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Работы, на которые ссылается эта работа

Работ: 125

Работа: Data-driven discovery of novel synthesizable MAX phase materials

  1. Pressure-Induced Stabilization and Insulator-Superconductor Transition of BH

    Chaohao Hu, Artem R. Oganov, Qiang Zhu +4

    Статья2013Цитирований: 3
    ABI

  2. Evolutionary method for predicting surface reconstructions with variable stoichiometry

    Qiang Zhu, Li Li, Artem R. Oganov +1

    Статья2013Цитирований: 3
    ABI

  3. USPEX—Evolutionary crystal structure prediction

    Colin W. Glass, Artem R. Oganov, Nikolaus Hansen

    Статья2006Цитирований: 3
    ABI

  4. Machine-learning-assisted materials discovery using failed experiments

    Paul Raccuglia, Katherine C. Elbert, Philip Adler +7

    Статья2016Цитирований: 3
    ABI

  5. The thermodynamic scale of inorganic crystalline metastability

    Wenhao Sun, Stephen Dacek, Shyue Ping Ong +6

    Статья2016Цитирований: 3
    ABI

  6. Thermodynamic limit for synthesis of metastable inorganic materials

    Muratahan Aykol, Shyam Dwaraknath, Wenhao Sun +1

    Статья2018Цитирований: 3
    ABI

  7. Machine-learning interatomic potentials enable first-principles multiscale modeling of lattice thermal conductivity in graphene/borophene heterostructures

    Bohayra Mortazavi, Evgeny V. Podryabinkin, Stephan Roche +3

    Статья2020Цитирований: 3
    ABI

  8. Machine-learning interatomic potentials enable first-principles multiscale modeling of lattice thermal conductivity in graphene/borophene heterostructures

    Mortazavi, Bohayra, Podryabinkin, Evgeny V., Roche, Stephan +3

    Статья2020Цитирований: 3
    ABI

  9. Predicting the Electronic and Structural Properties of Two-Dimensional Materials Using Machine Learning

    Ehsan Alibagheri, Bohayra Mortazavi, Timon Rabczuk

    Статья2021Цитирований: 3
    ABI

  10. Novel two-dimensional boron oxynitride predicted using the USPEX evolutionary algorithm

    Захар И. Попов, Kseniya A. Tikhomirova, V. A. Demin +4

    Статья2021Цитирований: 3
    ABI

  11. Remarkable Optoelectronic Characteristics of Synthesizable Square‐Octagon Haeckelite Structures: Machine Learning Materials Discovery

    Ehsan Alibagheri, Ahmad Ranjbar, Mohammad Khazaei +2

    Статья2024Цитирований: 3
    ABI

  12. Beyond metals: theoretical discovery of semiconducting MAX phases and their potential application in thermoelectrics

    Mohammad Khazaei, Iraj Maleki, Namitha Anna Koshi +11

    СтатьяMXene and MAX Phase MaterialsPhysical Chemistry Chemical Physics2024Цитирований: 2
    ABI

  13. <scp>LAX</scp> phases: A family of novel stable layered materials, informatics‐based discovery

    Ehsan Alibagheri, Mohammad Khazaei, Mehdi Estili +5

    СтатьяMXene and MAX Phase MaterialsInfoMat2025Цитирований: 2
    ABI

  14. Prediction of MAX phases, VN+1SiCN (N=1,2), from first-principles theory

    Chun Fang, Rajeev Ahuja, Olle Eriksson

    Статья2007Цитирований: 2
    ABI

  15. Trends in electronic structures and structural properties of MAX phases: a first-principles study on M<sub>2</sub>AlC (M = Sc, Ti, Cr, Zr, Nb, Mo, Hf, or Ta), M<sub>2</sub>AlN, and hypothetical M<sub>2</sub>AlB phases

    Mohammad Khazaei, M. Arai, Taizo Sasaki +2

    Статья2014Цитирований: 2
    ABI

  16. Accelerating materials property predictions using machine learning

    Ghanshyam Pilania, Chenchen Wang, Xun Jiang +2

    Статья2013Цитирований: 2
    ABI

  17. First‐Principles Determination of Multicomponent Hydride Phase Diagrams: Application to the Li‐Mg‐N‐H System

    Alireza Akbarzadeh, Vidvuds Ozoliņš, Chris Wolverton

    Статья2007Цитирований: 2
    ABI

  18. Prediction of Synthesis of 2D Metal Carbides and Nitrides (MXenes) and Their Precursors with Positive and Unlabeled Machine Learning

    Nathan C. Frey, Jin Wang, Gabriel Iván Vega Bellido +3

    Статья2019Цитирований: 2
    ABI

  19. In- and Out-of-Plane Ordered MAX Phases and Their MXene Derivatives

    Johanna Rosén, Martin Dahlqvist, Quanzheng Tao +1

    Глава2019Цитирований: 2
    ABI

  20. The role of Hume-Rothery's rules play in the MAX phases formability

    Yiming Zhang, Zeyu Mao, Qi Han +5

    Статья2020Цитирований: 2
    ABI

  21. Без названия

    ДругоеЦитирований: 2
    ABI

  22. Machine learning for high performance organic solar cells: current scenario and future prospects

    Asif Mahmood, Jin‐Liang Wang

    Статья2020Цитирований: 2
    ABI

  23. Machine Learning: An Advanced Platform for Materials Development and State Prediction in Lithium‐Ion Batteries

    Chade Lv, Xin Zhou, Lixiang Zhong +8

    Обзорная статья2021Цитирований: 2
    ABI

  24. Без названия

    ДругоеЦитирований: 2
    ABI

  25. Maximizing the mechanical performance of Ti3AlC2-based MAX phases with aid of machine learning

    Xingjun Duan, Zhi Fang, Tao Yang +5

    Статья2022Цитирований: 2
    ABI