Soft X-ray spectromicroscopic proof of a reversible oxidation/reduction of microbial biofilm structures using a novel microfluidic in situ electrochemical device
Bibliographic record
Abstract
Abstract In situ electrochemistry on micron and submicron-sized individual particles and thin layers is a valuable, emerging tool for process understanding and optimization in a variety of scientific and technological fields such as material science, process technology, analytical chemistry, and environmental sciences. Electrochemical characterization and manipulation coupled with soft X-ray spectromicroscopy helps identify, quantify, and optimize processes in complex systems such as those with high heterogeneity in the spatial and/or temporal domain. Here we present a novel platform optimized for in situ electrochemistry with variable liquid electrolyte flow in soft X-ray scanning transmission X-ray microscopes (STXM). With four channels for fluid control and a modular design, it is suited for a wealth of experimental conditions. We demonstrate its capabilities by proving the reversible oxidation and reduction of individual microbial biofilm structures formed by microaerophilic Fe(II)-oxidizing bacteria, also known as twisted stalks. We show spectromicroscopically the heterogeneity of the redox activity on the submicron scale. Examples are also provided of electrochemical modification of liquid electrolyte species (Fe(II) and Fe(III) cyanides), and in situ studies of electrodeposited copper nanoparticles as CO2 reduction electrocatalysts under reaction conditions.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".