High Performance Predictable Quantum Efficient Detector Based on Induced-Junction Photodiodes Passivated with SiO2/SiNx

We performed a systematic study involving simulation and experimental techniques to develop induced-junction silicon photodetectors passivated with thermally grown SiO2 and plasma-enhanced chemical vapor deposited (PECVD) SiNx thin films that show a record high quantum efficiency. We investigated PECVD SiNx passivation and optimized the film deposition conditions to minimize the recombination losses at the silicon–dielectric interface as well as optical losses. Depositions with varied process parameters were carried out on test samples, followed by measurements of minority carrier lifetime, fixed charge density, and optical absorbance and reflectance. Subsequently, the surface recombination velocity, which is the limiting factor for internal quantum deficiency (IQD), was obtained for different film depositions via 2D simulations where the measured effective lifetime, fixed charge density, and substrate parameters were used as input. The quantum deficiency of induced-junction photodiodes that would be fabricated with a surface passivation of given characteristics was then estimated using improved 3D simulation models. A batch of induced-junction photodiodes was fabricated based on the passivation optimizations performed on test samples and predictions of simulations. Photodiodes passivated with PECVD SiNx film as well as with a stack of thermally grown SiO2 and PECVD SiNx films were fabricated. The photodiodes were assembled as light-trap detector with 7-reflections and their efficiency was tested with respect to a reference Predictable Quantum Efficient Detector (PQED) of known external quantum deficiency. The preliminary measurement results show that PQEDs based on our improved photodiodes passivated with stack of SiO2/SiNx have negligible quantum deficiencies with IQDs down to 1 ppm within 30 ppm measurement uncertainty.

Electrophoretic Mobility and Electric Conductivity of Salt-Free Suspensions of Charged Soft Particles

A unit cell model is employed to analyze the electrophoresis and electric conduction in a concentrated suspension of spherical charged soft particles (each is a hard core coated with a porous polyelectrolyte layer) in a salt-free medium. The linearized Poisson–Boltzmann equation applicable to a unit cell is solved for the equilibrium electrostatic potential distribution in the liquid solution containing the counterions only surrounding a soft particle. The counterionic continuity equation and modified Stokes/Brinkman equations are solved for the ionic electrochemical potential energy and fluid velocity distributions, respectively. Closed-form formulas for the electrophoretic mobility of the soft particles and effective electric conductivity of the suspension are derived, and the effect of particle interactions on these transport characteristics is interesting and significant. Same as the case in a suspension containing added electrolytes under the Debye–Hückel approximation, the scaled electrophoretic mobility in a salt-free suspension is an increasing function of the fixed charge density of the soft particles and decreases with increases in the core-to-particle radius ratio, ratio of the particle radius to the permeation length in the porous layer, and particle volume fraction, keeping the other parameters unchanged. The normalized effective electric conductivity of the salt-free suspension also increases with an increase in the fixed charge density and with a decrease in the core-to-particle radius ratio, but is not a monotonic function of the particle volume fraction.

Analog/RF Performance of Triple Material Gate Stack-Graded Channel Double Gate-Junctionless Strained-Silicon MOSFET with Fixed Charges

In this paper, analog/radio frequency (RF) electrical characteristics of triple material gate stackgraded channel double gate-Junctionless (TMGS-GCDGJL) strained-Si (s-Si) MOSFET with fixed charge density is analyzed with the help of Sentaurus TCAD. By varying the various device parameters, the analog/RF performance of the proposed TMGS-GCDG-JL s-Si MOSFET is evaluated in terms of transconductance-generationfactor (TGF), early voltage, voltage gain, unity-powergain frequency ( f max ), unity-current-gain frequency ( f t ), and gain-transconductance frequency product (GTFP). The results confirm that the proposed TMGS-GCDGJL s-Si MOSFET has superior analog/RF performance compared to gate stack-graded channel double gatejunctionless (GS-GCDG-JL) s-Si device. However, the proposed MOSFET has less transconductance and less output conductance when compared with the GS-GCDGJL s-Si device in above threshold region, and reverse trend follows in sub-threshold region.

An in silico Framework of Cartilage Degeneration That Integrates Fibril Reorientation and Degradation Along With Altered Hydration and Fixed Charge Density Loss

Injurious mechanical loading of articular cartilage and associated lesions compromise the mechanical and structural integrity of joints and contribute to the onset and progression of cartilage degeneration leading to osteoarthritis (OA). Despite extensive in vitro and in vivo research, it remains unclear how the changes in cartilage composition and structure that occur during cartilage degeneration after injury, interact. Recently, in silico techniques provide a unique integrated platform to investigate the causal mechanisms by which the local mechanical environment of injured cartilage drives cartilage degeneration. Here, we introduce a novel integrated Cartilage Adaptive REorientation Degeneration (CARED) algorithm to predict the interaction between degenerative variations in main cartilage constituents, namely collagen fibril disorganization and degradation, proteoglycan (PG) loss, and change in water content. The algorithm iteratively interacts with a finite element (FE) model of a cartilage explant, with and without variable depth to full-thickness defects. In these FE models, intact and injured explants were subjected to normal (2 MPa unconfined compression in 0.1 s) and injurious mechanical loading (4 MPa unconfined compression in 0.1 s). Depending on the mechanical response of the FE model, the collagen fibril orientation and density, PG and water content were iteratively updated. In the CARED model, fixed charge density (FCD) loss and increased water content were related to decrease in PG content. Our model predictions were consistent with earlier experimental studies. In the intact explant model, minimal degenerative changes were observed under normal loading, while the injurious loading caused a reorientation of collagen fibrils toward the direction perpendicular to the surface, intense collagen degradation at the surface, and intense PG loss in the superficial and middle zones. In the injured explant models, normal loading induced intense collagen degradation, collagen reorientation, and PG depletion both on the surface and around the lesion. Our results confirm that the cartilage lesion depth is a crucial parameter affecting tissue degeneration, even under physiological loading conditions. The results suggest that potential fibril reorientation might prevent or slow down fibril degradation under conditions in which the tissue mechanical homeostasis is perturbed like the presence of defects or injurious loading.

Hyaluronidase reduced edema after experimental traumatic brain injury

Cerebral edema and the subsequent increased intracranial pressure are associated with mortality and poor outcome following traumatic brain injury. Previous in vitro studies have shown that the Gibbs-Donnan effect, which describes the tendency of a porous, negatively charged matrix to attract positive ions and water, applies to brain tissue and that enzymatic reduction of the fixed charge density can prevent tissue swelling. We tested whether hyaluronidase, an enzyme that degrades the large, negatively charged glycosaminoglycan hyaluronan, could reduce brain edema after traumatic brain injury. In vivo, intracerebroventricular injection of hyaluronidase after controlled cortical impact in mice reduced edema in the ipsilateral hippocampus at 24 h by both the wet-weight/dry-weight method (78.15 ± 0.65% vs. 80.4 ± 0.46%; p < 0.01) and T2-weighted magnetic resonance imaging (13.88 ± 3.09% vs. 29.23 ± 6.14%; p < 0.01). Hyaluronidase did not adversely affect blood–brain-barrier-integrity measured by dynamic contrast-enhanced magnetic resonance imaging, nor did hyaluronidase negatively affect functional recovery after controlled cortical impact measured with the rotarod or Morris water maze tasks. Reduction of fixed charge density by hyaluronidase was confirmed in cortical explants in vitro (5.46 ± 1.15 µg/mg vs. 7.76 ± 1.87 µg/mg; p < 0.05). These data demonstrate that targeting the fixed charge density with hyaluronidase reduced edema in an in vivo mouse model of traumatic brain injury.