Diffusion of polymer-grafted nanoparticles with dynamical fluctuations in unentangled polymer melts.

The dynamics of polymer-grafted nanoparticles (PGNPs) in melts of unentangled linear chains were investigated by means of coarse-grained molecular dynamics simulations. The results demonstrated that the graft monomers closer to the particle surface relax more slowly than those farther away due to the constraint of the grafted surface and the confinement of the neighboring chains. Such heterogeneous relaxations of the surrounding environment would perturb the particle motion, making them fluctuating around their centers before they can diffuse through the melt. During such intermediate-time stage, the dynamics is subdiffusive while the distribution of particle displacements is Gaussian, which can be described by the popular fractional Brownian motion model. For the long-time Fickian diffusion, we found that the diffusivity D decreases with increasing grafting density Σg, grafted chain length Ng, and matrix chain length Nm. This is due to the fact that the diffusivity is controlled by the viscous drag of an effective core, consisting of the NP and the non-draining layer of graft segments, and that of the free-draining graft layer outside the "core". With increasing Σg, the PGNPs become harder with greater effective size and thinner free draining layer, resulting in a reduction in D. At extremely high Σg, the diffusivity can even be estimated by the diameter-renormalized Stokes-Einstein (SE) relation. With increasing Ng, both the effective core size and the thickness of the free-draining layer increase, leading to a reduction in diffusivity by D ∼ N-γg with 0.5 < γ < 1. Increasing Nm would lead to the enlargement of the effective core size but meanwhile result in the reduction of the free-draining layer thickness due to autophobic dewetting. The counteraction between these two opposite effects leads to only a slight reduction in the diffusivity, significantly different from the typical SE behavior where D ∼ Nm-1. These findings bear significance in unraveling the fundamental physics of the anomalous dynamics of PGNPs in various polymers, including biological and synthetic.

High-power and reliable GaN-based vertical light-emitting diodes on 4-inch silicon substrate.

High-power and reliable GaN-based vertical light-emitting diodes (V-LEDs) on 4-inch silicon substrate were fabricated and characterized in this article. The metallization scheme reliability was improved by depositing the Pt/Ti films that surround the compressed Ag/TiW films to protect it from environmental humidity. We demonstrated that although current crowding in V-LEDs was not as severe as that in lateral light-emitting diodes (L-LEDs), high current density around the opaque metal n-electrode in V-LEDs remained a problem. A SiO2 current blocking layer (CBL) was incorporated in V-LEDs to modify the current distribution. Roughening the emitting surface of V-LEDs with KOH and H3PO4 etchant was compared and the influence of surface roughening on the emission property of V-LEDs was studied. The high-power V-LEDs showed low forward voltage with small series resistance and high light output power (LOP) without saturation up to 1300 mA. Under 350 mA injection current, V-LEDs achieved an excellent light output power (LOP) of 501 mW with the peak emission wavelength at 453 nm. The prominent output performance of V-LEDs demonstrated in this work confirmed that integrating the optimized metallization scheme, SiO2 CBL and surface texturing by KOH wet etching is an effective approach to higher performance V-LEDs.

An integrated method for compensating and correcting nonlinear error in five-axis machining utilizing cutter contacting point data.

In current five-axis computer numerical control (CNC) machining, the use of minute linear path segments as an approximation for the ideal cutter contacting (CC) point trajectory is still prevalent. However, introducing rotation axes leads to a deviation of the actual CC point trajectory from the ideal, resulting in nonlinear errors. An integrated method is proposed in this paper for compensating and correcting both the contour error, associated with the approximation of the part surface by the ideal CC point trajectory and the nonlinear error of the CC point trajectory based on the information in the CC point data. By analyzing the spatial relationship between the tool posture and the CC point path during the five-axis linear interpolation process, two adjacent machining tool positions containing CC point data information are selected as the starting and ending points of the five-axis linear interpolation machining. The ideal tool center point and the actual CC point are calculated during the interpolation process, as well as the distance and the unit vector in the perpendicular direction between the actual CC point and the ideal CC point trajectory segment. In the comprehensive error compensation and correction phase, the obtained unit vectors are used as direction vectors for error compensation, and the tool center point during interpolation is first compensated and corrected. This ensures the actual CC point and the contour curve are on the same plane. The compensation direction for contour error is calculated using the start/end tool axis vectors and the ideal CC point trajectory vectors. The size of the contour error approximating the contour curve is calculated through the chord error. A second compensation and correction are applied to the tool center point for interpolation, ultimately achieving comprehensive compensation and correction of nonlinear errors. The data calculations were conducted in the MATLAB environment using actual machining data. After compensation and correction, the contour error was reduced by 76%, the nonlinear error of the CC point trajectory decreased to below 0.88 µm, and the comprehensive nonlinear error of the CC point trajectory was reduced from 19 to 1.5 µm, a reduction of 93%. This demonstrates significant practical value in enhancing the accuracy of five-axis CNC machining. Through actual machining verification, after using the method described in this paper, the average surface roughness decreased from 1.133 to 0.220 µm, and the maximum surface roughness decreased from 6.667 to 1.240 µm. This significantly demonstrates that the compensation and correction method proposed in this paper can significantly improve the surface quality of machined parts.

