Tin naphthalocyanine complexes for infrared absorption in organic photovoltaic cells

In this work, we examine the optical properties of tin naphthalocyanine dichloride (SnNcCl₂), and its performance as an electron donor material in organic photovoltaic cells (OPVs). As an active material, SnNcCl₂ is attractive for its narrow energy gap which facilitates optical absorption past a wavelength of λ = 1100 nm. We demonstrate a power conversion efficiency of η_P = (1.2 ± 0.1)% under simulated AM1.5G solar illumination at 100 mW/cm² using the electron donor–acceptor pairing of SnNcCl₂ and C₆₀ in a bilayer device architecture. While some phthalocyanines have been previously used to improve infrared absorption, this is often realized through the formation of molecular dimers. In SnNcCl₂, the infrared absorption is intrinsic to the molecule, arising as a result of the extended conjugation. Consequently, it is expected that SnNcCl₂ could be utilized in bulk heterojunction OPVs without sacrificing infrared absorption.     

Mitigating jamming attacks in wireless broadcast systems

Wireless communications are vulnerable to signal jamming attacks. Spread spectrum mitigates these attacks by spreading normal narrowband signals over a much wider band of frequencies and forcing jammers who do not know the spreading pattern to expend much more effort to launch the attack. In broadcast systems, however, jammers can easily find out the spread pattern by compromising just a single receiver. Several group-based ideas have been proposed to deal with compromised receivers; they can tolerate up to t malicious receivers by adding 2t extra copies for each broadcast message. In this paper, we propose a novel scheme with random channel sharing. This scheme reduces the communication cost from 2t to (1 + p)t extra copies, where p determines the channel sharing probability (0 < p < 1). In addition, it does not increase the hardware complexity as it does not require a receiver to operate on multiple channels at the same time.     

PAM decomposition of M-ary multi-h CPM

It is known that any multilevel continuous phase-modulated (CPM) signal with a single modulation index can be exactly represented by a sum of pulse-amplitude modulated (PAM) waveforms. In this paper, we show how multi-h CPM signals can also be represented in this manner. The decomposition is presented in general terms as a function of the alphabet size, modulation indexes, and phase pulse of the CPM scheme. The number of pulses required to exactly construct the signal is shown to increase over that previously given for single-h schemes; this increase is in proportion to the number of modulation indexes. We propose an approximation which significantly reduces the number of signal pulses and which minimizes the mean-squared error for an arbitrary set of modulation indexes. We show that this approximation can have two objectives: 1) to reduce the number of pulses in the same manner as has been proposed for single-h schemes; and/or 2) to reduce the number of multi-h pulses; we also show the conditions where this latter objective is most practical. We compare this minimum mean-squared error approximation with another method which was recently proposed for CPM. We also give numerical results on detection performance which demonstrate the practicality of the proposed approximation.     

Insight into the Solid Electrolyte Interphase Formation in Bis(fluorosulfonyl)Imide Based Ionic Liquid Electrolytes

The formation of the solid electrolyte interphase (SEI) in an ionic liquid electrolyte of 0.5 m lithium bis(fluorosulfonyl)imide (LiFSI) in 1-ethyl-3-methylimidazolium bis(fluorosulfonyl)imide at high cell voltages (1.7–1.9 V) is investigated in ordered mesoporous carbon (OMC) based Li metal cells using an operando small-angle neutron scattering (SANS) technique coupled with electrochemical impedance spectroscopy and ex situ X-ray photoelectron spectroscopy (XPS). It is demonstrated that discharging the OMC Li metal cells to ≈2 V and holding the cell voltage constant induces a rapid current increase with time, confirming extensive reduction and SEI formation. XPS analysis reveals that LiF is formed at open cell voltage (OCV), which is attributed to the carbenes generated at the lithium negative electrode because of its reaction with EMIm cation diffusing to and initiating the reaction with FSI⁻ anions at the carbon positive electrode. It is confirmed that the chemical reaction at OCV and electrochemical reduction at high cell voltage of the FSI⁻ anion plays a protective role against EMIm cation co-intercalation into the carbon positive electrode during the initial discharge. Operando SANS studies also suggest that slight differences occur in the surface composition and reaction mechanism as a function of cell voltage.     

