Seongyong Kim

Multifunctional Silver‐Embedded Magnetic Nanoparticles as SERS Nanoprobes and Their Applications

In this study, surface-enhanced Raman spectroscopy (SERS)-encoded magnetic nanoparticles (NPs) are prepared and utilized as a multifunctional tagging material for cancer-cell targeting and separation. First, silver-embedded magnetic NPs are prepared, composed of an 18-nm magnetic core and a 16-nm-thick silica shell with silver NPs formed on the surface. After simple aromatic compounds are adsorbed on the silver-embedded magnetic NPs, they are coated with silica to provide them with chemical and physical stability. The resulting silica-encapsulated magnetic NPs (M-SERS dots) produce strong SERS signals and have magnetic properties. In a model application as a tagging material, the M-SERS dots are successfully utilized for targeting breast-cancer cells (SKBR3) and floating leukemia cells (SP2/O). The targeted cancer cells can be easily separated from the untargeted cells using an external magnetic field. The separated targeted cancer cells exhibit a Raman signal originating from the M-SERS dots. This system proves to be an efficient tool for separating targeted cells. Additionally, the magnetic-field-induced hot spots, which can provide a 1000-times-stronger SERS intensity due to aggregation of the NPs, are studied.

Magnetic surface-enhanced Raman spectroscopic (M-SERS) dots for the identification of bronchioalveolar stem cells in normal and lung cancer mice

Bronchioalveolar stem cells (BASCs) play an important role in the development of cancer. To study the characterization of BASCs, their isolation and purification are important. However, the cells are very rare in tissues and the available methods of isolating them are limited. The current study was performed to isolate BASCs in the murine lung using magnetic nanoparticle-based surface-enhanced Raman spectroscopic dots (M-SERS Dots). We used K-ras(LA1) mice, a laboratory animal model of non-small cell lung cancer of human, and C57BL/6 mice having the same age as a control. We compared the BASCs between 2 species by FACS analysis with 4 markers of BASCs, CCSP, SP-C, CD34, and Sca-1. We found that BASCs were more abundant in the K-ras(LA1) mice than in the C57BL/6 mice. Also, the M-SERS Dot-mediated positive selection of the CD34(pos) cells enabled the BASCs to be enriched to an approximately 4- to 5-fold higher level than that in the case without pre-separation. In summary, our study demonstrates the potential of using M-SERS Dots as a sorting system with very effective isolation of BASCs and multiplex targeting probe, showing that they may play an effective role in the study of BASCs in the future.

Macroscopic single-walled-carbon-nanotube fiber self-assembled by dip-coating method.

Pure macroscopic single-walled-carbon-nanotube (SWNT) fibers are fabricated by using a dip-coating method without any additive or additional electrical equipment or complex apparatus. The present method only utilizes microfluidics, which includes capillary condensation, capillary flow, and surface tension, and results in the self-assembly and self-alignment of SWNT colloids.

Two-photon imaging of localized optical fields in the vicinity of silver nanowires using a scanning near-field optical microscope

We report a near-field two-photon excitation imaging technique for silver nanostructures to visualize optical fields in the vicinity of nanostructures. We have found that the excitation image of an isolated wire shows an oscillating feature along the long axis of the wire. The period of the oscillation is in good agreement with that of plasmon wavefunctions resonant with the excitation light. The oscillation was thus attributed to the resonant plasmon wavefunction. We also found that bundles of wires exhibit more intense photoluminescence signals than do isolated wires, particularly at junctions between wire ends and the shafts of other wires, which was attributed to the amplified optical fields at the ends of nanowires or interstitial gaps between the wires. We discuss the mechanism of the photoluminescence from silver nanowires. The photoluminescence is most probably attributed to emission from the oxidized surface layer of the silver nanowires, which is enhanced in resonance with plasmons on the wires.

Proposal for a Method of Extracting Road Layers from Remote Sensing Images Using Conditional GANs

With the recent advances in unmanned aerial vehicle (UAV) technology, remote sensing images have become relatively easy to obtain and their accuracy has increased enough to be able to handle land information. Therefore, there is a growing demand to utilize remote sensing images for extracting semantic objects Conventional methods are mainly focused on pixel-based classification and recently people commonly use convolutional neural networks, which post processing is required to linearize roads that are cut off and accurately shape the contours of buildings. We propose the use of a generative model to carry out this post processing in the networks. Using conditional Generative Adversarial Network (GANs), we translate remote sensing images into map-based images from which roads are easily extracted, while retaining the underlying structure. Next, we extract road layers from the generated images. Through this approach, it is possible to achieve the same effect as if complicating post processing were done in the networks during the object extraction process.

Designing of Indoor Linkable Pedestrian Network Data Model for the Transportation Vulnerable

There has been a recent increasing interest in guaranteeing the right for mobility of the transportation vulnerable and the demand for indoor routing services has been increasing as well. This paper proposes an indoor pedestrian network data model for navigation services for the transportation vulnerable. Based on the proposed network data model, it will be possible to design and construct indoor and outdoor network data in the future. In the proposed model, indoor ambulation facilities have been included and properties of the connecting facilities have been defined in detail, compared to the previous models.

Application of Style Transfer in the Vectorization Process of Floorplans (Short Paper)

As the market for indoor spatial information burgeons, the construction of indoor spatial databases consequently gain attention. Since floorplans are portable records of buildings, they are an indispensable source for the efficient construction of indoor environments. However, as previous research on floorplan information retrieval usually targeted specific formats, a system for constructing spatial information must include heuristic refinement steps. This study aims to convert diverse floorplans into an integrated format using the style transfer by deep networks. Our deep networks mimic a robust perception of human that recognize the cell structure of floorplans under various formats. The integrated format ensures that unified post-processing steps are required to the vectorization of floorplans. Through this process, indoor spatial information is constructed in a pragmatic way, using a plethora of architectural floorplans.