Image-histogram-based secondary electron counting to evaluate detective quantum efficiency in SEM

Agarwal, Akshay; Simonaitis, John; Berggren, Karl K.

doi:10.1016/j.ultramic.2021.113238

Cited by 5 publications

(5 citation statements)

References 22 publications

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“…We will describe our counting algorithm in Section 2.5. In previous work, we had found that an imaging current of 2.3 pA was well within the linear response region of our SE detectors and had also described the statistics of these voltage pulses [10]. We had concluded that each pulse corresponds to one detected SE, thereby allowing the counting of SEs.…”

Section: Imaging Setupsupporting

confidence: 55%

“…Since the mean SE count scales linearly with the incident beam current [10], this difference represents an incident electron dose reduction of 30% due to SE count imaging for the same SNR.…”

Section: Resultsmentioning

confidence: 99%

“…We collected 32 acquisition frames from the same scan area on both the in-chamber and inlens SE detectors to construct SE count images of that area, at a beam current of 2.3 pA and a pixel dwell time of 440 ns. We had found the detective quantum efficiency (DQE) [15,2] of the in-chamber detector to be 0.16 and that of the in-lens detector to be 0.32 previously [10],…”

Section: Imaging Setupmentioning

confidence: 99%

“…Furthermore, the requirement for synchronizing electronics also limited this experiment to long pixel dwell times (typically tens of µs). More recently, SE image histograms have been investigated for counting SEs [2,10], motivated in part by similar work in scanning transmission electron microscopy (STEM) [11,12,13,14]. However, such techniques are limited by the same voltage signal variations that are present in conventional SE imaging.…”

Section: Introductionmentioning

confidence: 99%

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Secondary Electron Count Imaging in SEM

Simonaitis¹,

Goyal²,

Berggren³

2021

Preprint

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Scanning electron microscopy (SEM) is a versatile technique used to image samples at the nanoscale. Conventional imaging by this technique relies on finding the average intensity of the signal generated on a detector by secondary electrons (SEs) emitted from the sample and is subject to noise due to variations in the voltage signal from the detector. This noise can result in degradation of the SEM image quality for a given imaging dose. SE count imaging, which uses the direct count of SEs detected from the sample instead of the average signal intensity, would overcome this limitation and lead to improvement in SEM image quality.In this paper, we implement an SE count imaging scheme by synchronously outcoupling the detector and beam scan signals from the microscope and using custom code to count detected SEs. We demonstrate a ∼30% increase in the image signal-to-noise-ratio due to SE counting compared to conventional imaging. The only external hardware requirement for this imaging scheme is an oscilloscope fast enough to accurately sample the detector signal for SE counting, making the scheme easily implementable on any SEM.

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Section: Imaging Setupsupporting

confidence: 55%

Section: Resultsmentioning

confidence: 99%

Section: Imaging Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Secondary Electron Count Imaging in SEM

Simonaitis¹,

Goyal²,

Berggren³

2021

Preprint

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“…The signal generated by the SED consists of a series of voltage pulses of varying heights, where each pulse corresponds to a burst of detected SEs ( 29 ). The mean full width at half maximum (FWHM) of the pulses is

160 ns ( 30 ). In our experiments, we used beam current

pA (measured with a picoammeter connected to a Faraday cup), which was low enough to make pulse pile-up effects manageable.…”

Section: Resultsmentioning

confidence: 99%

Shot noise-mitigated secondary electron imaging with ion count-aided microscopy

Agarwal,

Kasaei,

et al. 2024

Proc. Natl. Acad. Sci. U.S.A.

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Modern science is dependent on imaging on the nanoscale, often achieved through processes that detect secondary electrons created by a highly focused incident charged particle beam. Multiple types of measurement noise limit the ultimate trade-off between the image quality and the incident particle dose, which can preclude useful imaging of dose-sensitive samples. Existing methods to improve image quality do not fundamentally mitigate the noise sources. Furthermore, barriers to assigning a physically meaningful scale make the images qualitative. Here, we introduce ion count-aided microscopy (ICAM), which is a quantitative imaging technique that uses statistically principled estimation of the secondary electron yield. With a readily implemented change in data collection, ICAM substantially reduces source shot noise. In helium ion microscopy, we demonstrate 3 × dose reduction and a good match between these empirical results and theoretical performance predictions. ICAM facilitates imaging of fragile samples and may make imaging with heavier particles more attractive.

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