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Record W3128631256 · doi:10.1021/acssuschemeng.0c07996

Selective Laser Sintering of Lignin-Based Composites

2021· article· en· W3128631256 on OpenAlexaff
Rubina Ajdary, Niklas Kretzschmar, Hossein Baniasadi, Jon Trifol, Jukka Seppälä, Jouni Partanen, Orlando J. Rojas

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of British Columbia
FundersTekniikan EdistämissäätiöAcademy of Finland
KeywordsMaterials scienceLigninComposite materialSelective laser sinteringUltimate tensile strengthWettingComposite numberSinteringContact angle

Abstract

fetched live from OpenAlex

Lignin is introduced as a suitable component for selective laser sintering (SLS) of polyamide (PA12) to reduce costs while maintaining or improving processability and performance. Alkali lignin (sourced as a polydisperse, amorphous powder) was used at a volume concentration of up to 60 vol % for three-dimensional (3D) printing of complex, layered structures. The latter were obtained as high axial aspect objects, produced in flat, flipped (90°), and vertical directions, which were further examined to elucidate the effect of lignin as a suitable component in SLS. The composite withstood heating during SLS, and sintered PA/lignin showed 30% less degradation at elevated temperatures compared to pure PA. The morphological, wetting, mechanical, and thermal characteristics associated with the 3D-printed structures were compared. For instance, the strength and wettability were highly dependent on processing orientation. Compared to objects produced from neat PA, those that included lignin presented a higher porosity (∼10%) with a simultaneous increase in stiffness (increased Young modulus, by ∼16%, and reduced tensile strength, by ∼7%). Owing to differences in surface roughness and composition, an important difference in the water contact angle (CA) of the samples printed in the flipped and flat orientations was observed (55 and 126°, respectively). Overall, SLS is shown as a developmental step toward lignin valorization in composites while allowing reduced cost, scalability, and facile processing.

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 categoriesMeta-epidemiology (narrow)
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 score0.125
Threshold uncertainty score1.000

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 head0.002
GPT teacher head0.165
Teacher spread0.163 · 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.

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

Citations66
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueACS Sustainable Chemistry & EngineeringSame topicLignin and Wood ChemistryFrench-language works237,207