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Improving Nanoparticle Tracking with 3D Nanoprinted Fiber-Integrated Hollow-Core Waveguides

A recent study published in Light: Science & Applications presents a new approach to nanoparticle tracking analysis (NTA) using compact square-core hollow-core waveguides (HCWs) directly integrated with standard optical fibers.

Developed with high-precision 3D nanoprinting, this fiber-interfaced system enhances the accuracy and consistency of nanoparticle measurement, offering a practical advance in integrated photonics with applications across life sciences, environmental sensing, and quantum technologies.

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Why Hollow-Core Waveguides?

HCWs guide light through a hollow region surrounded by a structured cladding, enabling strong light-matter interaction. This is especially valuable for analyzing nanoparticles in low-refractive-index media like water, where traditional waveguides struggle. Anti-resonant reflective optical waveguides (ARROWs), in particular, allow nearly full overlap between the guided light and surrounding medium, supporting more precise measurements under Beer-Lambert’s law.

Connecting HCWs to standard optical fibers removes the need for bulky optical setups, making the system more compact and easier to use. Recent progress in 3D nanoprinting enables the creation of highly tailored waveguide structures with submicron accuracy, which is essential for advanced applications in biosensing, fluidics, nonlinear optics, and quantum photonics.

Device Design and Fabrication

The team fabricated a single-piece HCW structure using direct laser writing with a commercial 3D nanoprinter and the photoresist IP-DIP2. The square-core waveguide was printed directly onto the end face of polarization-maintaining fibers (PMFs), ensuring efficient coupling through anti-resonant light guidance. The design achieved precise alignment and minimal fabrication defects.

To understand performance, the researchers used finite element modeling (FEM) to analyze mode coupling efficiency, light intensity distribution, and losses in both air and water. They also conducted experimental tests using spectrum analyzers, cameras, and a broadband light source with polarization control to verify transmission and modal behavior.

For tracking experiments, the team introduced gold nanospheres (50 nm and 100 nm) into the HCW’s fluid-filled core. A continuous-wave laser, coupling optics, and high-speed microscopy enabled real-time observation of Brownian motion within the channel.

Key Findings

Results showed that the new HCW delivered high accuracy in measuring nanoparticle sizes. The calculated mean hydrodynamic diameters were closely aligned with expected values.

Gold nanoparticles were tracked over longer periods thanks to stable, distortion-free imaging and uniform illumination, achieved through the perpendicular placement of the polymer membrane to the microscope axis and the use of a polarization-maintaining single-mode fiber.

Coupling efficiency between the optical fiber and HCW modes was above 70 % under polarization-matched conditions, allowing for effective light transfer. Modal losses were within an acceptable range of 1–2 dB per 100 µm, considering the device’s structural complexity. Optical tests confirmed the presence of the anti-resonance effect, which supported efficient light guidance.

During NTA, the HCW was placed in a fluidic chamber filled with a nanoparticle solution. Real-time imaging of Brownian motion enabled the capture of over 100 nanoparticle trajectories. Analysis of the mean-square displacement (MSD) produced size distributions consistent with results from dynamic light scattering (DLS), confirming the system’s reliability.

The waveguide’s ability to limit particle diffusion extended tracking time, reduced errors, and significantly improved measurement precision, making it a strong candidate for accurate nanoparticle characterization.

Broader Applications

This research has significant implications across multiple scientific disciplines. In bioanalytics and life sciences, the fiber-interfaced HCW system enables precise nanoparticle characterization for diagnostics, drug delivery, and cellular interaction studies. In environmental science, it enhances sensing capabilities for detecting pollutants at low concentrations, supporting more effective monitoring and remediation.

Integrating HCWs with optical fibers offers compact, flexible devices suitable for remote and in-field use. Its ability to enhance light-matter interactions opens new directions in quantum technologies, including advanced quantum devices and optical manipulation tools. The system has potential in microfluidics, gas sensing, and mid-infrared spectroscopy, broadening its utility in advanced sensing and analytical techniques.

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Conclusion and Future Directions

This work demonstrates that fiber-integrated square-core HCWs, fabricated through 3D nanoprinting, can significantly improve the accuracy and stability of nanoparticle tracking. The combination of compact design, high coupling efficiency, and reliable imaging makes it a strong candidate for advanced sensing systems.

Future developments may include the addition of microstructured elements and functional coatings for targeted detection. This research lays the groundwork for next-generation photonic devices with improved performance and broader applications in nanotechnology, spectroscopy, and analytical science.

Journal Reference

Pereira, D., et al. (2025). 3D nanoprinted fiber-interfaced hollow-core waveguides for high-accuracy nanoparticle tracking analysis. Light Sci Appl. DOI: 10.1038/s41377-025-01827-9, https://www.nature.com/articles/s41377-025-01827-9

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Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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