Through a holistic approach, APOLO aims to tackle the challenges of power conversion from ammonia and develop an efficient and flexible ammonia cracking technology. This technology will be coupled with fuel cells and engines to achieve complete decarbonization of the maritime sector. As the main objective of the call is to demonstrate scalability beyond 3MW, the consortium will focus on showcasing the following demonstration units: i) A 125kW power conversion system that utilizes an ammonia cracker coupled with a PEM fuel cell system, achieving an overall system efficiency of 51% to 54%. The ammonia cracker will be customized to work with different pressure conditions and efficiency levels of PEM fuel cells. A comparison of efficiency levels will be conducted to evaluate the flexibility of the cracking system for all types of PEM fuel cells. ii) A 125kW partial ammonia cracker coupled with a 4-stroke engine, exhibiting an overall system efficiency above 45% APOLO is dedicated to minimizing the ecological footprint of transportation and energy, focusing on the maritime sector. To achieve this, we're actively developing innovative power conversion technologies such as cracker, fuel cell, and engine, and utilizing life cycle assessment (LCA) at various stages of product development. The technologies developed in APOLO are capable of targeting the first 30,000 ships in the market. Initially, the focus will be on vessels with 1 to 10 MW propulsion, with a significant number of them being around 3 MW in the next decade, as these are the first vessels relevant for ammonia-powered solutions.

Remote sensing and monitoring in various environments solves many scientific and societal problems. Examples are: industrial air pollution control, global atmosphere surveillance, our planet system and the universe exploration, process controls in industry, and material research in laboratories. Molecular absorption/emission feature, combined with a high penetration depth of THz waves through dust, short wavelength allowing for high pointing directivity, all these factors determine the uniqueness of the THz range of electro-magnetic wave spectrum (0.1-10THz) in the mentioned applications. High radiometric sensitivity of THz wave detectors is a vital selection criterion for a THz system to become attractive. Uncooled THz detectors/mixers show adequate sensitivity only for frequencies below 1THz, whereas “supra-THz” (>1THz) detectors require cooling down to 4K. This limitation hinders exploitation of THz spectroscopy for such important application as atmosphere monitoring, local and global pollution surveillance, security, as well as universal sciences, in full. Small-scale satellites, balloons, portable sensors, can’t afford LHe cooling or power thirsty 4K cryo-coolers. For large-scale space missions, 4K cooling has already been utilized (e.g. Herschel and Planck Space observatories, COBE, etc), however it limited the missions lifetime significantly. In the frame of ERC StG grant Teramix, we developed technology, where high sensitivity and large bandwidth THz detection can be achieved at 20-40K temperature range, which can be accessed with compact and low power consumption coolers. The THOR project will lead the new technology through pre-commercial prototyping, a real-world application in an existing (representative) system, and explore marketing opportunities in both commercial and research areas.

Polymers are the most ubiquitous materials class in modern society. Most of us spend a significant part of our lives in buildings made of polymers, using electronics manufactured with special polymers, and taking medicines encapsulated in carefully-optimized polymer formulations. In many cases, the design of new polymers is key to addressing global challenges in sustainability, health, and security. However, current polymer design methods rely heavily on trial-and-error experimentation and are grounded on imprecise assumptions about their structure, which is not only time-consuming and costly, but also offers limited insights into the relationship between structure, synthesis, and properties beyond the simplest polymers. While data-driven methods for small molecule engineering have flourished in recent years, artificial intelligence (AI) methods designed for polymers remain severely underdeveloped due to the unique challenges they pose. Their design involves navigating a noisy data space in search of compounds satisfying a complex set of specifications, made even more challenging when we’re interested in sampling novel, unique materials. The lack of well-defined, regular structures in polymers, coupled with a vastly different synthesis space, has also led to inefficient representations for them and an overreliance on hand-crafted simplifications, necessitating the development of information-rich yet scalable representa-tions for diverse polymer classes. I will tackle these gaps in AI-guided polymer design through the de-velopment of new paradigms for (1) learnable polymer representations and (2) generative AI frameworks for polymer design and synthesis. The methods I will develop bridge unique ideas from polymer science and AI to create a ground-breaking new approach for engineering polymers to specification and transform the current polymer design landscape across many industries via scalable data-driven strategies.