Silver Nanoflower Decorated Graphene Oxide Sponges for Highly Sensitive Variable Stiffness Stress Sensors

Soft conductive materials should enable large deformation while keeping high electrical conductivity and elasticity. The graphene oxide (GO)‐based sponge is a potential candidate to endow large deformation. However, it typically exhibits low conductivity and elasticity. Here, the highly conductive and elastic sponge composed of GO, flower‐shaped silver nanoparticles (AgNFs), and polyimide (GO‐AgNF‐PI sponge) are demonstrated. The average pore size and porosity are 114 µm and 94.7%, respectively. Ag NFs have thin petals (8–20 nm) protruding out of the surface of a spherical bud (300–350 nm) significantly enhancing the specific surface area (2.83 m² g^?1). The electrical conductivity (0.306 S m^?1 at 0% strain) of the GO‐AgNF‐PI sponge is increased by more than an order of magnitude with the addition of Ag NFs. A nearly perfect elasticity is obtained over a wide compressive strain range (0–90%). The strain‐dependent, nonlinear variation of Young's modulus of the sponge provides a unique opportunity as a variable stiffness stress sensor that operates over a wide stress range (0–10 kPa) with a high maximum sensitivity (0.572 kPa^?1). It allows grasping of a soft rose and a hard bottle, with the minimal object deformation, when attached on the finger of a robot gripper.     

A Hemispherical Image Sensor Array Fabricated with Organic Photomemory Transistors

Hemispherical image sensors simplify lens designs, reduce optical aberrations, and improve image resolution for compact wide-field-of-view cameras. To achieve hemispherical image sensors, organic materials are promising candidates due to the following advantages: tunability of optoelectronic/spectral response and low-temperature low-cost processes. Here, a photolithographic process is developed to prepare a hemispherical image sensor array using organic thin film photomemory transistors with a density of 308 pixels per square centimeter. This design includes only one photomemory transistor as a single active pixel, in contrast to the conventional pixel architecture, consisting of select/readout/reset transistors and a photodiode. The organic photomemory transistor, comprising light-sensitive organic semiconductor and charge-trapping dielectric, is able to achieve a linear photoresponse (light intensity range, from 1 to 50 W m⁻²), along with a responsivity as high as 1.6 A W⁻¹ (wavelength = 465 nm) for a dark current of 0.24 A m⁻² (drain voltage = −1.5 V). These observed values represent the best responsivity for similar dark currents among all the reported hemispherical image sensor arrays to date. A transfer method was further developed that does not damage organic materials for hemispherical organic photomemory transistor arrays. These developed techniques are scalable and are amenable for other high-resolution 3D organic semiconductor devices.     

Abrogation of p53 function affects gadd gene responses to DNA base-damaging agents and starvation

The tumor suppressor p53 is required for induction of its downstream effector genes such as GADD45 and CIP1/WAF1 by ionizing radiation (IR). This response is probably mediated through defined p53 binding sites located in the promoter of CIP1/WAF1 and in the third intron of GADD45. In contrast, the gadd gene stress response to base-damaging agents, such as methylmethane sulfonate (MMS) or UV radiation, or medium depletion (starvation) occurs in all mammalian cells examined to date regardless of p53 status for both GADD45 and also GADD153, which is not IR-responsive in many lines with functional p53. These agents strongly induce the p53 protein and raise the possibility that, although p53 is not required for the typical "gadd" response to these agents, p53 may contribute to these non-IR stress responses. This possibility was confirmed by the finding that disruption of p53 function by transfection with dominant-negative vectors expressing HPV E6, mutant p53, or SV40 T Ag reduced the induction of GADD45 and GADD153 as measured by increases in mRNA and protein levels in human lines with wild-type p53. Similarly, induction of these genes by MMS or UV radiation was consistently stronger in the parental mouse embryo fibroblasts compared to cells derived from mice where both p53 alleles had been deleted. Similar qualitative responses were also seen for CIP1/WAF1. In agreement with reduced induction of p53-regulated genes, the G1 checkpoint activated by MMS or UV radiation was markedly abrogated in p53-wt human MCF-7 breast carcinoma cells by E6 expression. Interestingly, induction of reporter constructs driven by the GADD45 or GADD153 promoters was substantially reduced in human cells transfected with mutant p53 or E6 expression vectors or in cells lacking p53 following treatment with MMS, UV radiation, or starvation. Because neither promoter is inducible by IR, and neither contains a strong p53 binding site, these results indicate that p53 has a synergistic or cooperative role in these non-IR stress responses for both GADD45 and GADD153, and that this role is not mediated through identifiable p53-binding sites.     

