. Botti, M. A. L. Marques, M. Boley, M. Scheffler, M. Todorović, P. Rinke, C. Oses, A. Smolyanyuk, S. Curtarolo, A. Tkatchenko, A. P. Bartók, S. Manzhos, M. Ihara, T. Carrington, J. Behler, O. Isayev, M. Veit, A. Grisafi, J. Nigam, M. Ceriotti, K. T. Schütt, J. Westermayr, M. Gastegger, R. J. Maurer, B. Kalita, K. Burke, R. Nagai, R. Akashi, O. Sugino, J. Hermann, F. Noé, S. Pilati, C. Draxl, M. Kuban, S. Rigamonti, M. Scheidgen, M. Esters, D. Hicks, C. Toher, P. V. Balachandran, I. Tamblyn, S. Whitelam, C. Bellinger & L. M. Ghiringhelli

DOI: 10.1088/2516-1075/ac572f. [PDF]

Frontiers in Physics

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping

Front. Phys. 10, 815863 (2022)

Authors: A. G. Kusne, A. McDannald, B. DeCost, C. Oses, C. Toher, S. Curtarolo, A. Mehta & I. Takeuchi

DOI: 10.3389/fphy.2022.815863. [PDF]

MRS Bulletin

High-entropy ceramics: Propelling applications through disorder

MRS Bull. 47, 194–202 (2022)

Authors: C. Toher, C. Oses, M. Esters, D. Hicks, G. N. Kotsonis, C. M. Rost, D. W. Brenner, J.-P. Maria & S. Curtarolo

DOI: 10.1557/s43577-022-00281-x. [PDF]

2021

Nature Communications

Settling the matter of the role of vibrations in the stability of high-entropy carbides

Nat. Commun. 12, 5747 (2021)

Authors: M. Esters, C. Oses, D. Hicks, M. J. Mehl, M. Jahnátek, M. D. Hossain, J.-P. Maria, D. W. Brenner, C. Toher & S. Curtarolo

  • This paper was selected for Editors' Highlight by Springer Nature (2021).
DOI: 10.1038/s41467-021-25979-5. [PDF]

Advanced Materials

Entropy Landscaping of High-Entropy Carbides

Adv. Mater. 33(42), 2102904 (2021)

Authors: M. D. Hossain, T. Borman, C. Oses, M. Esters, C. Toher, L. Feng, A. Kumar, W. G. Fahrenholtz, S. Curtarolo, D. W. Brenner, J. M. LeBeau & J.-P. Maria

DOI: 10.1002/adma.202102904. [PDF]

Scientific Data

OPTIMADE: an API for exchanging materials data

Sci. Data 8, 217 (2021)

Authors: C. W. Andersen, R. Armiento, E. Blokhin, G. J. Conduit, S. Dwaraknath, M. L. Evans, Á. Fekete, A. Gopakumar, S. Gražulis, A. Merkys, F. Mohamed, C. Oses, G. Pizzi, G.-M. Rignanese, M. Scheidgen, L. Talirz, C. Toher, D. Winston, R. Aversa, K. Choudhary, P. Colinet, S. Curtarolo, D. Di Stefano, C. Draxl, S. Er, M. Esters, M. Fornari, M. Giantomassi, M. Govoni, G. Hautier, V. Hegde, M. K. Horton, P. Huck, G. Huhs, J. Hummelshøj, A. Kariryaa, B. Kozinsky, S. Kumbhar, M. Liu, N. Marzari, A. J. Morris, A. Mostofi, K. A. Persson, G. Petretto, T. Purcell, F. Ricci, F. Rose, M. Scheffler, D. Speckhard, M. Uhrin, A. Vaitkus, P. Villars, D. Waroquiers, C. Wolverton, M. Wu & X. Yang

contributed equally

DOI: 10.1038/s41597-021-00974-z. [PDF]

Physical Review Materials

Automated coordination corrected enthalpies with AFLOW-CCE

Phys. Rev. Mater. 5, 043803 (2021)

Authors: R. Friedrich, M. Esters, C. Oses, S. Ki, M. J. Brenner, D. Hicks, M. J. Mehl, C. Toher & S. Curtarolo

DOI: 10.1103/PhysRevMaterials.5.043803. [PDF]

Computational Materials Science

The AFLOW Library of Crystallographic Prototypes: Part 3

Comput. Mater. Sci. 199, 110450 (2021)

Authors: D. Hicks, M. J. Mehl, M. Esters, C. Oses, O. Levy, G. L. W. Hart, C. Toher & S. Curtarolo

