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Record W2563459173 · doi:10.1002/ente.201600703

The Water–Energy Nexus: Solutions towards Energy‐Efficient Desalination

2016· article· en· W2563459173 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.

Bibliographic record

VenueEnergy Technology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Ottawa
FundersMinistry of Higher Education, Malaysia
KeywordsDesalinationGeothermal desalinationWater-energy nexusRenewable energyEnergy consumptionEfficient energy useEnvironmental scienceProduction (economics)Reverse osmosisEnvironmental economicsWaste managementEnvironmental engineeringNexus (standard)Process engineeringEngineeringEconomicsChemistry

Abstract

fetched live from OpenAlex

Abstract Global water shortages across all continents have led to the explosive practice of desalination. However, desalination is undeniably recognized as one of the most energy‐intensive techniques for creating a clean and safe water supply. Cost reduction in different aspects is necessary to make desalination processes affordable and accessible. In fact, the cost of water from desalination facilities is momentously impacted by the energy requirements for water production. As the water production cost cannot be separated from the issue of energy, the desalination community is continuously seeking ways to reduce energy consumption further. Current research focuses on assessing and alleviating the major energy issues by finding ways to improve the energy efficiency of desalination facilities, which would pave the way for overall cost reduction. Improving the process and the efficiencies of materials implies improved water quality and an increase in the quantity produced per unit of energy consumed. This review highlights recent emerging approaches that aim to reduce the energy consumption and, hence, the water production cost of desalination technology. In brief, the advances made in membrane science and technology, the development of emerging desalination processes and their integrated systems, as well as the use of renewable energy and energy‐recovery systems are recognized as effective and feasible solutions towards energy‐efficient desalination to address the water crisis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.895
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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