Quantification of nickel, cobalt, and manganese concentration using ultraviolet-visible spectroscopy
Bibliographic record
Abstract
Ultraviolet-visible spectroscopy is one of the most effective, inexpensive, flexible, and simplest analytical techniques to measure species concentration in the liquid phase. It has a wide range of applications such as wastewater treatment, dye degradation, colloidal nanoparticle characterization. It is used in almost every spectroscopy laboratory for routine analysis or research. In the present study, a feasibility study was carried out to find the application of UV-Vis spectroscopy for onsite measurement of nickel, cobalt, manganese, and lithium as a replacement for the conventional method to measure the concentrations of these elements in battery and other applicable industries. Samples with different concentrations of individual elements and composites were prepared and analyzed using an ultraviolet-visible spectrometer. Based on the obtained results, mathematical relationships between concentration and absorbance were defined. The calculated concentration of different elements using the developed relationships was compared with the measured concentration using ICP-OES to find any deviation between the two. The effect of various parameters such as concentration, path length, number of elements in the solution, density, and pH was analyzed to verify the feasibility. The obtained results show that this technique can be effectively used to measure the concentration of nickel and cobalt with high accuracy.
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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".