Optimization of Cricket-inspired, Biomimetic Artificial Hair Sensors for Flow Sensing

High density arrays of artificial hair sensors, biomimicking the extremely sensitive mechanoreceptive filiform hairs found on cerci of crickets have been fabricated successfully. We assess the sensitivity of these artificial sensors and present a scheme for further optimization addressing the deteriorating effects of stress in the structures. We show that, by removing a portion of chromium electrodes close to the torsional beams, the upward lift at the edges of the membrane due to the stress, will decrease hence increase the sensitivity.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/EDA-Publishing

Biomimetic flow-sensor arrays based on the filiform hairs on the cerci of crickets

In this paper we report on the latest developments in biomimetic flow-sensors based on the flow sensitive mechano-sensors of crickets. Crickets have one form of acoustic sensing evolved in the form of mechanoreceptive sensory hairs. These filiform hairs are highly perceptive to low-frequency sound with energy sensitivities close to thermal threshold. Arrays of artificial hair sensors have been fabricated using a surface micromachining technology to form suspended silicon nitride membranes and double-layer SU-8 processing to form 1 mm long hairs. Previously, we have shown that these hairs are sensitive to low-frequency sound, using a laser vibrometer setup to detect the movements of the nitride membranes. We have now realized readout electronics to detect the movements capacitively, using electrodes integrated on the membranes

Structure and Evolution of the Envelopes of Deeply Embedded Massive Young Stars

The physical structure of the envelopes around a sample of fourteen massive (1000-100,000 solar L) young stars is investigated on 100- 100,000 AU scales using maps and spectra in submillimeter continuum and lines of C17O, CS and H2CO. The total column densities and the temperature profiles are obtained by fitting self-consistent dust models to submillimeter photometry. Both the molecular line and dust emission data indicate density gradients ~r^{-alpha}, with alpha=1.0-1.5, significantly flatter than the alpha=2.0 generally found for low-mass objects. This flattening may indicate that in massive young stellar objects, nonthermal pressure is more important for the support against gravitational collapse, while thermal pressure dominates for low-mass sources. We find alpha=2 for two hot core-type sources, but regard this as an upper limit since in these objects, the CS abundance may be enhanced in the warm gas close to the star.Comment: To be published in The Astrophysical Journal. 54 pages including 14 figures Revised version with references adde

Deep Learning for Galaxy Mergers in the Galaxy Main Sequence

Starburst galaxies are often found to be the result of galaxy mergers. As a result, galaxy mergers are often believed to lie above the galaxy main sequence: the tight correlation between stellar mass and star formation rate. Here, we aim to test this claim. Deep learning techniques are applied to images from the Sloan Digital Sky Survey to provide visual-like classifications for over 340 000 objects between redshifts of 0.005 and 0.1. The aim of this classification is to split the galaxy population into merger and non-merger systems and we are currently achieving an accuracy of 91.5%. Stellar masses and star formation rates are also estimated using panchromatic data for the entire galaxy population. With these preliminary data, the mergers are placed onto the full galaxy main sequence, where we find that merging systems lie across the entire star formation rate - stellar mass plane.Comment: 4 pages, 1 figure. For Proceedings IAU Symposium No. 34

Emergence of quasiparticle Bloch states in artificial crystals crafted atom-by-atom

The interaction of electrons with a periodic potential of atoms in crystalline solids gives rise to band structure. The band structure of existing materials can be measured by photoemission spectroscopy and accurately understood in terms of the tight-binding model, however not many experimental approaches exist that allow to tailor artificial crystal lattices using a bottom-up approach. The ability to engineer and study atomically crafted designer materials by scanning tunnelling microscopy and spectroscopy (STM/STS) helps to understand the emergence of material properties. Here, we use atom manipulation of individual vacancies in a chlorine monolayer on Cu(100) to construct one- and two-dimensional structures of various densities and sizes. Local STS measurements reveal the emergence of quasiparticle bands, evidenced by standing Bloch waves, with tuneable dispersion. The experimental data are understood in terms of a tight-binding model combined with an additional broadening term that allows an estimation of the coupling to the underlying substrate.Comment: 7 figures, 12 pages, main text and supplementary materia