Hierarchically Structured Magnetic Nanoconstructs with Enhanced Relaxivity and Cooperative Tumor Accumulation

Iron oxide nanoparticles are formidable multifunctional systems capable of contrast enhancement in magnetic resonance imaging, guidance under remote fields, heat generation, and biodegradation. Yet, this potential is underutilized in that each function manifests at different nanoparticle sizes. Here, sub‐micrometer discoidal magnetic nanoconstructs are realized by confining 5 nm ultra‐small super‐paramagnetic iron oxide nanoparticles (USPIOs) within two different mesoporous structures, made out of silicon and polymers. These nanoconstructs exhibit transversal relaxivities up to ≈10 times (r ₂ ≈ 835 mm ^?1 s^?1) higher than conventional USPIOs and, under external magnetic fields, collectively cooperate to amplify tumor accumulation. The boost in r ₂ relaxivity arises from the formation of mesoscopic USPIO clusters within the porous matrix, inducing a local reduction in water molecule mobility as demonstrated via molecular dynamics simulations. The cooperative accumulation under static magnetic field derives from the large amount of iron that can be loaded per nanoconstuct (up to ≈65 fg) and the consequential generation of significant inter‐particle magnetic dipole interactions. In tumor bearing mice, the silicon‐based nanoconstructs provide MRI contrast enhancement at much smaller doses of iron (≈0.5 mg of Fe kg^?1 animal) as compared to current practice.     

Ultra-Robust Flexible Electronics by Laser-Driven Polymer-Nanomaterials Integration

Polyethylene terephthalate (PET) is the most widely used polymer in the world. For the first time, the laser-driven integration of aluminum nanoparticles (Al NPs) into PET to realize a laser-induced graphene/Al NPs/polymer composite, which demonstrates excellent toughness and high electrical conductivity with the formation of aluminum carbide into the polymer is shown. The conductive structures show an impressive mechanical resistance against >10000 bending cycles, projectile impact, hammering, abrasion, and structural and chemical stability when in contact with different solvents (ethanol, water, and aqueous electrolytes). Devices including thermal heaters, carbon electrodes for energy storage, electrochemical and bending sensors show this technology's practical application for ultra-robust polymer electronics. This laser-based technology can be extended to integrating other nanomaterials and create hybrid graphene-based structures with excellent properties in a wide range of flexible electronics’ applications.     

THz Detection of Biomolecules in Aqueous Environments—Status and Perspectives for Analysis Under Physiological Conditions and Clinical use

Bioanalytical THz sensing techniques have proven to be an interesting and viable tool for the label-free detection and analysis of biomolecules. However, a major challenge for THz bioanalytics is to perform investigations in the native aqueous environments of the analytes. This review recapitulates the status and future requirements for establishing THz biosensing as a complementary toolbox in the repertoire of standard bioanalytic methods. The potential use in medical research and clinical diagnosis is discussed. Under these considerations, this article presents a comprehensive categorization of biochemically relevant analytes that have been investigated by THz sensing techniques in aqueous media. The detectable concentration levels of ions, carbohydrates, (poly-)nucleotides, active agents, proteins and different biomacromolecules from THz experiments are compared to characteristic physiological concentrations and lower detection limits of state-of-the-art bioanalytical methods. Finally, recent experimental developments and achievements are discussed, which potentially pave the way for THz analysis of biomolecules under clinically relevant conditions.

     

Benefits of the use of impairment constraint routing in optical networks

In transparent optical networks, the optical signal accumulates the effects of all physical impairments present along the path it traverses. The conventional selection of signal paths based on e.g. shortest path routing without considering the signal quality and its association with the physical impairments does not always provide the optimum solution in terms of network performance such as blocking and resource utilization. This paper proposes an impairment constraint based routing algorithm to achieve an optimal combination of physical and networking performance taking into account all physical linear impairments including noise, chromatic and polarization mode dispersion, crosstalk and filter concatenation effects in an integrated approach. The performance of a typical metropolitan area network is examined and the improvement achieved when using the proposed approach compared to the conventional shortest path routing is demonstrated.     

Functionalized Asymmetric Linear Acenes for High‐Performance Organic Semiconductors

A series of compounds from the tetraceno[2,3‐b]thiophene and the anthra[2,3‐b]thiophene family of semiconducting molecules has been made. Specifically, synthetic routes to functionalize the parent molecules with bromo and then hexyl groups are shown. The bromo‐ and hexyl‐functionalized tetraceno[2,3‐b]thiophene and anthra[2,3‐b]thiophene were characterized in the top‐contact thin‐film transistor (TFT) geometry. They give high mobilities, ranging from 0.12 cm² V^?1 s^?1 for α‐n‐hexylanthra[2,3‐ b]thiophene to as high as 0.85 cm² V^?1 s^?1 for α‐bromotetraceno[2,3‐b]thiophene. Notably, grain size increases, going from the shorter anthra[2,3‐b]thiophene core to the longer tetraceno[2,3‐b]thiophene core, with a corresponding increase in mobility. The transition from undesirable 3D to desirable 2D thin‐film growth is explained by the increase in length of the molecule, in this case by one benzene ring, which results in an increase in intralayer interactions relative to interlayer interactions.     

