Lifeboat Foundation

Metamaterial Space Applications:

In this presentation I will talk about nanophotonics, more specifically metasurfaces – subwavelength patterned surfaces – and explain how this can be used for space applications. As recently displayed by the stunning images from the James Webb space telescope, we often rely on recording the intensity of light (e.g. with a camera) to study the universe. However, light fundamentally has several additional degrees of freedom which can carry information, e.g. polarization, phase, and spectral content. While it is true that many conventional optical components can address these degrees of freedom individually (e.g., polarizers, phase retarders, and filters), metasurfaces enable general manipulations of phase, amplitude, and polarization on the nanoscale, thereby providing ample opportunity to create new versions of existing components and even enable functionality not possible using conventional technologies. In the presentation I will cover several examples of metasurfaces I have been working on and explain their relevance for space applications. I will attempt to explain the working principles, why metasurfaces can be useful, as well as how we fabricate metasurfaces in a cleanroom.

About the speaker: Dr. Tobias Wenger is a postdoc at JPL’s microdevices laboratory (MDL) where his main efforts relate to nanophotonics — light at the nanoscale – and how we can engineer structures and components in order to control light in new ways. Tobias received his PhD from Chalmers University of Technology, Sweden, where he worked on understanding the physical properties of plasmons in graphene.

At JPL, Tobias is applying his knowledge of subwavelength electromagnetics to design metasurface-based optical components, mainly for infrared wavelengths. Metasurfaces are a novel approach to optics which uses subwavelength elements for controlling the phase, amplitude and polarization of transmitted and/or reflected electromagnetic radiation. Tobias research interests intersect optics, computational electromagnetics, and microfabrication and he enjoys both the practical and theoretical aspects of this work. During his postdoc time at MDL, he has worked on metasurface-based optical concentrators, IR detectors, plasmonic filters, wavefront sensing, and grating replication.

Circa 2016

I use my thoughts and a brain-computer interface to swoop through the air.

Circa 2021 force field this can also shield the earth or cities.

The computational design of functional materials relies heavily on large-scale atomistic simulations. Such simulations are often problematic for conventional classical force fields, which require tedious and time-consuming parameterization of interaction parameters. The problem can be solved using a quantum mechanically derived force field (QMDFF)—a system-specific force field derived directly from the first-principles calculations. We present a computational approach for atomistic simulations of complex molecular systems, which include the treatment of chemical reactions with the empirical valence bond approach. The accuracy of the QMDFF is verified by comparison with the experimental properties of liquid solvents.

The future is now as IBM unveils its comprehensive strategy to take quantum computing from noisy to useful. property= description.

Brain-computer interfaces have become a practical (if limited) reality in the US. Synchron says it has become the first in the country to implant a BCI in a human patient. Doctors in New York’s Mount Sinai West implanted the company’s Stentrode in the motor cortex of a participant in Synchron’s COMMAND trial, which aims to gauge the usefulness and safety of BCIs for providing hands-free device control to people with severe paralysis. Ideally, technology like Stentrode will offer independence to people who want to email, text and otherwise handle digital tasks that others take for granted.

Surgeons installed the implant using an endovascular procedure that avoids the intrusiveness of open-brain surgery by going through the jugular vein. The operation went “extremely well” and let the patient return home 48 hours later, according to Synchron. An ongoing Australian trial has also proven successful so far, with four patients still safe a year after receiving their implants.

It may take a long time before doctors can offer Synchron’s BCIs to patients. The company received FDA approval for human trials in July 2021, and it’s still expanding the COMMAND trial as of this writing. Still, the US procedure represents a significant step toward greater autonomy for people with paralysis. It also represents a competitive victory — Elon Musk’s Neuralink has yet to receive FDA permission for its own implant.

Google takes on the cause of rehabilitating old hardware with Chrome OS Flex.

ChromeOS Flex is designed to make obsolete computers functional to do work in the 21st century.

Researchers at the SketchX, University of Surrey have recently developed a meta learning-based model that allows users to retrieve images of specific items simply by sketching them on a tablet, smartphone, or on other smart devices. This framework was outlined in a paper set to be presented at the European Conference on Computer Vision (ECCV), one of the top three flagship computer vision conferences along with CVPR and ICCV.

Researchers at the SketchX, University of Surrey have recently developed a meta learning-based model that allows users to retrieve images of specific items simply by sketching them on a tablet, smartphone, or on other smart devices. This framework was outlined in a paper set to be presented at the European Conference on Computer Vision (ECCV), one of the top three flagship computer vision conferences along with CVPR and ICCV.

“This is the latest along the line of work on ‘fine-grained image retrieval,’ a problem that my research lab (SketchX, which I direct and founded back in 2012) pioneered back in 2015, with a paper published in CVPR 2015 titled ‘Sketch Me That Shoe,’” Yi-Zhe Song, one of the researchers who carried out the study, told TechXplore. “The idea behind our paper is that it is often hard or impossible to conduct image retrieval at a fine-grained level, (e.g., finding a particular type of shoe at Christmas, but not any shoe).”

In the past, some researchers tried to devise models that can retrieve images based on text or voice descriptions. Text might be easier for users to produce, yet it was found only to work at a coarse level. In other words, it can become ambiguous and ineffective when trying to describe details.