Photoelectric conversion on Earth’s surface via widespread Fe- and Mn-mineral coatings
Bibliographic record
Abstract
Sunlight drives photosynthesis and associated biological processes, and also influences inorganic processes that shape Earth's climate and geochemistry. Bacterial solar-to-chemical energy conversion on this planet evolved to use an intricate intracellular process of phototrophy. However, a natural nonbiological counterpart to phototrophy has yet to be recognized. In this work, we reveal the inherent "phototrophic-like" behavior of vast expanses of natural rock/soil surfaces from deserts, red soils, and karst environments, all of which can drive photon-to-electron conversions. Using scanning electron microscopy, transmission electron microscopy, micro-Raman spectroscopy, and X-ray absorption spectroscopy, Fe and Mn (oxyhydr)oxide-rich coatings were found in rock varnishes, as were Fe (oxyhydr)oxides on red soil surfaces and minute amounts of Mn oxides on karst rock surfaces. By directly fabricating a photoelectric detection device on the thin section of a rock varnish sample, we have recorded an in situ photocurrent micromapping of the coatings, which behave as highly sensitive and stable photoelectric systems. Additional measurements of red soil and powder separated from the outermost surface of karst rocks yielded photocurrents that are also sensitive to irradiation. The prominent solar-responsive capability of the phototrophic-like rocks/soils is ascribed to the semiconducting Fe- and Mn (oxyhydr)oxide-mineral coatings. The native semiconducting Fe/Mn-rich coatings may play a role similar, in part, to photosynthetic systems and thus provide a distinctive driving force for redox (bio)geochemistry on Earth's surfaces.
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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".