ABSTRACT
In this work, the SET and RESET processes of bipolar resistive switching memories with silicon nanocrystals (Si-NCs) embedded in an oxide matrix is simulated by a stochastic model. This model is based on the estimation of two-dimensional oxygen vacancy configurations and their relationship with the resistive state. The simulation data are compared with the experimental current-voltage data of Si-NCs/SiO2 multilayer-based memristor devices. Devices with 1 and 3 Si-NCs/SiO2 bilayers were analyzed. The Si-NCs are assumed as agglomerates of fixed oxygen vacancies, which promote the formation of conductive filaments (CFs) through the multilayer according to the simulations. In fact, an intermediate resistive state was observed in the forming process (experimental and simulated) of the 3-BL device, which is explained by the preferential generation of oxygen vacancies in the sites that form the complete CFs, through Si-NCs.
ABSTRACT
In this work, we report the digital and analog resistive-switching (RS) characteristics in a memristor based on silicon nanocrystals (Si-NCs) integrated into a complementary metal-oxide-semiconductor (MOS) structure. Si-NCs with a diameter of 5.48 ± 1.24 nm embedded in a SiO2/Si-NCs/SiO2 multilayer structure acts as an RS layer. These devices exhibit bipolar RS with an intermediate resistance step during SET and RESET processes, which is believed to lie in the Si-NCs layer acting as charge-trapping nodes. The endurance studies of about 70 DC cycles indicate an ON/OFF ratio of ~106 and a retention time larger than 104 s. Long-term potentiation (LTP, -2 V) and long-term depression (LTD, +4 V) are obtained by applying consecutive identical pulse voltages of 150 ms duration. The current value gradually increases/decreases (LTP/LTD) as the pulse number increases. Three consecutive identical pulses of -2 V/150 ms (LTP) separated by 5 and 15 min show that the last current value obtained at the end of each pulse train is kept, confirming an analog RS behavior. These characteristics provide a possible way to mimic biological synapse functions for applications in neuromorphic computing in Si-NCs-based CMOS structures.
ABSTRACT
In this work, we explored the feasibility of the fabrication of PIN light-emitting diodes (LEDs) consisting of heterojunctions of amorphous silicon-carbide (a-Si1-xCx:H) thin films and crystalline silicon wafers (c-Si). The objective is the future development of electro-photonic systems in the same c-Si wafer, containing transistors, sensors, LEDs and waveguides. Two different heterojunction LEDs were fabricated consisting of PIN and PIN+N structures, where a-Si1-xCx:H thin films were used as P-type and I-type layers, while an N-type c-Si substrate was used as an active part of the device. The amorphous layers were deposited by the plasma-enhanced chemical vapor deposition (PECVD) technique at a substrate temperature of 200 °C. The PIN device presented electroluminescence (EL) only in the forward bias, while the PIN+N device presented in both the forward and reverse biases. The EL in reverse bias was possible due to the addition of an N+-type a-Si:H layer between the c-Si substrate and the I-type a-Si1-xCx:H active layer. Likewise, the EL intensity of the PIN+N structure was higher than that of the PIN device in forward bias, indicating that the addition of the N-type a-Si:H layer makes electrons flow more efficiently to the I layer. In addition, both devices presented red EL in the full area, which is observed with the naked eye.
ABSTRACT
A novel method to extract the seven parameters of the double-diode model of solar cells using the current-voltage (I-V) characteristics under illumination and in the dark is presented. The algorithm consists of two subroutines which are alternatively run to adjust all the parameters of the cell in an iterative process. Curve fitting of the light I-V characteristics ensures accuracy in the prediction of the maximum power point, whereas simultaneously fitting the dark I-V characteristics results in a set of physically meaningful parameters that provide information about the physical performance of the photovoltaic devices. Experimental I-V curves of in-house solar cells are used to validate the proposed parameter extraction method, which can be furthermore applied to other types of p-n junction-based photovoltaic devices.
