Single event soft error in advanced integrated circuit

As technology feature sizes decrease, single event upset (SEU), and single event transient (SET) dominate the radiation response of microcircuits. Multiple bit upset (MBU) (or multi cell upset) effects, digital single event transient (DSET) and analogue single event transient (ASET) caused serious problems for advanced integrated circuits (ICs) applied in a radiation environment and have become a pressing issue. To face this challenge, a lot of work has been put into the single event soft error mechanism and mitigation schemes. This paper presents a review of SEU and SET, including: a brief historical overview, which summarizes the historical development of the SEU and SET study since their first observation in the 1970's; effects prominent in advanced technology, which reviews the effects such as MBU, MSET as well as SET broadening and quenching with the influence of temperature, device structure etc.; the present understanding of single event soft error mechanisms, which review the basic mechanism of single event generation including various component of charge collection; and a discussion of various SEU and SET mitigation schemes divided as circuit hardening and layout hardening that could help the designer meet his goals.     

4500V SPT IGBT 动静态损耗优化

本文关注高压IGBT动静态性能的优化。对4500V增强型平面IGBT进行研究,该结构在阴极一侧具有载流子存储层。其中垂直结构采用软穿通(SPT)结构,顶部结构采用增强型平面结构,该结构被称为SPT IGBT,仿真结果显示4500V SPT 具有软关断波形,与SPT结构相比提升了导通压降和关断损耗之间的折衷关系。同时,对不同载流子存储层掺杂浓度对动静态性能的影响也进行了研究,以此来优化SPT IGBT的动静态损耗。     

Rapid Quantification of Live Cell Receptors Using Bioluminescence in a Flow‐Based Microfluidic Device

The number of receptors expressed by cells plays an important role in controlling cell signaling events, thus determining its behaviour, state and fate. Current methods of quantifying receptors on cells are either laborious or do not maintain the cells in their native form. Here, a method integrating highly sensitive bioluminescence, high precision microfluidics and small footprint of lensfree optics is developed to quantify cell surface receptors. This method is safe to use, less laborious, and faster than the conventional radiolabelling and near field scanning methods. It is also more sensitive than fluorescence based assays and is ideal for high throughput screening. In quantifying β₁ adrenergic receptors expressed on the surface of H9c2 cardiomyocytes, this method yields receptor numbers from 3.12 × 10⁵ to 9.36 × 10⁵ receptors/cell which are comparable with current methods. This can serve as a very good platform for rapid quantification of receptor numbers in ligand/drug binding and receptor characterization studies, which is an important part of pharmaceutical and biological research.     

Interstitial carbon formation in irradiated copper-doped silicon

The influence of a copper impurity on the spectrum of defects induced in p-Si crystals containing a low oxygen concentration by irradiation with electrons with an energy of 5 MeV at room temperature is studied by deep-level transient spectroscopy. It is found that interstitial carbon atoms (C _i ) which are the dominant defects in irradiated samples free of copper are unobservable immediately after irradiation, if the concentration of mobile interstitial copper atoms (Cu _i ) is higher than the concentration of radiation defects. This phenomenon is attributed to the formation of {Cu _i , C _i } complexes, which do not introduce levels into the lower half of the band gap. It is shown that these complexes dissociate upon annealing at temperatures of 300–340 K and, thus, bring about the appearance of interstitial carbon.

     

SiGe HBT的线性度研究（英文）

应用一种改进的片上线性度测试方法来对上海华虹宏力半导体制造有限公司生产的SiGe HBT进行测试,得到了一个较好的测试结果,同时对其线性度随偏置情况的变化以及引起变化的机制进行了分析和讨论。通过分析表明:在集电极偏置电流较小时,SiGe HBT的线性度主要受器件跨导和雪崩倍增效应的限制;在中等大小的集电极偏置电流下,SiGe HBT的非线性主要由集电结势垒电容所产生;在大的集电极偏置电流下,大电流效应是产生非线性的主要原因。     

命名实体识别技术综述

命名实体识别是自然语言处理中的热点研究方向之一,目的是识别文本中的命名实体并将其归纳到相应的实体类型中。首先阐述了命名实体识别任务的定义、目标和意义,分析提出了命名实体识别的主要难点在于领域命名实体识别局限性、命名实体表述多样性和歧义性、命名实体的复杂性和开放性;然后介绍了命名实体识别研究的发展进程,从最初的规则和字典方法到传统的统计学习方法再到现在的深度学习方法,不断地将新技术应用到命名实体识别研究中以提高性能;接着系统梳理了当下命名实体识别任务中的若干热门研究点,分别是匮乏资源下的命名实体识别、细粒度命名实体识别、嵌套命名实体识别以及命名实体链接;最后针对评判命名实体识别模型的好坏,总结了常用的若干数据集和实验测评指标,并给出了未来的研究建议。