A thermal model for static current characteristics of AlGaN/ GaN high electron mobility transistors including selfheating effect

A thermal model of AlGaN / GaN high electron mobility transistors ͑HEMTs͒ has been developed based on a quasi-two-dimensional numerical solution of Schrödinger's equation coupled with Poisson's equation. The static current characteristics of HEMT devices have been obtained with the consideration of the self-heating effect on related parameters including polarization, electron mobility, saturation velocity, thermal conductivity, drain and source resistance, and conduction-band discontinuity at the interface between AlGaN and GaN. The simulation results agree well with our experimental data. It has also been demonstrated that the reduction of the saturation drain current at high power dissipation is primarily due to the decrease of electron mobility in the channel. The proposed model is valuable for predicting and evaluating the performance of different device structures and packages for various applications

The Study of Deep Level Traps and Their Influence on Current Characteristics of InP/InGaAs Heterostructures

The damage mechanism of proton irradiation in InP/InGaAs heterostructures was studied. The deep level traps were investigated in detail by deep level transient spectroscopy (DLTS), capacitance–voltage (C–V) measurements and SRIM (the stopping and range of ions in matter, Monte Carlo code) simulation for non-irradiated and 3 MeV proton-irradiated samples at a fluence of 5 × 1012 p/cm2. Compared with non-irradiated samples, a new electron trap at EC-0.37 eV was measured by DLTS in post-irradiated samples and was found to be closer to the center of the forbidden band. The trap concentration in bulk, the interface trap charge density and the electron capture cross-section were 4 × 1015 cm−3, 1.8 × 1012 cm−2, and 9.61 × 10−15 cm2, respectively. The deep level trap, acting as a recombination center, resulted in a large recombination current at a lower forward bias and made the forward current increase in InP/InGaAs heterostructures for post-irradiated samples. When the deep level trap parameters were added into the technology computer-aided design (TCAD) simulation tool, the simulation results matched the current–voltage measurements data well, which verifies the validity of the damage mechanism of proton irradiation

Raman Study of Strain Relaxation from Grain Boundaries in Epitaxial Graphene Grown by Chemical Vapor Deposition on SiC

Strains in graphene play a significant role in graphene-based electronics, but many aspects of the grain boundary effects on strained graphene remain unclear. Here, the relationship between grain boundary and strain property of graphene grown by chemical vapor deposition (CVD) on the C-face of SiC substrate has been investigated by Raman spectroscopy. It is shown that abundant boundary-like defects exist in the graphene film and the blue-shifted 2D-band frequency, which results from compressive strain in graphene film, shifts downward linearly as 1/La increases. Strain relaxation caused by grain boundary diffusion is considered to be the reason and the mechanism is analyzed in detail

Stress-induced charge trapping and electrical properties of atomic-layer-deposited HfAlO/Ga2O3 metal-oxide-semiconductor capacitors

Electrical properties and trapping characteristics of an atomic layer deposited Al-rich HfAlO/beta-Ga2O3 capacitor were evaluated via constant-voltage stress (CVS), capacitance-voltage (C-V), and current-voltage (I-V) measurements. The magnitude of the stress-induced charge trapping increases with increasing voltage and time. The effective charges (N-eff) including the border traps located in near-interface oxide, interface traps (D-it) of HfAlO/beta-Ga2O3 interface, and fixed charges contribute significantly to the observed charge trapping, and it is found that interface traps contribute more under a large stress bias, compared with border traps. In addition, the effective charge density is increased with stress time, implying that the contribution of negative sheet charges during the CVS process might not be negligible. Measurements of oxide permittivity (10.74), interface state density (D-it similar to 1 x 10(12) eV(-1) cm(-2)), and gate leakage current (1.18 x 10( -5) A cm(-2) at +10 V) have been extracted, suggesting the great electrical properties of Al-rich HfAlO/beta-Ga203 MOSCAP. According to the above analysis, Al-rich HfAlO is an attractive candidate for normally off Ga2O3 transistors.Funding Agencies|National Natural Science Foundation of China [51742196, 5161101495, 61704125]; Fundamental Research Funds for the Central Universities [XJS17059, JBX171105]; Swedish Foundation for International Cooperation in Research and Higher Education (STINT) [CH2016-6722]; Key Laboratory of Microelectronic Devices and Integrated Technology, Chinese Academy of Sciences</p

Effects of 5 MeV Proton Irradiation on Nitrided SiO2/4H-SiC MOS Capacitors and the Related Mechanisms

In this paper the effects of 5 MeV proton irradiation on nitrided SiO2/4H-SiC metal&ndash;oxide&ndash;semiconductor (MOS) capacitors are studied in detail and the related mechanisms are revealed. The density of interface states (Dit) is increased with the irradiation doses, and the annealing response suggests that the worse of Dit is mainly caused by displacement effect of proton irradiation. However, the X-rays photoelectron spectroscopy (XPS) measurement shows that the quantity proportion of breaking of Si&equiv;N induced by displacement is only 8%, which means that the numbers of near interface electron traps (NIETs) and near interface hole traps (NIHTs) are not significantly changed by the displacement effect. The measurements of bidirectional high frequency (HF) C-V characteristics and positive bias stress stability show that the number of un-trapped NIETs and oxide electron traps decreased with increasing irradiation doses because they are filled by electrons resulted from the ionization effect of proton irradiation, benefiting to the field effective mobility (&mu;FE) and threshold voltage stability of metal&ndash;oxide&ndash;semiconductor field-effect transistors (MOSFETs). The obviously negative shift of flat-band voltage (VFB) resulted from the dominant NIHTs induced by nitrogen passivation capture more holes produced by ionization effect, which has been revealed by the experimental samples with different nitrogen content under same irradiation dose

Development and Comparison of Two Novel Hybrid Neural Network Models for Hourly Solar Radiation Prediction

There are a lot of developing countries with inadequate meteorological stations to measure solar radiation. This has been a major drawback for solar power applications in these countries as the performance of the solar-powered system cannot be accurately forecasted. In this study, two novel hybrid neural networks namely; convolutional neural network/artificial neural network (CNN-ANN) and convolutional neural network/long short-term memory/artificial neural network (CNN-LSTM-ANN), have been developed for hourly global solar radiation prediction. ANN models are also developed and the performance of the hybrid neural network models is compared with it. This study contributes to the search for more accurate solar radiation estimation methods. The hybrid neural network models are trained/tested with data from ten different countries across Africa. Results from this study indicate that the performance of all the hybrid models developed in this study is superior to what has been presented in existing literature with their r values ranging from 0.9662 to 0.9930. CNN-ANN model is the best for solar radiation forecasting in Southern, Central, and West Africa. CNN-LSTM-ANN is better for East Africa while both CNN-ANN and CNN-LSTM-ANN are suitable for North Africa. CNN-ANN application for solar radiation prediction in Chad had the overall best performance with an r-value, MAE, RMSE, and MAPE of 0.9930, 15.70 W/m2, 46.84 W/m2, and 4.98% respectively. The integration of CNN and LSTM algorithms with an ANN model enhanced long-term computational dependency and reduce error terms for the model