ABSTRACT
Two multilayer (ML) structures, composed of five layers of silicon-rich oxide (SRO) with different Si contents and a sixth layer of silicon-rich nitride (SRN), were deposited by low pressure chemical vapor deposition. These SRN/SRO MLs were thermally annealed at 1100 °C for 180 min in ambient N2 to induce the formation of Si nanostructures. For the first ML structure (MLA), the excess Si in each SRO layer was about 10.7 ± 0.6, 9.1 ± 0.4, 8.0 ± 0.2, 9.1 ± 0.3 and 9.7 ± 0.4 at.%, respectively. For the second ML structure (MLB), the excess Si was about 8.3 ± 0.2, 10.8 ± 0.4, 13.6 ± 1.2, 9.8 ± 0.4 and 8.7 ± 0.1 at.%, respectively. Si nanopyramids (Si-NPs) were formed in the SRO/Si substrate interface when the SRO layer with the highest excess silicon (10.7 at.%) was deposited next to the MLA substrate. The height, base and density of the Si-NPs was about 2-8 nm, 8-26 nm and ~6 × 1011 cm-2, respectively. In addition, Si nanocrystals (Si-ncs) with a mean size of between 3.95 ± 0.20 nm and 2.86 ± 0.81 nm were observed for the subsequent SRO layers. Meanwhile, Si-NPs were not observed when the excess Si in the SRO film next to the Si-substrate decreased to 8.3 ± 0.2 at.% (MLB), indicating that there existed a specific amount of excess Si for their formation. Si-ncs with mean size of 2.87 ± 0.73 nm and 3.72 ± 1.03 nm were observed for MLB, depending on the amount of excess Si in the SRO film. An enhanced photoluminescence (PL) emission (eight-fold more) was observed in MLA as compared to MLB due to the presence of the Si-NPs. Therefore, the influence of graded silicon content in SRN/SRO multilayer structures on the formation of Si-NPs and Si-ncs, and their relation to the PL emission, was analyzed.
ABSTRACT
The applicability of the path planning strategy to robotic manipulators has been an exciting topic for researchers in the last few decades due to the large demand in the industrial sector and its enormous potential development for space, surgical, and pharmaceutical applications. The automation of high-degree-of-freedom (DOF) manipulator robots is a challenging task due to the high redundancy in the end-effector position. Additionally, in the presence of obstacles in the workspace, the task becomes even more complicated. Therefore, for decades, the most common method of integrating a manipulator in an industrial automated process has been the demonstration technique through human operator intervention. Although it is a simple strategy, some drawbacks must be considered: first, the path's success, length, and execution time depend on operator experience; second, for a structured environment with few objects, the planning task is easy. However, for most typical industrial applications, the environments contain many obstacles, which poses challenges for planning a collision-free trajectory. In this paper, a multiple-query method capable of obtaining collision-free paths for high DOF manipulators with multiple surrounding obstacles is presented. The proposed method is inspired by the resistive grid-based planner method (RGBPM). Furthermore, several improvements are implemented to solve complex planning problems that cannot be handled by the original formulation. The most important features of the proposed planner are as follows: (1) the easy implementation of robotic manipulators with multiple degrees of freedom, (2) the ability to handle dozens of obstacles in the environment, (3) compatibility with various obstacle representations using mathematical models, (4) a new recycling of a previous simulation strategy to convert the RGBPM into a multiple-query planner, and (5) the capacity to handle large sparse matrices representing the configuration space. A numerical simulation was carried out to validate the proposed planning method's effectiveness for manipulators with three, five, and six DOFs on environments with dozens of surrounding obstacles. The case study results show the applicability of the proposed novel strategy in quickly computing new collision-free paths using the first execution data. Each new query requires less than 0.2 s for a 3 DOF manipulator in a configuration space free-modeled by a 7291 × 7291 sparse matrix and less than 30 s for five and six DOF manipulators in a configuration space free-modeled by 313,958 × 313,958 and 204,087 × 204,087 sparse matrices, respectively. Finally, a simulation was conducted to validate the proposed multiple-query RGBPM planner's efficacy in finding feasible paths without collision using a six-DOF manipulator (KUKA LBR iiwa 14R820) in a complex environment with dozens of surrounding obstacles.