Understanding and Controlling Polymer–Organometallic Precursor Interactions in Sequential Infiltration Synthesis
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
Sequential infiltration synthesis (SIS) is an emerging method for vapor-phase growth of inorganic materials within polymers that is utilized for hybrid organic–inorganic and inorganic nanostructure fabrication. The range of SIS applications has been continuously expanding for the past decade. A fundamental understanding of precursor–polymer interactions is, however, essential to expand the use of SIS to additional chemistries and move beyond thin film polymer templates. This work utilizes density functional theory (DFT) calculations and in situ gravimetric analysis to probe the growth mechanism of trimethylaluminum (TMA) within poly(methyl methacrylate) (PMMA) and poly(2-vinylpyridine) (P2VP). The theoretical and experimental analyses reveal that each precursor–polymer pair is characterized by a balance point temperature at which rates of forward and reverse precursor–polymer binding enable maximum mass gain at thermodynamic equilibrium. At short exposure times, mass gain is significantly influenced by the pressure profile of the process chamber. Mechanism comprehension enabled nanopatterning of a previously unsuitable block copolymer (BCP), polystyrene-block-P2VP (PS-b-P2VP), at elevated temperatures. It was proven possible to grow significant mass while maintaining the pattern by stabilizing the morphology via a single cycle at low-temperature SIS, thus overcoming self-assembly sensitivity to temperature.
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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 | 0.000 | 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 it