A one-step fabrication method for CNT–QD hybrid 3D architectures with engineered optoelectronic properties

Abstract

This study proposes a straightforward fabrication technique that enables precise 3D patterning of carbon nanotube (CNT)-based hybrid nanostructures, in particular CNT–quantum dot (QD) hybrid architectures. The proposed micropipette-based self-assembly method relies solely on readily available optical components, including manual and motorized stages, an objective lens, camera and light source, highlighting the accessibility and simplicity of the fabrication method. The proposed fabrication method facilitates the formation of complex 3D architectures by simultaneously assembling CNTs and QDs into arbitrary shapes, overcoming limitations inherent to conventional planar patterning technologies. The absence of photomasks and polymer binders minimizes potential contamination, enabling the full realization of intrinsic optoelectronic characteristics of CNTs and QDs. Various geometric configurations of CNT–QD hybrid nanostructures were successfully fabricated, demonstrating the feasibility of achieving precise 3D patterns previously difficult to achieve with traditional methods. Moreover, analysis of photoluminescence characteristics revealed shifts in emission peak positions and a corresponding reduction in PL lifetime, indicative of Förster resonance energy transfer between the CNT and QD interfaces. The developed 3D patterning approach, leveraging significant process simplification, is expected to advance the integration of CNT–QD hybrid nanostructures in future 3D optoelectronic devices.

Graphical abstract: A one-step fabrication method for CNT–QD hybrid 3D architectures with engineered optoelectronic properties

Supplementary files

Article information

Article type
Paper
Submitted
17 Nov 2025
Accepted
02 Feb 2026
First published
05 Feb 2026

Nanoscale, 2026, Advance Article

A one-step fabrication method for CNT–QD hybrid 3D architectures with engineered optoelectronic properties

J. Kim, H. Kim, Y. Lee, S. Eom, H. Seo, S. Gu, S. Kwak, J. Ko, W. Kim and J. Lee, Nanoscale, 2026, Advance Article , DOI: 10.1039/D5NR04848F

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