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Record W2022459714 · doi:10.1155/2013/686981

Reuse Feasibility of Electrocoagulated Metal Hydroxide Sludge of Textile Industry in the Manufacturing of Building Blocks

2013· article· en· W2022459714 on OpenAlexaff
Tanveer M. Adyel, Syed Hafizur Rahman, Mohammad Moniruz Zaman, Hossain Md. Sayem, Mala Khan, M. A. Gafur, S. M. Nazrul Islam

Bibliographic record

VenueJournal of Waste Management · 2013
Typearticle
Languageen
FieldEngineering
TopicRecycling and utilization of industrial and municipal waste in materials production
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsReuseWaste managementEnvironmental scienceUSableShrinkagePulp and paper industryMaterials scienceComposite materialEngineering

Abstract

fetched live from OpenAlex

During the last decade, the growing load of sludge from textile industries, the top foreign exchange earning sector of Bangladesh, is a common nuisance to environmental system and community health. The present study was aimed to minimize the environmental impact from the disposal of Electrocoagulated Metal Hydroxide Sludge (EMHS) by using it as a partial substitute of clay in the manufacturing of construction material like building blocks (BBs). Different batches of normal and pressurized building blocks (NBBs and PBBs, resp.) were prepared using up to 50% EMHS with clay and then fired at a particular temperature. EMHS proportion in the mixture and firing temperature were two key factors determining the quality of BB. BB did not show any deformation or uneven surfaces at any of the examined firing temperature. At higher firing temperature and EMHS proportion, more weight loss and shrinkage of BB were noticed. Higher compressive strength and lower water adsorption were found at lower EMHS content and higher firing temperature. It was explored that NBB and PBB with 20 and 30% EMHS in clay, respectively, and fired at 1050 °C would be usable for nonloading applications; namely, ornamental bricks, decoration purposes, and fence of garden.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.025
GPT teacher head0.256
Teacher spread0.232 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations21
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Waste ManagementSame topicRecycling and utilization of industrial and municipal waste in materials productionFrench-language works237,207