Background and justification:

Thanks to previous activities, GREAT2, GaN devices have been successfully developed enabling use of the devices into applications up to Ka-Band. However the efficiency is less than is required to meet future planned missions, in particular for the High Power Amplifier (HPA), which is a critical element for the deployment of active array/phase array antennas.  To achieve higher frequency transistor operation in the mm-wave range, design modifications of the device are required : it is necessary to shrink both the active device lateral (gate length) and vertical (channel barrier) dimensions.

The work carried out reports on a new machine learning-based software prototype for designing and optimising phased array antennas. The prototype can rapidly and accurately compute excitation coefficients for large-scale antenna arrays across diverse configurations and far-field requirements. The prototype relies on tailored neural networks integrating structural physics and domain knowledge using an encoder-decoder structure.

The SPOTTED project addresses the critical issue of marine debris, particularly plastic pollution, by enhancing detection and monitoring capabilities. Utilizing advanced spatio-temporal fusion (STF) techniques and Artificial Intelligence (AI) with high-resolution satellite imagery from Sentinel-2 (S2) and PlanetScope (PS), the project aims to refine S2 data and develop AI algorithms for identifying landfills and floating debris.

Conventional high-speed video cameras present major limitations for space applications, they are heavy, bulky and require a lot of resources to operate and to space qualify. The study proposes the use of the neuromorphic camera technology for high-speed imaging in space. Neuromorphic cameras, also called event-cameras, offer advantages such as small size, low power consumption, and high temporal resolution, making them suitable for detecting fast phenomena like lightning and space debris. The advantages also make them relatively easy to space-qualify.

Current European RF GaN power processes are optimised for up to K band, however the efficiency is less than is required to meet future planned missions. In order to meet the need for operation up to W band with up to 20% improvement in efficiency, together with improvements in linearity, a step change in device architecture is required.

Energy generation in Space poses a severe challenge, the answer to which may be the use of novel metamaterials for thermoelectric generators. Metamaterials can address this question by employing conventional materials and well-established fabrication technologies while leaving room for other approaches to increase the efficiency of thermoelectric generation. In the current study, we investigated possible configurations of metamaterials that could increase the efficiency of thermoelectric generators in Space.

The Rapid Apophis Mission for Security and Safety (RAMSES) primary mission objective is to characterize and monitor the dynamic behaviour of the asteroid 99942 Apophis before, during, and after its close Earth fly-by in 2029.

In this study we explore the potential of Large Language Models (LLMs) to interact with Earth Observation (EO) data with some promising first results. We source a first testing set for the BIG Bench framework. With 20+ subtasks, we aim for a large variety of questions which are currently beyond the capabilities of LLM and other models. Further, we implement a methodology to test proprietary state of the art models where token distribution may not be available.