Twinning of Rhombic Colloidal Crystals

We observe twinning of two-dimensional (2D) rhombic colloidal crystals of hard Brownian rhombic platelets. By contrast to square particles, which have higher symmetry but can also form rhombic lattices at high densities, each rhombic particle has a distinguishable bidirectional pointing axis. This key feature, which is not readily seen in rhombic crystals of square colloids, facilitates observations of different types of twinning: contact, polysynthetic, and cyclic. Moreover, we find that the twinned crystals are slightly offset spatially along their shared mirror line. In addition, the average pointing axis of the particles in a single crystal is also offset on average by a small angle, either clockwise or counterclockwise, from the average pointing axis of the rhombic lattice yielding a form of nonlocal chiral symmetry breaking. Because mirror lines between contact twins introduce only a small reduction in the total number of accessible states, compared to a perfect single crystal, twinning and piecewise linear defects are commonly observed. Thus, twinning, which is usually associated with complex compositions in certain minerals, also emerges in a simpler 2D system of entropically driven, hard, achiral objects

Enhanced Photocatalytic Removal of Sodium Pentachloro­phenate with Self-Doped Bi₂WO₆ under Visible Light by Generating More Superoxide Ions

In this study, we demonstrate that the photo­catalytic sodium penta­chloro­phenate removal efficiency of Bi₂WO₆ under visible light can be greatly enhanced by bismuth self-doping through a simple soft-chemical method. Density functional theory calculations and systematical characterization results revealed that bismuth self-doping did not change the redox power of photo­generated carriers but promoted the separation and transfer of photo­generated electron–hole pairs of Bi₂WO₆ to produce more super­oxide ions, which were confirmed by photocurrent generation and electron spin resonance spectra as well as super­oxide ion measurement results. We employed gas chromatography–mass spectrometry and total organic carbon analysis to probe the degradation and the mineralization processes. It was found that more super­oxide ions promoted the dechlori­nation process to favor the subsequent benzene ring cleavage and the final minerali­zation of sodium penta­chloro­phenate during bismuth self-doped Bi₂WO₆ photo­catalysis by producing easily decomposable quinone intermediates. This study provides new insight into the effects of photo­generated reactive species on the degradation of sodium penta­chloro­phenate and also sheds light on the design of highly efficient visible-light-driven photo­catalysts for chloro­phenol pollutant removal

Self-Powered Wireless Smart Sensor Node Enabled by an Ultrastable, Highly Efficient, and Superhydrophobic-Surface-Based Triboelectric Nanogenerator

Wireless sensor networks will be responsible for a majority of the fast growth in intelligent systems in the next decade. However, most of the wireless smart sensor nodes require an external power source such as a Li-ion battery, where the labor cost and environmental waste issues of replacing batteries have largely limited the practical applications. Instead of using a Li-ion battery, we report an ultrastable, highly efficient, and superhydrophobic-surface-based triboelectric nanogenerator (TENG) to scavenge wind energy for sustainably powering a wireless smart temperature sensor node. There is no decrease in the output voltage and current of the TENG after continuous working for about 14 h at a wind speed of 12 m/s. Through a power management circuit, the TENG can deliver a constant output voltage of 3.3 V and a pulsed output current of about 100 mA to achieve highly efficient energy storage in a capacitor. A wireless smart temperature sensor node can be sustainably powered by the TENG for sending the real-time temperature data to an iPhone under a working distance of 26 m, demonstrating the feasibility of the self-powered wireless smart sensor networks

Self-Powered Wireless Smart Sensor Node Enabled by an Ultrastable, Highly Efficient, and Superhydrophobic-Surface-Based Triboelectric Nanogenerator

Wireless sensor networks will be responsible for a majority of the fast growth in intelligent systems in the next decade. However, most of the wireless smart sensor nodes require an external power source such as a Li-ion battery, where the labor cost and environmental waste issues of replacing batteries have largely limited the practical applications. Instead of using a Li-ion battery, we report an ultrastable, highly efficient, and superhydrophobic-surface-based triboelectric nanogenerator (TENG) to scavenge wind energy for sustainably powering a wireless smart temperature sensor node. There is no decrease in the output voltage and current of the TENG after continuous working for about 14 h at a wind speed of 12 m/s. Through a power management circuit, the TENG can deliver a constant output voltage of 3.3 V and a pulsed output current of about 100 mA to achieve highly efficient energy storage in a capacitor. A wireless smart temperature sensor node can be sustainably powered by the TENG for sending the real-time temperature data to an iPhone under a working distance of 26 m, demonstrating the feasibility of the self-powered wireless smart sensor networks

Fraction of infected devices |<i>I</i>(<i>t</i>)|/<i>N</i> as a function of the number of <i>total</i> contacts, for the original contact trace and inducement-shuffled null models.

Fraction of infected devices |I(t)|/N as a function of the number of total contacts, for the original contact trace and inducement-shuffled null models.</p

Unique contacts per node.

Null models that destroy LN result in higher unique contacts.</p

A review of the acquisitions experience of major UK companies

SIGLEAvailable from British Library Document Supply Centre-DSC:98/08553 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Session volume over time shows diurnal and weekday/weekend patterns.

<p>Session volume over time shows diurnal and weekday/weekend patterns.</p

Total contacts per node.

<p>Total contacts per node are comparable across null models.</p

Unique locations per node.

The number of locations per node show the increase of unique locations per node when LN is broken.</p