Molecular Engineering of Silicon Phthalocyanine to Improve the Charge Transport and Ammonia Sensing Properties of Organic Heterojunction Gas Sensors
Bibliographic record
Abstract
Abstract Novel organic heterostructures fabricated with a bilayer consisting of an axially substituted silicon phthalocyanine (R2‐SiPc) derivative and lutetium bis‐phthalocyanine (LuPc2) are investigated for their ammonia sensing properties. Surface and microstructure characterization of the heterostructure films reveal either compact or highly porous surface topography in (345F)2‐SiPc and Cl2‐SiPc‐based heterostructures, while electrical characterization reveals a strong influence of the axial substituent in R2‐SiPc on NH3 sensing capabilities. Electrical characterization further demonstrates an apparent energy barrier for interfacial charge transport, which is higher in the (345F)2‐SiPc/LuPc2 heterojunction device. In‐depth charge transport studies by impedance spectroscopy further reveal a resistive interface in (345F)2‐SiPc/LuPc2 and faster bulk and interfacial charge transport in Cl2‐SiPc/LuPc2 heterojunction devices. Different interfacial charge transport capabilities and surface topographies affect NH3 sensing properties of the two heterojunction devices, in which (345F)2‐SiPc/LuPc2 reveals a fast and non‐linear response with a limit of detection (LOD) of 310 ppb, while Cl2‐SiPc/LuPc2 exhibits a slow, and linear response to NH3 with LOD of 100 ppb. Finally, different metrological parameters of the two sensors are correlated to the respective gas‐material interactions, in which adsorption and diffusion regimes are modulated by the surface topography and hydrophobicity of the sensing layer.
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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) | 0.000 | 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 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".