DOI: 10.1016/j.commatsci.2021.110450

Physical Review Materials

Tin-pest problem as a test of density functionals using high-throughput calculations

Phys. Rev. Mater. 5, 083608 (2021)

Authors: M. J. Mehl, M. Ronquillo, D. Hicks, M. Esters, C. Oses, R. Friedrich, A. Smolyanyuk, E. Gossett, D. Finkenstadt & S. Curtarolo

DOI: 10.1103/PhysRevMaterials.5.083608. [PDF]

Acta Materialia

Carbon Stoichiometry and Mechanical Properties of High Entropy Carbides

Acta Mater. 215, 117051 (2021)

Authors: M. D. Hossain, T. Borman, A. Kumar, X. Chen, A. Khosravani, S. R. Kalidindi, E. A. Paisley, M. Esters, C. Oses, C. Toher, S. Curtarolo, J. M. LeBeau, D. W. Brenner & J.-P. Maria

contributed equally

DOI: 10.1016/j.actamat.2021.117051. [PDF]

2020

Nature Communications

On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning

Nat. Commun. 11, 5966 (2020)

Authors: A. G. Kusne, H. Yu, C. Wu, H. Zhang, J. Hattrick-Simpers, B. DeCost, S. Sarker, C. Oses, C. Toher, S. Curtarolo, A. V. Davydov, R. Agarwal, L. A. Bendersky, M. Li, A. Mehta & I. Takeuchi

contributed equally

DOI: 10.1038/s41467-020-19597-w. [PDF]

npj Computational Materials

Discovery of novel high-entropy ceramics via machine learning

npj Comput. Mater. 6, 42 (2020)

Authors: K. Kaufmann, D. Maryanovsky, W. M. Mellor, C. Zhu, A. S. Rosengarten, T. J. Harrington, C. Oses, C. Toher, S. Curtarolo & K. S. Vecchio

DOI: 10.1038/s41524-020-0317-6. [PDF]

Nature Reviews Materials

High-entropy ceramics

Nat. Rev. Mater. 5, 295–309 (2020)

Authors: C. Oses, C. Toher & S. Curtarolo

  • This paper was highlighted as a "hot paper" by Web of Science (Clarivate Analytics) (November 16, 2021).
DOI: 10.1038/s41578-019-0170-8. [PDF]

2019

Acta Materialia

Metallic glasses for biodegradable implants

Acta Mater. 176, 297–305 (2019)

Authors: D. C. Ford, D. Hicks, C. Oses, C. Toher & S. Curtarolo

DOI: 10.1016/j.actamat.2019.07.008. [PDF]

npj Computational Materials

Predicting Superhard Materials via a Machine Learning Informed Evolutionary Structure Search

npj Comput. Mater. 5, 89 (2019)

Authors: P. Avery, X. Wang, C. Oses, E. Gossett, D. M. Proserpio, C. Toher, S. Curtarolo & E. Zurek

DOI: 10.1038/s41524-019-0226-8. [PDF]

npj Computational Materials

Unavoidable disorder and entropy in multi-component systems

npj Comput. Mater. 5, 69 (2019)

Authors: C. Toher, C. Oses, D. Hicks & S. Curtarolo

DOI: 10.1038/s41524-019-0206-z. [PDF]

npj Computational Materials

Coordination corrected ab initio formation enthalpies

npj Comput. Mater. 5, 59 (2019)

Authors: R. Friedrich, D. Usanmaz, C. Oses, A. R. Supka, M. Fornari, M. Buongiorno Nardelli, C. Toher & S. Curtarolo

DOI: 10.1038/s41524-019-0192-1. [PDF]

Physical Review Materials

AFLOW-QHA3P: Robust and automated method to compute thermodynamic properties of solids

Phys. Rev. Mater. 3, 073801 (2019)

Authors: P. Nath, D. Usanmaz, D. Hicks, C. Oses, M. Fornari, M. Buongiorno Nardelli, C. Toher & S. Curtarolo

DOI: 10.1103/PhysRevMaterials.3.073801. [PDF]

2018

Journal of Chemical Information and Modeling

AFLOW-CHULL: Cloud-oriented platform for autonomous phase stability analysis

J. Chem. Inf. Model. 58(12), 2477–2490 (2018)

Authors: C. Oses, E. Gossett, D. Hicks, F. Rose, M. J. Mehl, E. Perim, I. Takeuchi, S. Sanvito, M. Scheffler, Y. Lederer, O. Levy, C. Toher & S. Curtarolo

