Study of a hydrogen-bombardment process for molecular cross-linking within thin films
Bibliographic record
Abstract
A low-energy hydrogen bombardment method, without using any chemical additives, has been designed for fine tuning both physical and chemical properties of molecular thin films through selectively cleaving C-H bonds and keeping other bonds intact. In the hydrogen bombardment process, carbon radicals are generated during collisions between C-H bonds and hydrogen molecules carrying ∼10 eV kinetic energy. These carbon radicals induce cross-linking of neighboring molecular chains. In this work, we focus on the effect of hydrogen bombardment on dotriacontane (C(32)H(66)) thin films as growing on native SiO(2) surfaces. After the hydrogen bombardment, XPS results indirectly explain that cross-linking has occurred among C(32)H(66) molecules, where the major chemical elements have been preserved even though the bombarded thin film is washed by organic solution such as hexane. AFM results show the height of the perpendicular phase in the thin film decreases due to the bombardment. Intriguingly, Young's modulus of the bombarded thin films can be increased up to ∼6.5 GPa, about five times of elasticity of the virgin films. The surface roughness of the thin films can be kept as smooth as the virgin film surface after thorough bombardment. Therefore, the hydrogen bombardment method shows a great potential in the modification of morphological, mechanical, and tribological properties of organic thin films for a broad range of applications, especially in an aggressive environment.
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.
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".