• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.157-166
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• 2024

Probability of decryption failure of a public key cryptography based on LWE(learning with errors) is determined by its architecture and parameter settings. Since large decryption failure probability leads to attacks[1] on scheme as well as degradation of performance, TiGER[2], a Ring-LWE(R)-based KEM proposed for the first round of KpqC, tried to reduce the decryption failure probability by using error correction code Xef and D2 encoding method. However, D'Anvers et al. has shown that the commonly assumed independence of each bit error is not established since in the case of an encryption scheme based on Ring-LWE(R) using an error correction code, there is error dependency which is not negligible[3]. In this paper, since TiGER does not consider the error dependency, we calcualte the decryption failure probability of TiGER by considering the error dependency. In addition, we found that the bit error probability is incorrectly calculated in TiGER, so we present the correct calculation.

• Journal of the Mineralogical Society of Korea
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• v.21 no.3
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• pp.321-329
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• 2008

Amorphous silica nanoparticles are among the most fundamental $SiO_2$ compounds, having implications in diverse geological processes and technological applications. Here, we explore structural details of amorphous silica nanoparticles with varying particle sizes (7 and 14 nm) using $^{29}Si$ and $^{1}H$ MAS NMR spectroscopy together with quantum chemical calculations to have better prospect for their size-dependent atomic structures. $^{29}Si$ MAS NMR spectra at 9.4 T resolve $Q^2,\;Q^3$ and $Q^4$ species at -93 ppm, -101 ppm, -110 ppm, respectively. The fractions of $Q^2,\;Q^3,\;O^4$ species are $7{\pm}1%,\;27{\pm}2%$, and $66{\pm}2%$ for 7 nm amorphous silica nanoparticles and $6{\pm}1%,\;21{\pm}2%$, and $73{\pm}2%$ for 14 nm amorphous silica nanoparticles. Whereas it has been suggested that $Q^2$ and $Q^3$ species exist on particles surfaces, the difference in $Q^{2}\;+\;Q^{3}$ fraction in both 7 and 14 nm particles is not significant, suggesting that $Q^2$ and $Q^3$ species could exist inside particles. $^{1}H$ MAS NMR spectra at 11.7 T shows diverse hydrogen environments, including physisorbed water, hydrogen bonded silanol, and non-hydrogen bonded silanol with varying hydrogen bond strength. The hydrogen contents in the 7nm silica nanoparticles (including water and hydroxyl groups) are about 3 times of that of 14 nm particles. The larger chemical shills for proton environments in the former suggest stronger hydrogen bond strength. The fractions of non-hydrogen bonded silanols in the 14 nm amorphous silica nanoparticles are larger than those in 7 nm amorphous silica nanoparticles. This observation suggests closer proximity among hydrogen atoms in the nanoparticles with smaller diameter. The current results with high-resolution solid-state NMR reveal previously unknown structural details in amorphous silica nanoparticles with particle size.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.355-363
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• 2023

In this study, we explore the nature of clumped isotopes of H₂O molecule using quantum chemical calculations. Particularly, we estimated the relative clumping strength between diverse isotopologues, consisting of oxygen (¹⁶O, ¹⁷O, and ¹⁸O) and hydrogen (hydrogen, deuterium, and tritium) isotopes and quantify the effect of temperature on the extent of isotope clumping. The optimized equilibrium bond lengths and the bond angles of the molecules are 0.9631-0.9633 Å and 104.59-104.62°, respectively, and show a negligible variation among the isotopologues. The calculated frequencies of the modes of H₂O molecules decrease as isotope mass number increases, and show a more prominent change with varying hydrogen isotopes over those with oxygen isotopes. The equilibrium constants of isotope substitution reactions involving these isotopologues reveal a greater effect of hydrogen mass number than oxygen mass number. The calculated equilibrium constants of clumping reaction for four heavy isotopologues showed a strong correlation; particularly, the relative clumping strength of three isotopologues was 1.86 times (HT¹⁸O), 1.16 times (HT¹⁷O), and 0.703 times (HD¹⁷O) relative to HD¹⁸O, respectively. The relative clumping strength decreases with increasing temperature, and therefore, has potential for a novel paleo-temperature proxy. The current calculation results highlight the first theoretical study to establish the nature of clumped isotope fractions in H₂O including ¹⁷O and tritium. The current results help to account for diverse geochemical processes in earth's surface environments. Future efforts include the calculations of isotope fractionations among various phases of H₂O isotopologues with a full consideration of the effect of anharmonicity in molecular vibration.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.1
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• pp.1-10
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• 2020

