ABSTRACT
Corona Virus is spreading at an alarming rate in community causing respiratory diseases like SARS and MERS, which has laid down Government agencies and healthcare organizations to adopt and recommend various strategies in order to cease the spread of corona virus. Till the dawn of Vaccine, only available cost-effective preventive aid is the use of face mask. Since the outbreak of covid-19, demand for the face mask has been increased tremendously which has led to the shortage of face mask. Various masks are available in the market, but reuse and decontamination of reusable face mask has become the topic of concern. Commonly available masks in market are N-95, Medical/Surgical Mask and cloth masks. N-95 and Respirators should be reserved for frontline primary Healthcare professionals which are involved in High-risk aerosol generating procedures, while Surgical and medical mask should be used by secondary healthcare professionals and cloth masks by General public.
ABSTRACT
In the present investigation, we have fabricated copper oxide (CuO) thin film memristor by employing a hydrothermal method for neuromorphic application. The X-ray diffraction pattern confirms the films are polycrystalline in nature with the monoclinic crystal structure. The developed devices show analog memory and synaptic property similar to biological neuron. The size dependent synaptic behavior is investigated for as-prepared and annealed CuO memristor. The results suggested that the magnitude of synaptic weights and resistive switching voltages are dependent on the thickness of the active layer. Synaptic weights are improved in the case of the as-prepared device whereas they are inferior for annealed CuO memristor. The rectifying property similar to a biological neuron is observed only for the as-prepared device, which suggested that as-prepared devices have better computational and learning capabilities than annealed CuO memristor. Moreover, the retention loss of the CuO memristor is in good agreement with the forgetting curve of human memory. The results suggested that hydrothermally grown CuO thin film memristor is a potential candidate for the neuromorphic device development.
ABSTRACT
We report simulation of nanostructured memristor device using piecewise linear and nonlinear window functions for RRAM and neuromorphic applications. The linear drift model of memristor has been exploited for the simulation purpose with the linear and non-linear window function as the mathematical and scripting basis. The results evidences that the piecewise linear window function can aptly simulate the memristor characteristics pertaining to RRAM application. However, the nonlinear window function could exhibit the nonlinear phenomenon in simulation only at the lower magnitude of control parameter. This has motivated us to propose a new nonlinear window function for emulating the simulation model of the memristor. Interestingly, the proposed window function is scalable up to f(x) = 1 and exhibits the nonlinear behavior at higher magnitude of control parameter. Moreover, the simulation results of proposed nonlinear window function are encouraging and reveals the smooth nonlinear change from LRS to HRS and vice versa and therefore useful for the neuromorphic applications.
