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PUBMED FOR HANDHELDS

Journal Abstract Search


191 related items for PubMed ID: 25770548

  • 21.
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  • 22. Combinatorial measurement of critical cooling rates in aluminum-base metallic glass forming alloys.
    Liu N, Ma T, Liao C, Liu G, Mota RMO, Liu J, Sohn S, Kube S, Zhao S, Singer JP, Schroers J.
    Sci Rep; 2021 Feb 16; 11(1):3903. PubMed ID: 33594154
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  • 25. Evolutionary design of machine-learning-predicted bulk metallic glasses.
    Forrest RM, Greer AL.
    Digit Discov; 2023 Feb 13; 2(1):202-218. PubMed ID: 36798881
    [Abstract] [Full Text] [Related]

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  • 27. Proposed long-range empirical potential to study the metallic glasses in the Ni-Nb-Ta system.
    Dai Y, Li JH, Che XL, Liu BX.
    J Phys Chem B; 2009 May 21; 113(20):7282-90. PubMed ID: 19438281
    [Abstract] [Full Text] [Related]

  • 28. Fatigue and corrosion of a Pd-based bulk metallic glass in various environments.
    Watanabe LY, Roberts SN, Baca N, Wiest A, Garrett SJ, Conner RD.
    Mater Sci Eng C Mater Biol Appl; 2013 Oct 21; 33(7):4021-5. PubMed ID: 23910309
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  • 29. Atomistic modeling to optimize composition and characterize structure of Ni-Zr-Mo metallic glasses.
    Yang MH, Li SN, Li Y, Li JH, Liu BX.
    Phys Chem Chem Phys; 2015 May 28; 17(20):13355-65. PubMed ID: 25923843
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  • 30. Connectivity and free-surface effects in polymer glasses.
    Lappala A, Sefton L, Fenimore PW, Terentjev EM.
    Sci Rep; 2019 Mar 07; 9(1):3830. PubMed ID: 30846731
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  • 31. Predictive modeling of Time-Temperature-Transformation diagram of metallic glasses based on atomistically-informed classical nucleation theory.
    Sato Y, Nakai C, Wakeda M, Ogata S.
    Sci Rep; 2017 Aug 03; 7(1):7194. PubMed ID: 28775268
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  • 32. Designing High Entropy Bulk Metallic Glass (HE-BMG) by Similar Element Substitution/Addition.
    Ding H, Luan H, Bu H, Xu H, Yao K.
    Materials (Basel); 2022 Feb 23; 15(5):. PubMed ID: 35268898
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  • 33. Spin-exchange interaction between transition metals and metalloids in soft-ferromagnetic metallic glasses.
    Das S, Choudhary K, Chernatynskiy A, Choi Yim H, Bandyopadhyay AK, Mukherjee S.
    J Phys Condens Matter; 2016 Jun 02; 28(21):216003. PubMed ID: 27143686
    [Abstract] [Full Text] [Related]

  • 34. Thermodynamically-guided machine learning modelling for predicting the glass-forming ability of bulk metallic glasses.
    Ghorbani A, Askari A, Malekan M, Nili-Ahmadabadi M.
    Sci Rep; 2022 Jul 11; 12(1):11754. PubMed ID: 35817887
    [Abstract] [Full Text] [Related]

  • 35. Machine Learning Approach for Prediction and Understanding of Glass-Forming Ability.
    Sun YT, Bai HY, Li MZ, Wang WH.
    J Phys Chem Lett; 2017 Jul 20; 8(14):3434-3439. PubMed ID: 28697303
    [Abstract] [Full Text] [Related]

  • 36. Polyamorphism in a metallic glass.
    Sheng HW, Liu HZ, Cheng YQ, Wen J, Lee PL, Luo WK, Shastri SD, Ma E.
    Nat Mater; 2007 Mar 20; 6(3):192-7. PubMed ID: 17310140
    [Abstract] [Full Text] [Related]

  • 37. Atomic-Approach to Predict the Energetically Favored Composition Region and to Characterize the Short-, Medium-, and Extended-Range Structures of the Ti-Nb-Al Ternary Metallic Glasses.
    Cai B, Liu J, Li J, Yang M, Liu B.
    Materials (Basel); 2019 Jan 31; 12(3):. PubMed ID: 30708955
    [Abstract] [Full Text] [Related]

  • 38.
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  • 40. Formation of zirconium metallic glass.
    Zhang J, Zhao Y.
    Nature; 2004 Jul 15; 430(6997):332-5. PubMed ID: 15254533
    [Abstract] [Full Text] [Related]


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