In this paper, the role of introducing Germanium (Ge)/IGZO heterostructure in enhancing the Infrared (IR) photodetection properties of thin-film phototransistor (Photo- TFT) is presented. Numerical models for the investigated device are developed using ATLAS device simulator. The influence of Ge photosensitive layer thickness on the sensor IR photoresponse is carried out. It is revealed that the optimized IR Photo-TFT based on p-Ge/IGZO heterojunction can offer improved IR responsivity of 4.1×10(exp2) A/W, and over 10(exp6) of sensitivity. These improvements are attributed to the role of the introduced p-Ge/IGZO heterostructure in promoting IR photodetection ability and improved separation and transfer mechanisms of photo-exited electron/hole pairs. The photosensor is then implemented in an optical inverter gate circuit in order to assess its switching capabilities. It is found that the proposed phototransistor shows an improved optical gain thus indicating its excellent performance. Therefore, providing high IR responsivity and low dark noise effects, the optimized Ge/IGZO IR Photo-TFT can be a potential alternative photosensor for designing optoelectronic systems with high-performance and ultralow power consumption.

Using first-principles calculations, we study the structural, electronic and optical properties of the monolayer, bilayer and trilayer germanium monosulfide GeS. The results reveal an indirect semiconducting band gap for the monolayer and trilayer GeS, whereas the gap is direct for the bilayer GeS. Both the generalized gradient approximation and the screened hybrid functionals assess a decrease in band energy as the number of layers is improved. Furthermore, due to the high buckling of lattice structures, the optical spectra show significant degree of anisotropy. The number of layers engineers key optical parameters including the refractive index, the reflectivity absorption and provides the layered GeS with excellent absorption in the low energy region, namely the visible and UV range of the electromagnetic spectrum. Accordingly, 2D hexagonal GeS few-layers can be used as a highly promising material in the optoelectronic, ultraviolet optical nanodevices and photovoltaics.

In this paper, a new approach based on ZnO/Silicon interface engineering aspect is proposed to enhance the absorbance performance for n-ZnO/p-Si hetero-junction based solar cell. The merits of using grooves morphology in the ZnO/Silicon interface to improve the photovoltaic performance are investigated numerically using accurate solutions of Maxwell's equations. It is found that the proposed interface morphology arises the optical confinement effect which can efficiently improve the device optical performance. Besides, the proposed structure exhibits superior photovoltaic performance and offers improved absorbance behavior as compared to the conventional counterpart. Moreover, the introduced grooves in the n-ZnO/p-Si interface play a crucial role in increasing the light absorbance through modulating the electric field behavior inside the absorber region. These characteristics not only underline the enhanced optical behavior of the investigated structure but also bring the possibility of overcoming the tradeoff between the high efficiency and the low fabrication cost. This makes the proposed n-ZnO/p-Si hetero-junction solar cell with interface texturization a potential alternative for developing high-performance solar cell with low manufacturing cost.

This article deals with the study of a new swimming microrobot behavior using an analytical investigation. The analyzed microrobot is associated by a spherical head and hybrid tail. The principle of modeling is based on solving of the coupled elastic/fluidic problems between the hybrid tail’s deflections and the running environment. In spite of the resulting nonlinear model can be exploited to enhance both the sailing ability and also can be controlled in viscous environment using nonlinear control investigations. The applications of the micro-robot have required the precision of control for targeting the running area in terms of response time and tracking error. Due to these limitations, the Flatness-ANFIS based control is used to ensure a good control behavior in hazardous environment. Our control investigation is coupled the differential flatness and adaptive neuro-fuzzy inference techniques, in which the flatness is used to planning the optimal trajectory and eliminate the nonlinearity effects of the resulting model. In other hand, the neuro-fuzzy inference technique is used to build the law of control technique and minimize the dynamic error of tracking trajectory. In particular, we deduct from a non linear model to an optimal model of the design parameter’s using Multi-Objective genetic algorithms (MOGAs). In addition, Computational fluid dynamics modeling of the microrobot is also carried out to study the produced thrust and velocity of the microrobot displacement taking into account the fluid parameters. Our analytical results have been validated by the recorded good agreement between the numerical and analytical results.

In this paper, versatile structures based on dissimilar metallic nano-particles (Ag, Au, Ti, Al) are proposed to enhance the ZnO thin film optical performance for both optoelectronic and environment monitoring applications. An Exhaustive study of the proposed structure including metallic nano-particles has been performed numerically, in order to evaluate the optical behavior of the proposed ZnO thin films against the conventional design for optoelectronic applications. The numerical computations reveal that the proposed design exhibits an outstanding capability in improving the overall device optical parameters. In addition, the proposed device with Al metallic nano-particles offers superior absorbance as well as lower reflectance as compared to the conventional design. These achievements can be attributed essentially to the localized surface plasma resonance phenomenon and the improved light trapping capability resulted from the optical confinement effect. The recorded results signify the crucial role of the proposed feature in improving the ZnO thin films optical performance, which makes it very promising to be used in the future high performance optoelectronic devices.

In this paper, versatile structures based on dissimilar metallic nano-particles (Ag, Au, Ti, Al) are proposed to enhance the ZnO thin film optical performance for both optoelectronic and environment monitoring applications. An Exhaustive study of the proposed structure including metallic nano-particles has been performed numerically, in order to evaluate the optical behavior of the proposed ZnO thin films against the conventional design for optoelectronic applications. The numerical computations reveal that the proposed design exhibits an outstanding capability in improving the overall device optical parameters. In addition, the proposed device with Al metallic nano-particles offers superior absorbance as well as lower reflectance as compared to the conventional design. These achievements can be attributed essentially to the localized surface plasma resonance phenomenon and the improved light trapping capability resulted from the optical confinement effect. The recorded results signify the crucial role of the proposed feature in improving the ZnO thin films optical performance, which makes it very promising to be used in the future high performance optoelectronic devices.

In this study, an ultrasensitive biological boron nitride-based nanotube (Bio-BNNT) sensor is modeled and investigated by means of neural approach. The type of configuration studied is a cantilevered BNNT resonator sensor with an attached mass at the tip. The idea behind our resonator sensor is based on the determination of the natural BNNT frequency shift induced by added biological mass. A multilayer perceptron neural network is used to predict the attached mass, which causes a variation of the BNNTs frequency shift with different diameters and lengths. This model is implemented in the form of a component in the ORCAD-PSPICE electric simulator library. The component should reproduce faithfully the biological sensor behavior. Moreover, we have developed an inverse model called intelligent sensor in order to remove the nonlinearity response provided by the sensor. The association of this ANN-based corrector has brought significant improvement for high sensing performance.