Adaptive observer-based trajectory tracking control of nonholonomic mobile robots

In this paper, an adaptive observer-based trajectory tracking problem is solved for nonholonomic mobile robots with uncertainties. An adaptive observer is first developed to estimate the unmeasured velocities of a mobile robot with model uncertainties. Using the designed observer and the backstepping technique, a trajectory tracking controller is designed to generate the torque as an input. Using Lyapunov stability analysis, we prove that the closed-loop system is asymptotically stable with respect to the estimation errors and tracking errors. Finally, the simulation results are presented to validate the performance and robustness of the proposed control system against uncertainties.     

Memory effects of all‐solution‐processed oxide thin‐film transistors using ZnO nanoparticles

Abstract— Non‐volatile memory effects of an all‐solution‐processed oxide thin‐film transistor (TFT) with ZnO nanoparticles (NPs) as the charge‐trapping layer are reported. The device was fabricated by using a soluble MgInZnO active channel on a ZrHfO^x gate dielectric. ZnO NPs were used as the charge‐trapping site at the gate‐insulator—channel interface, and Al was used for source and drain electrodes. Transfer characteristics of the device showed a large clockwise hysteresis, which can be used to demonstrate its memory function due to electron trapping in the ZnO NP charge‐trapping layer. This memory effect has the potential to be utilized as a memory application on displays and disposable electronics.     

Optimization of silicon solar cell fabrication based on neural network and genetic programming modeling

This study describes techniques for the cascade modeling and the optimization that are required to conduct the simulator-based process optimization of solar cell fabrication. Two modeling approaches, neural networks and genetic programming, are employed to model the crucial relation for the consecutively connected two processes in solar cell fabrication. One model (Model 1) is used to map the five inputs (time, amount of nitrogen and DI water in surface texturing and temperature and time in emitter diffusion) to the two outputs (reflectance and sheet resistance) of the first process. The other model (Model 2) is used to connect the two inputs (reflectance and sheet resistance) to the one output (efficiency) of the second process. After modeling of the two processes, genetic algorithms and particle swarm optimization were applied to search for the optimal recipe. In the first optimization stage, we searched for the optimal reflectance and sheet resistance that can provide the best efficiency in the fabrication process. The optimized reflectance and sheet resistance found by the particle swarm optimization were better than those found by the genetic algorithm. In the second optimization stage, the five input parameters were searched by using the reflectance and sheet resistance values obtained in the first stage. The found five variables such as the texturing time, amount of nitrogen, DI water, diffusion time, and temperature are used as a recipe for the solar cell fabrication. The amount of nitrogen, DI water, and diffusion time in the optimized recipes showed considerable differences according to the modeling approaches. More importantly, repeated applications of particle swarm optimization yielded process conditions with smaller variations, implying greater consistency in recipe generation.     

Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm

This paper deals with a scheduling problem for reentrant hybrid flowshop with serial stages where each stage consists of identical parallel machines. In a reentrant flowshop, a job may revisit any stage several times. Local-search based Pareto genetic algorithms with Minkowski distance-based crossover operator is proposed to approximate the Pareto optimal solutions for the minimization of makespan and total tardiness in a reentrant hybrid flowshop. The Pareto genetic algorithms are compared with existing multi-objective genetic algorithm, NSGA-II in terms of the convergence to optimal solution, the diversity of solution and the dominance of solution. Experimental results show that the proposed crossover operator and local search are effective and the proposed algorithm outperforms NSGA-II by statistical analysis.