Electron Beam Guides Engineering of Functional Defects
May 20, 2015 — The electron beam of a scanning transmission electron microscope was applied to generate Se vacancies in a semiconducting monolayer of MoSe2, provide energy to drive the formation and growth of inversion domains and metallic 60˚ grain boundaries, and track the dynamics.
Oxygen Controls Surface of Epitaxial Manganite Films
May 18, 2015 — This atomically resolved study revealed a strong link between oxygen pressure and both surface-structure formation and growth dynamics in manganite thin films. The work provides key insights into controlling atomic-level behavior necessary for growing functional materials, such as manganese oxides for electronic and solid-oxide fuel cell applications.
Confining Liquids in Hollow Nanospheres Can Yield Superior Quasi-Solid Electrolytes
May 06, 2015 — The growth and proliferation of lithium dendrites during cell recharge seriously hinder development and application of rechargeable Li-metal batteries. Researchers developed a promising strategy for fabrication of quasi−solid electrolytes with superior lithium ionic conductivities, by using a hollow silica (HS) nanosphere-film architecture that blocks dendrites.
Materials scientists use ORNL’s CADES to transform big data to ‘smart data’ for rapid image analysis
April 20, 2015 — Materials scientists use ORNL’s CADES to transform big data to ‘smart data’ for rapid image analysis. ORNL material sciences researchers are collaborating with computer scientists in ORNL’s Compute and Data Environment for Science (CADES) to create a processing and analysis workflow for the expansive scanning probe and electron microscopy data generated at the Center for Nanophase Materials Sciences (CNMS).
Researchers use machine learning to find useful structural properties in neutron and x-ray data
April 17, 2015 — Using CADES compute and data resources, researchers are linking DOE experimental and computational facilities to uncover stacking faults in double-layered perovskite. Here is the title and blurb to use on the webpage: Researchers use machine learning to find useful structural properties in neutron and x-ray data. A team of ORNL researchers is using the lab’s Compute and Data Environment for Science (CADES) to analyze large volumes of neutron and x-ray scattering data to find and identify these defects—a first step to greatly reducing time researchers spend on comparing and contrasting scattering data to identify connections between structure and function.
True structure of pnictide 122 superconductors revealed
April 13, 2015 — High-resolution microscopy revealed an unexpected room-temperature crystal structure of the ‘122’ Ba(Fe1-xCox)2As2 superconductors, with domains similar to those in ferroelectrics but with nanometer size.
New model predicts formation of stable high-entropy alloys
April 09, 2015 — Researchers devised a model that can predict which combinations of 5 or more elements will form new “high-entropy alloys.” This work, which utilizes values obtained from data mining of high-throughput calculations of binary compounds, requires no experimental or empirically derived input and advances capabilities for “materials by design.
Atomic-Scale Observations Aid Mesoscale Catalyst Design
April 08, 2015 — Two phases of Mo-V-O–based oxides, M1 and M2, are promising catalysts for direct conversion of propane to acrylonitrile and are believed to act synergistically. Researchers engineered the mesoscale structure of M1- and M2-phase oxides to amplify these effects, greatly improving selectivity for propane ammoxidation.
Technique Recovers Atomic Resolution in Spectrum Images
April 08, 2015 — Researchers have demonstrated a technique for obtaining atomic-resolution information from spectrum images of thick specimens of MnFePSi compounds, which are promising for ecofriendly refrigeration. This technique allows the quantitative examination of specimens for which atomic-resolution spectroscopic analysis was previously impossible.
World's Thinnest Proton Channel
March 18, 2015 — Graphene is a single-atom thin 2-dimensional array of carbon atoms that represents a barrier that is impenetrable even to protons unless graphene membrane has macroscopic holes.