Multilayered optofluidics for sustainable buildings
Bibliographic record
Abstract
Indoor climate control is among the most energy-intensive activities conducted by humans. A building facade that can achieve versatile climate control directly, through independent and multifunctional optical reconfigurations, could significantly reduce this energy footprint, and its development represents a pertinent unmet challenge toward global sustainability. Drawing from optically adaptive multilayer skins within biological organisms, we report a multilayered millifluidic interface for achieving a comprehensive suite of independent optical responses in buildings. We digitally control the flow of aqueous solutions within confined milliscale channels, demonstrating independent command over total transmitted light intensity (95% modulation between 250 and 2,500 nm), near-infrared-selective absorption (70% modulation between 740 and 2,500 nm), and dispersion (scattering). This combinatorial optical tunability enables configurable optimization of the amount, wavelength, and position of transmitted solar radiation within buildings over time, resulting in annual modeled energy reductions of more than 43% over existing technologies. Our scalable "optofluidic" platform, leveraging a versatile range of aqueous chemistries, may represent a general solution for the climate control of buildings.
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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 | 0.001 |
| 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".