AtomVision: A Machine Vision Library for Atomistic Images.

Computer vision techniques have immense potential for materials design applications. In this work, we introduce an integrated and general-purpose AtomVision library that can be used to generate and curate microscopy image (such as scanning tunneling microscopy and scanning transmission electron microscopy) data sets and apply a variety of machine learning techniques. To demonstrate the applicability of this library, we (1) establish an atomistic image data set of about 10 000 materials with large structural and chemical diversity, (2) develop and compare convolutional and atomistic line graph neural network models to classify the Bravais lattices, (3) demonstrate the application of fully convolutional neural networks using U-Net architecture to pixelwise classify atom versus background, (4) use a generative adversarial network for super resolution, (5) curate an image data set on the basis of natural language processing using an open-access arXiv data set, and (6) integrate the computational framework with experimental microscopy images for Rh, Fe3O4, and SnS systems. The AtomVision library is available at https://github.com/usnistgov/atomvision.

The effect of Mg3As2 alloying on the thermoelectric properties of n-type Mg3(Sb, Bi)2.

Mg3Sb2-Mg3Bi2 alloys have been heavily studied as a competitive alternative to the state-of-the-art n-type Bi2(Te,Se)3 thermoelectric alloys. Using Mg3As2 alloying, we examine another dimension of exploration in Mg3Sb2-Mg3Bi2 alloys and the possibility of further improvement of thermoelectric performance was investigated. While the crystal structure of pure Mg3As2 is different from Mg3Sb2 and Mg3Bi2, at least 15% arsenic solubility on the anion site (Mg3((Sb0.5Bi0.5)1-xAsx)2: x = 0.15) was confirmed. Density functional theory calculations showed the possibility of band convergence by alloying Mg3Sb2-Mg3Bi2 with Mg3As2. Because of only a small detrimental effect on the charge carrier mobility compared to cation site substitution, the As 5% alloyed sample showed zT = 0.6-1.0 from 350 K to 600 K. This study shows that there is an even larger composition space to examine for the optimization of material properties by considering arsenic introduction into the Mg3Sb2-Mg3Bi2 system.

Weighted Mobility.

Engineering semiconductor devices requires an understanding of charge carrier mobility. Typically, mobilities are estimated using Hall effect and electrical resistivity meausrements, which are are routinely performed at room temperature and below, in materials with mobilities greater than 1 cm2 V-1 s-1 . With the availability of combined Seebeck coefficient and electrical resistivity measurement systems, it is now easy to measure the weighted mobility (electron mobility weighted by the density of electronic states). A simple method to calculate the weighted mobility from Seebeck coefficient and electrical resistivity measurements is introduced, which gives good results at room temperature and above, and for mobilities as low as 10-3 cm2 V-1 s-1 , [Formula: see text] Here, µw is the weighted mobility, ρ is the electrical resistivity measured in mΩ cm, T is the absolute temperature in K, S is the Seebeck coefficient, and kB /e = 86.3 µV K-1 . Weighted mobility analysis can elucidate the electronic structure and scattering mechanisms in materials and is particularly helpful in understanding and optimizing thermoelectric systems.