Three-Dimensional Integrated X-ray Diffraction Imaging of a Native Strain in Multi-Layered WSe₂

Abstract

Emerging two-dimensional (2-D) materials such as transition-metal dichalcogenides show great promise as viable alternatives for semiconductor and optoelectronic devices that progress beyond silicon. Performance variability, reliability, and stochasticity in the measured transport properties represent some of the major challenges in such devices. Native strain arising from interfacial effects due to the presence of a substrate is believed to be a major contributing factor. A full three-dimensional (3-D) mapping of such native nanoscopic strain over micron length scales is highly desirable for gaining a fundamental understanding of interfacial effects but has largely remained elusive. Here, we employ coherent X-ray diffraction imaging to directly image and visualize in 3-D the native strain along the (002) direction in a typical multilayered (∼100-350 layers) 2-D dichalcogenide material (WSe) on silicon substrate. We observe significant localized strains of ∼0.2% along the out-of-plane direction. Experimentally informed continuum models built from X-ray reconstructions trace the origin of these strains to localized nonuniform contact with the substrate (accentuated by nanometer scale asperities, i.e., surface roughness or contaminants); the mechanically exfoliated stresses and strains are localized to the contact region with the maximum strain near surface asperities being more or less independent of the number of layers. Machine-learned multimillion atomistic models show that the strain effects gain in prominence as we approach a few- to single-monolayer limit. First-principles calculations show a significant band gap shift of up to 125 meV per percent of strain. Finally, we measure the performance of multiple WSe transistors fabricated on the same flake; a significant variability in threshold voltage and the "off" current setting is observed among the various devices, which is attributed in part to substrate-induced localized strain. Our integrated approach has broad implications for the direct imaging and quantification of interfacial effects in devices based on layered materials or heterostructures.

Real-time coherent diffraction inversion using deep generative networks

“…Upon successful inversion of the diffraction pattern to an image, the local distortion of the crystal lattice is then displayed as a phase in the complex image of the sample 8 . X-ray CDI and Bragg CDI (BCDI) in particular have been widely used to provide an unique 4D view of dynamic processes including phonon transport 9 , 10 , transient melting 11 , dissolution and recrystallization 12 , phase transformations 13 , grain growth 14 and device characterization 15 , 16 . Notwithstanding its widespread use, reciprocal space phase retrieval algorithms suffer from several shortcomings.…”

“…8 X-ray CDI and Bragg CDI (BCDI) in particular have been widely used to provide an unique 4D view of dynamic processes including phonon transport, 9,10 transient melting, 11 dissolution and recrystallization, 12 phase transformations, 13 grain growth 14 and device characterization. 15,16 Notwithstanding its widespread use, reciprocal space phase retrieval algorithms suffer from several shortcomings. Firstly, the iterative phase retrieval algorithms that are commonly used, such as error-reduction (ER) and hybrid input-output (HIO) 17 or difference map (DM) 18 are time consuming, requiring thousands of iterations and multiple random initializations to converge to a solution with high confidence.…”

Time-Resolved X-Ray Microscopy for Materials Science

“…Figure 4 (a) Schematic of conventional CDI measurement in which the sample is smaller than the beam size. Reprinted with permission from (53). (b) Schematic of 3D Bragg ptychography where the sample is larger than the beam size and is scanned through overlapping measurements.…”

BLAST: bridging length/timescales via atomistic simulation toolkit

“…Despite significant improvements in materials modeling, our efforts to accurately capture atomic-scale dynamics, especially in low dimensional systems such as clusters and interfaces are still in their infancy. The interplay between often subtle dynamical processes at the nanoscale, including chemical reactions, transport of atoms and ions, defect chemistry, and solvation dynamics influences macroscopic observations and material properties [6][7][8][9][10][11][12]. A clear understanding of such dynamical in nanoscale clusters and across interfaces (e.g.…”