Optoelectronic-Coupled-Driven Microrobot for Biological Cargo Transport in Conductive Isosmotic Glucose Solution.

Journal: ACS applied materials & interfaces
PMID:

Abstract

Electric field-driven micro/nanorobots, as micro/nanodevices with autonomous motion capability, have emerged as promising candidates for targeted cargo delivery in biomedical applications due to their advantages of label-free operation, selectivity, and controllability. In biological systems, many biological cargos need to be operated in conductive isosmotic solutions to ensure their viability. However, in the conductive solution, electric field-driven micro/nanorobots exhibit significantly reduced propulsion performance, despite retaining the capability to manipulate cargos by the dielectrophoretic force. This limitation restricts the wider applicability of electric field-driven micro/nanorobots in biomedical fields. This paper presents a novel optoelectronic-coupled-driven α-FeO@aTiO/Au microrobot, which exhibits significantly improved mobility and enables biological cargo transportation in the conductive isosmotic glucose solution. Benefiting from the flowerlike surface structure and composite photocatalytic material, the proposed microrobot exhibits enhanced photocatalytic capability, enabling efficient propulsion in glucose solution under light irradiation. In addition, the motion behavior of the microrobot under light, electric, and optoelectronic-coupled fields is investigated. It is found that the speed of the microrobot could exceed 300 μm/s under coupled fields, which is more than ten times faster than that of previously reported electric field-driven micro/nanorobots. Due to the magnetic property, the proposed microrobot can be precisely navigated under the guidance of an external uniform magnetic field. Furthermore, the proposed microrobot can achieve the transportation of various biological cargos in a conductive isosmotic glucose solution. The proposed microrobot opens a new avenue for targeted delivery and holds great potential for applications in the biological and pharmaceutical fields.

Authors

  • Rencheng Zhuang
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
  • Xiaocong Chang
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
  • Jinrui Sha
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
  • Zehao Yu
    Department of Health Outcomes and Biomedical Informatics.
  • Enbo Shi
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
  • Minqiao Lu
    School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
  • Junmin Liu
    Robarts Research Institute, Western University, London, Ontario, Canada.
  • Guangyu Zhang
    School of Computer Science and Technology, Soochow University, 215006, Suzhou, China.
  • Dekai Zhou
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
  • Longqiu Li
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.