Quantitative Energy Dispersive X-ray Microanalysis of Electron Beam-Sensitive Alloyed Nanoparticles
Bibliographic record
Abstract
An energy dispersive X-ray spectrometry (EDXS) method is developed to evaluate the composition of alloyed nanoparticles (NPs) where one of the alloying elements is removed under the electron beam during microanalysis with a transmission electron microscope (TEM). The method is demonstrated for alloyed Au-Ag NPs of a diameter ranging from 6 to 20 nm produced by laser evaporation of a water-suspended Ag-Au powder mixture of varying composition. Series of EDXS spectra are recorded for 30 NPs from samples with five different Ag:Au ratios revealing Ag depletion from NPs during electron irradiation. By studying the evolution of NPs composition as a function of dose, the initial Ag content for each NP is extrapolated. The rate of Ag depletion is discussed in terms of sputtering and knock-on damage. On average, approximately one Ag atom is lost from the NP for each Ag L X-ray detected. To assess the limitations of microanalysis in these sensitive nanoscale structures, the concept of detectability limit is adapted to our method. This benchmark is then evaluated for Ag in Au-Ag NPs of various sizes and acquisition times. This study should be regarded as a guide for the design of analytical TEM measurements of beam-sensitive NPs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".