arXiv subjects

Alex Belianinov

Publications and source records attributed to Alex Belianinov.

4 recordsLinked to original sources

arXiv2019

USID and Pycroscopy -- Open frameworks for storing and analyzing spectroscopic and imaging data

Materials science is undergoing profound changes due to advances in characterization instrumentation that have resulted in an explosion of data in terms of volume, velocity, variety and complexity. Harnessing these data for scientific research requires an evolution of the associated computing and data infrastructure, bridging scientific instrumentation with super- and cloud- computing. Here, we describe Universal Spectroscopy and Imaging Data (USID), a data model capable of representing data from most common instruments, modalities, dimensionalities, and sizes. We pair this schema with the hierarchical data file format (HDF5) to maximize compatibility, exchangeability, traceability, and reproducibility. We discuss a family of community-driven, open-source, and free python software packages for storing, processing and visualizing data. The first is pyUSID which provides the tools to read and write USID HDF5 files in addition to a scalable framework for parallelizing data analysis. The second is Pycroscopy, which provides algorithms for scientific analysis of nanoscale imaging and spectroscopy modalities and is built on top of pyUSID and USID. The instrument-agnostic nature of USID facilitates the development of analysis code independent of instrumentation and task in Pycroscopy which in turn can bring scientific communities together and break down barriers in the age of open-science. The interested reader is encouraged to be a part of this ongoing community-driven effort to collectively accelerate materials research and discovery through the realms of big data.

physics.data-an↗

arXiv2017

High conduction hopping behavior induced in transition metal dichalcogenides by percolating defect networks: toward atomically thin circuits

Atomically thin circuits have recently been explored for applications in next-generation electronics and optoelectronics and have been demonstrated with two-dimensional lateral heterojunctions. In order to form true 2D circuitry from a single material, electronic properties must be spatially tunable. Here, we report tunable transport behavior which was introduced into single layer tungsten diselenide and tungsten disulfide by focused He$^+$ irradiation. Pseudo-metallic behavior was induced by irradiating the materials with a dose of ~1x10$^{16} He^+/cm^2$ to introduce defect states, and subsequent temperature-dependent transport measurements suggest a nearest neighbor hopping mechanism is operative. Scanning transmission electron microscopy and electron energy loss spectroscopy reveal that Se is sputtered preferentially, and extended percolating networks of edge states form within WSe$_2$ at a critical dose of 1x10$^{16} He^+/cm^2$. First-principles calculations confirm the semiconductor-to-metallic transition of WSe$_2$ after pore and edge defects were introduced by He$^+$ irradiation. The hopping conduction was utilized to direct-write resistor loaded logic circuits in WSe$_2$ and WS$_2$ with a voltage gain of greater than 5. Edge contacted thin film transistors were also fabricated with a high on/off ratio (> 10$^6$), demonstrating potential for the formation of atomically thin circuits.

cond-mat.mtrl-sci↗

arXiv2017

Two-Level Structural Sparsity Regularization for Identifying Lattices and Defects in Noisy Images

This paper presents a regularized regression model with a two-level structural sparsity penalty applied to locate individual atoms in a noisy scanning transmission electron microscopy image (STEM). In crystals, the locations of atoms is symmetric, condensed into a few lattice groups. Therefore, by identifying the underlying lattice in a given image, individual atoms can be accurately located. We propose to formulate the identification of the lattice groups as a sparse group selection problem. Furthermore, real atomic scale images contain defects and vacancies, so atomic identification based solely on a lattice group may result in false positives and false negatives. To minimize error, model includes an individual sparsity regularization in addition to the group sparsity for a within-group selection, which results in a regression model with a two-level sparsity regularization. We propose a modification of the group orthogonal matching pursuit (gOMP) algorithm with a thresholding step to solve the atom finding problem. The convergence and statistical analyses of the proposed algorithm are presented. The proposed algorithm is also evaluated through numerical experiments with simulated images. The applicability of the algorithm on determination of atom structures and identification of imaging distortions and atomic defects was demonstrated using three real STEM images. We believe this is an important step toward automatic phase identification and assignment with the advent of genomic databases for materials.

stat.AP↗

arXiv2017

Engineering the thermal conductivity along an individual silicon nanowire by selective helium ion irradiation

The ability to engineer the thermal conductivity of materials allows us to control the flow of heat and derive novel functionalities such as thermal rectification, thermal switching, and thermal cloaking. While this could be achieved by making use of composites and metamaterials at bulk scales, engineering the thermal conductivity at micro- and nano-scale dimensions is considerably more challenging. In this work we show that the local thermal conductivity along a single Si nanowire can be tuned to a desired value (between crystalline and amorphous limits) with high spatial resolution through selective helium ion irradiation with a well-controlled dose. The underlying mechanism is understood through molecular dynamics simulations and quantitative phonon-defect scattering rate analysis, where the behavior of thermal conductivity with dose is attributed to the accumulation and agglomeration of scattering centers at lower doses. Beyond a threshold dose, a crystalline-amorphous transition was observed.

cond-mat.mtrl-sci↗