Inorganic Tin Perovskites with Tunable Conductivity Enabled by Organic Modifiers
Bibliographic record
Abstract
Achieving control over the transport properties of charge-carriers is a crucial aspect of realizing high-performance electronic materials. In metal-halide perovskites, which offer convenient manufacturing traits and tunability for certain optoelectronic applications, this is challenging: The perovskite structure itself, poses fundamental limits to maximum dopant incorporation. Here, we demonstrate an organic modifier incorporation strategy capable of modulating the electronic density of states in halide tin perovskites without altering the perovskite lattice, in a similar fashion to substitutional doping in traditional semiconductors. By incorporating organic small molecules and conjugated polymers into cesium tin iodide (CsSnI3) perovskites, we achieve carrier density tunability over 2.7 decades, transition from a semiconducting to a metallic nature, and high electrical conductivity exceeding 200 S/cm. We leverage these tunable and enhanced electronic properties to achieve a thin-film, lead free, thermoelectric material with a near room-temperature figure-of-merit (ZT) of 0.21, the highest amongst all halide perovskite thermoelectrics. Our strategy provides an additional degree of freedom in the design of halide perovskites for optoelectronic and energy applications.
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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".