Bacterial diversity and production of sulfide in microcosms containing uncompacted bentonites
Bibliographic record
Abstract
Aims This study examined the diversity and sulfide-producing activity of microorganisms in microcosms containing commercial clay products (e.g., MX-80, Canaprill and National Standard) similar to materials which are currently considered for use in the design specifications for deep geologic repositories (DGR) for spent nuclear fuel. Methods and results In anoxic microcosms incubated for minimum of 60 days with 10 g l-1 NaCl, sulfide production varied with temperature, electron donor and bentonite type. Maximum specific sulfide production rates of 0.189 d−1, 0.549 d−1 and 0.157 d−1 occurred in lactate-fed MX-80, Canaprill and National Standard microcosms, respectively. In microcosms with 50 g l-1 NaCl, sulfide production was inhibited. Denaturing gradient gel electrophoresis (DGGE) profiling of microcosms revealed the presence of bacterial classes Clostridia, Bacilli, Gammaproteobacteria, Deltaproteobacteria, Actinobacteria, Sphingobacteriia and Erysipelotrichia. Spore-forming and non-spore-forming bacteria were confirmed in microcosms using high-throughput 16S rRNA gene sequencing. Sulfate-reducing bacteria of the genus Desulfosporosinus predominated in MX-80 microcosms; whereas, Desulfotomaculum and Desulfovibrio genera contributed to sulfate-reduction in National Standard and Canaprill microcosms. Conclusions Commercial clays microcosms harbour a sparse bacterial population dominated by spore-forming microorganisms. Detected sulfate- and sulfur-reducing bacteria presumably contributed to sulfide accumulation in the different microcosm systems. Significance and impact of study The use of carbon-supplemented, clay-in-water microcosms offered insights into the bacterial diversity present in as-received clays, along with the types of metabolic and sulfidogenic reactions that might occur in regions of a DGR (e.g., interfaces between the bulk clay and host rock, cracks, fissures, etc.) that fail to attain target parameters necessary to inhibit microbial growth and activity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".