Vertical GaN-on-GaN Schottky Diodes as α-Particle Radiation Sensors.

Among the different semiconductors, GaN provides advantages over Si, SiC and GaAs in radiation hardness, resulting in researchers exploring the development of GaN-based radiation sensors to be used in particle physics, astronomic and nuclear science applications. Several reports have demonstrated the usefulness of GaN as an α-particle detector. Work in developing GaN-based radiation sensors are still evolving and GaN sensors have successfully detected α-particles, neutrons, ultraviolet rays, x-rays, electrons and γ-rays. This review elaborates on the design of a good radiation detector along with the state-of-the-art α-particle detectors using GaN. Successful improvement in the growth of GaN drift layers (DL) with 2 order of magnitude lower in charge carrier density (CCD) (7.6 × 1014/cm3) on low threading dislocation density (3.1 × 106/cm2) hydride vapor phase epitaxy (HVPE) grown free-standing GaN substrate, which helped ~3 orders of magnitude lower reverse leakage current (IR) with 3-times increase of reverse breakdown voltages. The highest reverse breakdown voltage of -2400 V was also realized from Schottky barrier diodes (SBDs) on a free-standing GaN substrate with 30 µm DL. The formation of thick depletion width (DW) with low CCD resulted in improving high-energy (5.48 MeV) α-particle detection with the charge collection efficiency (CCE) of 62% even at lower bias voltages (-20 V). The detectors also detected 5.48 MeV α-particle with CCE of 100% from SBDs with 30-µm DL at -750 V.

Flexible Ionic-Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain-Inspired Neuromorphic Computing.

Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm2 V-1 s-1 with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time-dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation transparent neural circuits.