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Record W3206430249 · doi:10.3390/app11209605

Applications of Plant Polymer-Based Solid Foams: Current Trends in the Food Industry

2021· article· en· W3206430249 on OpenAlexaff
Marcela Jarpa–Parra, Lingyun Chen

Bibliographic record

VenueApplied Sciences · 2021
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsUniversity of Alberta
FundersComisión Nacional de Investigación Científica y Tecnológica
KeywordsMaterials sciencePolymerNanotechnologyProcess engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

Foams are a type of material of great importance, having an extensive range of applications due to a combination of several characteristics, such as ultra-low density, tunable porous architecture, and outstanding mechanical properties. The production of polymer foams worldwide is dominated by those based on synthetic polymers, which might be biodegradable or non-biodegradable. The latter is a great environmental concern and has become a major waste management problem. Foams derived from renewable resources have aroused the interest of researchers, solid foams made from plant polymers in particular. This review focuses on the development of plant polymer-based solid foams and their applications in the food industry over the last fifteen years, highlighting the relationship between their material and structural properties. The applications of these foams fall mainly into two categories: edible foams and packaging materials. Most plant polymers utilized for edible applications are protein-based, while starch and cellulose are commonly used to produce food packaging materials because of their ready availability and low cost. However, plant polymer-based solid foams exhibit some drawbacks related to their high water absorbency and poor mechanical properties. Most research has concentrated on improving these two physical properties, though few studies give a solid understanding and comprehension of the micro- to macrostructural modifications that would allow for the proper handling and design of foaming processes. There are, therefore, several challenges to be faced, the control of solid foam structural properties being the main one.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.052
GPT teacher head0.282
Teacher spread0.230 · 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

Citations26
Published2021
Admission routes1
Has abstractyes

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