Cephalopod-Inspired Stretchable Self-Morphing Skin Via Embedded Printing and Twisted Spiral Artificial Muscles

Cutaneous muscles drive the texture-modulation behavior of cephalopods by protruding several millimeters out of the skin. Inspired by cephalopods, a self-morphing, stretchable smart skin containing embedded-printed electrodes and actuated by Twisted Spiral Artificial Muscles (TSAMs) is proposed. Electrothermally actuated TSAMs are manufactured from inexpensive polymer fibers to mimic the papillae muscles of cephalopods. These spirals can produce strains of nearly 2000% using a voltage of only 0.02 V mm⁻¹. Stretchable and low-resistance liquid metal electrodes are embedded-printed inside the self-morphing skin to facilitate the electrothermal actuation of TSAMs. Theoretical and numerical models are proposed to describe the embedded printing of low-viscosity Newtonian liquid metals as conductive electrodes in a soft elastomeric substrate. Experimental mechanical tests are performed to demonstrate the robustness and electrical stability of the electrodes. Two smart skin prototypes are fabricated to highlight the capabilities of the proposed self-morphing system, including a texture-modulating wearable soft glove and a waterproof skin that emulates the texture-modulation behavior of octopi underwater. The proposed self-morphing stretchable smart skin can find use in a wide range of applications, such as refreshable Braille displays, haptic feedback devices, turbulence tripping, and antifouling devices for underwater vehicles.     

Adaptive WENO Methods Based on Radial Basis Function Reconstruction

We explore the use of radial basis functions (RBF) in the weighted essentially non-oscillatory (WENO) reconstruction process used to solve hyperbolic conservation laws, resulting in a numerical method of arbitrarily high order to solve problems with discontinuous solutions. Thanks to the mesh-less property of the RBFs, the method is suitable for non-uniform grids and mesh adaptation. We focus on multiquadric radial basis functions and propose a simple strategy to choose the shape parameter to control the balance between achievable accuracy and the numerical stability. We also develop an original smoothness indicator which is independent of the RBF for the WENO reconstruction step. Moreover, we introduce type I and type II RBF-WENO methods by computing specific linear weights. The RBF-WENO method is used to solve linear and nonlinear problems for both scalar and systems of conservation laws, including Burgers equation, the Buckley–Leverett equation, and the Euler equations. Numerical results confirm the performance of the proposed method. We finally consider an effective conservative adaptive algorithm that captures moving shocks and rapidly varying solutions well. Numerical results on moving grids are presented for both Burgers equation and the more complex Euler equations.     

Manipulation and tracking of superparamagnetic nanoparticles using MRI

The use of magnetic fields in magnetic resonance imaging (MRI) for the tracking and delivery of chemotherapeutics bound to superparamagnetic nanoparticles offers a promising method for the non-invasive treatment of inoperable tumours. Here we demonstrate that superparamagnetic magnetite nanoparticles fabricated by an easily scalable method can be driven and tracked in real time at high velocities in vitro using MRI hardware. Force balance calculations are consistent with the magnetic properties of individual 10 nm diameter particles that move collectively as micron sized agglomerates with hydrodynamic diameter similar to that inferred from zero-magnetic-field dynamic light scattering measurements.     

Extraction and quantification of phytoestrogens in foods using automated solid-phase extraction and LC/MS/MS

Phytoestrogens are a group of polyphenolic plant metabolites that can induce biological responses. Their bioactivity is based on their similarity to 17beta-estradiol and their ability to bind to the beta-estrogen receptor. Although epidemiological data are inconclusive, phytoestrogens are considered to be beneficial for a variety of conditions, for example, hormone-related cancers like breast and prostate cancer. To investigate the biological effects of these compounds and to assess the exposure of larger cohorts or the general public, reliable data on the phytoestrogen content of food is necessary. Previously, food analysis for phytoestrogens was performed using either HPLC-UV or GC/MS. Here, we describe the development of the first generic method for the analysis of phytoestrogens in food, using automated solid-phase extraction and liquid chromatography-tandem mass spectrometry. The presented method shows a good reproducibility and can be easily adapted to other phytoestrogens if required.     

In situ observations of catalyst dynamics during surface-bound carbon nanotube nucleation

We present atomic-scale, video-rate environmental transmission electron microscopy and in situ time-resolved X-ray photoelectron spectroscopy of surface-bound catalytic chemical vapor deposition of single-walled carbon nanotubes and nanofibers. We observe that transition metal catalyst nanoparticles on SiOx support show crystalline lattice fringe contrast and high deformability before and during nanotube formation. A single-walled carbon nanotube nucleates by lift-off of a carbon cap. Cap stabilization and nanotube growth involve the dynamic reshaping of the catalyst nanocrystal itself. For a carbon nanofiber, the graphene layer stacking is determined by the successive elongation and contraction of the catalyst nanoparticle at its tip.     

