• Current Applied Physics
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• v.18 no.12
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• pp.1564-1570
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• 2018

Charge transport dynamics in ZnO based inverted organic solar cell (IOSC) has been characterized with transient photocurrent spectroscopy and localised photocurrent mapping-atomic force microscopy. The value of maximum exciton generation rate was found to vary from $2.6{\times}10^{27}m^{-3}s^{-1}$ ($J_{sat}=79.7A\;m^{-2}$) to $2.9{\times}10^{27}m^{-3}s^{-1}$ ($J_{sat}=90.8A\;m^{-2}$) for devices with power conversion efficiency ranging from 2.03 to 2.51%. These results suggest that nanorods served as an excellent electron transporting layer that provides efficient charge transport and enhances IOSC device performance. The photovoltaic performance of OSCs with various growth times of ZnO nanorods have been analysed for a comparison between AM1.5G spectrum and local solar spectrum. The simulated PCE of all devices operating under local spectrum exhibited extensive improvement with the gain of 13.3-3.7% in which the ZnO nanorods grown at 15 min possess the highest PCE under local solar with the value of 2.82%.

• Current Applied Physics
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• v.18 no.12
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• pp.1465-1472
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• 2018

The magnetic and optical properties of Ce-doped ZnO systems have been widely demonstrated, but the effects of different strains of Ce-doped ZnO systems remain unclear. To solve these problems, this study identified the effects of biaxial strain on the electronic structure, absorption spectrum, and magnetic properties of Ce-doped ZnO systems by using a generalized gradient approximation + U (GGA + U) method with plane wave pseudopotential. Under unstrained conditions, the formation energy decreased, the system became stable, and the doping process became easy with the increase in the distances between two Ce atoms. The band gap of the systems with different strains became narrower than that of undoped ZnO without strain, and the absorption spectra showed a red shift. The band gap narrowed, and the red shift became weak with the increase of compressive strain. By contrast, the band gap widened, and the red shift became significant with the increase of tensile strain. The red shift was significant when the tensile strain was 3%. The systems with -1%, 0%, and 1% strains were ferromagnetic. For the first time, the magnetic moment of the system with -1% strain was found to be the largest, and the system showed the greatest beneficial value for diluted magnetic semiconductors. The systems with -3%, -2%, 2%, and 3% strains were non-magnetic, and they had no value for diluted magnetic semiconductors. The ferromagnetism of the system with -1% strain was mainly caused by the hybrid coupling of Ce-4f, Ce-5d, and O-2p orbits. This finding was consistent with Zener's Ruderman-Kittel-Kasuya-Yosida theory. The results can serve as a reference for the design and preparation of new diluted magnetic semiconductors and optical functional materials.

• Journal of Astronomy and Space Sciences
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• v.39 no.1
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• pp.11-22
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• 2022

It is suggested that magnetosonic waves (also known as equatorial noise) can scatter radiation belt electrons in the Earth's magnetosphere. Therefore, it is important to understand the global distribution of these waves between the proton cyclotron frequency and the lower hybrid resonance frequency. In this study, we developed an empirical model for estimating the global distribution of magnetosonic wave amplitudes and wave normal angles. The model is based on the entire mission period (approximately 2012-2019) of observations of Van Allen Probes A and B as a function of the distance from the Earth (denoted by L^*), magnetic local time (MLT), magnetic latitude (λ), and geomagnetic activity (denoted by the Kp index). In previous studies the wave distribution inside and outside the plasmasphere were separately investigated and modeled. Our model, on the other hand, identifies the wave distribution along with the ambient plasma environment-defined by the ratio of the plasma frequency (f_pe) to the electron cyclotron frequency (f_ce)-without separately determining the wave distribution according to the plasmapause location. The model results show that, as Kp increases, the dayside wave amplitude in the equatorial region intensifies. It thereby propagates the intense region towards the wider MLT and inward to L^* < 4. In contrast, the f_pe/f_ce ratio decreases with increasing Kp for all regions. Nevertheless, the decreasing aspect differs between regions above and below L^* = 4. This finding implies that the particle energy and pitch angle that magnetosonic waves can effectively scatter vary depending on the locations and geomagnetic activity. Our model agrees with the statistically observed wave distribution and ambient plasma environment with a coefficient of determination of > 0.9. The model is valid in all MLTs, 2 ≤ L^* < 6, |λ| < 20°, and Kp ≤ 6.

