Functional Materials for Microsystems: Smart Self-Assembled Photochromic Films: Final Report
Bibliographic record
Abstract
This project set out to scientifically-tailor ''smart'' interfacial films and 3-D composite nanostructures to exhibit photochromic responses to specific, highly-localized chemical and/or mechanical stimuli, and to integrate them into optical microsystems. The project involved the design of functionalized chromophoric self-assembled materials that possessed intense and environmentally-sensitive optical properties (absorbance, fluorescence) enabling their use as detectors of specific stimuli and transducers when interfaced with optical probes. The conjugated polymer polydiacetylene (PDA) proved to be the most promising material in many respects, although it had some drawbacks concerning reversibility. Throughout his work we used multi-task scanning probes (AFM, NSOM), offering simultaneous optical and interfacial force capabilities, to actuate and characterize the PDA with localized and specific interactions for detailed characterization of physical mechanisms and parameters. In addition to forming high quality mono-, bi-, and tri-layers of PDA via Langmuir-Blodgett deposition, we were successful in using the diacetylene monomer precursor as a surfactant that directed the self-assembly of an ordered, mesostructured inorganic host matrix. Remarkably, the diacetylene was polymerized in the matrix, thus providing a PDA-silica composite. The inorganic matrix serves as a perm-selective barrier to chemical and biological agents and provides structural support for improved material durability in microsystems. Our original goal was to use the composite films as a direct interface with microscale devices as optical elements (e.g., intracavity mirrors, diffraction gratings), taking advantage of the very high sensitivity of device performance to real-time dielectric changes in the films. However, our optical physics colleagues (M. Crawford and S. Kemme) were unsuccessful in these efforts, mainly due to the poor optical quality of the composite films.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".