• Proceedings of the KSME Conference
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• 2004.04a
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• pp.252-257
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• 2004

Nanometer-sized structures are being applied to many devices including micro/nano electronics, optoelectronics, quantum devices, MEMS/NEMS, biosensors, etc. Especially, the thin film with submicron thickness is a basic structure for fabricating these devices, but its mechanical behaviors are not well understood. The mechanical properties of the thin film are different from those of the bulk structure and are difficult to measure because of its handling inconvenience. Several techniques have been applied to mechanical characterization of the thin film, such as nanoindentation test, micro/nano tensile test, strip bending test, etc. In this study, we focus on the strip bending test because of its high accuracy and moderate specimen preparation efforts, and measure Au thin film, which is a very popular material in micro/nano electronic devices. Au film is deposited on Si substrate by evaporation process, of which thickness is 100nm. Using the strip bending test, we obtain elastic modulus, yield and ultimate tensile strength, and residual stress of Au thin film.

• Journal of the Optical Society of Korea
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• v.17 no.6
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• pp.513-517
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• 2013

Recently, maskless lithography (ML) systems have become popular in digital manufacturing technologies. To achieve high-throughput manufacturing processes, digital micromirror devices (DMD) in ML systems must be driven to their operational limits, often in harsh conditions. We propose an instrument and algorithm to detect DMD malfunctions to ensure perfect mask image transfer to the photoresist in ML systems. DMD malfunctions are caused by either bad DMD pixels or data transfer errors. We detect bad DMD pixels with $20{\times}20$ pixel by white and black image tests. To analyze data transfer errors at high frame rates, we monitor changes in the frame rate of a target DMD pixel driven by the input data with a set frame rate of up to 28000 frames per second (fps). For our data transfer error detection method, we verified that there are no data transfer errors in the test by confirming the agreement between the input frame rate and the output frame rate within the measurement accuracy of 1 fps.

• Computers and Concrete
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• v.32 no.4
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• pp.373-381
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• 2023

Fly ash, granulated blast furnace slag, marble waste powder, etc. are just some of the by-products of other sectors that the construction industry is looking to include into the many types of concrete they produce. This research seeks to use surrogate machine learning methods to forecast the compressive strength of self-compacting concrete. The surrogate models were developed using Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Random Forest (RF), and Gaussian Process Regression (GPR) techniques. Compressive strength is used as the output variable, with nano silica content, cement content, coarse aggregate content, fine aggregate content, superplasticizer, curing duration, and water-binder ratio as input variables. Of the four models, GBM had the highest accuracy in determining the compressive strength of SCC. The concrete's compressive strength is worst predicted by GPR. Compressive strength of SCC with nano silica is found to be most affected by curing time and least by fine aggregate.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.117-126
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• 2023

Traditional markets, formed naturally, often feature aged buildings and facilities that are susceptible to fire. However, the lack of adequate fire detection systems in these markets can easily lead to large-scale fires upon ignition. Therefore, this study was conducted with the aim of detecting fires in traditional markets, utilizing thermal imaging cameras for data collection and the YOLOv8 model for object detection experiments. Data were collected in the night markets within traditional markets of xx city and by simulating fire scenarios. A comparative analysis of the Nano and XL models of YOLOv8 revealed that the XL model is more effective in detecting fires. The XL model not only demonstrated higher accuracy in correctly identifying flames but also tended to miss fewer fires compared to the Nano model. In the case of objects other than flames, the XL model showed superior performance over the Nano model. Taking all these factors into account, it is anticipated that with further data collection and improvement in model performance, a suitable fire detection system for traditional markets can be developed.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.183-186
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• 2007

The injection molding process has high accuracy and good reproducibility that are essential for mass production at low cost. Conventional molding processes typically use the water-based mold heating and air cooling methods. However, in the nano injection molding processes, this semi-active mold temperature control results in the several defects such as air-flow mark, non-fill, sticking and tearing, etc. Therefore, in order to control temperature of the molds actively and improve the quality of the molded products, the novel nano injection molding system, which uses active heating and cooling method, has been introduced. By using the Peltier devices, the temperature of locally adiabatic molds can be controlled dramatically and the quality of the molded patterns can be improved.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3178-3182
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• 2007

