Isotopic fractionation by diffusion in groundwater
Bibliographic record
Abstract
During the last decade, isotopic fractionation has gained acceptance as an indicator of microbiological and chemical transformations of contaminants in groundwater. These transformation processes typically favor isotopically light, compared to isotopically heavy, contaminants, resulting in enrichment of the latter in the residual aqueous phase. In these isotope applications, it has been generally presumed that physical transport processes in groundwater have a negligible effect on isotopic enrichment. It is well known, however, that aqueous phase diffusion generally proceeds faster for isotopically light, compared to isotopically heavy, solute molecules, often resulting in isotopic fractionation in groundwater. This paper considers the potential for isotopic fractionation during transport in groundwater resulting from minute isotopic effects on aqueous diffusion coefficients. Analyses of transport in heterogeneous systems delimit the viable range of isotopic fractionation by diffusion in groundwater. Results show that diffusion can result in similar degrees of depletion and enrichment of isotopically heavy solutes during transport in heterogeneous systems with significant diffusion rate–limited mass transfer between fast‐ and slow‐flow zones. Additional analyses and examples explore conditions that attenuate the development of significant fractionation. Examples are presented for 13C methyl tertiary butyl ether and deuterated and nondeuterated isopropanol and tertiary butyl alcohol using aqueous diffusion coefficients measured by the Taylor dispersion method with refractive index profiling as a part of this study. Examples elucidate the potential for diffusive fractionation as a confounder in isotope applications and emphasize the importance of hydrogeologic analysis for assessing the role of diffusive fractionation in isotope applications at contaminant field sites.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".