An optimized HNO<sub>3</sub> and HBF<sub>4</sub> digestion method for multielemental soil and sediment analysis using inductively coupled plasma quadrupole mass spectrometry
Bibliographic record
Abstract
A robust and reliable analytical procedure for the determination of trace (mg∙kg −1 ) and ultra-trace elements (μg∙kg −1 ) in soil and sediments by inductively coupled plasma quadrupole mass spectrometry (ICP-QMS) was optimized. Aliquots of ∼200 mg of two certified reference materials (IAEA Soil-7, soil and IAEA SL-1, lake sediments) were digested in nitric acid (HNO 3 ) purified twice by sub-boiling distillation using a microwave-heated high-pressure autoclave. Incremental addition of tetrafluoroboric acid (HBF 4 , 0.1–2 mL) to HNO 3 was evaluated for yield. The selection of appropriate proportions of digestion acids was crucial to obtain accurate results. Digested samples were analyzed for a range of trace elements including those that are potentially toxic (Ag, Cd, Pb, Sb, and Tl), plant micronutrients (Cu, Fe, Mn, and Zn), those enriched in bitumen (Mo, Ni, and V), and lithophile elements (Al, Ba, Co, Cr, Rb, Sr, Th, Ti, Y, and Zr). Nitric acid alone proved to be sufficient to completely liberate Cd, Co, Cr, Fe, Mn, Ni, Pb, V, and Zn in both soil and sediments (87%–120% recovery). For almost all the other elements, addition of HBF 4 was needed for improved recovery. A combination of 3 mL of HNO 3 and 1.5 mL of HBF 4 was optimal to fully liberate an extended list of elements including Ba, Sb, and Sr from both the reference materials. Conservative lithophile elements (Th, Ti, Y, and Zr) could not be completely recovered with the proposed method, requiring hydrofluoric acid for complete dissolution of recalcitrant minerals.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".