Google (UBC/MIT/LBNL) post Nature updates.

Quote from Ahlfors

Private companies affiliated:

Ross Koningstein, Google Inc, USA

Ned Allen, Lockheed Martin, USA (to be confirmed)

Thank you for your finds!

"

Ian Langmore studied the mathematics of inverse problems under Gunther Uhlmann at the University of Washington

. After his PhD, he worked on probabilistic methods for inverse problems in transport with Guillaume Bal at Columbia.

At Google, Ian worked on Bayesian modeling for local search algorithms, before moving on to the inverse problem of plasma state reconstruction.

This places him happily at the intersection of applied probability, software engineering, and physics,

all with a real-world purpose. His secret goal is to use rigorous mathematics in engineering. "

https://research.google/people/IanLangmore/

Lots of maths .....but all this does is simply model everything we know anyway. How does this get us anywhere? Where is the new physics we need TG?

New Google USPTO patent --

United States Patent 10,566,094 February 18, 2020

Enhanced electron screening through plasmon oscillations

Abstract

Enhanced Coulomb repulsion screening around light element nuclei is achieved by way of utilizing electromagnetic (EM) radiation to induce plasmon oscillations in target structures (e.g., nanoparticles) in a way that produces high density electron clouds in localized regions of the target structures, thereby generating charge density variations around light element atoms located in the localized regions. Each target structure includes an electrically conductive body including light elements (e.g., a metal hydride/deuteride/tritide) that is configured to undergo plasmon oscillations in response to the applied EM radiation. The induced oscillations causes free electrons to converge in the localized region, thereby producing transient high electron charge density levels that enhance Coulomb repulsion screening around light element (e.g., deuterium) atoms located in the localized regions. Various systems capable of implementing enhanced Coulomb repulsion screening are described, and various nanostructure compositions and configurations are disclosed that serve to further enhance fusion reaction rates.

http://patft.uspto.gov/netacgi…,566,094&RS=PN/10,566,094

I wonder if TG have actually made a working reactor system based on this patent. The nanoparticles setup described is remarkably similar to Takahashi at al's distribution of CuNi or Pd/Ni nanoparticles distributed as 'islands' on a Zirconia base so since this has been now shown repeatably to produce excess heat

there's a high probability that this TG proposed device will also work. But why no examples of this working device in the patent? Possibly the Thz EM stimulation is provided simply by heating the Takahashi samples up to 300 deg . C. Interesting that two unrelated groups are coming up with similar nanoparticles designs at the same time, throwing in some KFeO2 catalyst to increase the probability of fusion by quasi-neutron or H* formation in addition to electron screening completes the picture!

Quote from Dr Richard

I wonder if TG have actually made a working reactor system based on this patent. The nanoparticles setup described is remarkably similar to Takahashi at al's distribution of CuNi or Pd/Ni nanoparticles distributed as 'islands' on a Zirconia base so since this has been now shown repeatably to produce excess heat

there's a high probability that this TG proposed device will also work. But why no examples of this working device in the patent? Possibly the Thz EM stimulation is provided simply by heating the Takahashi samples up to 300 deg . C. Interesting that two unrelated groups are coming up with similar nanoparticles designs at the same time, throwing in some KFeO2 catalyst to increase the probability of fusion by quasi-neutron or H* formation in addition to electron screening completes the picture!

If the rate of interaction, efficiency, density and intensity of the many pico-chemical reactions between hydrogen isotopes, electrons, catalysts and hydride forming transition metals were kindled I don't think we would need the fusion/fission/annialation reactions! We are playing with smoldering embers that can arise with engineering, becoming powerful engines!