• Advances in nano research
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• v.13 no.2
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• pp.187-197
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• 2022

The synthesis of organic and hybrid organic-inorganic perovskites directly from solution improves the cost- and energy-efficiency of processing. To date, numerous research efforts have been devoted to investigating the influence of the various solvent parameters for the synthesis of lead halide perovskites, focused on the effects of different single solvents on the efficiency of the resulting perovskites. In this work, we investigated the effect of solvent blends for the first time on the structure and phase of perovskites produced via the Lewis base vapor diffusion method to develop a new synthetic approach for water-stable CsPbBr₃ particles with nanometer-sized dimensions. Solvent blends prepared with DMF and water-miscible solvents with different Gutmann's donor numbers (D_N) affect the Pb ions differently, resulting in a variety of lead bromide species with various colors. The use of a DMF/isopropanol solvent mixture was found to induce the formation of the Ruddlesden-Popper perovskite based on lead bromide. This perovskite undergoes a blue color shift in the solvated state owing to the separation of nanoplatelets. In contrast, the replacement of isopropanol with DMSO, which has a high DN, induces the formation of spherical CsPbBr₃ perovskite nanoparticles that exhibit green emission. Finally, the integration of acetone in the solvent system leads to the formation of lead bromide complexes with a yellow-orange color and the perovskite CsPbBr₃.

• Advances in nano research
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• v.12 no.5
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• pp.515-527
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• 2022

The application of fibers in concrete obviously enhances the properties of concrete, also the application of natural fibers in concrete is raising due to the availability, low cost and environmentally friendly. Besides, predicting the mechanical properties of concrete in general and shear strength in particular is highly significant in concrete mixture with fiber nanocomposite reinforced concrete (FRC) in construction projects. Despite numerous studies in shear strength, determining this strength still needs more investigations. In this research, Adaptive Neuro-Fuzzy Inference System (ANFIS) have been employed to determine the strength of reinforced concrete with fiber. 180 empirical data were gathered from reliable literature to develop the methods. Models were developed, validated and their statistical results were compared through the root mean squared error (RMSE), determination coefficient (R²), mean absolute error (MAE) and Pearson correlation coefficient (r). Comparing the RMSE of PSO (0.8859) and ANFIS (0.6047) have emphasized the significant role of structural parameters on the shear strength of concrete, also effective depth, web width, and a clear depth rate are essential parameters in modeling the shear capacity of FRC. Considering the accuracy of our models in determining the shear strength of FRC, the outcomes have shown that the R² values of PSO (0.7487) was better than ANFIS (2.4048). Thus, in this research, PSO has demonstrated better performance than ANFIS in predicting the shear strength of FRC in case of accuracy and the least error ratio. Thus, PSO could be applied as a proper tool to maximum accuracy predict the shear strength of FRC.

• Journal of People, Plants, and Environment
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• v.23 no.5
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• pp.545-554
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• 2020

Background and objective: Moth orchids in the vegetative stage are suitable for a multi-layer growing environment in a closed-type plant factory which can be a good alternative that can reduce production costs by reducing cultivation time and energy cost per plant. This study was conducted to find out the optimal rhizospheric environment for different irrigation methods without a potting medium and rhizospheric ventilation for the vegetative growth of young Phalaenopsis hybrid 'Blanc Rouge' (P. KV600 × P. Kang 1) and Phalaenopsis Queen Beer 'Mantefon' in a closed-type plant factory system. Methods: The one-month-old clonal micropropagules with bare roots rapped with a sponges were fixed on the holes of styrofoam plates above growth beds, and were watered using the ebb-and-flow (EBB) and aeroponic (AER) methods with Ichihashi solution (0.5 strength) once a day at 06:00 (P) or 18:00 (S), and both (PS). Rhizospheric ventilation (V) was also applied to change the temperature, relative humidity, and CO₂ concentration of the beds. Plants potted into sphagnum moss and watered once a week were used as the control group. Results: After 12 months of treatment, the growth characteristics of the EBB groups were the best among the treatment groups without a medium, but no effect of irrigation timing was observed. V reduced the temperature, relative humidity and CO₂ concentration of the beds. Whereas, EBB+V (ebb-and-flow with ventilation) improved plant growth and reduced the occurrence of disorders and withering. Especially, EBB+V showed a similar performance to the control group. Conclusion: The results indicated that the optimal irrigation method without a potting medium for producing middle-aged potted moth orchids was the EBB system with forced rhizospheric ventilation. Therefore, further studies on the optimal ventilation method and moisture control of the crown need to be carried out to develop the irrigation system without a potting medium for vertical farming in closed-type plant factories.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.100-108
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• 2023

