Investigation of imaging ToF‐SIMS as a means to study coatings on wood
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Measurement of the penetration of coatings into wood may be performed by SEM analysis with OsO 4 or other markers used for post‐treatment labeling. However, there are indications that the Os only binds with the uncured components of the resin. Since these are mainly located at the surface of the coating, the use of Os could thus misinterpret the actual penetration of the coatings into the wood surface. Time‐of‐Flight Secondary Ion Mass Spectrometry (ToF‐SIMS) provides a unique means by which the penetration depths of the various components of the coating (resin + pigments) into the wood microstructure can be visualized. This arises from both the high spatial resolution (<100 nm) and high mass resolution achievable with the technique (albeit not at the same time). The latter feature is of importance to resolve different molecular fragments of similar molecular weight which could be needed as markers for the various components in the complex hydrocarbon systems constituting wood and the coating materials, whilst the former is required to ascertain differences in penetration depth of the components. In this work, imaging ToF‐SIMS spectra are obtained on cross‐sections of coated wood samples using a Bi cluster ion source. Coating distribution is followed by identifying fragments associated more with the coating and with the wood respectively. Sample preparation techniques are of importance and thus results are compared for cross‐sections prepared both by microtoming, as well as by mounting in epoxy resin and polishing. Copyright © 2010 John Wiley & Sons, Ltd.
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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) | 0.000 | 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 it