Mlatticeabc: Generic Lattice Constant Prediction of Crystal Materials Using Machine Learning

Yuxin Li; Wenhui Yang; Rongzhi Dong; Jianjun Hu

doi:10.1021/acsomega.1c00781

Mlatticeabc: Generic Lattice Constant Prediction of Crystal Materials Using Machine Learning

ACS Omega ◽

10.1021/acsomega.1c00781 ◽

2021 ◽

Vol 6 (17) ◽

pp. 11585-11594

Author(s):

Yuxin Li ◽

Wenhui Yang ◽

Rongzhi Dong ◽

Jianjun Hu

Keyword(s):

Machine Learning ◽

Lattice Constant

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Machine Learning the Lattice Constant of Cubic Pyrochlore Compounds

International Journal of Applied Ceramic Technology ◽

10.1111/ijac.13709 ◽

2021 ◽

Author(s):

Yun Zhang ◽

Xiaojie Xu

Keyword(s):

Machine Learning ◽

Lattice Constant ◽

Pyrochlore Compounds

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Mind wandering as data augmentation: How mental travel supports abstraction

Behavioral and Brain Sciences ◽

10.1017/s0140525x1900311x ◽

2020 ◽

Vol 43 ◽

Author(s):

Myrthe Faber

Keyword(s):

Machine Learning ◽

Data Augmentation ◽

Mental Content ◽

Mind Wandering ◽

Theoretical Framework ◽

Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

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Atomic structure of stair rod misfit dislocations at the GaAs on Si(100) interface

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100174849 ◽

1990 ◽

Vol 48 (4) ◽

pp. 342-343

Author(s):

D. Gerthsen

Keyword(s):

Lattice Constant ◽

Atomic Structure ◽

Spherical Aberration ◽

Stacking Faults ◽

Misfit Dislocations ◽

Gaas On Si ◽

Thermal Expansion Coefficients ◽

Transmission Electron ◽

Intersection Line ◽

Oriented Parallel

The prospect of technical applications has induced a lot of interest in the atomic structure of the GaAs on Si(100) interface and the defects in its vicinity which are often studied by high resolution transmission electron microscopy. The interface structure is determined by the 4.1% lattice constant mismatch between GaAs and Si, the large difference between the thermal expansion coefficients and the polar/nonpolar nature of the GaAs on Si interface. The lattice constant mismatch is compensated by misfit dislocations which are characterized by a/2<110> Burgers vectors b which are oriented parallel or inclined on {111} planes with respect to the interface. Stacking faults are also frequently observed. They are terminated by partial dislocations with b = a/6<112> on {111} planes. In this report, the atomic structure of stair rod misfit dislocations is analysed which are located at the intersection line of two stacking faults at the interface.A very thin, discontinous film of GaAs has been grown by MBE on a Si(100) substrate. Fig.1.a. shows an interface section of a 27 nm wide GaAs island along [110] containing a stair rod dislocation. The image has been taken with a JEOL 2000EX with a spherical aberration constant Cs = 1 mm, a spread of focus Δz = 10 nm and an angle of beam convergence ϑ of 2 mrad.

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