There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

International Technology Roadmap for Semiconductors 2003の要求清浄度について － シリコンウエハ表面と雰囲気環境に要求される清浄度, 分析方法の現状について －

Monte Carlo simulations have been widely used by microscopists for the last few decades. In the beginning it was a tedious and slow process, requiring a high level of computer skills from users and long computational times. Recent progress in the microelectronics industry now provides researchers with affordable desktop computers with clock rates greater than 3 GHz. With this type of computing power routinely available, Monte Carlo simulation is no longer an exclusive or long (overnight) process. The aim of this paper is to present a new user-friendly simulation program based on the earlier CASINO Monte Carlo program. The intent of this software is to assist scanning electron microscope users in interpretation of imaging and microanalysis and also with more advanced procedures including electron-beam lithography. This version uses a new architecture that provides results twice as quickly. This program is freely available to the scientific community and can be downloaded from the website: (www.gel.usherb.ca/casino).

/pdf/casino-v2-42-a-fast-and-easy-to-use-modeling-tool-for-4x80ysvonj.pdf

CASINO V2.42: a fast and easy-to-use modeling tool for scanning electron microscopy and microanalysis users.

An adaptive inference method for crossbar (AIDX) is presented based on an optimization scheme for adjusting the duration and amplitude of input voltage pulses. AIDX minimizes the long-term effects of memristance drift on artificial neural network accuracy. The sub-threshold behavior of memristor has been modeled and verified by comparing with fabricated device data. The proposed method has been evaluated by testing on different network structures and applications, e.g., image reconstruction and classification tasks. The results showed an average of 60% improvement in convolutional neural network (CNN) performance on CIFAR10 dataset after 10000 inference operations as well as a 78.6% error reduction in image reconstruction.

AIDX: Adaptive Inference Scheme to Mitigate State-Drift in Memristive VMM Accelerators

This paper presents the fabrication, electrical characterization, and simulation of planar single electron transistors. Two single electron transistors facing each other have been used to demonstrate single charge detection. The manufacturable fabrication process combined with both single charge detection and the simulation tool are a powerful platform for quantum cellular automata that can be applied for interfacing classical computing with future quantum computing.

A manufacturable process for single electron charge detection, a step towards quantum computing

An inductively coupled plasma etch process for the fabrication of TiN nanostructures over nanotopography is presented. Using a Cl2/Ar/N2 plasma, a selectivity of 50 is achieved over SiO2. The effect of N2 flow rate on the etch rates and the nonvolatile residues on TiN sidewalls is investigated. As N2 flow rate is increased up to 50 sccm, a change in the deposition of the nonvolatile residues on TiN sidewalls is observed. The current density–voltage characterizations of TiN devices fabricated with TiN nanostructure sidewalls are presented. The measured current densities of two different samples etched with low and high N2 flow rate, respectively, demonstrated the presence after cleaning of an insulating layer deposited on the sidewalls for low N2 flow rate only.

/pdf/selective-dry-etching-of-tin-nanostructures-over-sio2-3jj865jumk.pdf

Selective dry etching of TiN nanostructures over SiO2 nanotrenches using a Cl2/Ar/N2 inductively coupled plasma

An adaptive inference method for crossbar (AIDX) is presented based on an optimization scheme for adjusting the duration and amplitude of input voltage pulses. AIDX minimizes the long-term effects of memristance drift on artificial neural network accuracy. The sub-threshold behavior of memristor has been modeled and verified by comparing with fabricated device data. The proposed method has been evaluated by testing on different network structures and applications, e.g., image reconstruction and classification tasks. The results showed an average of 60% improvement in convolutional neural network (CNN) performance on CIFAR10 dataset after 10000 inference operations as well as 78.6% error reduction in image reconstruction.

The increasing application of GaN in blue and UV light emitting diodes and lasers has generated considerable interest in its optical and electrical properties. These optical devices exhibit extremely high emission efficiencies despite the presence of a very high concentration of threading dislocations (l08 10 ern") that act as non-radiative recombination channels. This perceived contradiction can be been explained by small « 100 urn) carrier diffusion lengths which effectively negate the effect of the threading dislocations on the radiative recombination efficiency. These short exciton and minority carrier diffusion lengths in GaN can be explored by cathodoluminescence (CL) microscopy and spectroscopy using a SEM equipped with a Schottky field emission gun operating at 1kV.

/pdf/probing-carrier-behavior-at-the-nanoscale-in-gallium-nitride-3hogd2tk2p.pdf

Dominique Drouin

Papers

AIDX: Adaptive Inference Scheme to Mitigate State-Drift in Memristive VMM Accelerators

A manufacturable process for single electron charge detection, a step towards quantum computing

Selective dry etching of TiN nanostructures over SiO2 nanotrenches using a Cl2/Ar/N2 inductively coupled plasma

AIDX: Adaptive Inference Scheme to Mitigate State-Drift in Memristive VMM Accelerators

Probing Carrier Behavior at the Nanoscale in Gallium Nitride using Low Voltage Cathodoluminescence