Quote from Dr Richard

I wonder if TG have actually made a working reactor system based on this patent. The nanoparticles setup described is remarkably similar to Takahashi at al's distribution of CuNi or Pd/Ni nanoparticles distributed as 'islands' on a Zirconia base so since this has been now shown repeatably to produce excess heat

there's a high probability that this TG proposed device will also work. But why no examples of this working device in the patent? Possibly the Thz EM stimulation is provided simply by heating the Takahashi samples up to 300 deg . C. Interesting that two unrelated groups are coming up with similar nanoparticles designs at the same time, throwing in some KFeO2 catalyst to increase the probability of fusion by quasi-neutron or H* formation in addition to electron screening completes the picture!

There was a publication a little while ago from Berlinguette's team, with David Fork as a co-author, that related to palladium nanoparticles and hydrogen absorption. It's of course speculation, but it certainly seems like they've made it a focus of their program?

https://pubs.acs.org/doi/abs/10.1021/acs.chemmater.9b02193

This reminds me of the principles of thermoacoustic engines - e.g. creating pressure oscillations to extract energy from the higher pressure portions of the sonic waves

for a ref see: NEW VARIETIES OF THERMOACOUSTIC ENGINES, S,Backhaus and G.Swift, LANL report LA-UR-02-2721, available at http://citeseerx.ist.psu.edu/v…19.9971&rep=rep1&type=pdf

Strain Influences the Hydrogen Evolution Activity and Absorption Capacity of Palladium

Ryan P. Jansonius, Phil A. Schauer, David J. Dvorak, Benjamin P. MacLeod, David. K. Fork, Curtis Berlinguette

Strain‐engineering can be used to increase the activity and selectivity of an electrocatalyst. Tensile strain is known to improve the electrocatalytic activity of palladium electrodes for reduction of carbon dioxide or dioxygen, but determining how strain affects the hydrogen evolution reaction (HER) is complicated by the fact that palladium can absorb hydrogen concurrently with HER. We report here a custom electrochemical cell that applies tensile strain to a flexible working electrode that enabled us to resolve how tensile strain affects hydrogen absorption and HER activity for a thin film palladium electrocatalyst. When the electrodes were subjected to mechanically‐applied tensile strain, the amount of hydrogen that absorbed into the palladium decreased, and HER electrocatalytic activity increased. This study showcases how strain can be used to modulate the hydrogen absorption capacity and HER activity of palladium.

https://onlinelibrary.wiley.co…bs/10.1002/anie.202005248

I'm guessing that strain from bending a piece of palladium would open up cracks on one side and squeeze them shut on the other.
(Paper is paywalled)

Aspen Winter Meeting : probably a very cool place. Hope I will sell a patent or two in rder to be able to go there next year ...

https://www.simonsfoundation.o…ation-meets-experiments/#

Quantifying Defects in Thin Films using Machine Vision

Nina Taherimakhsousi, Benjamin P. MacLeod, Fraser G. L. Parlane, Thomas D. Morrissey, Edward P. Booker, Kevan E. Dettelbach, Curtis P. Berlinguette

The sensitivity of thin-film materials and devices to defects motivates extensive research into the optimization of film morphology. This research could be accelerated by automated experiments that characterize the response of film morphology to synthesis conditions. Optical imaging can resolve morphological defects in thin films and is readily integrated into automated experiments but the large volumes of images produced by such systems require automated analysis. Existing approaches to automatically analyzing film morphologies in optical images require application-specific customization by software experts and are not robust to changes in image content or imaging conditions. Here we present a versatile convolutional neural network (CNN) for thin-film image analysis which can identify and quantify the extent of a variety of defects and is applicable to multiple materials and imaging conditions. This CNN is readily adapted to new thin-film image analysis tasks and will facilitate the use of imaging in automated thin-film research systems.

https://arxiv.org/abs/2003.04860

Quote from fabrice DAVID

Aspen Winter Meeting : probably a very cool place. Hope I will sell a patent or two in rder to be able to go there next year ...

https://www.simonsfoundation.o…ation-meets-experiments/#

Это где мой друг, ссылка не открывается, еще раз глянь...

Matt Trevithick just tweeted this:

https://www.prnewswire.com/new…imate-tech-301077638.html