Younghwan Son

Bio: Younghwan Son is an academic researcher from Seoul National University. The author has contributed to research in topics: Bottom ash & MOSFET. The author has an hindex of 11, co-authored 79 publications receiving 454 citations.

Characterization of oxide traps leading to RTN in high-k and metal gate MOSFETs

Abstract: We proposed a new method for characterization of oxide traps leading to Random Telegraph Noise (RTN) in high-k and metal gate MOSFETs considering their energy band structure. Through this method and drain and gate current RTN measurement, we extracted positions, energy levels and activation energies of oxide traps in high-k dielectric as well as in interfacial layer.

Characterization of an Oxide Trap Leading to Random Telegraph Noise in Gate-Induced Drain Leakage Current of DRAM Cell Transistors

Abstract: An accurate method for extracting the depth and the energy level of an oxide trap from random telegraph noise (RTN) in the gate-induced drain leakage (GIDL) current of a metal-oxide-semiconductor field-effect transistor (MOSFET) is developed, which correctly accounts for variation in surface potential and Coulomb energy. The technique employs trap capture and emission times defined from the characteristics of GIDL. Ignoring this variation in surface potential leads to an error of up to 116% in trap depth for 80-nm technology generation MOSFETs. RTN amplitude as a function of MOSFET drain-gate voltage is also investigated.

Characterization of the Variable Retention Time in Dynamic Random Access Memory

Abstract: To study the relationship between the original leakage current fluctuation and the detected variable retention time (VRT) from the retention test of dynamic random access memory (DRAM), we simulated the real procedure of the VRT measurement of DRAM. By investigating the results of the simulation, we proposed a new effective VRT measurement method based on the comparison between measurement and simulation. In addition, we investigated the characteristics of the VRT phenomenon in DRAM using the VRT characterization method developed in this study.

Design of a simple paper-based colorimetric biosensor using polydiacetylene liposomes for neomycin detection

Abstract: We developed a paper-based analytical device (μPAD) combined with self-signaling polydiacetylene (PDA) liposomes for convenient visual neomycin detection The simple dot array type of μPAD was fabricated by the wax printing technique, and the PDA liposomes in the aqueous solution were facilely immobilized onto the hydrophilic dot region of the paper substrate We found that, when the PDA liposomes were inserted to the paper matrix, the stability of the PDA liposomes can be significantly enhanced by adding a hydrophilic reagent such as polyvinyl alcohol and glycerol to the liposome solution In particular, polyvinyl alcohol (PVA) provides the best stabilization among the various hydrophilic reagents tested in this contribution, and the enhanced stability sharply increased the sensitivity of the PDA liposomes in the paper matrix Based on the above results, we successfully detected neomycin through both naked-eye observation and fluorescence measurement of PDA signals The detection limit was 1 ppm and was selective to non-aminoglycoside antibiotics

American Society for Testing and Materials

Abstract: The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.

Global increasing trends in annual maximum daily precipitation

Abstract: This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann‐Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature,withthemedianintensityofextremeprecipitationchanginginproportionwithchangesinglobal mean temperature at a rate of between 5.9% and 7.7%K 21 , depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 138S and 118N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

Geostatistics For Environmental Scientists

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An experimental study of data retention behavior in modern DRAM devices: implications for retention time profiling mechanisms

Abstract: DRAM cells store data in the form of charge on a capacitor. This charge leaks off over time, eventually causing data to be lost. To prevent this data loss from occurring, DRAM cells must be periodically refreshed. Unfortunately, DRAM refresh operations waste energy and also degrade system performance by interfering with memory requests. These problems are expected to worsen as DRAM density increases.The amount of time that a DRAM cell can safely retain data without being refreshed is called the cell's retention time. In current systems, all DRAM cells are refreshed at the rate required to guarantee the integrity of the cell with the shortest retention time, resulting in unnecessary refreshes for cells with longer retention times. Prior work has proposed to reduce unnecessary refreshes by exploiting differences in retention time among DRAM cells; however, such mechanisms require knowledge of each cell's retention time.In this paper, we present a comprehensive quantitative study of retention behavior in modern DRAMs. Using a temperature-controlled FPGA-based testing platform, we collect retention time information from 248 commodity DDR3 DRAM chips from five major DRAM vendors. We observe two significant phenomena: data pattern dependence, where the retention time of each DRAM cell is significantly affected by the data stored in other DRAM cells, and variable retention time, where the retention time of some DRAM cells changes unpredictably over time. We discuss possible physical explanations for these phenomena, how their magnitude may be affected by DRAM technology scaling, and their ramifications for DRAM retention time profiling mechanisms.

AVATAR: A Variable-Retention-Time (VRT) Aware Refresh for DRAM Systems

Abstract: Multirate refresh techniques exploit the non-uniformity in retention times of DRAM cells to reduce the DRAM refresh overheads. Such techniques rely on accurate profiling of retention times of cells, and perform faster refresh only for a few rows which have cells with low retention times. Unfortunately, retention times of some cells can change at runtime due to Variable Retention Time (VRT), which makes it impractical to reliably deploy multirate refresh. Based on experimental data from 24 DRAM chips, we develop architecture-level models for analyzing the impact of VRT. We show that simply relying on ECC DIMMs to correct VRT failures is unusable as it causes a data error once every few months. We propose AVATAR, a VRT-aware multirate refresh scheme that adaptively changes the refresh rate for different rows at runtime based on current VRT failures. AVATAR provides a time to failure in the regime of several tens of years while reducing refresh operations by 62%-72%.