A Charge-Orbital Balance Picture of Doping in Colloidal Quantum Dot Solids
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Bibliographic record
Abstract
We present a framework--validated using both modeling and experiment--to predict doping in CQD films. In the ionic semiconductors widely deployed in CQD films, the framework reduces to a simple accounting of the contributions of the oxidation state of each constituent, including both inorganic species and organic ligands. We use density functional theory simulations to confirm that the type of doping can be reliably predicted based on the overall stoichiometry of the CQDs, largely independent of microscopic geometrical bonding configurations. Studies employing field-effect transistors constructed from CQDs that have undergone various chemical treatments, coupled with Rutherford backscattering and X-ray photoelectron spectroscopy to provide compositional analysis, allow us to test and confirm the proposed model in an experimental framework. We investigate both p- and n-type electronic doping spanning a wide range of carrier concentrations from 10(16) cm(-3) to over 10(18) cm(-3), and demonstrate reversible switching between p- and n-type doping by changing the CQD stoichiometry. We show that the summation of the contributions from all cations and anions within the film can be used to predict accurately the majority carrier type. The findings enable predictable control over majority carrier concentration via tuning of the overall stoichiometry.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 it