Highlight Articles

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  Mössbauer studies and inductive thermal properties of Mg_x‑doped maghemite nanoparticles

  Hyunkyung Choi, Chul Sung Kim, Young Bae Lee

  J. Korean Phys. Soc. 80(12), 1148 - 1152 (2022)

  Magnetic nanoparticles-based hyperthermia has remarkable potential for cancer treatment. In particular, maghemite (γ-Fe₂O₃) is a technologically important compound because of its nontoxicity and thermal and chemical stability. We focused on magnetic induction heating research by controlling the content of Mg-ions occupying Fe vacancies inside the octahedral site of maghemite as Mg²⁺ cations are considered as factors that can improve biocompatibility in terms of bio-application. For hyperthermia applications, we treated nanoparticles with plasma to maximize the results of the induction heating experiment. We also discuss the magnetic induction heating in AC magnetic fields and Mössbauer studies of the Mg_x-doped γ-Fe₂O₃ nanoparticles.
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  Long‑range distribution of high‑quality time‑bin entangled photons
  for quantum communication

  Jin‑Hun Kim, Jin‑Woo Chae, Youn‑Chang Jeong et al.

  J. Korean Phys. Soc. 80(3), 203 - 213 (2022)

  Distributing entangled states to remote users via widely distributed fiber networks has been a difficult task, especially in a high-quality manner. we present an experimental distribution of high-quality entangled qubits over long-distance fiber channels, utilizing time-bin mode in particular because to its exceptional robustness in fiber-optic distributions. We demonstrate that time-bin entanglement can be reliably shared between two distant parties separated by up to 60 kilometers in all fiber-based implementations, and showing the significance of our study in long-range, long-lasting quantum communication.
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  Propagation of stochastic fluctuations in RNA polymerase abundance
  in constitutive gene expression

  Juneil Jang, Cheol‑Min Ghim

  J. Korean Phys. Soc. 80(3), 279 - 283 (2022)

  Varied intracellular abundance of gene expression machineries, such as RNA polymerase (RNAP) or ribosome, comprises a source of cell-to-cell variability emerging from an isogenic cell population. The stochastic model of gene expression, where the varying RNAP copy number acts as a major source of extrinsic noise, shows that the noise in the downstream protein expression can be mitigated when varied RNAP availability is incorporated with less efficient but steady translation. This is actually the case of the bacteriophage T7 RNAP-based expression system often employed in synthetic biology applications. Slow and steady beats the noise.
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  The inclination of threading dislocation in chemical vapor deposition-grown single-crystal diamond analyzed by synchrotron white beam X-ray topography

  Hyemin Jang, Moonkyong Na, Wook Bahng et al.

  J. Korean Phys. Soc. 80(2), 175 - 184 (2022)

  In this study, the inclination of threading dislocations in an on-axis single-crystal free-standing diamond grown by microwave plasma-enhanced chemical vapor deposition (MPCVD) was analyzed using synchrotron white beam X-ray topography (SWBXRT). The majority of dislocations in CVD-grown diamond were known as [001] threading dislocation; however, SWBXRT indicated that the dislocations were inclined from [001] direction. The exact [001] dislocation accounted for 20 % of investigated dislocations, and the remaining dislocations inclined randomly from the [001] direction with 7–12°. The analyzed sample has no dependence on a particular direction due to localized step flow caused by on-axis growth.
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  Iterative peak-fitting of frequency-domain data via deep convolution neural networks

  Seong-Heum Park, Hyeongseon Park, Hyunbok Lee et al.

  J. Korean Phys. Soc. 79(12), 1199 - 1208 (2021)

  We combine deep convolution neural networks and conventional global optimization techniques to analyze x-ray photoemission data. By employing the most advanced form of convolution neural network architecture, we could iteratively subtract peak features from synthetic and actual photoemission spectra, after which conventional global optimization methods can be applied to calibrate the results. Our model could recognize defect-induced peaks in MoS2 and WS2 that could be easily overlooked, showing the power of deep neural network models in capturing subtle but existing features from experimental results.
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  Synthesis of Ni-based fluoroperovskites by solvent-free mechanochemical reaction

  Jin San Choi, Muhammad Sheeraz, Fazli Akram et al.

  J. Korean Phys. Soc. 79(11), 1042 - 1050 (2021)

  Ni-based fluoroperovskite ANiF₃ (A = Na, K, and Ag) is a promising candidate of emerging materials due to potential applications to functional devices as well as large variety of novel physical phenomena. Despite the tremendous interest, synthesis of the fluoroperovskites is challenging owing to their vulnerability to humidity. Herein, we demonstrate the realization of Ni-based fluoroperovskites using solvent-free mechanochemical methods based on the conventional solid-state reaction. The physical properties of the as-synthesized ANiF₃ powders are characterized by various experimental techniques. We also discuss an effect of chemical off-stoichiometry on the structural phases of fluoride perovskites through the Rietveld refinement analyses.