Search for: All records

Ultra-wide bandgap (UWBG) Al0.65Ga0.35N channel high electron mobility transistors (HEMTs) were deposited using a close-coupled showerhead metal-organic chemical vapor deposition reactor on AlN-on-sapphire templates to investigate the effect of transport properties of the two-dimensional electron gas (2DEG) on the epitaxial structure design. The impact of various scattering phenomena on AlGaN channel HEMTs was analyzed with respect to the channel, buffer, and AlN interlayer design, revealing that the alloy disorder and ionized impurity scattering mechanisms were predominant, limiting the mobility of 2DEG up to 180 cm2/Vs for a sheet charge density of 1.1 × 1013 cm−2. A surface roughness of <1 nm (2 μm × 2 μm atomic force microscopy scan) was achieved for the epitaxial structures demonstrating superior crystalline quality. The fabricated HEMT device showed state-of-the-art contact resistivity (ρc = 8.35 × 10^−6 Ω · cm2), low leakage current (<10^−6 A/mm), high ION/IOFF ratio (>10^5), a breakdown voltage of 2.55 kV, and a Baliga's figure of merit of 260 MW/cm2. This study demonstrates the optimization of the structural design of UWBG AlGaN channel HEMTs and its effect on transport properties to obtain state-of-the-art device performance. 

Abstract 3 kV breakdown voltage was demonstrated in monolithic bidirectional Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs) having potential applications in 1200 V or 1700 V class power converters. The on-resistance of the fabricated transistors was ∼20 Ω.mm (∼11 mΩ.cm²). The breakdown voltage was optimized with two field plates on either side of the transistor. Shorter first field plate lengths (≤2 μm) resulted in higher breakdown voltage and the possible reason was discussed. The transistors had a steep subthreshold swing of 92 mV dec⁻¹. The fabricated transistor was benchmarked against the state-of-the-art monolithic bidirectional GaN HEMTs in the performance matrices of breakdown voltage—on resistance, that showed crucial progress. 

Abstract High voltage (∼2 kV) Al_0.64Ga_0.36N-channel high electron mobility transistors were fabricated with an on-resistance of ∼75 Ω. mm (∼21 mΩ. cm²). Two field plates of variable dimensions were utilized to optimize the breakdown voltage. The breakdown voltage reached >3 kV (tool limit) before passivation however it reduced to ∼2 kV after Si₃N₄surface passivation and field plate deposition. The breakdown voltage and on-resistance demonstrated a strong linear correlation in a scattered plot of ∼50 measured transistors. The fabricated transistors were electrically characterized and benchmarked against the state-of-the-art high-voltage (> 1 kV) Al-rich (>40%) AlGaN-channel transistors in breakdown voltage and on-resistance, indicating significant progress. 

Thin Si-doped Al-rich (xAl > 0.85) regrown Al(Ga)N layers were deposited on AlN on sapphire template using metal-organic chemical vapor deposition (MOCVD) techniques. The optimization of the deposition conditions, such as temperature (1150 °C), V/III ratio (750), deposition rate (0.7 Å/s), and Si concentration (6 × 10^19/cm3), resulted in a high charge carrier concentration (> 10^15 cm−3) in the Si-doped Al-rich Al(Ga)N films. A pulsed deposition condition with pulsed triethylgallium and a continuous flow of trimethylaluminum and ammonia was employed to achieve a controllable Al composition xAl > 0.95 and to prevent unintended Ga incorporation in the AlGaN material deposited using the close-coupled showerhead reactor. Also, the effect of unintentional Si incorporation on free charge carrier concentration at the regrowth interface was studied by varying the thickness of the regrown Al(Ga)N layer from 65 to < 300 nm. A maximum charge carrier concentration of 4.8 × 10^16 and 7.5 × 10^15/cm3 was achieved for Al0.97Ga0.03N and AlN films with thickness <300 nm compared to previously reported n-Al(Ga)N films with thickness ≥400 nm deposited using MOCVD technique. 

We present an online post-hoc calibration method, called Online Platt Scaling (OPS), which combines the Platt scaling technique with online logistic regression. We demonstrate that OPS smoothly adapts between i.i.d. and non-i.i.d. settings with distribution drift. Further, in scenarios where the best Platt scaling model is itself miscalibrated, we enhance OPS by incorporating a recently developed technique called calibeating to make it more robust. Theoretically, our resulting OPS+calibeating method is guaranteed to be calibrated for adversarial outcome sequences. Empirically, it is effective on a range of synthetic and real-world datasets, with and without distribution drifts, achieving superior performance without hyperparameter tuning. Finally, we extend all OPS ideas to the beta scaling method. 

We study the problem of making calibrated probabilistic forecasts for a binary sequence generated by an adversarial nature. Following the seminal paper of Foster and Vohra (1998), nature is often modeled as an adaptive adversary who sees all activity of the forecaster except the randomization that the forecaster may deploy. A number of papers have proposed randomized forecasting strategies that achieve an ϵ-calibration error rate of O(1/sqrt T), which we prove is tight in general. On the other hand, it is well known that it is not possible to be calibrated without randomization, or if nature also sees the forecaster's randomization; in both cases the calibration error could be Ω(1). Inspired by the equally seminal works on the "power of two choices" and imprecise probability theory, we study a small variant of the standard online calibration problem. The adversary gives the forecaster the option of making two nearby probabilistic forecasts, or equivalently an interval forecast of small width, and the endpoint closest to the revealed outcome is used to judge calibration. This power of two choices, or imprecise forecast, accords the forecaster with significant power -- we show that a faster ϵ-calibration rate of O(1/T) can be achieved even without deploying any randomization.