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Modulated martensites play an important role in magnetic shape memory alloys, because all functional properties are closely connected to the twin microstructure and the phase boundary. The nature of the modulated martensites is still…
The computational prediction of the structure and stability of hybrid organic-inorganic interfaces provides important insights into the measurable properties of electronic thin film devices, coatings, and catalyst surfaces and plays an…
The development of permanent magnets containing less or no rare-earth elements is linked to profound knowledge of the coercivity mechanism. Prerequisites for a promising permanent magnet material are a high spontaneous magnetization and a…
Cell cell and cell matrix adhesions are fundamental in all multicellular organisms. They play a key role in cellular growth, differentiation, pattern formation and migration. Cell-cell adhesion is substantial in the immune response,…
Simulations of metal nanopatterns embedded in a thin photovoltaic absorber show significantly enhanced absorbance within the semiconductor, with a more than 300% increase for {\lambda} = 800 nm. Integrating with AM1.5 solar irradiation,…
Molecular systems are materials that intersect with many different promising fields such as organic/molecular electronics and spintronics, organic magnetism and quantum computing1-7. Particularly, magnetism in organic materials is very…
How does magnetism behave when the physical dimension is reduced to the size of nanostructures? The multiplicity of magnetic states in these systems can be very rich, in that their properties depend on the atomic species, the cluster size,…
Considering the growing interest in magnetic materials for unconventional computing, data storage, and sensor applications, there is active research not only on material synthesis but also characterisation of their properties. In addition…
The mechanosensitivity of cells, which determines how they are able to respond to mechanical signals received from their environment, is crucial for the functioning of all biological systems. In experiments, cells placed on cyclically…
The advent of computational statistical disciplines, such as machine learning, is leading to a paradigm shift in the way we conceive the design of new compounds. Today computational science does not only provide a sound understanding of…
Free-standing, interconnected metallic nanowire networks with density as low as 40 mg/cm^{3} have been achieved over cm-scale areas, using electrodeposition into polycarbonate membranes that have been ion-tracked at multiple angles.…
Antiferromagnetism in stacked nanographite is investigated with using the Hubbard-type models. The A-B stacking or the stacking near to that of A-B type is favorable for the hexagonal nanographite with zigzag edges, in order that magnetism…
We extend a model for the morphology and dynamics of a crawling eukaryotic cell to describe cells on micropatterned substrates. This model couples cell morphology, adhesion, and cytoskeletal flow in response to active stresses induced by…
Inspired by biology's most sophisticated computer, the brain, neural networks constitute a profound reformulation of computational principles. Remarkably, analogous high-dimensional, highly-interconnected computational architectures also…
The possibility to guide and control magnetic nanoparticles in a non-invasive manner has spawned various applications in biotechnology such as targeted drug delivery and sensing of biological substances. These applications are facilitated…
The adaptive and surprising emergent properties of biological materials self-assembled in far-from-equilibrium environments serve as an inspiration for efforts to design nanomaterials and their properties. In particular, controlling the…
Our recent studies on Co-clusters embedded in various matrices reveal that the co-deposition technique (simultaneous deposition of two beams : one for the pre-formed clusters and one for the matrix atoms) is a powerful tool to prepare…
Deep learning models have proven to be exceptionally useful in performing many machine learning tasks. However, for each new dataset, choosing an effective size and structure of the model can be a time-consuming process of trial and error.…
The ability to assemble mesoscopic colloidal lattices above a surface is important for fundamental studies related with nucleation and crystallization, but also for a variety of technological applications in photonics and micro-engineering.…
Micromanipulation of magnetotactic bacteria with a microelectromagnet matrix was demonstrated. Magnetotactic bacteria synthesize a chain of magnetic nanoparticles inside their body to guide their motion in the geomagnetic field. A…