Janus Cellular Design Drives Solar‐Powered Spatial Lithium Extraction and Water Co‐Generation from Salt‐Lake Brines
Bibliographic record
Abstract
Abstract Lithium plays a vital role in energy storage technologies, with global demand rapidly increasing. Current adsorption‐based direct lithium extraction from salt‐lake brines holds promise but suffers from low ion extraction efficiency due to sluggish intercalation kinetics and poor selectivity, necessitating repeated cycles that increase water and energy consumption. Here, a Janus cellular‐structured solar‐powered platform (JCSP) is developed for energy‐efficient lithium extraction and sustainable water harvesting. The cellular platform features a symmetrical, multi‐branched cantilever geometry with distinct upper and lower lattice architectures, where the lower lattice is functionalized with titanium‐based porous adsorbents. This rational lattice design and functionalized adsorption interfaces enhance light absorption, sustain evaporative flow, and create an ion diffusion gradient for selective lithium extraction. Its cantilever configuration enables a self‐flipping mechanism, preventing salt crystallization and ensuring long‐term stability in high‐salinity environments. This design boosts water evaporation efficiency to 3.85 kg m −2 h −1 , increases lithium adsorption capacity to 43.5 mg g −1 , and enhances Li + /Na + and Li + /Mg 2+ selectivity to 112 and 268, respectively, when treating multi‐ionic hypersaline environment (20 wt% total dissolved salt). The JCSP system demonstrates stable long‐term performance in water evaporation and lithium recovery under extreme conditions, providing a sustainable solution to global water scarcity and rising lithium demand.
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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".