The interferometer method with nano-scale spatial resolution has been developed in this study. To enhance the accuracy of the previous developed method, the 14 bit cooled CCD camera with 1280 by 980 spatial resolution was applied to the measurement. And optical alignment has been carried out on the highly accurate position sensors with 500nm resolution so as to be able to calibrate the detected interference image with the field of view. Also the measurements were applied to the ultra thin oil film between the Al coated cylinder mirror with 38.1mm radius and 0.5mm cover glass to verify the developed method. The measured result showed the good agreement with the used cylinder curvature with ${\pm}$5.18run uncertainty.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.10a
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• pp.154-157
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• 2003

Precision displacement of less than a few nm resolution was measured in real-time using fiber optic EFPI sensor. The novel method for real-time processing of analyzing EFPI output signal was developed and verified. Linearity in the mean values of interferometric light intensity among adjacent fringes was shown, and the sinusoidal approximation algorithm that estimates past and coming fringe values was verified through the linearity. Real-time signal processing program was developed, and the intensity signal of the EFPI sensor was transformed to the phase shift with this program. The resolution below 0.4 ~ 10 nm in the displacement range of $0 ~ 300\mu\textrm{m}$ was obtained by reducing the photodetector noise using low-pass filter and signal averaging. The nano-translation stage with a Piezo-electric actuator and the EFPI sensor system was designed and tested. This stage successfully reached to the desired destination in $15\mu\textrm{m}$ range within 1 nm accuracy.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.3
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• pp.40-45
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• 2008

This paper presents a linear positioning system and its control algorithm design with nano accuracy/resolution. The basic linear stage structure is driven by an ultrasonic motor and its displacement feedback is detected by a LDGI (Laser Diffraction Grating Interferometer), which can achieve nanometer resolution. Due to the friction driving property of the ultrasonic motor, the driving situation differs in various ranges along the travel. Experiments have been carried out in order to observe and realize the phenomena of the three main driving modes: AC mode (for mm motion), Gate mode (for ${\mu}m$ motion), and DC mode (for nm motion). A proposed FCMAC (Fuzzy Cerebella Model Articulation Controller) control algorithm is implemented for manipulating and predicting the velocity variation during the motion of each mode respectively. The PCbased integral positioning system is built up with a NI DAQ Device by a BCB (Borland $C^{++}$ Builder) program to accomplish the purpose of an intelligent nanopositioning control.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.386-393
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• 2008

A position control method for interpolating aspherical grinding and polishing tool path was reviewed and experimented in a nano precision machine. The position-base algorithm was reformed from the time-base algorithm, proposed in the previous study. The characteristics of the algorithm were in the velocity control loop with position feedback. The aspherical surface was divided by an interval at which each velocity and acceleration were calculated. The theoretical velocity was corrected by position error during processing. In the experiment, a machine was constructed and nano-scale linear encoders were installed at each axis. Relation between process parameters and the variation of position error was monitored and discussed. The best result from optimized parameters showed that the accuracy was 150nm and improved from the previous report.

• Journal of the Korean Society of Visualization
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• v.2 no.1
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• pp.12-17
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• 2004

The physical characteristics of soot near the soot inception point were investigated with various measurements. In-situ measurements of particle size and volume fraction were introduced based on time resolved laser-induced incandescence (TIRE-LII) and laser-induced ion mobility (LIIM). The one has more convenience and accuracy than conventional LII technique and the other works best for particle sizes of a few nanometers at high concentrations in a uniform concentration field. A complementary ex-situ measurement of particle size is nano differential mobility analyzer (Nano-DMA), which recently developed for measuring particle sizes between 2nm and 100nm and provides high-resolution size information for early soot. Particles will be also collected on transmission electron microscope (TEM) grids using rapid thermophoretic sampling and analyzed for morphology. These measurements will allow fresh and original insight into the characterizing soot inception process. The measured physical properties of incipient soot will clarify the controlling growth mechanism combined with chemical ones, and the dominant mechanism for soot modeling can be deduced from the information.