Following my retirement, we have closed our company for new business.

Please do not hesitate to contact me directly, our email portal remains open and I would be delighted to hear from you and provide ongoing support or advice.

Richard Thomson

support@rta-instruments.com

Companies represented up to the end of December 2023. Please now contact them directly.

k-Space Associates, Inc.
Phone: +1 (734) 426-7977
requestinfo@k-space.com
https://www.k-space.com

STAIB INSTRUMENTS GmbH
Phone: +49 8761 76 24 0
sales@staibinstruments.com
https://www.staibinstruments.com/

Friday 29 March 2019

Thursday 28 March 2019

Wednesday 20 March 2019

PVD Products, Inc. partnership with Northwestern University

Through extensive communication, PVD and Northwestern University have developed a custom system that allowed them to expand and improve their deposition applications. 

Friday 15 March 2019

Thermo Scientific correlates XPS and Raman

Correlative chemical & structural analysis of 2D materials is easy with the right tool like the Thermo Scientific™ Nexsa™ XPS System. Watch the webinar, it’s around 10 minutes, so perfect for a coffee break!

Wednesday 13 March 2019

LIGO to double

A  $35M upgrade to the Laser Interferometer Gravitational-Wave Observatory will see a doubling of its sensitivity to gravitational waves. 

Monday 11 March 2019

Taiwan (21.8%) and S. Korea (21.3%) head the global IC wafer capacity in 2018 according to the Global Wafer Capacity 2019-2023 report.

Friday 8 March 2019

Oppy dies on Mars

Rover over, One dead?
Last month NASA declared that after nearly 15 years of successfully trundling around Mars the exploration rover nicknamed "Oppy" had ceased to function. A far less auspicious Martian enterprise may also have come to an end with Mars One Ventures AG entering administration. The proposed reality TV funded project to send people to Mars may sadly linger on through a new investor.

Wednesday 6 March 2019

Dangerous tools?
A paper at the American Association for the Advancement of Science meeting has questioned whether we are producing erroneous science by the use of machine learning algorithms. The concern being that these tools have been developed specifically to find interesting things in datasets and so when they search through huge amounts of data they will inevitably find a pattern. A lack of reproducibility in science may also be a result. Others suggest that it is not the tools but how they are used that produces problems.