Mercury Lα1 High Energy Resolution Fluorescence Detected X-ray Absorption Spectroscopy: A Versatile Speciation Probe for Mercury
Bibliographic record
Abstract
Mercury is in some sense an enigmatic element. The element and some of its compounds are a natural part of the biogeochemical cycle; while many of these can be deadly poisons at higher levels, environmental levels in the absence of anthropogenic contributions would generally be below the threshold for concern. However, mercury pollution, particularly from burning fossil fuels such as coal, is providing dramatic and increasing emissions into the environment. Because of this, the environmental chemistry and toxicology of mercury are of growing importance, with the fate of mercury being vitally dependent upon its speciation. X-ray absorption spectroscopy (XAS) provides a powerful tool for in situ chemical speciation, but is severely limited by poor spectroscopic energy resolution. Here, we provide a systematic examination of mercury Lα1 high energy resolution fluorescence detected XAS (HERFD–XAS) as an approach for chemical speciation of mercury, in quantitative comparison with conventional Hg L III -edge XAS. We show that, unlike some lighter elements, chemical shifts in the Lα1 X-ray fluorescence energy can be safely neglected, so that mercury Lα1 HERFD–XAS can be treated simply as a high-resolution version of conventional XAS. We present spectra of a range of mercury compounds that may be relevant to the environmental and life science research and show that density functional theory can produce adequate simulations of the spectra. We discuss strengths and limitations of the method and quantitatively demonstrate improvements both in speciation for complex mixtures and in background rejection for low concentrations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".