#electron diffraction

wednesday 08/02/23

besties oh besties things have been falling apart LOL. but also not rly. after mocks i was beaten but now finals stretch started! 2/4 ias done, and my mocks results were relatively promising. finding love for class again, pictured are my physics notes on quantum physics theory

Let machines do the work: Automating semiconductor research with machine learning

The semiconductor industry has been growing steadily ever since its first steps in the mid-twentieth century and, thanks to the high-speed information and communication technologies it enabled, it has given way to the rapid digitalization of society. Today, in line with a tight global energy demand, there is a growing need for faster, more integrated, and more energy-efficient semiconductor devices.

However, modern semiconductor processes have already reached the nanometer scale, and the design of novel high-performance materials now involves the structural analysis of semiconductor nanofilms. Reflection high-energy electron diffraction (RHEED) is a widely used analytical method for this purpose. RHEED can be used to determine the structures that form on the surface of thin films at the atomic level and can even capture structural changes in real time as the thin film is being synthesized!

Unfortunately, for all its benefits, RHEED is sometimes hindered by the fact that its output patterns are complex and difficult to interpret. In virtually all cases, a highly skilled experimenter is needed to make sense of the huge amounts of data that RHEED can produce in the form of diffraction patterns. But what if we could make machine learning do most of the work when processing RHEED data?

Road to Crystalline © Tanya Rusnak

X-ray diffraction, a phenomenon in which the atoms of a crystal, by virtue of their uniform spacing, cause an interference pattern of the waves present in an incident beam of X rays. The atomic planes of the crystal act on the X rays in exactly the same manner as does a uniformly ruled grating on a beam of light.

Determining the structure of a molecule with laser-induced electron diffraction

Light microscopes have revolutionized our understanding of the microcosmos, but their resolution is limited to about 100 nanometers. To see how molecules bond, break, or change their structure, we need at least 1000 times better resolution.

Laser induced electron diffraction (LIED) is a technique which allows to pinpoint the individual atoms inside a single molecule, and to see where each atom moves when the molecule undergoes a reaction. This technique proved to be an amazing tool for the imaging molecules, such as water, carbonyl sulfide or carbon disulfide. However, using a strong laser field to generate the electron diffraction presented challenges in retrieving the exact structure, since the structural resolution depended on exact knowledge of the laser field itself.

In a study recently published in Nature Communications, ICFO researchers Aurelien Sanchez, Kasra Amini, Tobias Steinle, Xinyao Liu, led by ICREA Prof. at ICFO Jens Biegert, in collaboration with researchers from Kansas State University, Max-Planck-Institut für Kernphysik, Physikalisch-Technische Bundesanstalt, and Friedrich-Schiller-Universität Jena, have reported on an alternative and novel approach that retrieves accurate and precise information about the atomic structure without exact knowledge over the laser field. They successfully applied the method to imaging gas-phased molecule carbonyl sulfide (OCS), in particular on the bond lengths between the constituent atoms, showing a significant bent and asymmetrically stretched configuration of the ionized OCS+ structure.

Snapshots of Ultrafast Switching in Quantum Electronics Could Lead to Faster Computing Devices

They discover a short-lived state that could lead to faster and more energy-efficient computing devices.

Electronic circuits that compute and store information contain millions of tiny switches that control the flow of electric current. A deeper understanding of how these tiny switches work could help researchers push the frontiers of modern computing.

Now scientists have made the first snapshots of atoms moving inside one of those switches as it turns on and off. Among other things, they discovered a short-lived state within the switch that might someday be exploited for faster and more energy-efficient computing devices.

The research team from the Department of Energy’s SLAC National Accelerator Laboratory, Stanford University, Hewlett Packard Labs, Penn State University and Purdue University described their work in a paper published in Science today (July 15, 2021).