Ferroelectric Materials: Probing Local and Global Ferroelectric Phase Stability and Polarization Switching in Ordered Macroporous PZT (Adv. Funct. Mater. 5/2011)

We describe the characterization, ferroelectric phase stability and polarization switching in strain‐free assemblies of PbZr_0.3Ti_0.7O₃ (PZT) nanostructures. The 3‐dimensionally ordered macroporous structures present uniquely large areas and volumes of PZT where the microstructure is spatially modulated and the composition is homogeneous. Variable temperature powder X‐ray diffraction (XRD) studies show that the global structure is crystalline and tetragonal at room temperature and undergoes a reversible tetragonal to cubic phase transition on heating/cooling. The measured phase‐transition temperature is 50–60 °C lower than bulk PZT of the same composition. The local ferroelectric properties were assessed using piezoresponse force spectroscopy that reveal an enhanced piezoresponse from the nanostructured films and demonstrate that the switching polarization can be spatially mapped across these structures. An enhanced piezoresponse is observed in the nanostructured films which we attribute to the formation of strain free films, thus for the first time we are able to assess the effects of crystallite‐size independently of internal stress. Corresponding polarization distributions have been calculated for the bulk and nanostructured materials using a direct variational method and Landau‐Ginzburg‐Devonshire (LGD) theory. By correlating local and global characterization techniques we have for the first time unambiguously demonstrated the formation of tetragonal and ferroelectric PZT in large volume nanostructured architectures. With the wide range of materials available that can be formed into such controlled architectures we conclude that this study opens a pathway for the effective studies of nanoscale ferroelectrics in uniquely large volumes.     

Cross-layer network formation for energy-efficient IEEE 802.15.4/ZigBee Wireless Sensor Networks

In IEEE 802.15.4/ZigBee Wireless Sensor Networks (WSNs) a specific node (called the PAN coordinator or sink) controls the whole network. When the network operates in a multi-hop fashion, the position of the PAN coordinator has a significant impact on the performance: it strongly affects network energy consumption for both topology formation and data routing. The development of efficient self-managing, self-configuring and self-regulating protocols for the election of the node that coordinates and manages the IEEE 802.15.4/ZigBee WSN is still an open research issue. In this paper we present a cross-layer approach to address the problem of PAN coordinator election on topologies formed in accordance with the IEEE 802.15.4. Our solution combines the network formation procedure defined at the MAC layer by the IEEE 802.15.4 standard with a topology reconfiguration algorithm operating at the network layer. We propose a standard-compliant procedure (named PAN coordinator ELection – PANEL) to self-configure a IEEE 802.15.4/ZigBee WSN by electing, in a distributed way, a suitable PAN coordinator. A protocol implementing this solution in IEEE 802.15.4 is also provided. Performance results show that our cross-layer approach minimizes the average number of hops between the nodes of the network and the PAN coordinator allowing to reduce the data transfer delay and determining significant energy savings compared with the performance of the IEEE 802.15.4 standard.     

Seminar zum systematischen Erfinden

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Seminar zum systematischen Erfinden     

Evolving Fuzzy Modeling for MANETs Using Lightweight Online Unsupervised Learning

The study presents a methodology for evolving fuzzy modeling tasks in Mobile Ad hoc Networks (MANETs) based on distributed data-driven fuzzy clustering and reasoning. The fuzzy clustering is exploited for the purpose of learning fuzzy inference rules online. That calls for one-pass Lightweight Evolving Fuzzy Clustering Method (LEFCM) suitable for deploying on mobile devices with constrained resources in MANETs. There is no standard method to determine the optimal number of fuzzy rules and most of the fuzzy systems still apply the trial and error method, unsuitable for online modeling tasks. The proposed methodology addresses the issues of uncertainties, simplicity and speed to run in non-intrusive way. It estimates online the number of clusters and their centers in the input data space, accordingly the fuzzy rules, by online adaptation of the LEFCM threshold value that affects the number of clusters. Adaptation is based on the combination of geometrical and statistical analyses, as well as on incorporating a multidimensional fuzzy membership degree into the clustering process. The proposed LEFCM is proven by using traditional cluster validity indexes and tested on real data sets.