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α,ε-杂合肽稳定的磁性纳米颗粒包覆的纸基致动器

α,ε-Hybrid Peptide-Stabilized Magnetic Nanoparticle-Coated Paper-Based Actuators.

作者信息

Shit Ananda, Singh Surajit, Ibukun Olamilekan Joseph, Gumtya Milan, Haldar Debasish

机构信息

Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India.

出版信息

ACS Omega. 2023 Feb 24;8(9):8712-8721. doi: 10.1021/acsomega.2c08092. eCollection 2023 Mar 7.

DOI:10.1021/acsomega.2c08092
PMID:36910952
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9996580/
Abstract

The development of α,ε-hybrid peptide-stabilized magnetic nanoparticles and their application to fabricate a paper-based actuator has been reported. From single-crystal diffraction analysis, the nitropeptide has an extended structure with a geometry. The one-pot in situ multiple oxidation-reduction reaction of a synthetic nitropeptide solution in ammonium hydroxide and FeCl leads to the formation of FeO nanoparticles. The reduction reaction replaces the nitro group with an amine group, which finally acts as capping agent for the stabilization of the FeO nanoparticles. Paper-based soft magneto machines with multivariant actuation modes such as contraction-expansion, bending, and uplifting locomotion have been studied. The device has potential as controllable paper-based soft robots.

摘要

α,ε-杂合肽稳定的磁性纳米颗粒的开发及其在制造纸基致动器中的应用已有报道。通过单晶衍射分析,硝肽具有伸展结构和特定几何形状。在氢氧化铵和氯化铁中,合成硝肽溶液的一锅原位多氧化还原反应导致形成FeO纳米颗粒。还原反应将硝基替换为胺基,该胺基最终作为封端剂用于稳定FeO纳米颗粒。具有收缩-膨胀、弯曲和提升运动等多变量驱动模式的纸基软磁机器已得到研究。该装置有潜力成为可控的纸基软机器人。

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本文引用的文献

1
High-throughput fabrication of soft magneto-origami machines.高通量制造软磁折纸机。
Nat Commun. 2022 Jul 19;13(1):4177. doi: 10.1038/s41467-022-31900-5.
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Materials for Smart Soft Actuator Systems.智能软驱动器系统材料。
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Self-powered soft robot in the Mariana Trench.马里亚纳海沟中的自供电软体机器人。
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Bioinspired Synergistic Photochromic Luminescence and Programmable Liquid Crystal Actuators.受生物启发的协同光致变色发光与可编程液晶致动器
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From Understanding Mechanical Behavior to Curvature Prediction of Humidity-Triggered Bilayer Actuators.从理解湿度触发双层致动器的力学行为到曲率预测
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