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Record W4402733985 · doi:10.1002/anie.202415936

Hollow Hydrogels for Excellent Aerial Water Collection and Autonomous Release

2024· article· en· W4402733985 on OpenAlexfundno aff
Shumin Liang, Tao Chen, Pancě Naumov, Lidong Zhang

Bibliographic record

VenueAngewandte Chemie International Edition · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsnot available
FundersTamkeenNational Natural Science Foundation of ChinaYork UniversityNew York University Abu DhabiNatural Science Foundation of Shanghai
KeywordsSelf-healing hydrogelsEnvironmental scienceMaterials sciencePolymer chemistry

Abstract

fetched live from OpenAlex

Air moisture is a valuable and omnipresent resource of fresh water. However, traditional water collectors come with an enduring problem of the water-release step, which requires special devices and additional energy to remove the water from the adsorbent, such as heat, sunlight, or both. Herein, we report the first composite conical hollow hydrogel architecture fabricated through a film-to-tube transforming protocol, designed to harvest water from aerial humidity. This hollow hydrogel device can rapidly collect water from humid air to a saturation point, whereupon it automatically and continually releases fresh water at room temperature. The entire water collection and release process does not require any external assistance. Therefore, this device is highly suitable for emergency water collection in arid areas. As an exemplary demonstration, positioning the hollow hydrogel device next to a plant turns into an individualized system for irrigation. Since the device is biodegradable, it eventually decomposes and becomes an organic fertilizer after the water supply is not required. For long-term application, the water-release process can be monitored in real time by an electronic device to indicate the amount of collected water. The hollow hydrogel combines the humidity-adsorbing capacity with autonomous water release that carries the potential for harvesting water from humidity to address the shortage of fresh water, especially in arid locations where other sources of water are scarce or inaccessible.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.019
GPT teacher head0.260
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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