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Record W4416534477 · doi:10.1002/admt.202501621

Photothermomechanically Efficient, Low‐Cost, High‐Cycle‐Life, Hybrid MXene‐Polymer Actuators

2025· article· en· W4416534477 on OpenAlexfundno aff
Ken Iiyoshi, Γεώργιος Κορρές, Olivér Nagy, Gabriel Roldán, Pancě Naumov, Stefan Schramm, Mohamad Eid

Bibliographic record

VenueAdvanced Materials Technologies · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsnot available
FundersTamkeenYork UniversityNew York University Abu Dhabi
KeywordsActuatorBendingPhotothermal therapyDurabilitySoft roboticsPower (physics)ScalabilityCharacterization (materials science)Artificial muscle

Abstract

fetched live from OpenAlex

ABSTRACT Photothermomechanical polymer film actuators stand out among the dynamic components available for soft robotics due to a combination of assets, such as capability for rapid energy transduction, wireless control, and ease of miniaturization. Despite their anticipated superior performance, several design challenges remain. These include high operational temperatures, inadequate mechanical output relative to the radiation energy provided, limited durability during repeated use, and high production costs; such factors hinder the scalability of these actuating materials in practical applications. Here, we report a viable solution by substituting performance‐enhancing nanoparticles with MXenes—carbon‐based, 2D materials known for their theoretical photothermal conversion efficiency of up to 100%. This led to the development of MXene‐dispersed polymer trilayer actuators (MPTAs). Extensive photothermal and thermomechanical characterization demonstrated superior performance compared to previously reported actuators, with a reduced shed power demand (0.1 mW cm −2 °C −1 ), substantial bending capacity per irradiation power per time (0.1° mW −1 cm 2 s −1 ), and enhanced cyclic longevity, with fatigueless operation of at least 1000 cycles. We demonstrate three applications: A kirigami‐inspired flower, parallel manipulator, and soft gripper. Additionally, these materials are cost‐effective; thus, they are the optimal choice for long‐term, reversible operation with efficient heat‐to‐work transduction.

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 score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.003
GPT teacher head0.208
Teacher spread0.204 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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