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Record W4417264137 · doi:10.1007/s43939-025-00493-3

The impacts of compaction on the properties of mycelium-based materials

2025· article· en· W4417264137 on OpenAlexaff
Yang Qiu, Georg Hausner, Qiuyan Yuan

Bibliographic record

VenueDiscover Materials · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCompactionAbsorption of waterCompressive strengthExpanded polystyreneWater contentPolystyreneProctor compaction test

Abstract

fetched live from OpenAlex

Abstract Mycelium-based materials (MBMs) are a new type of biomaterial made of mycelium and lignocellulosic wastes. Due to their environmental friendliness, they offer an alternative to expanded polystyrene (EPS) as packaging materials. This study assessed the effects of compaction on MBMs’ characteristics. Three mycelium-generating strains and three types of substrates were utilized to produce MBMs using different protocols. As part of the various protocols compacted samples and uncompacted samples were applied. The physical and mechanical properties of MBMs are essential for their application in the packaging industry. Dry density, water absorption, and compressive properties were compared between MBMs with applied compaction and those without compaction. Compacted samples in this study showed a 9.57–34.29% increase in dry density, but the value was still lower than that of pulp moulding packaging (0.2–1.0 g/cm 3 ), a commonly used green packaging material nowadays. Compacted samples also saw a 28.57–129.63% increase in compressive strength at 10% strain, a 37.32–139.42% increase at 35% strain, and a 27.66–142.35% increase in compressive Young’s modulus. The impact of compaction on the water absorption of the MBM samples varied depending on the samples’ recipes/composition. At 60% RH, the weight gain ranged from 4.49 to 7.21% and 4.59% to 6.98% for samples without compaction and with compaction, respectively. At 80% RH, the weight increase of uncompacted and compacted samples was 10.68–15.42% and 11.02–19.04%, respectively.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.157

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.214
Teacher spread0.193 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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