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Performance of molecular crystals in conversion of light to mechanical work.
Mahmoud Halabi, Jad; Ahmed, Ejaz; Sofela, Samuel; Naumov, Pance.
Afiliação
  • Mahmoud Halabi J; Smart Materials Lab (SML), Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates.
  • Ahmed E; Smart Materials Lab (SML), Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates.
  • Sofela S; Division of Engineering, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates.
  • Naumov P; Smart Materials Lab (SML), Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates; pance.naumov@nyu.edu.
Proc Natl Acad Sci U S A ; 118(5)2021 02 02.
Article em En | MEDLINE | ID: mdl-33495317
ABSTRACT
Dynamic molecular crystals have recently received ample attention as an emerging class of energy-transducing materials, yet have fallen short of developing into fully realized actuators. Through the trans-cis surface isomerization of three crystalline azobenzene materials, here, we set out to extensively characterize the light-to-work energy conversion of photoinduced bending in molecular crystals. We distinguish the azobenzene single crystals from commonly used actuators through quantitative performance evaluation and specific performance indices. Bending molecular crystals have an operating range comparable to that of microactuators such as microelectromechanical systems and a work-generating capacity and dynamic performance that qualifies them to substitute micromotor drivers in mechanical positioning and microgripping tasks. Finite element modeling, applied to determine the surface photoisomerization parameters, allowed for predicting and optimizing the mechanical response of these materials. Utilizing mechanical characterization and numerical simulation tools proves essential in accelerating the introduction of dynamic molecular crystals into soft microrobotics applications.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article