Corey Oses

Materials Science, Duke University

Personal Information

corey.oses@duke.edu

phone

(W) +1 (919) 684 1553

pdf

Google Scholar

link

Work Experience

Postdoctoral Fellow

2018–present

Duke University

Supervisor: S. Curtarolo

Internship

Summer 2013

Cornell High Energy Synchrotron Source (BioSAXS on F2 and G Beamlines)

Supervisors: R. E. Gillilan & E. Fontes

Internship

Summer 2012

Cornell High Energy Synchrotron Source (Capillary Optics Group)

Supervisors: R. Huang & E. Fontes

Education

Ph.D.

2013–2018

Duke University

Department: Mechanical Engineering and Materials Science

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

ProQuest: link

Advisor: S. Curtarolo

B.Sc.

2009–2013

Cornell University

Department: Applied and Engineering Physics

Thesis: Plume Propagation Simulation for Pulsed Laser Deposition

Advisor: J. Brock

Press and News Releases

University of Buffalo

September 2019

"Scientists predict new forms of superhard carbon"

This press release is featured on Phys.org, ScienceDaily, SciTechDaily, and Tribonet.

buffalo.edu/ubnow/stories/2019/09/zurek-superhard-carbon.html

Duke University Pratt School of Engineering

November 2018

"Disordered Materials Could Be Hardest, Most Heat-Tolerant Ever"

This press release is featured on AAAS EurekAlert!, Phys.org, ScienceDaily, Science Bulletin, Naaju, NewsBeezer, RemoNews, Tech2, and LongRoom News.

pratt.duke.edu/about/news/chaotic-carbides

MRS Bulletin

August 2017

"Universal fragment descriptor predicts materials properties"

cambridge.org/core/journals/mrs-bulletin/news/universal-fragment-descriptor-predicts-materials-properties

UNC Eshelman School of Pharmacy

June 2017

"Breakthrough Tool Predicts Properties of Theoretical Materials, Finds New Uses for Current Ones"

This press release is featured on AAAS EurekAlert!, Phys.org, and ScienceDaily.

pharmacy.unc.edu/news/2017/06/06/breakthrough-tool-predicts-properties-theoretical-materials-finds-new-uses-current-ones/

Duke University Pratt School of Engineering

April 2017

"Computers Create Recipe for Two New Magnetic Materials"

This press release is featured on Phys.org, Slashdot, Hacker News, Reddit, Engadget, Engineering.com, Science Alert, Azo Materials, Next Big Future, Futurism, New Atlas, and International Business Times.

pratt.duke.edu/about/news/predicting-magnets

MRS Bulletin

April 2015

"Materials fingerprints identified for informatics"

doi.org/10.1557/mrs.2015.76

Computational Chemistry Highlights

January 2015

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

"This paper is a tour de force for computational materials science" — Prof. Aspuru-Guzik.

compchemhighlights.org/2015/01/materials-cartography-representing-and.html

Duke University Research

January 2015

"Molecular Tornado"

research.duke.edu/molecular-tornado

Duke University Graduate School

October 2014

"Competing for NSF Fellowships: Advice from a Current Fellow"

gradschool.duke.edu/professional-development/blog/competing-nsf-fellowships-advice-current-fellow

ERN Conference 2013

February 2013

"2013 Oral and Poster Presentation Award Winners"

new.emerging-researchers.org/2013-oral-and-poster-presentation-winners

Honors and Awards

Publication Award

2018

Editor's Choice, Publication in Comput. Mater. Sci., Elsevier

Publication Award

2017

Editor's Choice, Publication in Comput. Mater. Sci., Elsevier

Award

August 14, 2015

Best Teaching Assistant Award (ME 221), Duke University Department of Mechanical Engineering and Materials Science

Publication Award

2015

Editor's Choice, Publication in Comput. Mater. Sci., Elsevier

Publication Award

2015

Editor's Choice, Publication in Chem. Mater., American Chemical Society

Fellowship

2013–2016

Graduate Research Fellowship, National Science Foundation

Award

August 22, 2013

Best Presentation Award at the MEMS Departmental Retreat, Duke University Department of Mechanical Engineering and Materials Science

Award

March 02, 2013

First Place in Nanoscience and Physics Research Presentation, NSF / AAAS / EHR Emerging Researchers National Conference

Scholarship

2011–2013

Shell Incentive Fund Scholarship

Scholarship

2010 & 2011

Xerox Corporation Scholarship

Scholarship

2010 & 2011

Intel Academic Award

Grant

June 18, 2010

Cornell University Unmanned Air Systems Team awarded $1,000 grant, AUVSI Student Unmanned Aerial Systems Competition

Scholarship

2009–2013

Meinig Family Cornell National Scholars

Workshops

Organizer And Presenter

2020

AFLOW School: Integrated infrastructure for computational materials discovery

Co-Organizers: C. Toher, D. Hicks, M. Esters, E. Gossett, R. Friedrich, M. J. Brenner & S. Curtarolo

