Effect of Bacillus and Pseudomonas biofilms on the corrosion behavior of AISI 304 stainless steel
Bibliographic record
Abstract
In this research work, the corrosion tendency of stainless steel (SS 304) caused by the Pseudomonas aeruginosa ZK (PA-ZK) and Bacillus subtilis S1X (BS-S1X) bacterial strains is investigated. The topographical features of the biofilms and SS304 substrate achieved after 14 days of incubation at 37 °C were examined by scanning electron microscopy (SEM). Fourier Transform Infrared Spectroscopic (FTIR) analysis of the extracellular polymer substance (EPS) was also carried out to estimate the chemical composition of the biofilm. Electrochemical Impedance Spectroscopy (EIS) and Tafel Polarization test methods were applied to understand the in-situ corrosion tendency of the SS304 in the presence of PA-ZK and BS-S1X strains. Compared to the biofilm produced by the PA-ZK, the EPS in the BS-S1X containing bacteria was porous and non-uniform as revealed in the SEM analysis. The improved hydrophobicity and uniformity of the PA-ZK containing biofilm retarded the corrosion of the underlying SS304 sample. Appreciably large resistance of the PA-ZK biofilm (~ 6.04 kΩ-cm2) and hindered charge transport (11.12 kΩ-cm2) was evident from the EIS analysis. In support of these results, a large cathodic Tafel slope (0.2 V/decade) and low corrosion rate (1.69 µA/cm2) were corroborated to the inhibitive properties of the PA-ZK containing biofilm. However, the formation of porous biofilm and non-homogeneity of the EPS layer produced by the BS-S1X bacteria enhanced localized corrosion as evident from the low charge transfer resistance, a high corrosion rate and formation of pits on the surface of SS304 were comparable to the surface features obtained after exposure to the controlled medium. These results highlighted the poor corrosion inhibitive properties of the BS-S1X bacteria compared to the PK-ZK bacterial strain.
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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) | 0.001 | 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".