Characterization of the Performance of a Thin Si-based Timepix3 Detector at 10–30 keV Electron Energies
Bibliographic record
Abstract
Direct electron detectors such as hybrid pixel array detectors based on the Timepix3 chip [1] have received increasing attention within the electron microscopy community due to their high signal-to-noise ratio and dynamic range as compared to conventional indirect detectors, as well as their ability to perform energy filtering [2]. Earlier applications of these direct electron detectors have focused on techniques based in transmission electron microscope (TEM). More recently, the use of direct detectors has also been probed in lower electron energy applications, especially those based in scanning electron microscope (SEM), such as electron backscatter diffraction [3]. Lower incident electron energies will reduce the depth at which electron energy is deposited, and therefore enable the potential use of thinner sensing layers. Reduced diffusion of signal-carriers produced by incident electrons in thinner sensors should improve the imaging performance compared with thicker sensors. To assess the value of these imaging detectors, the detector performance can be quantified through analysis of the modulation transfer function (MTF) and detective quantum efficiency (DQE). The MTF measures the transfer of contrast as a function of spatial frequency, and the DQE is an overall measure of the effective transfer of signal. While many previous works have measured the MTF and DQE at electron energies typical for TEMs (e.g. 60–200 keV), there is limited information available of detector performance at the lower energies used in SEM-based microscopy (up to 35 keV). In this work, we characterize a Timepix3-based direct electron detector with a 100-μm thick Si sensing layer at lower (10–30 keV) electron energies. A new experimental protocol to facilitate the measurements which can be conducted in SEM is proposed. Measurements of MTF and DQE were performed in a field-emission gun SEM using the knife edge method and a flat field image method respectively [4]. The MTF was found to decrease with higher electron energy, which agrees with the trend based on previous literature, and shows improvement of MTF from higher electron energies and thicker sensing layers [5–6]. Measurements of the DQE, currently ongoing, will confirm the extent to which a thin sensor improves the device's ability to resolve features of different sizes when the total number of electrons contributing to image formation is limited. Our measurements have found that thin hybrid pixel array detectors provide improved electron detection and imaging in SEMs (including operation in scanning electron microscopy-based transmission modes) for electron energies between 10 and 30 keV. This data can support and motivate the wider-adoption of these direct detectors for electron diffraction and related SEM-based microstructural analysis methods [7].
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".