Synthesis, Structure, and Stability of Gallium Arsenate Dihydrate, Indium Arsenate Dihydrate, and Lanthanum Arsenate
Bibliographic record
Abstract
This paper reports on the hydrothermal synthesis, structural characterization, and chemical stability−leachability of three metal arsenates, namely gallium arsenate dihydrate (GaAsO 4 ·2H 2 O), indium arsenate dihydrate (InAsO 4 ·2H 2 O), and lanthanum arsenate (LaAsO 4 ). The new standard synthesis method involves hydrothermal precipitation at 433 K (160 °C) from equimolar (0.3 M) M(III)−As(V) nitrate solutions over a period of 24 h. The produced materials were found to be essentially stoichiometric and to exhibit very good crystallinity. The two dihydrates were found further to be made up of uniformly grown crystallites either aggregated (GaAsO 4 ·2H 2 O) or nonaggregated (InAsO 4 ·2H 2 O), reflecting their common orthorhombic crystal habit, while LaAsO 4 consisted of large aggregated particles with monoclinic habit features. In terms of stability, InAsO 4 ·2H 2 O and LaAsO 4 were found to release less than 1 mg/L arsenic when subjected to a TCLP-like leachability test (24 h contact at pH 5) while GaAsO 4 ·2H 2 O released 2.4 mg/L arsenic. An extended leachability study over a period of several weeks resulted in higher concentrations of arsenic released via an incongruent dissolution mechanism. Of the three compounds, LaAsO 4 was determined to be the most stable with arsenic equilibrium solubility equal to 4 and 13 mg/L, respectively, at pH 5 and 7 at 22 °C.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 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".