Validation of Roofing Membrane Composition by NMR: Products of Ketone-Ethylene Ester and Polyvinyl Chloride
Bibliographic record
Abstract
Roofing membranes produced with ketone-ethylene-ester (KEE) and polyvinyl chloride (PVC) are defined within the standard specification for KEE-based sheet roofing, ASTM D6754, Standard Specification for Ketone Ethylene Ester Based Sheet Roofing, in which it is specified that such membranes must contain at least 50% (wt.) KEE. Until the recent release of ASTM D8154, Standard Test Methods for 1H-NMR Determination of Ketone-Ethylene-Ester and Polyvinyl Chloride Contents in KEE-PVC Roofing Fabrics, in which the determination of KEE content is based on nuclear magnetic resonance (NMR) spectroscopy, no method was sufficiently precise or accurate to measure the KEE content within 1% or better. In this paper, a description is provided of the development and the basic process behind the use of 1H-NMR to establish KEE content in KEE/PVC membranes as described in ASTM D8154. To develop a quantitative method to assess KEE concentration in roofing membranes, several NMR approaches were used, including both solid-state and liquid-state NMR. Approaches using solid-state NMR, including carbon-13 and proton spectroscopy, proved inadequate for the quantification of KEE because of insufficient spectral resolution. Liquid-state NMR proved to be a better approach, but accurate results are achieved only after the KEE-PVC blend is extracted from the roofing membrane through a multistep process. The liquid-state NMR work led to two methods to quantitatively measure the KEE content in blends with PVC. Method A is the simplest, and its accuracy is better than 2.3%. Method B is more protracted, but its accuracy is better than 0.6%.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".