Hydrogen Gas Sensors Using Two-Dimensional Electron Gas
Bibliographic record
Abstract
Hydrogen (H2) has been considered as a clean and environment-friendly energy source on account of its low ignition energy and high heat of combustion from which the combustion product is H2O.[1] Recently, H2 gas is regarded as the most important energy source for the operation of electrical vehicles.[2,3] However, H2 is not only flammable but also explosive in the concentration of 4-75%.Unfortunately, it is impossible to detect H2 gas by human beings because of its colorless and odorless property.Therefore, a development of sensitive H2 gas sensor is required for human safety.[4,5] Two-dimensional electron gas (2DEG) was observed at the interface of oxide heterostructure in 2004.[6] The model system for 2DEG at the oxide heterostructure is epitaxial interface of LaAlO3/SrTiO3 heterostructure.Recently, we reported that 2DEG can be created at the oxide heterostructure by using amorphous Al2O3 top layer.[7]Here, we demonstrate highperformance H2 gas sensor using 2DEG at the interface of Al2O3/SrTiO3 heterostructure using atomic layer deposition (ALD).Palladium (Pd) or platinum (Pt) catalysts are used on top of the Al2O3/SrTiO3 heterostructure.[8]At first, we will show a H2 gas sensing performance using 2DEG at the interface of Al2O3/SrTiO3 heterostructure.The H2 gas sensor using Al2O3/SrTiO3 exhibited a wide sensing range of H2 concentration (5ppm-1%) even room temperature with fast response time.The more H2 gas concentration increased, the more H2 gas sensitive increased.The Pd/Al2O3/SrTiO3 sensor showed a fast response time to detect H2 gas (<30 s) at room temperature.Owing to a wide bandgap (>3.2 eV) of Al2O3/SrTiO3, a transparent gas sensor (transmittance >83% in the visible spectrum) was realized.2DEG resistance is changed by adsorbing H2 gas because the work function of Pd nanoparticles is modulated by the H2 adsorption.Alteration of work function induced the change of the 2DEG resistance.The detailed detection principle will be explained in the presentation.H2 gas sensor using 2DEG at heterostructure such as AlGaN/GaN is another candidate for H2 detection, thus, H2 sensor using AlGaN/GaN is compared with Al2O3/SrTiO3 sensor.H2 gas sensor using AlGaN/GaN heterostructure showed a slow H2 detection speed, but superior sensitivity (~30000%) compared to the Al2O3/SrTiO3 sensor.In addition, enhanced detection performances of H2 gas sensor with AlGaN/GaN heterostructures using atomic-layer-thick ZnO on Pt (or Pd) on 2DEG are addressed, which improved a decrease of recovery time.The atomic-layer-thick ZnO layer was grown by ALD which will be introduced in the presentation.
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.
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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".