New structural materials with higher strength and temperature capabilities are the key enablers of sustain-able energy conversion and transport technology of the future. The question is: How do we find those central high-performers combining high strength and the essential deformability giving safety in application? It is the aim of FUNBLOCKS to provide the first systematic studies of plasticity mechanisms in the most fundamental building blocks of complex crystals. These will allow us to deduce the missing basic mechanisms and signatures of plasticity. FUNBLOCKS will take a new approach by studying the much simpler sub-units that form the multitude of more complex crystals with large unit cells amongst the intermetallics. This has three major implications: i) the reduction to fundamental units allows suffi-cient time to unravel the major deformation mechanisms to the atomic level, ii) the recurrent nature of the few fundamental building blocks will allow a transfer of this knowledge to a large number of complex phases and iii) together, this will enable data mining from the vast and largely unexplored phase space of intermetallics. The key aspect of FUNBLOCKS is therefore to close the existing gap in knowledge and allow us to find promising new phases by elucidating the fundamental relationships between crystal structure and plasticity beyond what we know in simple metals. To identify and quantify the intrinsic mechanical properties of each sub-unit, state-of-the-art micromechanical testing techniques will be used. Transfer of data and verification of the central hypothesis, that fundamental units govern plasticity in complex crystals, will be achieved via additional alloyed crystals forming ternary variants of the binary structures. Ultimately, FUNBLOCKS will answer fundamental questions in plasticity, most prominently the interplay of deformation and structure in complex crystals, and thereby support the development of new high performance materials.

This project will develop a unifying framework of novel methods for sequence classification and thus make a major break-through in automatic speech recognition and machine translation, advancing these areas of human language technology (HLT) beyond state-of-the-art. Despite the huge progress made in the field, the specific aspect of sequence classification has not been addressed adequately in the past research in these disciplines and remains a big challenge. The proposed project will provide a novel framework under consistent consideration of the leading aspect of sequence classification. It will break the ground for a deeper, more comprehensive foundation for sequence classification and pave the way for a new generation of algorithms that will put human language technology on a more solid basis and that will accelerate progress in the field across several disciplines. The leading research objectives are: 1. A novel theoretical framework for sequence classification. 2. Consistent sequence modeling across training and testing, which is specifically lacking in machine translation. 3. Adequate sequence-level performance-aware training criteria to learn the free parameters of the models. 4. Investigation of (true) unsupervised training for HLT sequence classification: its principles, its prerequisites, its limitations and its practical usage. The study of these four problems will provide key enabling techniques for HLT sequence classification in general that will carry over to and create high impact on the areas of speech recognition, machine translation and handwritten text recognition. Using our top-ranking research prototype systems, we will verify the validity and effectiveness or our research on public international benchmarks.

Ionic conducting materials form the basis of solid oxide fuel cells, solid oxide electrolyser cells, and batteries, which form a key component of the EU Energy 2050 long-term strategy. There is a need to develop faster ionic conductors, however progress has been slow. Recently, several studies have demonstrated photo-enhanced iodine-ion diffusion as well as suggested interactions between photons and oxygen-ion defects in oxide materials may be possible. The proposed research plan, OPTICS, aims to address the question: Can changes in ion transport be enhanced in technologically relevant ionically conducting oxides (O-ion, H-ion, and Li-ion) by light illumination? There are challenges in studying these effects using conventional methods. Namely, absorption only occurring at the surface in thick samples, artefacts in conductivity measurements stemming from photocurrents and electrode effects, and difficulties understanding the mechanisms due to the indirect nature of photon-ion interactions. In OPTICS, these challenges will be overcome employing isotopic tracer diffusion measurements on epitaxial thin films carried out in tandem with atomistic and continuum simulations to identify the underlying mechanisms. Combining the Host’s (Prof. Roger De Souza) expertise in tracer diffusion and atomistic modelling with the Applicants experience with optical measurements on epitaxial films, photo-enhanced ionic diffusion will be studied experimentally and computationally in the bulk, at surfaces, and at interfaces of nanostructured materials. Light-enhanced ionic transport has the potential, though OPTICS, to lead to substantial improvements in technologically relevant ionic conductors leading to a new class of photo-ionic fuel cells, electrolysers, and batteries.