Nanowires with varying magnetic properties

In magnetic nanowires composed from alternating segments of CoNi and Ni, different magnetization modes were found in both materials. While CoNi revealed vortex states or multi-vortex states in experiment and simulation, the Ni segments between showed an axial magnetization direction without domain walls in the segments.

Shape-memory polymers

PLA belongs to the well-known shape-memory polymers which can be used, e.g., to completely modify the geometry of open-pore 3D printed PLA objects and afterwards restore the original shape by warming up the object.

Recently, poly(ethylene glycol) (PEG) was also found to show shape-memory properties. Using PEG with different low molecular weights, the materials were chain-end functionalized with isocyanate ethyl methacrylate and UV-photo-cured, resulting in nearly complete cross-linking. In 3-point bending tests, nearly 100 % strain fixity rates were found.

Surface patterning for controlled growth of neuronal cells

Electrospun nanofiber mats belong to the often examined substrates for tissue engineering, cell growth promotion or generally as an orientation for growth of diverse cells and small organisms, such as algae. A completely different approach was recently published: A UV laser lithography method which was used to design and produce plain multi-electrode arrays could also be used for surface patterning to pave ways for growth of neuronal cells.

Investigating magnetic nano-chains

Chains of asymmetric nanodots were modelled, using micromagnetic simulations, to verify the possibility to introduce magnetic domain-walls. For this, a combination of an anisotropy, defining the direction in which the domain wall should move, with alternating magnetic fields of suitable frequency and amplitude was found to be necessary.

Controlling vortex circularity and polarity

Magnetic vortices are of high interest in basic and applied research, e.g. for possible applications in data storage, signal transfer, logic devices, etc. They can be described by the polarity of the central core (with the magnetization pointing "up" or "down") and their circularity (rotational direction of the magnetization around the central core). If it were possible to manipulate both properties independently, two bits could be realized by one such nano-dot with a vortex, similar to our approaches utilizing fourfold nanomagnets.

Electric field simulation for needle-electrospinning

Electrospinning can be used to create sub-micron fibers from diverse materials, from polymers to blends to ceramics. Electrospinning can be performed with two wires as electrodes, but most often a syringe is used to press the polymer solution (or melt) via a needle into the electric field where the material is stretched and drawn to a counter-electrode.

Possible hardware-based solutions leading to cognitive computing

The hardware emulation of stochastic invertible logic based on Arduino microcontrollers or implemented in magnetic tunnel junctions, the hardware belief networks, have been proposed recently by researchers from the School of Electrical and Computer Engineering, Purdue University (IN), USA. Importantly, the provided solutions realize not only standard stochastic computing of the Boolean type, but do it very precisely and in the invertible manner. The proposed computing network imitating synapses consists of elementary switches based on stochastic magnetic tunnel junctions.

Production parameters for carbon nanofibers

Polyacrylonitrile (PAN) is the most often used material for carbon fiber production. Carbon nanofibers, however, created from electrospun PAN nanofibers, necessitate different production parameters during stabilization and carbonization steps. Investigation of these parameters can be performed by various optical, chemical and other examinations, e.g. of the sample color (with increasing stabilization, samples get darker and darker), using FTIR, DSC, TGA, and other techniques.

Complexity and emergence of cognition

With the development of cognitive computing the next generation of future computing paradigms will be related to interesting issue of emergence of the new functionalities that results from increasing complexity of systems. The fundamental question is; at what level of complexity, and why at that level, a given functionality is accessible? And, an another specific question can be asked; is there the need to make observation in time or conclusion about the specific functionality can be extracted from the static, read at one moment, information?