Materials Chemistry to Advance the Speed and Sensitivity of Infrared Solution-Cast Photodetectors
Bibliographic record
Abstract
There has been considerable interest in solution-processed semiconductors for use in near-infrared (NIR) and short-wavelength infrared (SWIR) photodetectors. In this regard, perovskites and colloidal quantum dots (CQDs) are two prominent materials. I aim, in this thesis, to explore the chemistry of these material systems to enable efficient, stable, and fast solution-based infrared photodetectors. In Pb-Sn binary perovskite photodetectors, I uncover a low charge collection efficiency that results from the chemical incompatibility between tin perovskite material processing and metal oxide transport layers. I develop a new approach, revisiting the method used in chemically reducing the tin precursor. I report photodetectors with an external quantum efficiency of 85% at 850 nm, a dark current below 10-8 A/cm2, and a response time faster than 100 picoseconds. I showcase the application of these detectors in LiDAR, demonstrating sub-millimeter distance resolution. I turn my attention to SWIR InAs CQD photodiodes, finding that there is a non-optimal band alignment at the interface between the QD layer and the hole transport layer. I utilize functionalized molecular ligands to engineer the energy levels of QDs. The incorporation of molecularly tuned QDs as hole transport layers improves charge extraction efficiency from 20% to 31% at 1120 nm and leads to a two-orders-of-magnitude improvement in the dark current, reaching 4×10-7 A/cm2. I then use energy level tuning in QDs to design an electron transport layer that replaces conventional metal oxides in SWIR PbS CQD photodetectors. The favorable band alignment and improved passivation of the QD-based transport layer results in a one-order-of magnitude suppression of the dark current down to ~1×10-6 A/cm2 while maintaining an external quantum efficiency ~70% at 1450 nm. I then apply the knowledge gained on CQD surface modification to devise an efficient ligand exchange route for small-bandgap PbS CQDs. In devices, the CQD solids give rise to an external quantum efficiency greater than 80% at 1550 nm, a measured detectivity of 8×1011 Jones, and a 10 ns response time. The studies in this thesis suggest future routes to sensitive, fast, and stable photodetectors that bring out the full potential of solution-processed materials in advanced light-sensing 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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".