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In this work, a high performance GaN-on-Si quasi vertical PiN diode was demonstrated by the combination of a beveled sidewall and self-aligned fluorine plasma treatment. The didoes achieved a remarkable breakdown voltage ($\text{V}_{\text {BR}}{)}$ of 930 V and an ultra-low reverse leakage current. Meanwhile the didoes showed a low specific on-resistance ($\text{R}_{ \mathrm{\scriptscriptstyle ON},\textit {sp}}$) of 0.43 $\text{m}\Omega \cdot $ cm2, a high on/off current ratio ($\text{I}_{ \mathrm{\scriptscriptstyle ON}}/\text{I}_{ \mathrm{\scriptscriptstyle OFF}}$) of $10^{{11}}$ , and an excellent Baliga’s figure of merit (BFOM) of 2.01 GW/cm2. The measurement results of X-ray spectroscopy (XPS) and Kelvin Probe Force Microscopy (KPFM) proved the presence of F ions and the decrease of surface potential, which reduced the electric field peak and suppressed the leakage current. These results show a great potential of GaN on Si PiN diode for power applications. [ABSTRACT FROM AUTHOR]

To realize the complementary circuit on the GaN-on-Si platform, an investigation of p-channel heterostructure field-effect transistors (p-HFETs) is necessary. In this study, an analytical model for the estimation of the threshold voltage (${V}_{\text {TH}}$) for GaN-based p-HFETs was developed. In this model, the impact of polarization charges at different interfaces, the influence of interface charges at oxide/GaN interface, as well as the out-diffusion effect of Mg dopant in the p-GaN layer were all taken into consideration for systematic exploration. Herein, GaN-based p-HFETs were fabricated to verify the relationship between the ${V}_{\text {TH}}$ and the thickness of the GaN channel layer by using the proposed model. The ${V}_{\text {TH}}$ model was further confirmed through TCAD simulations. The influences of the thickness of oxide layer, Mg doping concentration in p-GaN layer, and the Al mole fraction of AlxGa $_{{1}-{x}}\text{N}$ layer on ${V}_{\text {TH}}$ were also discussed in detail. The model serves as more accurate guidance for the optimization of such p-HFETs design and complementary circuits. [ABSTRACT FROM AUTHOR]

The gate and drain bias dependence of hot electron-induced degradation in GaN-based metal–insulator–semiconductor high electron mobility transistors (MIS-HEMTs) was investigated in this work. Devices exhibit an abnormal increase in peak transconductance (${G}_{m}$ ,max) during hot carrier stress (HCS) and a partially quick recovery of that after removing the electrical stress. A physical model is proposed to explain the abnormal electrical characteristics caused by HCS. By using density functional theory (DFT), we calculated the energy for electrons to dehydrogenate preexisting [NGaH3]−1 complexes in GaN layer during stress. The dehydrogenation of defects affects the Gm,max of devices. Meanwhile, the neutralization of donor traps in AlGaN barrier layer also plays a significant role in the increase of Gm,max and the detrapping effect of electrons from these traps after removing the electrical stress accounts for the partially quick recovery of ${G}_{m, \text{max}}$. [ABSTRACT FROM AUTHOR]

Carbon nanotube (CNT) film has great potential in the application as a cold cathode in vacuum power electron devices. Pulse field emission of CNT film is investigated to achieve large current and current density. A maximum current of 16 mA is obtained from a 0.02-cm^2 CNT film with a current density of 800 mA/cm^2. The pulsewidth and area of CNT film have strong effects on field emission characteristics of CNT film, such as total current, current density, and current stability. The reason for this is discussed in detail. The results are useful for the design of the large current and current density CNT cold cathodes. [ABSTRACT FROM AUTHOR]

This study proposed a novel frequency-specific (FS) algorithm framework for enhancing control state detection using short data length toward high-performance asynchronous steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCI). The FS framework sequentially incorporated task-related component analysis (TRCA)-based SSVEP identification and a classifier bank containing multiple FS control state detection classifiers. For an input EEG epoch, the FS framework first identified its potential SSVEP frequency using the TRCA-based method and then recognized its control state using one of the classifiers trained on the features specifically related to the identified frequency. A frequency-unified (FU) framework that conducted control state detection using a unified classifier trained on features related to all candidate frequencies was proposed to compare with the FS framework. Offline evaluation using data lengths within 1 s found that the FS framework achieved excellent performance and significantly outperformed the FU framework. 14-target FS and FU asynchronous systems were separately constructed by incorporating a simple dynamic stopping strategy and validated using a cue-guided selection task in an online experiment. Using averaged data length of 591.63±5.65 ms, the online FS system significantly outperformed the FU system and achieved an information transfer rate, true positive rate, false positive rate, and balanced accuracy of 124.95±12.35 bits/min, 93.16±4.4%, 5.21±5.85%, and 92.89±4.02%, respectively. The FS system was also of higher reliability by accepting more correctly identified SSVEP trials and rejecting more wrongly identified ones. These results suggest that the FS framework has great potential to enhance the control state detection for high-speed asynchronous SSVEP-BCIs.