David Cheney

Electric-Field-Driven Degradation in off-State Step-Stressed AlGaN/GaN High-Electron Mobility Transistors

The critical degradation voltage of AlGaN/GaN high-electron mobility transistors during off-state electrical stress was determined as a function of Ni/Au gate dimensions (0.1-0.17 μm), drain bias voltage, and source/drain-gate contact distance. Devices with different gate lengths and gate-drain distances were found to exhibit the onset of degradation at different source-drain biases but similar electric field strengths, showing that the degradation mechanism is primarily field driven. The degradation field was calculated to be ~ 1.8 MV/cm by Automatically Tuned Linear Algebra Software simulations. Transmission electron microscopy imaging showed creation of defects under the gate after dc stress.

Reliability studies of AlGaN/GaN high electron mobility transistors

AlGaN/GaN high electron mobility transistors are gaining commercial acceptance for use in high power and high frequency applications, but the degradation mechanisms that drive failure in the field are not completely understood. Since some of these mechanisms are current or field driven, reliability studies must go beyond the typical Arrhenius-accelerated life tests. In this paper, we summarize recent work on electric field or current driven degradation in devices with different gate metallization, device dimensions, electric field mitigation techniques (such as source field plates) and the effect of device fabrication processes for both dc and RF stress conditions.

Degradation Mechanisms for GaN and GaAs High Speed Transistors

We present a review of reliability issues in AlGaN/GaN and AlGaAs/GaAs high electron mobility transistors (HEMTs) as well as Heterojunction Bipolar Transistors (HBTs) in the AlGaAs/GaAs materials systems. Because of the complex nature and multi-faceted operation modes of these devices, reliability studies must go beyond the typical Arrhenius accelerated life tests. We review the electric field driven degradation in devices with different gate metallization, device dimensions, electric field mitigation techniques (such as source field plate), and the effect of device fabrication processes for both DC and RF stress conditions. We summarize the degradation mechanisms that limit the lifetime of these devices. A variety of contact and surface degradation mechanisms have been reported, but differ in the two device technologies: For HEMTs, the layers are thin and relatively lightly doped compared to HBT structures and there is a metal Schottky gate that is directly on the semiconductor. By contrast, the HBT relies on pn junctions for current modulation and has only Ohmic contacts. This leads to different degradation mechanisms for the two types of devices.

Wireless, In Vivo Neural Recording using a Custom Integrated Bioamplifier and the Pico System

This paper describes a wireless system for sampling multiple channels of neural activity based on a low-power, custom 80dB-gain integrated bioamplifier, Texas Instruments MSP430 microprocessors, and Nordic Semiconductors ultra low power, high bandwidth RF transmitter/receivers. The systems features are presented as well as results of spike potentials from a live subject.

Wireless Transmission of Neural Signals Using Entropy and Mutual Information Compression

Two of the most critical tasks when designing a portable wireless neural recording system are to limit power consumption and to efficiently use the limited bandwidth. It is known that for most wireless devices the majority of power is consumed by the wireless transmitter and it often represents the bottleneck of the overall design. This paper compares two compression techniques that take advantage of the sparseness of the neural spikes in neural recordings using an information theoretic formalism to enhance the well-established vector quantization (VQ) algorithm. The two discriminative VQ algorithms are applied to neuronal recordings proving their ability to accurately reconstruct action potential (AP) regions of the neuronal signal while compressing background activity without using thresholds. The two operational modes presented offer distinct characteristics to lossy compression. The first approach requires no preprocessing or prior knowledge of the signal while the second requires a training set of spikes to obtain AP templates. The compression algorithms are implemented on an on-board digital signal processor (DSP) and results show that power consumption is decreased while the bandwidth is more efficiently utilized. The compression algorithms have been tested in real time on a hardware platform (PICO DSP ) enhanced with the DSP which runs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range from 70:1 and 40:1 depending on the signal to noise ratio (SNR) of the input signal. The spike sorting accuracy in the reconstructed data is 95% compatible to the original neural data.

Neural signal sampling via the low power wireless pico system.

This paper presents a powerful new low power wireless system for sampling multiple channels of neural activity based on Texas Instruments MSP430 microprocessors and Nordic Semiconductors ultra low power high bandwidth RF transmitters and receivers. The systems development process, component selection, features and test methodology are presented

Comparison of passivation layers for AlGaN/GaN high electron mobility transistors

AlGaN/GaN high electron mobility transistors require surface passivation layers to reduce the effects of surface traps between the gate and drain contacts. These traps lead to the creation of a virtual gate and the associated collapse of drain current under rf conditions. The authors have investigated three different materials for passivation layers, namely thin (7.5 nm) Al2O3 and HfO2 deposited with an atomic layer deposition system and conventional, thick (200 nm) plasma enhanced chemically vapor deposited SiNX. The latter is found to be the most effective in reducing drain current loss during gate lag measurements in both single and double pulse mode, but also reduces fT and fMAX through additional parasitic capacitance.

Investigation of traps in AlGaN/GaN high electron mobility transistors by sub-bandgap optical pumping

Sub-bandgap optical pumping with wavelengths of 671, 532, or 447 nm was employed to study traps in AlGaN/GaN high electron mobility transistors. The trap energies were determined from the Arrhenius plots of transient drain current at different temperatures. Prominent states were located around 0.7 eV below the conduction band, and these are commonly reported to be nonradiative traps due to defects trapped on dislocations or possibly Ga interstitials. In addition, traps located at 1.9 and 2.35 eV below the conduction band were found, which have been reported as NGa antisite and VGa–ON complexes, respectively. The postillumination drain current decays were analyzed with a persistent photoconductivity method, and time constants were extracted and associated with the recapture process in the AlGaN barrier and GaN channel layers.

Compression of neural signals using discriminative coding for wireless applications

One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.

Identification of trap locations in AlGaN/GaN high electron mobility transistors by varying photon flux during sub-bandgap optical pumping

By varying the photon flux during sub-bandgap optical pumping, the locations of traps associated with sub-bandgap laser pumping in AlGaN/GaN high electron mobility transistors (HEMTs) were identified. Fixed photon flux of sub-bandgap optical pumping was previously employed to determine the activation energies of traps in AlGaN/GaN HEMT; traps with activation energies of 0.73 eV, both 0.73 and 1.91 eV or all three trap states detected for the 671, 532, or 477 nm laser illumination, respectively. However, by illuminating the HEMTs with lower photon fluxes from 532 or 447 nm lasers, the traps with 0.73 eV were absent, and only the traps associated with higher activation energies were activated by the laser light. This indicated that the traps related to the activation energies of 1.91 and 2.35 eV are likely located at the surface of the HEMTs. Photon flux dependent gate-lag measurements were also conducted. Laser illumination of 671 nm did not affect the drain current during the gate lag measurement, implyin...