Editors’ Choice—Review—Solid-State Electrochemical Carbon Dioxide Sensors: Fundamentals, Materials and Applications
Bibliographic record
Abstract
The recent series of global catastrophic events (e.g., heatwaves, flooding) have again raised the concerns over the greater impact of climate change. The focus has been concentrated towards reducing CO2 emissions from fossil fuel based energy systems. It is necessary to build a commercially viable CO2 sensor with high reliability. The gas-sensing field has shifted from using a cumbersome gas-reference electrode to solid-state electrochemical devices because they can be employed to detect CO2 in real-time overcoming the limits of widely used IR-based CO2 sensors. Here, solid electrolytes and mixed conducting semiconductor-based gas sensors for various gaseous species including CO2 are reviewed. The study on semiconducting metal oxides (SMOs) has been pushed forward as a most viable option for commercializing monolithic all-solid-state electrochemical gas sensors. Among SMOs, the perovskite-type metal oxides are considered as one of the promising structures for next-generation greenhouse gas sensors due to their remarkable thermal and chemical stability. This article also includes the fundamental understanding of essential factors that govern the electrical signals in all-solid-state electrochemical gas sensors.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.016 |
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".