DNA origami nanopores

We demonstrate the assembly of functional hybrid nanopores for single molecule sensing by inserting DNA origami structures into solid-state nanopores. In our experiments, single artificial nanopores based on DNA origami are repeatedly inserted in and ejected from solid-state nanopores with diameters around 15 nm. We show that these hybrid nanopores can be employed for the detection of λ-DNA molecules. Our approach paves the way for future development of adaptable single-molecule nanopore sensors based on the combination of solid-state nanopores and DNA self-assembly.     

Hydroxyapatite/gelatin/gellan sponges as nanocomposite scaffolds for bone reconstruction

The aim of this work was the morphological, physicochemical, mechanical and biological characterization of a new composite system, based on gelatin, gellan and hydroxyapatite, and mimicking the composition of natural bone. Porous scaffolds were prepared by freeze–drying technique, under three different conditions of freezing. The morphological analysis showed a homogeneous porosity, with well interconnected pores, for the sample which underwent a more rapid freezing. The elastic modulus of the same sample was close to that of the natural bone. The presence of interactions among the components was demonstrated through the physicochemical investigation. In addition, the infrared chemical imaging analysis pointed out the similarity among the composite scaffold and the natural bone, in terms of chemical composition, homogeneity, molecular interactions and structural conformation. Preliminary biological characterization showed a good adhesion and proliferation of human mesenchymal stem cells.     

Inherently fluorescent polyaniline nanoparticles in a dynamic landscape

In this paper we report for the first time on the emissive behavior of two polyaniline (PANI) nanoparticle systems produced via oxidative chemical polymerization in the presence of either poly(vinyl alcohol) (PVA) or chitosan as polymeric stabilizers in water. The emission from PANI nanoparticles is irreversibly quenched by an increase of pH of the suspending medium from acid to neutral (chitosan-PANI) or alkaline (PVA-PANI). Conversely, PANI nanorods synthesized in the same conditions of the above, but in presence of poly(N-vinyl pyrrolidone), is not emissive at any pH. The role of the polymeric surfactant as a soft template is key in controlling the morphology and the properties of the obtained PANI dispersions. FTIR, UV-Vis absorption and photoluminescence excitation (PLE) spectra studies suggest that the emissive properties are related to the establishment of strong, non-covalent interactions between nanoscalar PANI particles and the polymeric surfactant at the pH of synthesis. Morphology examination of the three systems, by both dynamic light scattering (DLS) and Transmission Electron Microscopy (TEM), reveal that photoluminescence is associated to the presence of a genuinely 3D nanoscalar morphology, together with an ordered disposition of PANI chains into aligned crystal planes. Concomitant to the irreversible quenching of the emission signal with increasing pH, there is an evolution of the morphology leading to particle coalescence, coarsening and ultimately phase-separation, with consequent modification of PANI-polymeric surfactant interactions, PANI chains supra-molecular organization and optical properties of the PANI nanoparticles dispersion.     

An Algorithm for Parameter Identification of UAS from Flight Data

The aim of the present work is to realize an identification algorithm especially devoted to UAS （unmanned aerial systems）. Because UAS employ low cost sensor, very high measurement noise has to be taken into account. Therefore, due to both modelling errors and atmospheric turbulence, noticeable system noise has also to be considered. To cope with both the measurement and system noise, the identification problem addressed in this work is solved by using the FEM （filter error method） approach. A nonlinear mathematical model of the subject aircraft longitudinal dynamics has been tuned up through semi-empirical methods, numerical simulations and ground tests. To take into account model nonlinearities, an EKF （extended Kalman filter） has been implemented to propagate the state. A procedure has been tuned up to determine either aircraft parameters or the process noise. It is noticeable that, because the system noise is treated as unknown parameter, it is possible to identify system affected by noticeable modelling errors. Therefore, the obtained values of process noise covariance matrix can be used to highlight system failure. The obtained results show that the algorithm requires a short computation time to determine aircraft parameter with noticeable precision by using low computation power. The present procedure could be employed to determine the system noise for various mechanical systems, since it is particularly devoted to systems which present dynamics that are difficult to model. Finally, the tuned up off-line EKF should be employed to on-line estimation of either state or unmeasurable inputs like atmospheric turbulence.