DOI: 10.1021/acs.jcim.8b00393. [PDF]

MRS Bulletin

Data-driven design of inorganic materials with the Automatic Flow Framework for Materials Discovery

MRS Bull. 43(9), 670–675 (2018)

Authors: C. Oses, C. Toher & S. Curtarolo

DOI: 10.1557/mrs.2018.207. [PDF]

Nature Communications

High-entropy high-hardness metal carbides discovered by entropy descriptors

Nat. Commun. 9, 4980 (2018)

Authors: P. Sarker, T. J. Harrington, C. Toher, C. Oses, M. Samiee, J.-P. Maria, D. W. Brenner, K. S. Vecchio & S. Curtarolo

contributed equally

DOI: 10.1038/s41467-018-07160-7. [PDF]

npj Computational Materials

Machine learning modeling of superconducting critical temperature

npj Comput. Mater. 4, 29 (2018)

Authors: V. Stanev, C. Oses, A. G. Kusne, E. Rodriguez, J. Paglione, S. Curtarolo & I. Takeuchi

DOI: 10.1038/s41524-018-0085-8. [PDF]

Computational Materials Science

AFLOW-ML: A RESTful API for machine-learning prediction of materials properties

Comput. Mater. Sci. 152, 134–145 (2018)

Authors: E. Gossett, C. Toher, C. Oses, O. Isayev, F. Legrain, F. Rose, E. Zurek, J. Carrete, N. Mingo, A. Tropsha & S. Curtarolo

  • This paper was selected for Editors' Choice by Elsevier (2018).
DOI: 10.1016/j.commatsci.2018.03.075. [PDF]

Acta Crystallographica Section A

AFLOW-SYM: platform for the complete, automatic and self-consistent symmetry analysis of crystals

Acta Cryst. A 74, 184–203 (2018)

Authors: D. Hicks, C. Oses, E. Gossett, G. Gomez, R. H. Taylor, C. Toher, M. J. Mehl, O. Levy & S. Curtarolo

DOI: 10.1107/S2053273318003066. [PDF]

2017

Inorganic Chemistry

The structure and composition statistics of 6A binary and ternary structures

Inorg. Chem. 57(2), 653–667 (2017)

Authors: A. Hever, C. Oses, S. Curtarolo, O. Levy & A. Natan

DOI: 10.1021/acs.inorgchem.7b02462. [PDF]

Computational Materials Science

AFLUX: The LUX materials search API for the AFLOW data repositories

Comput. Mater. Sci. 137, 362–370 (2017)

Authors: F. Rose, C. Toher, E. Gossett, C. Oses, M. Buongiorno Nardelli, M. Fornari & S. Curtarolo

  • This paper was selected for Editors' Choice by Elsevier (2017).
DOI: 10.1016/j.commatsci.2017.04.036. [PDF]

Nature Communications

Universal Fragment Descriptors for Predicting Properties of Inorganic Crystals

Nat. Commun. 8, 15679 (2017)

Authors: O. Isayev, C. Oses, C. Toher, E. Gossett, S. Curtarolo & A. Tropsha

contributed equally

DOI: 10.1038/ncomms15679. [PDF]

Physical Review Materials

Combining the AFLOW GIBBS and elastic libraries to efficiently and robustly screening thermomechanical properties of solids

Phys. Rev. Mater. 1, 015401 (2017)

Authors: C. Toher, C. Oses, J. J. Plata, D. Hicks, F. Rose, O. Levy, M. de Jong, M. Asta, M. Fornari, M. Buongiorno Nardelli & S. Curtarolo

DOI: 10.1103/PhysRevMaterials.1.015401. [PDF]

Acta Materialia

A Computational High-Throughput Search for New Ternary Superalloys

Acta Mater. 122, 438–447 (2017)

Authors: C. Nyshadham, C. Oses, J. E. Hansen, I. Takeuchi, S. Curtarolo & G. L. W. Hart

DOI: 10.1016/j.actamat.2016.09.017. [PDF]

Science Advances

Accelerated Discovery of New Magnets in the Heusler Alloy Family

Sci. Adv. 3(4), e1602241 (2017)

Authors: S. Sanvito, C. Oses, J. Xue, A. Tiwari, M. Žic, T. Archer, P. Tozman, M. Venkatesan, J. M. D. Coey & S. Curtarolo

DOI: 10.1126/sciadv.1602241. [PDF]

