Simple and Accurate Calibration of the Flory-Huggins Interaction Parameter
Bibliographic record
Abstract
This work improves on a standard method used to calibrate χ, the Flory-Huggins interaction parameter, in experimental systems. The common method is to fit the order-disorder transition (ODT) of symmetric diblock copolymer melts to the mean-field prediction (χN)_{ODT} = 10.495. This work improves the calibration by using the more accurate prediction of (χN)_{ODT} from Morse and coworkers, correcting for the small degrees of polydispersity and compositional asymmetry that exist in real diblock copolymers. To find the correction, polydisperse lattice simulations are conducted over a wide range of invariant \npolymerization indices. The correction for compositional asymmetry is extracted from simulations for asymmetric diblocks conducted by Ghasimakbari and Morse. This improved calibration is demonstrated for 19 different chemistries, using previously published data from experiments. This calibration provides a considerable increase in accuracy, while still being simple to apply.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".