Bibliographic record
Abstract
Two dimensional (2D) van der Waals materials with a lattice mismatch or a relative twist angle, stacked atop each other forms a moiré superlattice. The electronic properties of such a system can be modified by controlling the relative twist angle between the layers, the most famous example being magic-angle twisted bilayer graphene. Since the observation of correlated insulator states and superconductivity in this flat band moiré system, investigations on other 2D moiré systems has gathered pace. Two Bernal stacked bilayer graphene sheets twisted relative to each other, i.e., twisted double bilayer graphene, gives the additional opportunity of tuning the electronic structure by a displacement electric field. This thesis presents the fabrication and electrical transport measurements of twisted double bilayer graphene devices. In order to compare the efficacy of various fabrication techniques, we fabricated the devices using two different modified dry transfer techniques: “tear-and-stack” and “cut-and-stack”. By calculating the twist angles from the electrical transport data, we find the “cut-and-stack” technique to give a better control of the twist angle of the fabricated devices. Subsequently, we studied the transport properties of a device with a twist angle of 1.39 degree, in order to replicate the electronic phase diagram of twisted double bilayer graphene devices. Tuning the displacement electric field and carrier density independently in a double gated geometry, we were able to observe correlated insulating states at quarter, half and three-quarter filling of the moiré band for a range of electric field values. The evolution of these insulating states in an in-plane magnetic field suggests spin/valley polarization. Additionally, the metallic states surrounding the correlated insulating state at half-filling displays a strong temperature dependence and nonlinear current-voltage characteristics, the nature of which remains ambiguous in our measurements.
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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".