2016

Physical Review X

High-Throughput Computation of Thermal Conductivity of High-Temperature Solid Phases: The Case of Oxide and Fluoride Perovskites

Phys. Rev. X 6(4), 041061 (2016)

Authors: A. van Roekeghem, J. Carrete, C. Oses, S. Curtarolo & N. Mingo

DOI: 10.1103/PhysRevX.6.041061. [PDF]

Chemistry of Materials

Modeling Off-Stoichiometry Materials with a High-Throughput Ab-Initio Approach

Chem. Mater. 28(18), 6484–6492 (2016)

Authors: K. Yang, C. Oses & S. Curtarolo

DOI: 10.1021/acs.chemmater.6b01449. [PDF]

2015

Computational Materials Science

The AFLOW Standard for High-Throughput Materials Science Calculations

Comput. Mater. Sci. 108A, 233–238 (2015)

Authors: C. E. Calderon, J. J. Plata, C. Toher, C. Oses, O. Levy, M. Fornari, A. Natan, M. J. Mehl, G. L. W. Hart, M. Buongiorno Nardelli & S. Curtarolo

  • This paper was selected for Editors' Choice by Elsevier (2015).
DOI: 10.1016/j.commatsci.2015.07.019. [PDF]

Chemistry of Materials

Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints

Chem. Mater. 27(3), 735–743 (2015)

Authors: O. Isayev, D. Fourches, E. N. Muratov, C. Oses, K. M. Rasch, A. Tropsha & S. Curtarolo

  • This paper was selected for Editors' Choice by the American Chemical Society (2015).
DOI: 10.1021/cm503507h. [PDF]

Book Publications

2019

Book Chapter

Automated computation of materials properties

Materials Informatics: Methods, Tools and Applications, Ch. 7

Authors: C. Toher, C. Oses & S. Curtarolo

DOI: 10.1002/9783527802265.ch7. [PDF]

2018

Book Chapter

Machine learning and high-throughput approaches to magnetism

Handbook of Materials Modeling. Volume 2 Applications: Current and Emerging Materials

Authors: S. Sanvito, M. Žic, J. Nelson, T. Archer, C. Oses & S. Curtarolo

DOI: 10.1007/978-3-319-50257-1_108-1. [PDF]
Book Chapter

The AFLOW Fleet for Materials Discovery

Handbook of Materials Modeling. Volume 1 Methods: Theory and Modeling

Authors: C. Toher, C. Oses, D. Hicks, E. Gossett, F. Rose, P. Nath, D. Usanmaz, D. C. Ford, E. Perim, C. E. Calderon, J. J. Plata, Y. Lederer, M. Jahnátek, W. Setyawan, S. Wang, J. Xue, K. M. Rasch, R. V. Chepulskii, R. H. Taylor, G. Gomez, H. Shi, A. R. Supka, R. Al Rahal Al Orabi, P. Gopal, F. T. Cerasoli, L. Liyanage, H. Wang, I. Siloi, L. A. Agapito, C. Nyshadham, G. L. W. Hart, J. Carrete, F. Legrain, N. Mingo, E. Zurek, O. Isayev, A. Tropsha, S. Sanvito, R. M. Hanson, I. Takeuchi, M. J. Mehl, A. N. Kolmogorov, K. Yang, P. D'Amico, A. Calzolari, M. Costa, R. De Gennaro, M. Buongiorno Nardelli, M. Fornari, O. Levy & S. Curtarolo

DOI: 10.1007/978-3-319-42913-7_63-2. [PDF]

Teaching Experience

Co-Instructor

ME 555: Applications of Artificial Intelligence in Materials, Duke University Department of Mechanical Engineering and Materials Science

Teaching Assistant

ME 555: Computational Materials Science by Examples and Applications, Duke University Department of Mechanical Engineering and Materials Science

Teaching Assistant

ME 221: Structure and Properties of Solids, Duke University Department of Mechanical Engineering and Materials Science

  • Best Teaching Assistant Award, August 14, 2015

Workshops

Organizer And Presenter

AFLOW School: Integrated infrastructure for computational materials discovery

Co-Organizers: D. Hicks, C. Toher, M. Esters, R. Friedrich, E. Gossett, A. Smolyanyuk, H. Eckert, S. Divilov, F. Rose, M. J. Brenner & S. Curtarolo

  1. Organizer and presenter at Johns Hopkins University, Baltimore, Maryland — September 21, 2022.

  1. Presenter for the Machine Learning for Materials Research Bootcamp of the University of Maryland/NIST/MRS, College Park, Maryland — August 11, 2022.