In hybrid block-based video coding, transform coding converts spatial domain residual signals into frequency domain data and concentrates energy in a low frequency band to achieve a high compression efficiency in entropy coding. The state-of-the-art video coding standard, VVC(Versatile Video Coding), uses DCT-2(Discrete Cosine Transform type 2), DST-7(Discrete Sine Transform type 7), and DCT-8(Discrete Cosine Transform type 8) for primary transform. In this paper, considering that DCT-2, DST-7, and DCT-8 are all linear transformations, we propose an inverse transform that reduces the number of multiplications in the inverse transform by using the linearity of the linear transform. The proposed inverse transform method reduced encoding time and decoding time by an average 26%, 15% in AI and 4%, 10% in RA without the increase of bitrate compared to VTM-8.2.

• Steel and Composite Structures
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• v.47 no.2
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• pp.167-184
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• 2023

In this study, a new recentering friction device (RFD) to retrofit steel moment frame structures is introduced. The device provides both self-centering and energy dissipation capabilities for the retrofitted structure. A hybrid performance-based seismic design procedure considering multiple limit states is proposed for designing the device and the retrofitted structure. The design of the RFD is achieved by modifying the conventional performance-based seismic design (PBSD) procedure using computational intelligence techniques, namely, genetic algorithm (GA) and artificial neural network (ANN). Numerous nonlinear time-history response analyses (NLTHAs) are conducted on multi-degree of freedom (MDOF) and single-degree of freedom (SDOF) systems to train and validate the ANN to achieve high prediction accuracy. The proposed procedure and the new RFD are assessed using 2D and 3D models globally and locally. Globally, the effectiveness of the proposed device is assessed by conducting NLTHAs to check the maximum inter-story drift ratio (MIDR). Seismic fragilities of the retrofitted models are investigated by constructing fragility curves of the models for different limit states. After that, seismic life cycle cost (LCC) is estimated for the models with and without the retrofit. Locally, the stress concentration at the contact point of the RFD and the existing steel frame is checked being within acceptable limits using finite element modeling (FEM). The RFD showed its effectiveness in minimizing MIDR and eliminating residual drift for low to mid-rise steel frames models tested. GA and ANN proved to be crucial integrated parts in the modified PBSD to achieve the required seismic performance at different limit states with reasonable computational cost. ANN showed a very high prediction accuracy for transformation between MDOF and SDOF systems. Also, the proposed retrofit showed its efficiency in enhancing the seismic fragility and reducing the LCC significantly compared to the un-retrofitted models.

• Journal of Electrochemical Science and Technology
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• v.13 no.2
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• pp.177-185
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• 2022

Electrochemical properties of LiMn₂O₄ cathode were investigated in three types of Zn-containing electrolytes: lithium-zinc sulfate electrolyte (1M ZnSO₄ / 2M Li₂SO₄), zinc sulfate electrolyte (2MZnSO₄) and lithium-zinc-manganese sulfate electrolyte (1MZnSO₄ / 2MLi₂SO₄ / 0.1MMnSO₄). Cyclic voltammetry measurements demonstrated that LiMn₂O₄ is electrochemically inactive in pure ZnSO₄ electrolyte after initial oxidation. The effect of manganese (II) additive in the zinc-manganese sulfate electrolyte on the electrochemical performance was analyzed. The initial capacity of LiMn₂O₄ is higher in presence of MnSO₄ (140 mAh g^-1 in 1 M ZnSO₄ / 2 M Li₂SO₄ / 0.1 M MnSO₄ and 120 mAh g^-1 in 1 M ZnSO₄ / 2MLi₂SO₄). The capacity increase can be explained by the electrodeposition of MnO_x layer on the electrode surface. Structural characterization of postmortem electrodes with use of XRD and EDX analysis confirmed that partially formed in pure ZnSO₄ electrolyte Zn-containing phase leads to fast capacity fading which is probably related to blocked electroactive sites.