Heat and hydrogen co-production based on photoresponsive electrode in the full-spectrum SOEC hybrid system
Bibliographic record
Abstract
Facing the growing demand for clean and efficient energy conversion, this study presents the first full-spectrum SOEC hybrid system that co-produces heat and hydrogen by integrating a photoresponsive electrode. The electrode is directly irradiated to generate an additional photocurrent, thereby boosting hydrogen yield, while spectral splitting technology simultaneously supplies the SOEC with both heat and electricity. A comprehensive modeling framework, including the SOEC, balance of plant, and solar photoresponsive models, is developed to evaluate system energy and water flow and to analyze factor interactions within the photoresponsive material. Under optimized conditions, the system achieves an exergy efficiency of 58.98%, a solar-to-hydrogen (STH) efficiency of 28.30%, and a solar-to-thermal (STT) efficiency of 43.78%, offering new theoretical insights and practical design rules for highly efficient, flexible full-spectrum solar hydrogen production. A full-spectrum SOEC system for co-production of heat and hydrogen was introduced. Direct solar irradiation enhances hydrogen output via photocurrent, achieving 58.98% exergy, 28.30% STH, and 43.78% STT efficiency under optimized conditions. • A full-spectrum SOEC system for co-production of heat and hydrogen. • Direct solar irradiation induces photocurrent to boost hydrogen output. • Output stable energy distribution across solar concentration ratios from 4 to 113. • Achieves 58.98% exergy efficiency under optimized conditions. • Achieves 28.30% STH and 43.78% STT efficiency under optimized conditions.
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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".