We demonstrate record performance in a novel normally-off GaN vertical transistor with submicron finshaped channels. This vertical fin transistor only needs nGaN layers, with no requirement for epitaxial regrowth or pGaN layers. A specific on-resistance of 0.2 mΩ·cm2 and a breakdown voltage over 1200 V have been demonstrated with extremely high ON current (over 25 kA/cm2) and low OFF current at 1200 V (below 10-4 A/cm2), rendering an excellent Baliga’s figure of merit up to 7.2 GW/cm2. A threshold voltage of 1 V was achieved and was stable up to 150 oC.Large devices with high current up to 10 A and breakdown voltage over 800 V were also demonstrated. These results show the great potential of GaN vertical fin transistors for high-current and high-voltage power applications.

Multiplexing is an important strategy in multichannel acquisition systems. The per-channel antialiasing filters needed in the traditional multiplexing architecture limit its scalability for applications requiring high channel density, high channel count, and low noise. A particularly challenging example is multielectrode arrays for recording from neural systems. We show that conventional approaches must tradeoff recording density and noise performance, at a scale far from the ideal goal of one-to-one mapping between neurons and sensors. We present a multiplexing architecture without per-channel antialiasing filters. The sparsely sampled data are recovered through a compressed sensing strategy, involving statistical reconstruction and removal of the undersampled thermal noise. In doing so, we replace large analog components with digital signal processing blocks, which are much more amenable to scaled CMOS implementation. The resulting statistically reconstructed multiplexing architecture recovers input signals at significantly improved signal-to-noise ratios when compared to conventional multiplexing with antialiasing filters at the same per-channel area. We implement the new architecture in a 65 536-channel neural recording system and show that it is able to recover signals with performance comparable to conventional high-performance, single-channel systems, despite a more than four-orders-of-magnitude increase in channel density.

Lipid bilayers provide many benefits for ion channel recordings, such as control of membrane composition and transport molecules. However, they suffer from high membrane capacitance limiting the bandwidth and impeding analysis of fast gating. This can be overcome by fitting the deviations of the open-channel noise from the baseline noise by extended beta distributions. We demonstrate this analysis step-by-step by applying it to the example of viral K⁺ channels (Kcv), from the choice of the gating model through the fitting process, validation of the results, and what kinds of results can be obtained. These voltage sensor-less channels show profoundly voltage-dependent gating with dwell times in the closed state of about 50 μs. Mutations assign it to the selectivity filter.

In traditional electrophysiology, spatially inefficient electronics and the need for tissue-toelectrode proximity defy non-invasive interfaces at scales of more than a thousand low noise, simultaneously recording channels. Using compressed sensing concepts and silicon complementary metal-oxide-semiconductors (CMOS), we demonstrate a platform with 65,536 simultaneously recording and stimulating electrodes in which the per-electrode electronics consume an area of 25.5 μm by 25.5 μm. Application of this platform to mouse retinal studies is achieved with a high-performance processing pipeline with a 1 GB/s data rate. The platform records from 65,536 electrodes concurrently with a ~10 µV r.m.s. noise;senses spikes from more than 34,000 electrodes when recording across the entire retina; automatically sorts and classifies greater than 1700 neurons following visual stimulation; and stimulates individual neurons using any number of the 65,536 electrodes while observing spikes over the entire retina. The approaches developed here are applicable to other electrophysiological systems and electrode configurations.

Phased-array antennas that conform to body surfaces efficiently transfer electromagnetic energy to miniaturized semiconductor devices implanted in pigs.