Structural Evolution of Millisecond Laser-Induced Metastable Crystalline GeTe
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Discovering new inorganic materials using solid-state synthesis in an accelerated fashion is difficult due their sluggish diffusion coefficients and long diffusion distances. Furthermore, high temperatures used in these reactions generally produce thermodynamically stable products, which provides limited control on the reaction and prevents access to functional metastable phases. Herein, we report the use of a millisecond laser annealing technique to regulate the crystallographic phases of germanium telluride films of varying thicknesses. After laser heating, we combine temperature-dependent synchrotron grazing incidence measurements and transmission electron microscopy to study the structural evolution of the post-laser-heated GeTe. On average, we observe that millisecond laser heating induced the transformation of amorphous GeTe samples up to a ∼40% to 60% mixture of cubic β-GeTe ( Fm 3̅ m ) and rhombohedral α-GeTe ( R 3 m ) for GeTe films (thicknesses between 100 nm and 2 μm) deposited on thermally conducting substrates (such as Si), as opposed to phase-pure α-GeTe, which is obtained on low thermal conductivity substrates (quartz). Further, a room-temperature thermoelectric power factor of 6.10 μV cm –1 K –2 was measured for a laser-heated film on quartz. These findings suggest that conformal interfaces on substrates with high thermal conductivity facilitate accelerated rates of heat extraction at the sample–substrate interface to achieve phase control. We believe our strategy opens new avenues for the development of materials that are stabilized far from their equilibrium conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.006 | 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