Effect of Lithium Manganese Oxide on Lithium Detection in Microfluidic Electrochemical Sensor
Bibliographic record
Abstract
This paper presents a novel, low-cost and easy-to-fabricate Microfluidic Electrochemical Sensor (MES) capable of detecting LiCl-based lithium (Li) ions in water. The MES consisted of inexpensive Pressure Sensitive Adhesive (PSA) and Polyethylene Terephthalate (PET) sheets to fabricate a curved microchannel over three carbon-based electrodes. The MES was tested with various concentrations of Lithium Manganese Oxide (LMO) in 1 mL N-methyl-2-pyrrolidone (NMP), mixed in a 1:1 mass ratio with Graphene Carbon Paste (GCP) to create the Li-specific electrodes. The electrodes formed in a mixture of 300 mg/mL LMO in NMP performed the best, with Cyclic Voltammetry (CV) currents indicating a reduction peak of$265 \ \mu \mathrm{A}$at 1.0 M LiCI and no significant reduction for competitive 1.0 M NaCl and KCl salts. These results demonstrate the MESs strong selectivity towards Li. Due to the use of low-cost and readily available materials, the MES used in this study has a high potential to be a reliable, portable, and efficient sensor for Li detection.
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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) | 0.001 | 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 | 0.001 | 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".