Optimization of a lithium assay method in oil fields brines by using experimental design methodology and its validation by the accuracy profile approach
Bibliographic record
Abstract
ABSTRACT To cover the excessive demand of lithium compounds, especially for the manufacture of vehicle batteries, several extraction technologies from natural resources and mainly geothermal brines are applied. These brines are distinguished by the complexity of its chemical composition. So, the quantification of lithium amount by spectroscopic methods will be disturbed by some interferences due to the cohabitation of major cations and anions. The originality of this investigated work is to optimize, by using the response surface methodology, and to validate, by the application of the accuracy profile approach, the analytical method for lithium assay by flame emission spectroscopy. After identification of the major ions in the oilfield brine sample (Ca, Mg, Na, K and Cl), a specificity test is applied, which reveals the presence of chemical interferences. For this reason, a spiked synthetic solution by a lithium standard (20 mg/L) is prepared for each run of the Doehlert design. Four studied factors, which are the major cations ([Ca 2+ ] ( X 1 ), [Mg 2+ ] ( X 2 ), [Na + ] ( X 3 ) and [K + ] ( X 4 )), are used to build this design and to determine their effects on the lithium recovery yield response ( Y (%)). As resulted outcomes, a polynomial valid and predictive model is statistically qualified and used to plot the iso-responses curves of the chosen response. Consequently, the optimal conditions are determined by: [Ca 2+ ] ( X 1 ) = 1.7 mol/L, [Mg 2+ ] ( X 2 ) = 0.02 mol/L, [Na + ] ( X 3 ) = 0.36 mol/L and [K + ] ( X 4 ) = 0.01 mol/L, which correspond to 64.128, 2.43, 60 and 2 g/L, respectively and the theoretical lithium recovery yield is nearby 98% in five-fold diluted composition. Moreover, the validation by the accuracy profile approach is performed after the robustness test. The resulted β-expectation tolerance interval is within the acceptability limits, which means that the analytical method, used for lithium assay by flame emission spectroscopy, is valid and the response variances are almost constant (homoscedasticity) over the predefined range concentration (8–50 mg/L) and it can be used for routine analysis.
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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 | 0.000 | 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 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".