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Record W4411194816 · doi:10.1038/s41545-025-00484-0

A review of fundamentals, challenges, prospects, and emerging trends in hydrate-based desalination

2025· review· en· W4411194816 on OpenAlex
Rouhollah Jalili, Γεώργιος Κολλιόπουλος

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

Venuenpj Clean Water · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversité Laval
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsDesalinationNexus (standard)SustainabilityHydrateProcess engineeringEnvironmental scienceProcess (computing)Biochemical engineeringComputer scienceEngineeringChemistry

Abstract

fetched live from OpenAlex

Hydrate-based desalination (HBD) has emerged as a promising technology among conventional desalination methods due to its low energy consumption, wide operating window with regards to total dissolved solids (TDS), and efficient water recovery. This paper provides an in-depth review of the fundamental properties of hydrates, including thermodynamic and kinetic aspects of their formation. Then, it delves into recent advancements in thermodynamic and kinetic hydrate promoters that aim to address HBD's main challenge, which is the slow hydrate formation process. Subsequently, the review systematically examines environmental and toxicity concerns associated with chemicals used in HBD, addressing the growing demand for sustainable and biodegradable desalination solutions. Finally, a comparative analysis between HBD and conventional methods highlights its potential as an energy-efficient and selective desalination process poised to enhance sustainability within the water-energy-environment nexus.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.030
GPT teacher head0.298
Teacher spread0.267 · 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