谷歌浏览器插件
订阅小程序
在清言上使用

Benchmarking of X-Ray Fluorescence Microscopy with Ion Beam Implanted Samples Showing Detection Sensitivity of Hundreds of Atoms

SMALL METHODS(2024)

引用 0|浏览20
暂无评分
摘要
Single impurities in insulators are now often used for quantum sensors and single photon sources, while nanoscale semiconductor doping features are being constructed for electrical contacts in quantum technology devices, implying that new methods for sensitive, non-destructive imaging of single- or few-atom structures are needed. X-ray fluorescence (XRF) can provide nanoscale imaging with chemical specificity, and features comprising as few as 100 000 atoms have been detected without any need for specialized or destructive sample preparation. Presently, the ultimate limits of sensitivity of XRF are unknown - here, gallium dopants in silicon are investigated using a high brilliance, synchrotron source collimated to a small spot. It is demonstrated that with a single-pixel integration time of 1 s, the sensitivity is sufficient to identify a single isolated feature of only 3000 Ga impurities (a mass of just 350 zg). With increased integration (25 s), 650 impurities can be detected. The results are quantified using a calibration sample consisting of precisely controlled numbers of implanted atoms in nanometer-sized structures. The results show that such features can now be mapped quantitatively when calibration samples are used, and suggest that, in the near future, planned upgrades to XRF facilities might achieve single-atom sensitivity. Advancements in X-ray fluorescence microscopy demonstrate metrological quantification of the sensitivity for just a few hundred buried impurity atoms in clusters of only a few 10's of nanometers in size, using specially designed test structures made with gallium implanted into silicon. Non-destructive observation of single-atom implants is predicted in the near future. image
更多
查看译文
关键词
gallium impurities,silicon-based quantum technology,single-atom detection,synchrotron X-ray fluorescence
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要