Overcoming the Inhibition Effects of Citrate: Precipitation of Ferromagnetic Magnetite Nanoparticles with Tunable Morphology,Magnetic Properties,and Surface Charge via Ferrous Citrate Oxidation

This study demonstrates how the method of thermally assisted oxidative precipitation in water can be opened for—the so far neglected—metal organic iron(II) complexes (herein: citrate) in order to obtain, in one step, ferromagnetic magnetite nanoparticles, possessing essential ligand properties. Based on a dedicated analysis of the specific precursor in combination with the consideration of known properties of the ligand, it is possible to identify existing inhibition-attributes of the iron organyl such that these can be overcome. Moreover, they can be exploited in a targeted manner; thus, simply by changing concentrations, a variety of magnetite nanoparticle morphologies with distinct properties can be obtained. In the case of the herein investigated ferrous citrate, three major inhibition effects are identified. While two of them efficiently prevent the formation of magnetite and need to be addressed to be overcome, the third can be exploited to selectively synthesize, for example, relatively stable carboxyl group-bearing nuclei clusters, exhibiting the properties of magnetically responsive photonic crystals, or relatively large mesocrystals, whose intraparticular magnetic interactions are apparently disturbed.     

Computation and efficiency of potential function minimizers of combinatorial congestion games

Mathematical Programming - We study the computation and efficiency of pure Nash equilibria in combinatorial congestion games, where the strategies of each player i are given by the binary vectors...     

The memory of thin polymer films generated by spin coating

The European Physical Journal E - The interstitial tumor microenvironment is composed of heterogeneously organized collagen-rich porous networks as well as channel-like structures and interfaces...     

NIFTy 3 – Numerical Information Field Theory: A Python Framework for Multicomponent Signal Inference on HPC Clusters

NIFTy , “Numerical Information Field Theory,” is a software framework designed to ease the development and implementation of field inference algorithms. Field equations are formulated independently of the underlying spatial geometry allowing the user to focus on the algorithmic design. Under the hood, NIFTy ensures that the discretization of the implemented equations is consistent. This enables the user to prototype an algorithm rapidly in 1D and then apply it to high‐dimensional real‐world problems. This paper introduces NIFTy  3, a major upgrade to the original NIFTy  framework. NIFTy  3 allows the user to run inference algorithms on massively parallel high performance computing clusters without changing the implementation of the field equations. It supports n‐dimensional Cartesian spaces, spherical spaces, power spaces, and product spaces as well as transforms to their harmonic counterparts. Furthermore, NIFTy  3 is able to handle non‐scalar fields, such as vector or tensor fields. The functionality and performance of the software package is demonstrated with example code, which implements a mock inference inspired by a real‐world algorithm from the realm of information field theory. NIFTy  3 is open‐source software available under the GNU General Public License v3 (GPL‐3) at https://gitlab.mpcdf.mpg.de/ift/NIFTy/tree/NIFTy_3 .     

Mean field limits for nonlinear spatially extended Hawkes processes with exponential memory kernels

We consider spatially extended systems of interacting nonlinear Hawkes processes modeling large systems of neurons placed in ${\mathbb{R}}^d$ and study the associated mean field limits. As the total number of neurons tends to infinity, we prove that the evolution of a typical neuron, attached to a given spatial position, can be described by a nonlinear limit differential equation driven by a Poisson random measure. The limit process is described by a neural field equation. As a consequence, we provide a rigorous derivation of the neural field equation based on a thorough mean field analysis.     

Capacitive Sensor to Monitor Enzyme Activity by Following Degradation of Macromolecules in Real Time

Applied Biochemistry and Biotechnology - A capacitive sensor was developed to analyze the presence and enzymatic activity of a model protease from standard solutions by following the degradation of...