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Record W4400581642 · doi:10.1021/acs.langmuir.4c01385

High-Efficiency Photothermal Water Evaporation under Low-Intensity Sunlight Using Wood Biochar Monolith

2024· article· en· W4400581642 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLangmuir · 2024
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiocharMonolithEvaporationPhotothermal therapyChemistrySunlightAdsorptionLight intensityIntensity (physics)Chemical engineeringEnvironmental chemistryMaterials sciencePyrolysisNanotechnologyCatalysisOptics

Abstract

fetched live from OpenAlex

Utilizing energy directly from the sun, solar water evaporation drives the global hydrological cycle and produces freshwater from saline water in the oceans and on land. As water is a poor solar absorber, a photothermal material is needed to facilitate the conversion of photons to thermal energy and increase the efficiency of solar desalination. However, the current photothermal materials are less efficient and expensive to be manufactured. Inspired by nature, we created a new photothermal material called a wood biochar monolith (WBM) by carbonizing wood using the pyrolysis process at 1000 °C and subsequently steaming at high pressure. Under low light intensity (193 W/m 2 ), the light to vapor efficiency of maple WBM is more than 100%. The outstanding performance of WBM is attributed to (1) the facilitated water transport in the hierarchical, open-pore network preserved from the wood precursor in WBM and (2) the reduced evaporation enthalpy of confined water in WBM and the high broadband sunlight absorptivity of WBM. Moreover, the high evaporation rate causes the temperature of WBM to be lower than that of the surrounding water, enabling thermal energy harvesting by WBM from water and making a light-to-vapor efficiency of >100% feasible. This discovery offers opportunities for developing low-cost, high-performance water desalination or humidification devices deployable in remote areas with nonconcentrated natural sunlight.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.021
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)0.0010.001

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 head0.030
GPT teacher head0.285
Teacher spread0.256 · 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