Determining the molecular weight, aggregation, structures and interactions of natural organic matter using diffusion ordered spectroscopy
Bibliographic record
Abstract
Abstract Diffusion ordered spectroscopy (DOSY) was applied to examine the chemical and physical properties of soil organic matter, a complex natural mixture. Soil organic matter extracts are often termed humic substances (HS), which traditionally have been thought to be high molecular weight, cross‐linked macromolecules with undetermined structures. Separation of the components in the studied humic acid (HA) clearly indicates that the HS studied here are pseudo‐high molecular weight materials only, and associations or aggregates of molecules of smaller molecular sizes, which can be disrupted with organic acids. At high concentration, these aggregates display diffusivities that are consistent with those observed in large proteins (>66 kDa). After disaggregation and at low concentration, DOSY NMR reveals components that have chemical shifts that are consistent with lignins, polysaccharides and peptides, and have diffusivities consistent with molecular weights of ∼2500, ∼1000 and 200–600 Da, respectively. Diffusion studies of fulvic acids (FA) indicate that little if any aggregation occurs in solution and that, on average, the components display diffusivities that are consistent with molecules that have relatively low molecular weights of ∼1000 Da. However, in addition to a range of small molecular components, DOSY NMR reveals for the first time direct evidence that larger molecular weight components also exist within the mixtures. In an FA isolated from the surface soil of an oak forest, large polysaccharides with average diffusivities similar to 6000 Da maltodextrins can be identified. In an FA from an agricultural soil, components consistent with peptides/proteins are identified that have aggregate/molecular sizes in the region of 12 000 Da. It is logical that an operationally defined extract of soils will result in a mixture of plant components at various stages of humification with a range of molecular sizes and structures rather than macromolecules with undetermined structures. In addition to advancing our structural understanding of natural organic matter (NOM), DOSY provides potential to study the interactions of these mixtures with contaminants. This paper explorers the interaction of a HA with two organic contaminants (MTBE and chlorsulfuron) and an FA with cadmium. Diffusion measurements show that MTBE has a weaker interaction with the organic materials than chlorsulfuron. Studies with cadmium suggest that the metal exhibits dynamic exchange which is fast on the NMR time‐scale. Such findings have strong implications for understanding the behavior and toxicity of cadmium in the environment. Although cadmium has an affinity for NOM, it is clear that it is not irreversibly bound and may be bioavailable under many conditions. Copyright © 2002 John Wiley & Sons, Ltd.
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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 | 0.000 | 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 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".