Four-quadrant fast compressive tracking of breast ultrasound videos for computer-aided response evaluation of neoadjuvant chemotherapy in mice.

BACKGROUND AND OBJECTIVE: Neoadjuvant chemotherapy (NAC) is a valuable treatment approach for locally advanced breast cancer. Contrast-enhanced ultrasound (CEUS) potentially enables the assessment of therapeutic response to NAC. In order to evaluate the response accurately, quantitatively and objectively, a method that can effectively compensate motions of breast cancer in CEUS videos is urgently needed. METHODS: We proposed the four-quadrant fast compressive tracking (FQFCT) approach to automatically perform CEUS video tracking and compensation for mice undergoing NAC. The FQFCT divided a tracking window into four smaller windows at four quadrants of a breast lesion and formulated the tracking at each quadrant as a binary classification task. After the FQFCT of breast cancer videos, the quantitative features of CEUS including the mean transit time (MTT) were computed. All mice showed a pathological response to NAC. The features between pre- (day 1) and post-treatment (day 3 and day 5) in these responders were statistically compared. RESULTS: When we tracked the CEUS videos of mice with the FQFCT, the average tracking error of FQFCT was 0.65 mm, reduced by 46.72% compared with the classic fast compressive tracking method (1.22 mm). After compensation with the FQFCT, the MTT on day 5 of the NAC was significantly different from the MTT before NAC (day 1) (p = 0.013). CONCLUSIONS: The FQFCT improves the accuracy of CEUS video tracking and contributes to the computer-aided response evaluation of NAC for breast cancer in mice.

3-D Gabor-based anisotropic diffusion for speckle noise suppression in dynamic ultrasound images.

Speckle noise contaminates medical ultrasound images, and the suppression of speckle noise is helpful for image interpretation. Traditional ultrasound denoising (i.e., despeckling) methods are developed on two-dimensional static images. However, one of the advantages of ultrasonography is its nature of dynamic imaging. A method for dynamic ultrasound despeckling is expected to incorporate both the spatial and temporal information in successive images of dynamic ultrasound and thus yield better denoising performance. Here we regard a dynamic ultrasound video as three-dimensional (3-D) images with two dimensions in the spatial domain and one in the temporal domain, and we propose a despeckling algorithm for dynamic ultrasound named the 3-D Gabor-based anisotropic diffusion (GAD-3D). The GAD-3D expands the classic two-dimensional Gabor-based anisotropic diffusion (GAD) into 3-D domain. First, we proposed a robust 3-D Gabor-based edge detector by capturing the edge with 3-D Gabor transformation. Then we embed this novel detector into the partial differential equation of GAD to guide the 3-D diffusion process. In the simulation experiment, when the noise variance is as high as 0.14, the GAD-3D improves the Pratt's figure of merit, mean structural similarity index and peak signal-to-noise ratio by 24.32%, 10.98%, and 6.51%, respectively, compared with the best values of seven other methods. Experimental results on clinical dynamic ultrasonography suggest that the GAD-3D outperforms the other seven methods in noise reduction and detail preservation. The GAD-3D is effective for dynamic ultrasound despeckling and may be potentially valuable for disease assessment in dynamic medical ultrasonography.

Mesoporous WO3 modified by Au nanoparticles for enhanced trimethylamine gas sensing properties.

In this paper, KIT-6 is used as a template to prepare ordered mesoporous materials WO3 and Au-loaded WO3 (Au-WO3). The pristine WO3 sensor and the Au-WO3 sensor are fabricated for the detection of 19 important gases, such as trimethylamine, formaldehyde and CS2. The results show that the Au-WO3 sensor has better selectivity and higher response to TMA. At a working temperature of 268 °C, the response (Ra/Rg) of the Au-WO3 sensor to 100 ppm of TMA is 41.56 and the response time is 1 s. In addition, the sensor has excellent response/recovery capabilities and stability. These high sensing performances are mainly attributed to the electronic and chemical sensitization of the noble metal Au and the presence of a high specific surface area supported by the mesoporous structure. Therefore, Au-doped mesoporous WO3 should be a promising material for a high performance TMA gas sensor.

Development of deep learning algorithms for predicting blastocyst formation and quality by time-lapse monitoring.

Approaches to reliably predict the developmental potential of embryos and select suitable embryos for blastocyst culture are needed. The development of time-lapse monitoring (TLM) and artificial intelligence (AI) may help solve this problem. Here, we report deep learning models that can accurately predict blastocyst formation and usable blastocysts using TLM videos of the embryo's first three days. The DenseNet201 network, focal loss, long short-term memory (LSTM) network and gradient boosting classifier were mainly employed, and video preparation algorithms, spatial stream and temporal stream models were developed into ensemble prediction models called STEM and STEM+. STEM exhibited 78.2% accuracy and 0.82 AUC in predicting blastocyst formation, and STEM+ achieved 71.9% accuracy and 0.79 AUC in predicting usable blastocysts. We believe the models are beneficial for blastocyst formation prediction and embryo selection in clinical practice, and our modeling methods will provide valuable information for analyzing medical videos with continuous appearance variation.

