MétaCan
Menu
Back to cohort
Record W4416917717 · doi:10.1016/j.ceja.2025.100979

A new L-PLA@Croconaine-based all organic composite: selective management of thermophysical properties of L-PLA by a photothermal croconaine-based molecular additive

2025· article· en· W4416917717 on OpenAlexaff
Maria Montrone, Umberto Berardi, Paola Fini, P. Bison, Stefano Rossi, Salvatore Gambino, Marco Pugliese, Jennifer Gubitosa, Pinalysa Cosma, Vito Rizzi, Maria Annunziata M. Capozzi

Bibliographic record

VenueChemical Engineering Journal Advances · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Toronto
FundersMinistero dell'Università e della RicercaMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsThermal diffusivityThermal stabilityPhotothermal therapyDifferential scanning calorimetryThermogravimetric analysisComposite numberThermal conductivityDispersion (optics)

Abstract

fetched live from OpenAlex

• A new all-organic composite material L-PLA@CR-BI was developed by incorporating a benzoindolenine-based croconaine (CR-BI) into L-PLA matrix. • CR-BI acts as a photothermal molecular additive with high affinity for the PLA, forming a homogeneous molecular network inner L-PLA. • With just 1% CR-BI we are able to selectively modulate the thermal properties of PLA, with an impressive increase of more than three times of thermal diffusivity and conductivity, while preserving electrical insulation. • The very low concentration of CR-BI additive allows to preserve the thermal stability of PLA. • CR-BI molecules into PLA matrix increases the polymer chain mobility, facilitating the release of thermal energy thank to the formation of newly ordered structures, making this composite material interesting also for energy storage applications. Selective management of chemico-physical properties of l -polylactic acid (L-PLA) is pivotal to broaden the application range of this polymer. As a thermally and electrically insulating polymer, its application in energy field and electronic instruments requires innovative strategies capable of selectively tune thermal and electrical properties, safeguarding mechanical properties and thermal stability. Here, we propose a molecular approach to selectively enhance thermal conductivity of l -PLA, preserving electrical insulating capacity, by incorporating a benzoindolenine-based croconaine (CR-BI) as functional photothermal additive. l -PLA@CR-BI composite solid layers were prepared via solution casting, by combining different amounts of CR-BI and comprehensively characterized by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), UV–vis and FTIR spectroscopy, electrical, photothermal and thermophysical measurements. l -PLA@CR-BI composites displayed homogeneous coloration and a uniform CR-BI molecular dispersion inner l -PLA, with a molecular-level thermal network resulting in a strong impact on its thermal properties. Remarkably, the inclusion of only 1wt% CR-BI led to an over threefold increase in thermal diffusivity and conductivity compared to neat l -PLA. TGA evidenced a CR-BI-induced enhancement of polymer chain mobility and the formation of new crystalline domains, improving heat transfer and suggesting thermal energy storage applications. Importantly, the electrical insulating nature of l -PLA remained unchanged across all compositions. To the best of our knowledge, this work provides the first demonstration of croconaines as molecular modulators of l -PLA’s chemico-physical properties, enabling selective and efficient enhancement of thermal transport while maintaining electrical insulation- an advance with significant implications for sustainable polymer-based electronic and energy materials.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.003
GPT teacher head0.186
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueChemical Engineering Journal AdvancesSame topicAdvanced Battery Materials and TechnologiesFrench-language works237,207