Insights into the interfacial dynamics and interaction mechanisms between phosphate-solubilizing bacteria and straw-derived biochar
Bibliographic record
Abstract
Abstract To alleviate soil phosphorus deficiency, integrating straw-derived biochar with phosphate-solubilizing bacteria (PSB) has been recognized as a promising solution and is gaining growing attention. However, the mechanisms of bacterial immobilization and the influences of the physicochemical attributes of biochar remain unclear. In this study, we investigated the single-cell interactions of gram-negative Acinetobacter pittii and gram-positive Bacillus subtilis with cotton straw-derived biochars, subjected to progressively increasing pyrolysis temperatures, to understand the attributes of gradually modified biochar properties. The results revealed the correlations between adhesion forces and biochar properties (e.g., surface area and surface charge), and the strongest adhesion for both strains for the biochar pyrolyzed at 700 °C. The extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) model, structured to predict interaction energy, was subsequently compared with experimental observations made using atomic force microscopy (AFM). Discrepancies between the predicted high adhesion barriers and the observed attraction suggested that forces beyond Lifshitz-van der Waals also influenced the immobilization of PSB. Adhesion-distance spectroscopy and XDLVO theory jointly revealed four distinct phases in the immobilization process by biochar: planktonic interaction, secondary minimum entrapment, primary barrier transcendence, and initial reversible adherence, collectively facilitating biofilm formation. Notably, initial reversible adhesion positively correlated with increased protein and polysaccharide levels in extracellular polymeric substances (EPS) (R 2 > 0.67), highlighting its importance in biofilm formation. Unraveling PSB–biochar interactions can improve the effectiveness of soil inoculants, thereby enhancing phosphorus availability in soil, a crucial factor for promoting plant growth and supporting environmental sustainability. Graphical Abstract
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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".