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Record W4407549587 · doi:10.1002/adma.202417742

Crossing the Dimensional Divide with Optoelectronic Tweezers: Multicomponent Light‐Driven Micromachines with Motion Transfer in Three Dimensions

2025· article· en· W4407549587 on OpenAlexaff
Gong Li, Bingrui Xu, Xiaopu Wang, Jiangfan Yu, Yifan Zhang, Rongxin Fu, Yang Fan, Hongcheng Gu, Yuchen Huang, Yujie Chen, Yanfeng Zhang, Zhuoran Wang, Guozhen Shen, Yeliang Wang, Huikai Xie, Aaron R. Wheeler, Jiafang Li, Shuailong Zhang

Bibliographic record

VenueAdvanced Materials · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaSouthern University of Science and TechnologyNatural Science Foundation of ChongqingNatural Science Foundation of Beijing MunicipalitySun Yat-sen UniversitySoutheast UniversityNational Natural Science Foundation of China
KeywordsMicroscale chemistryMicrosystemMaterials scienceNanotechnologyTweezersOptical tweezersLevitationEngineeringMechanical engineeringPhysicsOpticsElectrical engineering

Abstract

fetched live from OpenAlex

Micromachines capable of performing diverse mechanical tasks in complex and constrained microenvironments are of great interest. Despite important milestones in this pursuit, until now, micromachines are confined to actuation within a single 2D plane due to the challenges of transferring motion across different planes in limited space. Here, a breakthrough method is presented to overcome this limitation: multi-component micromachines that facilitate 3D motion transfer across different planes. These light-driven 3D micromachines, fabricated using standard photolithography combined with direct laser writing, are assembled and actuated via programmable light patterns within an optoelectronic tweezers system. Utilizing charge-induced repulsion and dielectrophoretic levitation effects, the micromachines enable highly efficient mechanical rotation and effective inter-component motion transfer. Through this work, fascinating patterns of similarities are unveiled for the new microscale 3D systems when compared with the macro-scale world in which they live, paving the way for the development of micromechanical devices and microsystems with ever increasing functionality and versatility.

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 score0.013
Threshold uncertainty score0.541

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 head0.005
GPT teacher head0.227
Teacher spread0.223 · 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

Citations10
Published2025
Admission routes1
Has abstractyes

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