Nonenzymatic Electrochemical Glutamate Sensor Using Copper Oxide Nanomaterials and Multiwall Carbon Nanotubes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Glutamate is an important neurotransmitter due to its critical role in physiological and pathological processes. While enzymatic electrochemical sensors can selectively detect glutamate, enzymes cause instability of the sensors, thus necessitating the development of enzyme-free glutamate sensors. In this paper, we developed an ultrahigh sensitive nonenzymatic electrochemical glutamate sensor by synthesizing copper oxide (CuO) nanostructures and physically mixing them with multiwall carbon nanotubes (MWCNTs) onto a screen-printed carbon electrode. We comprehensively investigated the sensing mechanism of glutamate; the optimized sensor showed irreversible oxidation of glutamate involving one electron and one proton, and a linear response from 20 μM to 200 μM at pH 7. The limit of detection and sensitivity of the sensor were about 17.5 μM and 8500 μA·mM−1·cm−2, respectively. The enhanced sensing performance is attributed to the synergetic electrochemical activities of CuO nanostructures and MWCNTs. The sensor detected glutamate in whole blood and urine and had minimal interference with common interferents, suggesting its potential for healthcare applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it