Effect of Molybdenum Oxide Electronic Structure on Organic Photovoltaic Device Performance: An X-ray Absorption Spectroscopy Study
Bibliographic record
Abstract
While molybdenum oxide (MoO 3 ) has been shown to be an effective hole transport layer in organic photovoltaic (OPV) devices, a complete understanding of its electronic behavior has proven elusive. In this work, thin films of substoichiometric molybdenum oxide (MoO 3– x ) were prepared via thermal evaporation and subjected to a variety of annealing conditions. The films were employed as the hole transport layers in organic photovoltaic devices, and the device performance was found to depend strongly on the annealing conditions: as-prepared MoO 3– x films produced poly(3-hexylthiophene)/[6,6]-phenyl-C 61 -butyric acid methyl ester devices with good performance (3.1% power conversion efficiency), while films annealed at higher temperatures or in a reducing atmosphere produced devices with very low efficiencies (≤1%). Through X-ray absorption near-edge structure (XANES) measurements at the Mo L 3 -edge, we show that while oxygen vacancies present in the as-prepared films may play a key role in hole extraction, extensive reduction of the molybdenum ions leads to more metallic behavior that results in a pronounced drop in device efficiency. These results clearly show that careful control over the MoO 3– x stoichiometry is necessary in order to achieve the highest performance in OPV devices and further demonstrate the utility of XANES in correlating OPV device performance to changes in electronic structure.
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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) | 0.001 | 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".