Tunable Shortwave Infrared and Midwave Infrared Optoelectronics in Germanium/Germanium Tin Core/Shell Nanowires
Bibliographic record
Abstract
Semiconductor nanowire(NW)-based optoelectronic devices can exhibit superior performances in comparison to their thin film counterparts, as a result of their improved electrical and optical properties. For example, the light-matter interaction in nanowires is enhanced due to the high surface-volume ratio and the light confinement effect resulting from the resonant cavity formed by the nanowire. The enhanced light absorption when using a nanowire geometry can be exploited to increase the responsivity of nanowire-based photodetectors. Light detection and emission at near-IR wavelengths (NIR, 0.8-1.5 μm) can be tailored via strain engineering using Ge-based NW devices.[1] Furthermore, by incorporating Sn in the Ge lattice a direct band gap can be achieved across the short-wave-IR (SWIR, 1.5-3.0 μm) and mid-IR (MIR, 3-8 μm) wavelength range.[2] Despite the equilibrium solubility of Sn in Ge being limited to ~1at.%, non-equilibrium growth methods recently developed in a chemical vapor deposition (CVD) reactor demonstrated a Sn content of 18 at.% with a room-temperature photoluminescence emission up to 4.0 μm [3]. Similarly, when moving to the nanoscale a Sn incorporation well above 10 at.% with a direct band gap emission was demonstrated using Ge/GeSn core/shell NWs.[4] In this presentation, we will discuss the opto-electronic properties of Ge and Ge/GeSn core/shell NWs grown in a CVD reactor using a Ge or Si (111) substrate. The structural properties of the NWs were evaluated by combining Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM) and Atom Probe Tomography (APT) in order to understand the nanowire growth direction, crystalline properties as well as Sn distribution uniformity in the shell of the nanowires. Photoluminescence, absorption and Raman measurements will elucidate the effect of strain on the MIR direct bandgap emission/absorption of the GeSn shell. Finally, wewill discuss the electrical characterization of individual Ge and GeSn NW photodetectors. Our devices are fabricated by Electro-Beam Photolithography (EBL) based on metal-semiconductor-metal (M-S-M) structure to address the dependence of the photocurrent under illumination at different SWIR-MIR wavelengths. The time response and transport properties of Ge and Ge/GeSn core/shell NW Field Effect Transistor (FET) in back-gated structure are compared with their counterparts of conventional thin film heterostructures. References Pilon, FT Armand, et al. "Lasing in strained germanium microbridges." Nature communications1 (2019): 1-8. Assali, S., J. Nicolas, and O. Moutanabbir. "Enhanced Sn incorporation in GeSn epitaxial semiconductors via strain relaxation." Journal of Applied Physics2 (2019): 025304. Assali, S., et al. "Atomically uniform Sn-rich GeSn semiconductors with 3.0–3.5 μ m room-temperature optical emission." Applied Physics Letters25 (2018): 251903. Assali, S., et al. "Growth and optical properties of direct band gap Ge/Ge0. 87Sn0. 13 core/shell nanowire arrays." Nano letters3 (2017): 1538-1544.
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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".