Laanait, N. | Search NASA

DOE OSTI2019

Optical creation of a supercrystal with three-dimensional nanoscale periodicity

Stimulation with ultrafast light pulses can realize and manipulate states of matter with emergent structural, electronic and magnetic phenomena. However, these non-equilibrium phases are often transient and the challenge is to stabilize them as persistent states. Here, we show that atomic-scale PbTiO 3 /SrTiO 3 superlattices, counterpoising strain and polarization states in alternate layers, are converted by sub-picosecond optical pulses to a supercrystal phase. This phase persists indefinitely under ambient conditions, has not been created via equilibrium routes, and can be erased by heating. X-ray scattering and microscopy show this unusual phase consists of a coherent three-dimensional structure with polar, strain and charge-ordering periodicities of up to 30 nm. By adjusting only dielectric properties, the phase-field model describes this emergent phase as a photo-induced charge-stabilized supercrystal formed from a two-phase equilibrium state. Furthermore our results demonstrate opportunities for light-activated pathways to thermally inaccessible and emergent metastable states.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform

Abstract Many spectral responses in materials science, physics, and chemistry experiments can be characterized as resulting from the superposition of a number of more basic individual spectra. In this context, unmixing is defined as the problem of determining the individual spectra, given measurements of multiple spectra that are spatially resolved across samples, as well as the determination of the corresponding abundance maps indicating the local weighting of each individual spectrum. Matrix factorization is a popular linear unmixing technique that considers that the mixture model between the individual spectra and the spatial maps is linear. Here, we present a tutorial paper targeted at domain scientists to introduce linear unmixing techniques, to facilitate greater understanding of spectroscopic imaging data. We detail a matrix factorization framework that can incorporate different domain information through various parameters of the matrix factorization method. We demonstrate many domain-specific examples to explain the expressivity of the matrix factorization framework and show how the appropriate use of domain-specific constraints such as non-negativity and sum-to-one abundance result in physically meaningful spectral decompositions that are more readily interpretable. Our aim is not only to explain the off-the-shelf available tools, but to add additional constraints when ready-made algorithms are unavailable for the task. All examples use the scalable open source implementation from https://github.com/ramkikannan/nmflibrary that can run from small laptops to supercomputers, creating a user-wide platform for rapid dissemination and adoption across scientific disciplines.

47 OTHER INSTRUMENTATION↗