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Comparative Degradation of LDPE, HDPE and HMHDPE under Different Soil Conditions

2014· article· en· W2097442069 on OpenAlexafffundvenue
Mohan K.R. Konduri, Venkata Reddy Bogolu

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsLakehead University
FundersLakehead University
KeywordsHigh-density polyethyleneLow-density polyethylenePolyethyleneElongationMaterials scienceUltimate tensile strengthDegradation (telecommunications)Composite materialFourier transform infrared spectroscopyChemical engineering

Abstract

fetched live from OpenAlex

The Present work includes, degradation of polyethylene under different environmental conditions to know the effect of physical, chemical and biological factors prevailing in those conditions on degradation of polyethylene. Plastic films viz., Low density polyethylene (LDPE), High density polyethylene (HDPE) and High molecular weight high density polyethylene (HMHDPE) each were incubated in three different conditions viz., black soil, sandy soil and red soil for a period of 3 months. The changes in the properties of plastic films after incubation was studied by change in the weight of the plastic film and mechanical parameters like tensile strength, breaking load and percentage of elongation. Among all the plastic films HDPE was found to be highly susceptible with 33% weight loss and 40% reduction in percentage of elongation compared to LDPE with 26% weight loss and 34 % reduction in percentage of elongation in black soil. Whereas HMHDPE found to be highly resistant in all the soils with no significant weight loss and percentage of elongation (15%). None of the plastic films had shown degradation in sandy soil even after incubation for 3 months. FTIR spectroscopy results showed that HDPE film incubated in black soil had undergone extensive degradation when compared with un incubated HDPE film.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.036
GPT teacher head0.343
Teacher spread0.308 · 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

Citations2
Published2014
Admission routes3
Has abstractyes

Explore more

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