• The Korean Journal of Vision Science
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• v.20 no.4
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• pp.561-568
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• 2018

Purpose : The size and regular array of the collagen fibers in the corneal stroma have very close correlation with transparency. Simulation was carried out to investigate the change of light transmittance according to the array structure and collagen fiber layer thickness. Methods : The collagen fibers in corneal stroma were arranged in regular hexagonal, hexagonal, square and random shapes with OptiFDTD simulation software, and the light transmittance was analyzed. In square array, the light transmittance according to the density change was confirmed by when the number of collagen fibers in the simulation space was the same and the light transmittance was examined when the number and density of collagen fibers were changed. Results : When the number of collagen fibers is the same, the density becomes smaller and the thickness of the fibrous layer becomes thicker in order of arrangement of square, regular hexagonal, random and hexagonal. As a result of measuring the light transmittance by changing the array structure, the light transmittance measured at the detector at the same position was almost similar regardless of the array structure. In the detectors D0, D1, D2 and D3, the maximum transmittance is shown in square, hexagonal and square, regular hexagonal and regular hexagonal array structure, and the minimum transmittance is hexagonal, random, hexagonal and square, and square array structure. However, the difference between the maximum transmittance and the minimum transmittance was almost the same within 1%. When the number of collagen fibers was the same, the light transmittance of the rectangular array structure decreased with increasing fiber layer thickness. And as the thickness increased, the light transmittance decreased more when the number of collagen fibers decreased. Conclusion : Even though the collagen array structure changed, the light transmittance is almost similar regardless of the arrangement structure. However, as the array structure was changed, the thickness of the collagen fiber layer changed, and as the thickness increased, the light transmittance decreased. In other words, the transparency of the corneal stroma is more closely related to the thickness of the fibrous layer than the array of collagen fibers.

• Korean Journal of Optics and Photonics
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• v.20 no.1
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• pp.1-5
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• 2009

Recently, much research has been done for to realizeing nano-scale photonic circuits based on photonic crystal, plasmonics and silicon photonics in order to overcome fundamental limits of electronic circuits. These limits include such as bottleneck of speed, and size that cannot be reduced. Even though several kinds of coupling schemes have been reported, coupling structures are still large when it is compared with the nano-scale optical circuit. In this paper, we proposed using a very thin Fresnel lens while shortening the focal length of the Fresnel lens as much as possible. We proposed, for the first time, to utilize metal slits that are able to use the optical coupling system between a nano-scale optical circuit and the standard single mode optical fiber for overcoming the limitation of focal length shortening of the Fresnel lens. Comparative study has been carried out with a FDTD simulation between normal and metal slit assisted Fresnel lens. From the result of simulation, we can achieve 65% coupling efficiency for the metal-slit Fresnel lens when the focal length of metal-slit Fresnel lens is just $4{\mu}m$. On the other hand, the coupling efficiency of the normal Fresnel lens is about 43%.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.493-493
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• 2014

The manufacturing cost of thin-film photovoltics can potentially be lowered by minimizing the amount of a semiconductor material used to fabricate devices. Thin-film solar cells are typically only a few micrometers thick, whereas crystalline silicon (c-Si) wafer solar cells are $180{\sim}300\mu}m$ thick. As such, thin-film layers do not fully absorb incident light and their energy conversion efficiency is lower compared with that of c-Si wafer solar cells. Therefore, effective light trapping is required to realize commercially viable thin-film cells, particularly for indirect-band-gap semiconductors such as c-Si. An emerging method for light trapping in thin film solar cells is the use of metallic nanostructures that support surface plasmons. Plasmon-enhanced light absorption is shown to increase the cell photocurrent in many types of solar cells, specifically, in c-Si thin-film solar cells and in poly-Si thin film solar cell. By proper engineering of these structures, light can be concentrated and coupled into a thin semiconductor layer to increase light absorption. In many cases, silver (Ag) nanoparticles (NP) are formed either on the front surface or on the rear surface on the cells. In case of poly-Si thin film solar cells, Ag NPs are formed on the rear surface of the cells due to longer wavelengths are not perfectly absorbed in the active layer on the first path. In our cells, shorter wavelengths typically 300~500 nm are also not effectively absorbed. For this reason, a new concept of plasmonic nanostructure which is NPs formed both the front - and the rear - surface is worth testing. In this simulation Al NPs were located onto glass because Al has much lower parasitic absorption than other metal NPs. In case of Ag NP, it features parasitic absorption in the optical frequency range. On the other hand, Al NP, which is non-resonant metal NP, is characterized with a higher density of conduction electrons, resulting in highly negative dielectric permittivity. It makes them more suitable for the forward scattering configuration. In addition to this, Ag NP is located on the rear surface of the cell. Ag NPs showed good performance enhancement when they are located on the rear surface of our cells. In this simulation, Al NPs are located on glass and Ag NP is located on the rear Si surface. The structure for the simulation is shown in figure 1. Figure 2 shows FDTD-simulated absorption graphs of the proposed and reference structures. In the simulation, the front of the cell has Al NPs with 70 nm radius and 12.5% coverage; and the rear of the cell has Ag NPs with 157 nm in radius and 41.5% coverage. Such a structure shows better light absorption in 300~550 nm than that of the reference cell without any NPs and the structure with Ag NP on rear only. Therefore, it can be expected that enhanced light absorption of the structure with Al NP on front at 300~550 nm can contribute to the photocurrent enhancement.

