Amorphous and nanocrystalline silicon made by varying deposition pressure in PECVD process

Silicon thin films are deposited using plasma enhanced chemical vapor deposition (PECVD) of silane, argon, hydrogen mixture at various pressures in the range of 2–8 Torr. Raman scattering shows these to be amorphous in the pressure range 6–8 Torr, and nanocrystalline in the range 2–4 Torr. The volume fraction of nanocrystals is estimated by fitting the Raman data to three peaks and is found to be ～75% for the films deposited at low pressure, density of states of these films was measured. It is observed that the electrical conduction in these films depends on the crystalline volume fraction (ρ), estimated from the laser Raman Spectroscopy. Temperature dependence electrical conductivity shows that at lower temperatures thermionic emission dominates for the films with lower ρ, whereas, hopping is the main conduction mechanism for the films having high ρ. The density of states is estimated from the space charge limited currents (SCLC) observed at high fields. Photoconductivity at room temperature is also measured. The amorphous films are found to be more photosensitive than the nanocrystalline one. In the context of these findings, changes in the properties of silicon from amorphous to nanocrystalline are described.     

ABCAttack: A Gradient-Free Optimization Black-Box Attack for Fooling Deep Image Classifiers

The vulnerability of deep neural network (DNN)-based systems makes them susceptible to adversarial perturbation and may cause classification task failure. In this work, we propose an adversarial attack model using the Artificial Bee Colony (ABC) algorithm to generate adversarial samples without the need for a further gradient evaluation and training of the substitute model, which can further improve the chance of task failure caused by adversarial perturbation. In untargeted attacks, the proposed method obtained 100%, 98.6%, and 90.00% success rates on the MNIST, CIFAR-10 and ImageNet datasets, respectively. The experimental results show that the proposed ABCAttack can not only obtain a high attack success rate with fewer queries in the black-box setting, but also break some existing defenses to a large extent, and is not limited by model structure or size, which provides further research directions for deep learning evasion attacks and defenses.     

Modulation of Biophysical Cues in Nature Inspired Patterning of Porous Silk Fibroin Scaffold for Replenishable Controlled Drug Delivery

While a sticking plasteris enough for healing of most of the minor cuts they may get routinely, critical situations like surgical, gunshot, accidental or diabetic wounds;lacarations and other cutaneous deep cuts may require implants and simultaneous medications for healing. From the biophysical standpoint, an internal force-based physical surface stimulusis crucial for cellular sensing during wound repair. In this paper, the authors report the fabrication of a porous, biomimmetically patterned silk fibroin scaffold loaded with ampicillin, which exhibits controlled release of the drug along with possible replenishment of the same. In vitro swelling study reveals that the scaffolds with hierarchical surface patterns exhibit lower swelling and degradation than other types of scaffolds. The scaffolds, that show remarkable broad–spectrum antibacterial efficacy, exhibit Korsemeyer–Peppas model for the ampicillin release patterns due to the structural hydrophobicity imparted by the patterns. Four distinct cell-matrix adhesion regimes are investigated for the fibroblasts to eventually form cell sheets all over the hierarchical surface structures. 4',6–diamidino–2–phenylindole (DAPI) and Fluorescein Diacetate (FDA) fluorescent staining clearly demonstrate the superiority of patterned surface over its other variants. A comparative immunofluorescence study among collagen I, vinculin, and vimentin expressions substantiated the patterned surface to be superior to others.