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Record W4312185084 · doi:10.1002/solr.202201014

Systematic Review of Material and Structural Design in Interfacial Solar Evaporators for Clean Water Production

2022· article· en· W4312185084 on OpenAlexaff
Yuxuan Ren, Rufan Zhou, Ruijie Yang, Tao Dong, Qingye Lu

Bibliographic record

VenueSolar RRL · 2022
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRenewable energyEvaporationSolar energyEnvironmental scienceProcess engineeringVaporizationEngineering physicsMaterials scienceEnvironmental engineeringEngineeringMeteorologyChemistry

Abstract

fetched live from OpenAlex

Rational and sustainable utilization of resources is critical for the continuous development of this society. Solar energy, as one of the renewables, shows great potential in replacing part of the traditional energy supplies since it is clean, abundant, and easily convertible to thermal, electrical, and biological energies. Using solar energy as the green driving force, interfacial solar evaporation is a promising way for clean water production to alleviate global water shortage, taking advantage of its high evaporation efficiency (more than 80%) and strong adaptability toward various water sources and fields. In recent years, various kinds of materials with diverse designs have been synthesized and applied in interfacial solar evaporation for clean water production. Herein, recent progress in interfacial solar evaporators for clean water production is systematically reviewed, based on the photothermal conversion mechanisms of solar absorbers, including carbonous, semiconductor‐based, and plasmatic ones. Furthermore, key design factors and strategies in interfacial solar evaporators are reviewed and discussed from material and structural design point of view, such as water transport, thermal management, latent heat for water vaporization, and salt accumulation. Finally, some perspectives related to resolving existing problems in the field are given.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.027
GPT teacher head0.289
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations36
Published2022
Admission routes1
Has abstractyes

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