• Geophysics and Geophysical Exploration
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• v.9 no.4
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• pp.304-315
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• 2006

We have examined the applicability of f-k analysis to the GPR direct wave measurement for water content to characterize vadose zone condition. When the vadose zone consists of a dry surface layer over wet substratum, we obtained f-k spectra where most of the energy is bounded by the air and dry soil velocities. In this case, dry soil velocity was successfully estimated by using high frequency data. On the other hands, when wet soil overlies dry substratum, the f-k spectra show a contrasting response where most of the energy travels with the velocity bounded by dry and wet soil velocities. In this case, the radar waves are trapped and guided within wet soil layer, exhibiting velocity dispersion. By adopting modal propagation theory, we could formulae a simple inversion code to find two layer's dielectric constants as well as layer thickness. By inverting the velocity dispersion curve obtained from f-k spectra of synthetic modeling data, we could obtain good estimates of dielectric constants of each layer as well as first layer thickness. Moreover, we could obtain more accurate results by including the higher mode data. We expect this method will be useful to get the quantitative property of real subsurface when the field condition is similar.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.276-276
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• 2010

Localized surface plasmon resonance (LSPR) has been explored recently as a promising approach to increase energy conversion efficiency in photovoltaic devices, particularly for thin film hydrogenated amorphous silicon (a-Si:H) solar cells. The LSPR is frequently excited via an electromagnetic (EM) radiation in proximate metallic nanostructures and its primary con sequences are selective photon extinction and local EM enhancement which gives rise to improved photogeneration of electron-hole (e-h) pairs, and consequently increases photocurrent. In this work, high-dielectric-constant (k) $ZrO_2$ (refractive index n=2.22, dielectric constant $\varepsilon=4.93$ at the wavelength of 550 nm) is proposed as spacing layer to enhance the LSPR for application to the thin film silicon solar cells. Compared to excitation of the LSPR using $SiO_2$ (n=1.46, $\varepsilon=2.13$ at the wavelength of 546.1 nm) spacing layer with Au nanoparticles of the radius of 45nm, that using $ZrO_2$ dielectric shows the advantages of(i) ~2.5 times greater polarizability, (ii) ~3.5 times larger scattering cross-section and ~1.5 times larger absorption cross-section, (iii) 4.5% higher transmission coefficient of the same thickness and (iv) 7.8% greater transmitted electric filed intensity at the same depth. All those results are calculated by Mie theory and Fresnel equations, and simulated by finite-difference time-domain (FDTD) calculations with proper boundary conditions. Red-shifting of the LSPR wavelength using high-k $ZrO_2$ dielectric is also observed according to location of the peak and this is consistent with the other's report. Finally, our experimental results show that variation of short-circuit current density ($J_{sc}$) of the LSPR enhanced a-Si:H solar cell by using the $ZrO_2$ spacing layer is 45.4% higher than that using the $SiO_2$ spacing layer, supporting our calculation and theory.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.98-104
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• 2011

Numerical simulation in exploration geophysics provides important insights into subsurface wave propagation phenomena. Although elastic wave simulations take longer to compute than acoustic simulations, an elastic simulator can construct more realistic wavefields including shear components. Therefore, it is suitable for exploration of the responses of elastic bodies. To overcome the long duration of the calculations, we use a Graphic Processing Unit (GPU) to accelerate the elastic wave simulation. Because a GPU has many processors and a wide memory bandwidth, we can use it in a parallelised computing architecture. The GPU board used in this study is an NVIDIA Tesla C1060, which has 240 processors and a 102 GB/s memory bandwidth. Despite the availability of a parallel computing architecture (CUDA), developed by NVIDIA, we must optimise the usage of the different types of memory on the GPU device, and the sequence of calculations, to obtain a significant speedup of the computation. In this study, we simulate two- (2D) and threedimensional (3D) elastic wave propagation using the Finite-Difference Time-Domain (FDTD) method on GPUs. In the wave propagation simulation, we adopt the staggered-grid method, which is one of the conventional FD schemes, since this method can achieve sufficient accuracy for use in numerical modelling in geophysics. Our simulator optimises the usage of memory on the GPU device to reduce data access times, and uses faster memory as much as possible. This is a key factor in GPU computing. By using one GPU device and optimising its memory usage, we improved the computation time by more than 14 times in the 2D simulation, and over six times in the 3D simulation, compared with one CPU. Furthermore, by using three GPUs, we succeeded in accelerating the 3D simulation 10 times.