arXiv subjects

Berardi Sensale Rodriguez

Publications and source records attributed to Berardi Sensale Rodriguez.

3 recordsLinked to original sources

arXiv2025

Degradation of 2.4-kV $Ga_{2}O_{3}$ Schottky Barrier Diode at High Temperatures up to 500 °C

Ga2O3 Schottky barrier diodes featuring a field plate and a composite SiO2/SiNx dielectric layer beneath the field plate were fabricated, achieving a breakdown voltage of 2.4 kV at room temperature. Electrical performance and degradation were analyzed via I-V and C-V measurements from 25 °C to 500 °C, revealing temperature-dependent transport, interface stability, and device stability. Upon returning to room temperature, the diodes exhibited nearly unchanged forward characteristics, while the breakdown voltage declined significantly from 2.4 kV to 700 V. This behavior indicates a temperature-induced reduction in the barrier height. Detailed analysis revealed that variable range hopping (VRH) dominated the leakage mechanism at moderate temperatures, while thermal emission (TE) became increasingly significant at temperatures exceeding 400 °C.

cond-mat.mtrl-sci↗

arXiv2021

Real-time Multi-Task Diffractive Deep Neural Networks via Hardware-Software Co-design

Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing efforts on optical neural networks and optical computing based DNNs hardware, which bring significant advantages for deep learning systems in terms of their power efficiency, parallelism and computational speed. Among them, free-space diffractive deep neural networks (D$^2$NNs) based on the light diffraction, feature millions of neurons in each layer interconnected with neurons in neighboring layers. However, due to the challenge of implementing reconfigurability, deploying different DNNs algorithms requires re-building and duplicating the physical diffractive systems, which significantly degrades the hardware efficiency in practical application scenarios. Thus, this work proposes a novel hardware-software co-design method that enables robust and noise-resilient Multi-task Learning in D$^2$NNs. Our experimental results demonstrate significant improvements in versatility and hardware efficiency, and also demonstrate the robustness of proposed multi-task D$^2$NN architecture under wide noise ranges of all system components. In addition, we propose a domain-specific regularization algorithm for training the proposed multi-task architecture, which can be used to flexibly adjust the desired performance for each task.

cs.LG↗

arXiv2020

An inverse designed achromatic flat lens operating in the ultraviolet

We demonstrate an inverse designed achromatic, flat, polarization-insensitive diffractive optic element, i.e., multilevel diffractive lens (MDL), operating across a broadband range of UV light (250 nm - 400 nm) via numerical simulations. The simulated average on-axis focusing efficiency of the MDL is optimized to be as high as ~86%. We also investigate the off-axis focusing characteristics at different incident angles of the incoming UV radiation such that the MDL has a full field of view of 30 degrees. The simulated average off-axis focusing efficiency is ~67%, which is the highest reported till date for any chromatic or achromatic UV metalens or diffractive lens to the best of our knowledge. The designed MDL is composed of silicon nitride. The work reported herein will be useful for the miniaturization and integration of lightweight and compact UV optical systems.

physics.optics↗