Modeling and Simulation of Hafnium Oxide RRAM Based on Oxygen Vacancy Conduction

The resistive memory has become one of the most promising new memory types because of its excellent performance, and HfO2 resistive material has attracted extensive attention. The conduction mechanism based on oxygen vacancy is widely recognized in the research of new nonvolatile memory. An RRAM electrothermal coupling model based on the oxygen vacancy conduction mechanism was constructed using COMSOL. The resistance process of the device is simulated by solving the coefficient partial differential equation, and the distribution of oxygen vacancy concentration, temperature, electric field, electric potential and other parameters in the dielectric layer at different voltages are obtained. The effects of temperature, dielectric layer thickness, top electrode thermal conductivity and conductive wire size on the resistance characteristics of the device are studied. It has guiding significance to further study the RRAM mechanism.

CNN-Based Smart Sleep Posture Recognition System

Sleep pattern and posture recognition have become of great interest for a diverse range of clinical applications. Autonomous and constant monitoring of sleep postures provides useful information for reducing the health risk. Prevailing systems are designed based on electrocardiograms, cameras, and pressure sensors, which are not only expensive but also intrusive in nature, and uncomfortable to use. We propose an unobtrusive and affordable smart system based on an electronic mat called Sleep Mat-e for monitoring the sleep activity and sleep posture of individuals living in residential care facilities. The system uses a pressure sensing mat constructed using piezo-resistive material to be placed on a mattress. The sensors detect the distribution of the body pressure on the mat during sleep and we use convolution neural network (CNN) to analyze collected data and recognize different sleeping postures. The system is capable of recognizing the four major postures—face-up, face-down, right lateral, and left lateral. A real-time feedback mechanism is also provided through an accompanying smartphone application for keeping a diary of the posture and send alert to the user in case there is a danger of falling from bed. It also produces synopses of postures and activities over a given duration of time. Finally, we conducted experiments to evaluate the accuracy of the prototype, and the proposed system achieved a classification accuracy of around 90%.

Design of A NEMS Cantilever Sensor for Explosive Detection

The particular recognition of explosives in countering fear monger dangers and follow explosives has turned into an appallingly progressed and expensive exertion. This happens because of different impacts, similar to the extensive broad assortment of materials which will be used as explosives, the deficiency of basically perceivable marks, and the monstrous assortment of roads by these weapons might be sent and consequently there will be absence of shoddy sensors with high sensitivity and low vapor analyte property. High sensitivity and property joined with the power, to cut down the orchestrating cost of sensors. Misuse age is basic in winning the war an explosives based demonstration of psychological warfare. Nanosensors can possibly satisfy every one of the necessities of an effective stage for the follow identification explosives. Enhance the sensitivity and selectivity of NEMS cantilever for piezo resistive material in Humidity conditions and manufacture Rectangular Shape Omni directional NEMS cantilever cheap IC and Characteristic chip with Real time reenactment utilizing omnicant.

FLEXIBLE ROBOTIC ELECTRONIC SKIN WITH HIGH SENSITIVITY SENSOR ARRAYS

In this paper, we propose a flexible robotic electronic skin (e-skin) with high sensitivity sensor arrays. The sensor arrays are designed and fabricated on thin flexible silicone film. It uses piezo-resistive material Samarian Monosulphide and graphite rods for interconnection between the layers. Along with the pressure sensing capability of SmS, temperature and humidity sensors are also integrated in the silicone layers along with photovoltaic thin layer cells that provide energy independence to the module. The data procured from the e-skin is transferred to the analog to digital converter unit and further, to the PC through USB interface for analysis.