The atomic structures of silicate liquids at high pressure provide insights into the transport properties including thermal conductivities or elemental partitioning behavior between rocks and magmas in Earth's interior. Whereas the local electronic structure around silicon may vary with the arrangement of the nearby oxygens, the detailed nature of such relationship remains to be established. Here, we explored the atomic origin of the pressure-induced changes in the electronic structure around silicon by calculating the partial electronic density of states and L₃-edge X-ray absorption spectra of SiO₂ polymorphs. The result showed that the Si PDOS at the conduction band varies with the crystal structure and local atomic environments. Particularly, d-orbital showed the distinct features at 108 and 130 eV upon the changes in the coordination number of Si. Calculated Si XAS spectra showed features due to the s,d-orbitals at the conduction band and varied similarly with those observed in s,d-orbitals upon changes in the crystal structures. The calculated Si XAS spectrum for α-quartz was analogous to the experimental Si XRS spectrum for SiO₂ glass, implying the overall similarities in the local atomic environments around the Si. The edge energies at the center of gravity of XAS spectra were closely related to the Si-O distance, thus showing the systematic changes upon densification. Current results suggest that the Si L_2,3-edge XRS, sensitive probe of the Si-O distance, would be useful in unveiling the densification mechanism of silicate glasses and melts at high pressure.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.6
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• pp.442-450
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• 2014

Concern has grown over a presence of micropollutants in natural water since sulfonamide antibiotic substances such as sulfamethazine, sulfamethoxazole, sulfathiazole have been frequently detected in Nakdong River, Korea. The current work investigates the degradation of the three sulfonamide substances by using quantum chemistry calculations of density functional theory (DFT) and experimental measurement techniques of Fourier transform infrared spectroscopy (FT-IR) and ultraviolet-visible spectrophotometer (UV-VIS). DFT calculations demonstrate that the lowest energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbitals (LUMO) lies in sulfanilamide functional group of sulfonamide, implying that the sulfanilamide functional group would be the most active site for ozone oxidation. Also, UV-VIS spectra and FT-IR analysis reveal that 260 nm band originated from sulfanilamide group was absent after ozone oxidation, indicating that a functional group of amine (N-H) was removed from sulfanilamide. Both theoretical and experimental observations agree well with each other, demonstrating the DFT calculation tool can be an alternative tool for the prediction of chemical reactions in purification treatment processes.

• Journal of the Korean Vacuum Society
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• v.21 no.5
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• pp.273-278
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• 2012

Over the last decade, the hafnium-based gate dielectric materials have been studied for many application fields. Because these materials had excellent behaviors for suppressing the quantum-mechanical tunneling through the thinner dielectric layer with higher dielectric constant (high-K) than $SiO_2$ gate oxides. Although high-K materials compensated the deterioration of electrical properties for decreasing the thickness of dielectric layer in MOSFET structure, their nano-mechanical properties of $HfO_2$ thin film features were hardly known. Thus, we examined nano-mechanical properties of the Hafnium oxide ($HfO_2$) thin film in order to optimize the gate dielectric layer. The $HfO_2$ thin films were deposited by rf magnetron sputter using hafnium (99.99%) target according to various oxygen gas flows. After deposition, the $HfO_2$ thin films were annealed after annealing at $400^{\circ}C$, $600^{\circ}C$ and $800^{\circ}C$ for 20 min in nitrogen ambient. From the results, the current density of $HfO_2$ thin film for 8 sccm oxygen gas flow became better performance with increasing annealing temperature. The nano-indenter and Weibull distribution were measured by a quantitative calculation of the thin film stress. The $HfO_2$ thin film after annealing at $400^{\circ}C$ had tensile stress. However, the $HfO_2$ thin film with increasing the annealing temperature up to $800^{\circ}C$ had changed compressive stress. This could be due to the nanocrystal of the $HfO_2$ thin film. In particular, the $HfO_2$ thin film after annealing at $400^{\circ}C$ had lower tensile stress, such as 5.35 GPa for the oxygen gas flow of 4 sccm and 5.54 GPa for the oxygen gas flow of 8 sccm. While the $HfO_2$ thin film after annealing at $800^{\circ}C$ had increased the stress value, such as 9.09 GPa for the oxygen gas flow of 4 sccm and 8.17 GPa for the oxygen gas flow of 8 sccm. From these results, the temperature dependence of stress state of $HfO_2$ thin films were understood.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.