Ultrasensitive Strain Gauges Enabled by Graphene‐Stabilized Silicone Emulsions

Here, an approach is presented to incorporate graphene nanosheets into a silicone rubber matrix via solid stabilization of oil‐in‐water emulsions. These emulsions can be cured into discrete, graphene‐coated silicone balls or continuous, elastomeric films by controlling the degree of coalescence. The electromechanical properties of the resulting composites as a function of interdiffusion time and graphene loading level are characterized. With conductivities approaching 1 S m^?1, elongation to break up to 160%, and a gauge factor of ≈20 in the low‐strain linear regime, small strains such as pulse can be accurately measured. At higher strains, the electromechanical response exhibits a robust exponential dependence, allowing accurate readout for higher strain movements such as chest motion and joint bending. The exponential gauge factor is found to be ≈20, independent of loading level and valid up to 80% strain; this consistent performance is due to the emulsion‐templated microstructure of the composites. The robust behavior may facilitate high‐strain sensing in the nonlinear regime using nanocomposites, where relative resistance change values in excess of 10⁷ enable highly accurate bodily motion monitoring.     

Mathematical model for the hemodynamic response to venous occlusion measured with near-infrared spectroscopy in the human forearm

We propose a mathematical model to describe the hemodynamic changes induced by a venous occlusion in a human limb. These hemodynamic changes, which include an increase in blood volume, a reduction in blood flow, and modifications to the oxygen saturation of hemoglobin, can all be measured noninvasively with near-infrared spectroscopy (NIRS). To test the model, we have performed NIRS measurements on the human forearm, specifically on the brachioradialis muscle, during venous occlusion induced by a pneumatic cuff inflated around the upper arm to pressures within the range 10-60 mmHg. We have found a good agreement between parameters measured by NIRS (total hemoglobin concentration and hemoglobin saturation) and the corresponding model parameters (capacitor voltage and arterial/capillary branch current). In particular, model and experiment indicate that the time constant for blood accumulation during venous occlusion (approximately 73-79 s) is much slower than the time constant for blood drainage following cuff release (approximately 5 s). These results indicate that this mathematical model can be a valuable analytical tool to characterize, optimize, and further develop diagnostic measurement schemes that use venous occlusion approaches.     

Efficient entropy estimation based on doubly stochastic models for quantized wavelet image data.

Under a rate constraint, wavelet-based image coding involves strategic discarding of information such that the remaining data can be described with a given amount of rate. In a practical coding system, this task requires knowledge of the relationship between quantization step size and compressed rate for each group of wavelet coefficients, the R-Q curve. A common approach to this problem is to fit each subband with a scalar probability distribution and compute entropy estimates based on the model. This approach is not effective at rates below 1.0 bits-per-pixel because the distributions of quantized data do not reflect the dependencies in coefficient magnitudes. These dependencies can be addressed with doubly stochastic models, which have been previously proposed to characterize more localized behavior, though there are tradeoffs between storage, computation time, and accuracy. Using a doubly stochastic generalized Gaussian model, it is demonstrated that the relationship between step size and rate is accurately described by a low degree polynomial in the logarithm of the step size. Based on this observation, an entropy estimation scheme is presented which offers an excellent tradeoff between speed and accuracy; after a simple data-gathering step, estimates are computed instantaneously by evaluating a single polynomial for each group of wavelet coefficients quantized with the same step size. These estimates are on average within 3% of a desired target rate for several of state-of-the-art coders.     

Au@Hg Nanoalloy Formation Through Direct Amalgamation: Structural,Spectroscopic, and Computational Evidence for Slow Nanoscale Diffusion

Dynamic core–shell nanoparticles have received increasing attention in recent years. This paper presents a detailed study of Au–Hg nanoalloys, whose composing elements show a large difference in cohesive energy. A simple method to prepare Au@Hg particles with precise control over the composition up to 15 atom% mercury is introduced, based on reacting a citrate stabilized gold sol with elemental mercury. Transmission electron microscopy shows an increase of particle size with increasing mercury content and, together with X‐ray powder diffraction, points towards the presence of a core–shell structure with a gold core surrounded by an Au–Hg solid solution layer. The amalgamation process is described by pseudo‐zero‐order reaction kinetics, which indicates slow dissolution of mercury in water as the rate determining step, followed by fast scavenging by nanoparticles in solution. Once adsorbed at the surface, slow diffusion of Hg into the particle lattice occurs, to a depth of ca. 3 nm, independent of Hg concentration. Discrete dipole approximation calculations relate the UV–vis spectra to the microscopic details of the nanoalloy structure. Segregation energies and metal distribution in the nanoalloys were modeled by density functional theory calculations. The results indicate slow metal interdiffusion at the nanoscale, which has important implications for synthetic methods aimed at core–shell particles.     

On the variability of manual spike sorting

The analysis of action potentials, or "spikes," is central to systems neuroscience research. Spikes are typically identified from raw waveforms manually for off-line analysis or automatically by human-configured algorithms for on-line applications. The variability of manual spike "sorting" is studied and its implications for neural prostheses discussed. Waveforms were recorded using a micro-electrode array and were used to construct a statistically similar synthetic dataset. Results showed wide variability in the number of neurons and spikes detected in real data. Additionally, average error rates of 23% false positive and 30% false negative were found for synthetic data.