Ikjun Hong

Ikjun Hong

Final-year Ph.D. candidate at Vanderbilt University working on integrated photonics, optical sensing, and AI-assisted data analysis.

Posts by Collection

other_projects

Transformer Time-Series Forecasting

OLED luminance degradation prediction over future time windows using a transformer-based time-series model. Delta luminance was incorporated to improve training stability and forecasting performance.

portfolio

Quasi-Q-switched mode-locked fiber laser for efficient second-harmonic generation

Developed a ytterbium-doped fiber laser using subharmonic cavity modulation to generate quasi-Q-switched mode-locked pulses for enhanced 532 nm second-harmonic generation in MgO:PPLN.
Challenge – Efficient nonlinear frequency conversion is limited by insufficient peak power and pulse dynamics in conventional fiber laser systems.
Approach – Designed a quasi-Q-switched mode-locked fiber laser using subharmonic cavity modulation. Enhanced pulse energy and peak power to improve nonlinear interaction efficiency in MgO:PPLN for 532 nm SHG.
Techniques – Fiber laser systems, AOM-based modulation, nonlinear optics (SHG), optical amplification, RF modulation
Instruments – Optical spectrum analyzer (OSA), oscilloscope, RF spectrum analyzer; photodetectors, CMOS cameras; gain fibers (Er, Yb), WDM, isolators, wave plates, RF drivers

Hybrid nanophotonic tweezers for nanoscale particle manipulation

Designed an anapole-enhanced dielectric nanotweezer platform combining optical and diffusiophoretic forces for low-power, label-free nanoparticle manipulation.
Challenge- Near-field trapping experiments are strongly influenced by Brownian motion, making it difficult for nanoparticles to approach the nanoresonator. An additional transport mechanism is required to guide particles into the near-field region.
Approach- We utilize diffusiophoresis induced by localized thermal gradients from the nanoantenna. This generates fluid-driven transport, enabling particles to be delivered toward the resonator for efficient trapping.
Techniques- Thermonanophotonics, EM/thermal/fluid simulations, Nanofabrication (EBL, PECVD, RIE)
Instruments- Nikon microscopy systems, CW lasers, Photodetectors, CMOS cameras

Nanophotonic particle trapping using DBR-enhanced optical fields

Demonstrated nanoparticle trapping using distributed Bragg reflector (DBR)-enhanced optical fields for improved confinement and manipulation at the nanoscale.
Challenge- Effective nanoscale particle trapping is fundamentally limited by the diffraction of light. Here, we enhance the near-field intensity in a single nanoantenna to increase the optical gradient force, enabling stable trapping of particles smaller than 50 nm.
Approach- We leverage near-field enhancement from the slot effect in a reflector-backed nanoantenna system supported by a distributed Bragg reflector (DBR). The slot geometry concentrates the electric field within the low-index gap, consistent with Maxwell’s boundary conditions, thereby significantly enhancing the local field intensity.
Techniques- Thermonanophotonics, coupled EM/thermal/optical force simulations, thin-film optimization (DBR), Nanofabrication (EBL, PECVD, RIE)
Instruments- Nikon microscopy systems, CW lasers, Photodetectors, CMOS cameras

Parallel nanophotonic trapping platform enabled by photolithographic scalability

Developed a parallelized nanophotonic trapping system using photolithographically defined structures, enabling rapid and scalable manipulation of nanoscale particles beyond conventional single-beam optical tweezers. Keywords: parallel trapping, nanophotonics, photolithography, optical tweezers, scalable sensing.
Challenge- Achieving high-efficiency, comprehensive analysis of single nanoparticles to determine their size, shape, and composition is essential for understanding particle heterogeneity with applications ranging from drug delivery to environmental monitoring. Existing techniques are hindered by low throughput, lengthy trapping times, irreversible particle adsorption, or limited characterization capabilities.
Approach- We introduce Interferometric Electrohydrodynamic Tweezers (IET), an integrated platform that combines rapid molecular trapping, interferometric scattering imaging, and Raman scattering to rapidly trap and characterize single nanoparticles within seconds in one integrated platform.
Techniques- Thermal/flow simulations(DBR),Nanofabrication (Lithography, Evaporation)
Instruments- Nikon microscopy systems, CW lasers, Photodetectors, CMOS cameras

AI-assisted interferometric nanotweezers for label-free EV detection

Developed an AI-enhanced interferometric nanotweezer platform for label-free detection of extracellular vesicles using deep-learning-based segmentation, contrast enhancement, and quantitative image analysis. Keywords: AI segmentation, interferometric imaging, nanophotonics, optical trapping, label-free sensing.
Challenge- Characterization of single nanoparticles requires accurate analysis of particle trajectories, which depends on reliable segmentation of low signal-to-noise interferometric images, Conventional segmentation approaches are time-consuming and limit scalable, high-throughput extraction of particle properties such as refractive index and size
Approach- Incorporated particle tracking algorithms with U-Net–assisted segmentation to enable automated and robust extraction of particle trajectories
Techniques- Label-free Optical Imaging system using interferences, Python assisted tracking, AI assisted Segmentation (training/prediction), Image processing for the contrast enhancement, Automated data sampling
Instruments- Micro-Manager, Nikon SDK, CW lasers, CMOS cameras

publications

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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