Presenter at the Dresden Center for Computational Materials Science (DCMS) Materials 4.0 Summer School 2020, Technische Universität Dresden — August 18, 2020.
- "Thermodynamics: AFLOW-CHULL" recording: youtu.be/ncm356YNBVc

Presenter at the NIST/Moore Foundation/University of Maryland Machine Learning for Materials Research Bootcamp 2019 & Workshop on Machine Learning Quantum Materials, Institute for Bioscience & Biotechnology Research in Gaithersburg, Maryland — July 23, 2020.
- "Materials Database and Machine Learning: AFLOW-ML" recording: youtu.be/x2qeBtOXues

Organizer and presenter at the Texas A&M University AFLOW Multi-Day Workshop, College Station, Texas — June 16–18, 2020.
- "Introduction to Density Functional Theory: VASP" recording: youtu.be/ChySAfo2w7g
- "Thermodynamics: AFLOW-CHULL" recording: youtu.be/9Sa8D4inJ5w
- "Disorder: AFLOW-POCC" recording: youtu.be/xr-mU-1ShQQ

Presenter at the NIST/Moore Foundation/University of Maryland Machine Learning for Materials Research Bootcamp 2019 & Workshop on Machine Learning Quantum Materials, Institute for Bioscience & Biotechnology Research in Gaithersburg, Maryland — August 05, 2019.

Organizer and presenter at the University of Pennsylvania AFLOW Full-Day Workshop, Philadelphia, Pennsylvania — May 03, 2019.

Organizer and presenter at the North Carolina State University AFLOW Full-Day Workshop, Raleigh, North Carolina — March 12, 2019.

Organizer and presenter at the Carnegie Mellon University AFLOW Full-Day Workshop, Pittsburgh, Pennsylvania — January 21, 2019.

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

Journal Publications

2020

Under Review

The Tin Pest Problem as a Test of Density Functionals Using High-Throughput Calculations

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

arXiv: arxiv:2010.07168

Under Review

Carbon Stoichiometry and Mechanical Properties of High Entropy Carbide

Authors: M. D. Hossain^†, T. Borman^†, F. 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

Under Review

Fermi energy engineering of enhanced toughness in high entropy carbides

Authors: T. J. Harrington^†, C. Oses^†, C. Toher, W. M. Mellor, K. Kaufmann, J. Gild, A. Wright, J. Luo, S. Curtarolo & K. S. Vecchio

^† contributed equally

Nature Communications

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

Nat. Commun. in press (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. Davidov, R. Agarwal, L. Bendersky, M. Li, A. Mehta & I. Takeuchi

^† contributed equally

DOI: 10.1038/s41467-020-19597-w

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

Nature Reviews Materials

High-entropy ceramics

Nat. Rev. Mater. 5, 295–309 (2020)

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

DOI: 10.1038/s41578-019-0170-8

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

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

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

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

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

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

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

Nature Communications

Novel 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

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

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 Editor's Choice.

DOI: 10.1016/j.commatsci.2018.03.075

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

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

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 Editor's Choice.

DOI: 10.1016/j.commatsci.2017.04.036

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

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

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. Hart

DOI: 10.1016/j.actamat.2016.09.017

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. D. Coey & S. Curtarolo

DOI: 10.1126/sciadv.1602241

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

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

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. Hart, M. Buongiorno Nardelli & S. Curtarolo

This paper was selected for Editor's Choice.

DOI: 10.1016/j.commatsci.2015.07.019

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 Editor's Choice.

DOI: 10.1021/cm503507h

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

URL: wiley.com/en-us/Materials+Informatics%3A+Methods%2C+Tools%2C+and+Applications-p-9783527802272

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

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. 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_63-1

Teaching Experience

Teaching Assistant

Spring 2020

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

Teaching Assistant

Fall 2014–Spring 2015

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

Best Teaching Assistant Award, August 14, 2015

Certifications

Participant

June 8–12, 2020

CECAM (Centre Européen de Calcul Atomique et Moléculaire) Open Databases Integration for Materials Design (OPTiMaDe) Workshop at the École polytechnique fédérale de Lausanne (EPFL)

Participant

June 11–14, 2019

CECAM (Centre Européen de Calcul Atomique et Moléculaire) Open Databases Integration for Materials Design (OPTiMaDe) Workshop at the École polytechnique fédérale de Lausanne (EPFL)

Graduate

June 25–29, 2018

Machine Learning Summer School (MLSS) at Duke University

Participant

June 11–15, 2018

CECAM (Centre Européen de Calcul Atomique et Moléculaire) Open Databases Integration for Materials Design (OPTiMaDe) Workshop at the École polytechnique fédérale de Lausanne (EPFL)

Graduate

January 7–16, 2015

Machine Learning Summer School (MLSS) at the University of Texas at Austin

Graduate

May 22–27, 2011

The LeaderShape Institute at Cornell University

Technician License

July 29, 2010

American Radio Relay League (ARRL) in Roselle, New Jersey