Effect of strain relaxation on performance of InGaN/GaN green LEDs grown on 4-inch sapphire substrate with sputtered AlN nucleation layer.

Here we demonstrate high-brightness InGaN/GaN green light emitting diodes (LEDs) with in-situ low-temperature GaN (LT-GaN) nucleation layer (NL) and ex-situ sputtered AlN NL on 4-inch patterned sapphire substrate. Compared to green LEDs on LT-GaN (19 nm)/sapphire template, green LEDs on sputtered AlN (19 nm)/template has better crystal quality while larger in-plane compressive strain. As a result, the external quantum efficiency (EQE) of green LEDs on sputtered AlN (19 nm)/sapphire template is lower than that of green LEDs on LT-GaN (19 nm)/sapphire template due to strain-induced quantum-confined Stark effect (QCSE). We show that the in-plane compressive strain of green LEDs on sputtered AlN/sapphire templates can be manipulated by changing thickness of the sputtered AlN NL. As the thickness of sputtered AlN NL changes from 19 nm to 40 nm, the green LED on sputtered AlN (33 nm)/sapphire template exhibits the lowest in-plane compressive stress and the highest EQE. At 20 A/cm2, the EQE of 526 nm green LEDs on sputtered AlN (33 nm)/sapphire template is 36.4%, about 6.1% larger than that of the green LED on LT-GaN (19 nm)/sapphire template. Our experimental data suggest that high-efficiency green LEDs can be realized by growing InGaN/GaN multiple quantum wells (MQWs) on sputtered AlN/sapphire template with reduced in-plane compressive strain and improved crystal quality.

Speckle Suppression of Ultrasonography Using Maximum Likelihood Estimation and Weighted Nuclear Norm Minimization.

Speckle noise corrupts medical ultrasound images and suppression of speckle noise is valuable for image interpretation. This paper presents a new method for speckle suppression named the maximum likelihood based weighted nuclear norm minimization (MLWNNM) filtering by integrating the maximum likelihood estimation (MLE) with the weighted nuclear norm minimization (WNNM). The MLE is first used to get an initially filtered image with reduced Rayleigh distributed noise, and then the WNNM is applied to further improve the denoising effect by preserving and enhancing tissue details. Simulation work shows that when the noise variance is as high as 0.14, the MLWNNM improves the Pratt's figure of merit, peak signal to noise ratio, and mean structural similarity by 123.51%, 0.84%, and 6.13%, respectively, in contrast to the best values of other six methods. Experimental results on clinical ultrasound images suggest that the MLWNNM outperforms other six methods in noise reduction and detail preservation.

Effect of Dielectric Distributed Bragg Reflector on Electrical and Optical Properties of GaN-Based Flip-Chip Light-Emitting Diodes.

We demonstrated two types of GaN-based flip-chip light-emitting diodes (FCLEDs) with distributed Bragg reflector (DBR) and without DBR to investigate the effect of dielectric TiO2/SiO2 DBR on optical and electrical characteristics of FCLEDs. The reflector consisting of two single TiO2/SiO2 DBR stacks optimized for different central wavelengths demonstrates a broader reflectance bandwidth and a less dependence of reflectance on the incident angle of light. As a result, the light output power (LOP) of FCLED with DBR shows 25.3% higher than that of FCLED without DBR at 150 mA. However, due to the better heat dissipation of FCLED without DBR, it was found that the light output saturation current shifted from 268 A/cm² for FCLED with DBR to 296 A/cm² for FCLED without DBR. We found that the use of via-hole-based n-type contacts can spread injection current uniformly over the entire active emitting region. Our study paves the way for application of DBR and via-hole-based n-type contact in high-efficiency FCLEDs.

The effect of nanometre-scale V-pits on electronic and optical properties and efficiency droop of GaN-based green light-emitting diodes.

The development of efficient green light-emitting diodes (LEDs) is of paramount importance for the realization of colour-mixing white LEDs with a high luminous efficiency. While the insertion of an InGaN/GaN superlattice (SL) with a lower In content before the growth of InGaN/GaN multiple quantum wells (MQWs) is known to increase the efficiency of LEDs, the actual mechanism is still debated. We therefore conduct a systematic study and investigate the different mechanisms for this system. Through cathodoluminescence and Raman measurements, we clearly demonstrate that the potential barrier formed by the V-pit during the low-temperature growth of an InGaN/GaN SL dramatically increases the internal quantum efficiency (IQE) of InGaN quantum wells (QWs) by suppressing non-radiative recombination at threading dislocations (TDs). We find that the V-pit potential barrier height depends on the V-pit diameter, which plays an important role in determining the quantum efficiency, forward voltage and efficiency droop of green LEDs. Furthermore, our study reveals that the low-temperature GaN can act as an alternative to an InGaN/GaN SL structure for promoting the formation of V-pits. Our findings suggest the potential of implementing optimized V-pits embedded in an InGaN/GaN SL or low-temperature GaN structure as a beneficial underlying layer for the realization of highly efficient green LEDs.