  1. Organizer and presenter at the East African Institute for Fundamental Research, University of Rwanda, Kigali, Rwanda — February 21–24, 2022.

  1. Organizer and presenter at the Technische Universität (TU) Dresden and Helmholtz-Zentrum Dresden-Rossendorf — September 6–10, 2021.
  1. Organizer and presenter at the University of Virginia, Charlottesville, Virginia — August 17, 2021.
  1. Presenter for the Machine Learning for Materials Research Bootcamp of the University of Maryland/NIST, College Park, Maryland — July 29, 2021.
  1. Organizer and presenter at Texas A&M University, College Station, Texas — July 12–15, 2021.
  1. Session Chair for the Virtual Spring Meeting of the Materials Research Society — April 17, 2021.

  1. Presenter for the Materials 4.0 Summer School 2020 at the Dresden Center for Computational Materials Science (DCMS), Technische Universität (TU) Dresden — August 18, 2020.
  1. Presenter for the Machine Learning for Materials Research Bootcamp & Workshop on Machine Learning Microscopy Data of the University of Maryland/NIST, College Park, Maryland — July 23, 2020.
  1. Organizer and presenter at Texas A&M University, College Station, Texas — June 16–18, 2020.
  1. Presenter for the Machine Learning for Materials Research Bootcamp & Workshop on Autonomous Materials Research of the University of Maryland/NIST, College Park, Maryland — August 05, 2019.

  1. Organizer and presenter at the University of Pennsylvania, Philadelphia, Pennsylvania — May 03, 2019.

  1. Organizer and presenter at the North Carolina State University, Raleigh, North Carolina — March 12, 2019.

  1. Organizer and presenter at Carnegie Mellon University, Pittsburgh, Pennsylvania — January 21, 2019.

  1. Presenter for the Machine Learning for Materials Research Bootcamp & Workshop on Machine Learning Quantum Materials of the University of Maryland/NIST/Moore Foundation, Institute for Bioscience & Biotechnology Research in Gaithersburg, Maryland — August 02, 2018.

Press and News Releases

White House Office of Science & Technology Policy
"Featured Vignette in the November 2021 Materials Genome Initiative Strategic Plan (page 9)"
University of Buffalo
"Scientists predict new forms of superhard carbon"
Duke University Pratt School of Engineering
"Disordered Materials Could Be Hardest, Most Heat-Tolerant Ever"
MRS Bulletin
UNC Eshelman School of Pharmacy
"Breakthrough Tool Predicts Properties of Theoretical Materials, Finds New Uses for Current Ones"
Duke University Pratt School of Engineering
MRS Bulletin
"Materials fingerprints identified for informatics"
Computational Chemistry Highlights
"Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints"
Duke University Research
Duke University Graduate School
ERN Conference 2013
"2013 Oral and Poster Presentation Award Winners"

Honors and Awards

Publication Award
"Hot paper", Publication in Nat. Rev. Mater., Web of Science (Clarivate Analytics)
  • Published in the past two years and received enough citations in July/August 2021 to place it in the top 0.1% of papers in the academic field of Materials Science
Publication Award
Editors' Highlight, Publication in Nat. Commun., Springer Nature
Publication Award
Editors' Choice, Publication in Comput. Mater. Sci., Elsevier
Publication Award
Editors' Choice, Publication in Comput. Mater. Sci., Elsevier
Award
Best Teaching Assistant Award (ME 221), Duke University Department of Mechanical Engineering and Materials Science
Publication Award
Editors' Choice, Publication in Comput. Mater. Sci., Elsevier
Publication Award
Editors' Choice, Publication in Chem. Mater., American Chemical Society
Fellowship
Graduate Research Fellowship, National Science Foundation
Award
Best Presentation Award at the MEMS Departmental Retreat, Duke University Department of Mechanical Engineering and Materials Science
Award
First Place in Nanoscience and Physics Research Presentation, NSF / AAAS / EHR Emerging Researchers National Conference
Scholarship
Shell Incentive Fund Scholarship
Scholarship
Xerox Corporation Scholarship
Scholarship
Intel Academic Award
Grant
Cornell University Unmanned Air Systems Team awarded $1,000 grant, AUVSI Student Unmanned Aerial Systems Competition
Scholarship
Meinig Family Cornell National Scholars
  • Awarded by Peter Meinig (Past Chairman of the Board of Trustees at Cornell University)