Hafnium oxide (Hf02) based ferroelectrics have gained significant attention as non-volatile ferroelectric random-access memories (FeRAM) due to its scalability and integrability in complementary metal oxide semiconductor (CMOS). To enable large scale FeRAM with CMOS integration, a large polarization at low temperature processing and low electric field is essential. Various reports show high polarization at the cost of high processing temperature and higher electric fields. In this paper, we report a low field (3.14 MV / cm) and large polarization (2Pr ~72 $\mu \mathrm{C}/\text{cm}2)$ in atomic layer deposition (ALD) grown (at 200 o C) ferroelectric Hf0.5Zr0.502 (HZO) thin film at lower post metallization annealing at 600o C. We discuss the impact of the source of oxygen from H20 precursor in ALD process in creating O-vacancies during deposition with X-Ray diffraction analysis (XRD). Then we discuss the role of low thermal expansion coefficient of tungsten (W) as top and bottom electrode to induce in -plane tensile strain during annealing to enhance orthorhombic phase (o-phase) - essential to get high polarization. A high dielectric constant $\varepsilon \mathrm{r}\sim 42$ at −3V shows the improved quality of the ferroelectric film. Finally, we discuss the impact of electric field and frequency on the polarization.
Out of various modeling approaches for high electron mobility transistors (HEMT), the physics-oriented models are the most advantageous ones considering accuracy, prediction beyond measured data and scalability, etc. In this regard, we have proposed a simplified compact DC model which captures current-voltage (I-V) and capacitance-voltage (C-V) characteristics of (AlxGa1-x)2O3/Ga2O3 HEMT, the most recent power HEMTs. We have also proposed an RF model that captures unity current gain cutoff frequency and power gain ranging from low frequencies up to MHz of range.
The new generation SOCs requires a thermal solution to maintain temperatures within operating limits. Design and optimization of suitable thermal solution and upfront thermal analysis are key to design thermal friendly design based on all critical workloads in very fast manner. There are two common methods of predicting SOC thermal performance: computational simulation and experimental measurement. These two approaches include complicated operations and experimental setup. Thus, it is quite difficult to build computational simulations that fully capture the complex logical relationships between the properties of a material, geometry, power and their related factors, and some of these relationships may even be unknown. Therefore, there is an urgent need to develop intelligent and high-performance prediction models that can correctly predict the SOC thermal solution at a low temporal and computational cost. In this work, a new methodology for optimization of SOC Thermal Performance process is developed, using Regression-Based Reduced-Order Modelling Techniques. This methodology can be applied to any type of platform configurations to reduce computation effort, results reduction in overall design time and cost. Also, this approach (Implemented through software applications-tool) can be deployed internally as well as customer experience thermal tool, allows customers to predict the optimum thermal solutions tailored to their project requirements. This tool is developed using blending different regression models for better prediction of SOC thermal performance, it comprises different types of heat sink models (extruded, folded fin, heat pipe embedded, and vapor chamber) allows user to select right tradeoff between performance and cost. In this work, a new methodology to estimate thermal performance analysis is demonstrated for complex inhouse SOC with about 100X faster and with about 95% accurate reference to industry solutions available. In this analysis all data are normalized to ensure sensitive design details are protected
Even though multiple reports are available on photodetectors, the problem that still remain unaddressed is the low photoresponsivity while trying to increase the range of detection. In this work, broadband (UV-visible) photodetector was demonstrated by integrating zero-dimensional (0D) WS2-QDs on two-dimensional (2D) monolayer MoS2. WS2-QDs are sensitive to UV light, and MoS2 is sensitive to visible light. The maximum responsivity of the fabricated WS2-QDs/MoS2 device was found to be ~ 392 A/W. In this work, not only the photodetection range but also photoresponsivity is improved, which is a major step in the design of next-generation 2D materials based optoelectronics.
Molecular memristor comprising a Ru-coordinated bis ligated complex has been designed. Depending on different operating conditions such as Voltage and temperature, its current-voltage characteristics changes gradually. Whereas the voltage helps to achieve different molecular conductance states, temperature variation from 300K to 4K can control various supramolecular dynamical components. Imposing different operating conditions can lead to practically all the possible memristive functionalities starting from bipolar, unipolar, volatile, non-volatile, ternary, and binary responses with gradual analog and sharp digital transitions as well as diode characteristics. A mathematical model comprising of multiple parameter design space has been constructed to model all these characteristics.
