From Anisotropic Molecules and Particles to Small-Scale Actuators and Robots: An Account of Polymerized Liquid Crystals
Notice bibliographique
Résumé
Conspectus Untethered small-scale (milli-, micro-, and nano-) soft robots promise minimally invasive and targeted medical procedures in tiny, flooded, and confined environments like inside the human body. Despite such potentials, small-scale robots have not yet found their way to real-world applications. This can be mainly attributed to the fundamental and technical challenges in the fabrication, powering, navigation, imaging, and closed-loop control of robots at submillimiter scales. Pertinent to this Account, the selection of building block materials of small-scale robots also poses a challenge that is directly related to their fabrication and function. Early work in microrobotics focused on the mechanism of locomotion in fluids with low Reynolds number ( Re ≪ 1), which was mainly inspired by the motility of cells and microorganisms. Looking closely at the motile cells and microorganisms, one can find both order and anisotropy within their microstructure, driving out-of-equilibrium asymmetric deformations of their soft bodies and appendages like cilia and flagella, resulting in locomotion and function in environments with low Re number. Microroboticists aim to mimic microorganisms’ locomotion and function in developing mobile small-scale robots. It is known that soft, ordered, and anisotropic microstructures of microorganisms are examples of liquid crystalline systems. With this in mind, we believe that liquid crystals are underutilized in the design of small-scale robots, even though they have remarkable similarities to biological materials and constructs. In this Account, we have shed light on the role liquid crystals have played and can play in the design of small-scale robots. For this, we have first elaborated on the fundamentals of liquid crystals, which include a discussion of the various types of liquid crystals and their characteristics, their mesophase behavior, and their anisotropic properties. Then, we have discussed the applicability of anisotropic elastic networks of liquid crystals in the design of actuators which must satisfy all four programming pillars, including elasticity, alignment, responsiveness, and initial geometry. We have highlighted landmark reports where anisotropic elastic networks of liquid crystals, such as liquid crystal elastomers (LCEs), networks (LCNs), and hydrogels, are utilized as structural materials in the design of soft, small-scale actuators and robots. We point out the prevalence of the nematic phase and thermotropic liquid crystals utilized in these constructs over other mesophases and liquid crystal types as part of our discussion on the pros and cons of liquid crystals for microrobotics research. Finally, paths forward for the widespread applicability of liquid crystal microrobotics are envisaged. Specifically, the potential of soft robots constructed from elastic networks of chromonic and micellar lyotropic liquid crystals provides a substantial, yet daunting, opportunity for research. Furthermore, miniaturizing these constructs through innovative, combinatorial alignment–fabrication strategies on the microscale could realize liquid crystal soft robots suitable for biomedical applications, unlike those made from thermotropic liquid crystals. Additionally, programming alignment in alternative mesophases, such as smectic, may portray new research avenues in this emerging technology.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».