Designable excitonic effects in van der Waals artificial crystals with exponentially growing thickness
Bibliographic record
Abstract
When disassembled into monolayers from their bulk crystals, two-dimensional (2D) transition metal dichalcogenides (TMDCs) exhibit exotic optical properties dominated by strong excitonic effects. Reassembling 2D TMDC layers to build bulk excitonic crystals can significantly boost their optical performance and introduce emerging functionalities toward optoelectronic and valleytronic applications. However, maintaining or manipulating 2D excitonic properties in bulk structures or superlattices is challenging. Herein, we developed a method to precisely construct m∙2N-layer artificial excitonic crystals with only a number N of stacking operations (m denotes the layer number of the initial material unit), referred to as the “2^N method”. We successfully fabricated a millimeter-scale weakly coupled 16-layer MoS2 single crystal with zero interlayer twist angle, which retains monolayer-like exciton properties and exhibits remarkable enhancements up to 643% and 646% in their absorption and photoluminescence (PL) features, respectively. Moreover, we created a WSe2/(MoS2/WSe2)3/MoS2 superlattice starting from monolayer WSe2 and MoS2, which demonstrated an intensity increase of up to 400% in quadrupolar interlayer exciton (IX) emission as compared to dipolar IXs in its bilayer counterpart. Our work shows a promising approach for the design and bottom-up fabrication of excitonic crystals, promoting the exploration of excitonic physics in complex van der Waals (vdW) structures and their applications in optoelectronic devices. The fabrication of artificial crystals by reassembling monolayer semiconductors enables on-demand engineering of their excitonic properties. Here, the authors report an efficient stacking method to fabricate millimetre-scale van der Waals homo-/hetero-crystals, demonstrating enhanced monolayer-like photoluminescence emission and quadrupolar interlayer exciton emission.
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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".