https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/50 2026-04-04T09:02:22Z https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/36598 Title: Forecasting daily reference evapotranspiration under different hydrological conditions using a hybrid wavelet-Bayesian optimization-Gaussian process regression model Authors: Khoshkam, Helaleh; Valipour, Mohammad; Bateni, Sayed M.; Jun, Changhyun; Kim, Dongkyun; Deenik, Jonathan L.; Karbasi, Masoud; Xu, Tongren Abstract: This study aimed to forecast daily reference evapotranspiration (ETo) for different horizons (1-, 3-, 5-, and 7-d-ahead) at six sites in China using Gaussian process regression (GPR), wavelet transform (WT) with GPR (W-GPR), Bayesian optimization (BO) with GPR (BO-GPR), and W-BO-GPR approaches. These sites were selected to sample various climatic and vegetative conditions. All approaches were subjected to two input configurations: the first consisted of the daily ETo, and the second included the daily mean air temperature, relative humidity, solar radiation, and ETo. Meteorological data from 2010 to 2016 and 2017 to 2019 at each station were used to train and test the models, respectively. The results show that preprocessing the input data with the WT improves the performance of GPR and BO-GPR. For the first (second) input configuration, the six-site average root mean square errors (RMSEs) of ETo forecasts from W-GPR for 1-, 3-, 5-, and 7-d-ahead were 75.6 %, 54.2 %, 41.6 %, and 32.9 % (73.6 %, 51.6 %, 38.2 %, and 28.2 %) less than those of GPR, respectively. A similar reduction was observed in the RMSEs when BO-GPR was hybridized with the WT approach. The BO can successfully tune the hyperparameters of the GPR. For the first input configuration, the six-site average mean absolute errors (MAEs) of ETo forecasts from BO-GPR for the 1-, 3-, 5-, and 7-d horizons were 0.568, 0.709, 0.741, and 0.765 mm/d, respectively, which were 8.4 %, 8.3 %, 8.2 %, and 7.4 % smaller than the GPR MAEs (0.620, 0.773, 0.807, and 0.826 mm/d, respectively). Similarly, for the second input combination, BO-GPR outperformed GPR. Finally, the developed models were evaluated against two benchmark models: random forest (RF) and long short-term memory (LSTM). The proposed W-BO-GPR model demonstrated superior performance compared to the other models. 2026-06-01T00:00:00Z https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/36485 Title: Fabrication of additive-free manganese-1,3,5-benzenetricarboxylate thin-film anodes via alternating current electrophoretic deposition for stable lithium storage Authors: Lee, Jiyeon; Park, Byoungnam Abstract: We report a binder- and conductive-additive-free Mn-BTC metal–organic framework anode for lithium-ion batteries fabricated by AC electrophoretic deposition (AC-EPD). The AC-EPD process produces a uniform, mechanically robust, and electronically percolated Manganese-1,3,5-benzenetricarboxylate (Mn-BTC) layer directly on the current collector, eliminating inactive components and maximizing the fraction of electrochemically active material. As a result, the Mn-BTC anode delivers high reversible capacity with excellent rate capability and stable long-term cycling, maintaining its performance over repeated charge–discharge processes. Compared with conventional slurry-cast Mn-BTC electrodes that require polymer binders and carbon additives, our AC-EPD-derived electrodes exhibit superior kinetics and durability, demonstrating a scalable route to high-performance MOF-based anodes. © 2024 2026-05-15T00:00:00Z https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/36486 Title: Interface-dominated photocurrent suppression in ZnO/MAPbI₃/Ag phototransistors Authors: Park, Byoungnam Abstract: This work investigates zinc oxide (ZnO)-templated methylammonium lead iodide (MAPbI₃) field-effect transistors with and without silver (Ag) nanodots, focusing on how the ZnO/perovskite buried interface and Ag-induced surface doping jointly govern charge transport and photoresponse. Although Ag nanodots are generally introduced to enhance device performance through plasmonic effects, incorporating a ZnO templating layer leads to a fundamentally different operating behavior. From a structural perspective, the ZnO underlayer induces the formation of larger perovskite grains, which markedly enhances dark p-channel conductivity by suppressing carrier scattering. In contrast, under optical excitation, the Ag-decorated MAPbI₃/ZnO heterostructure exhibits pronounced photocurrent suppression, resulting in poorer photoresponse compared to the pristine device. This counterintuitive behavior is strongly supported by device-level evidence indicating nonradiative recombination and efficient carrier quenching at the electronically mismatched n-type ZnO/p-doped Ag–perovskite interface. Together, these findings highlight a critical trade-off between morphological benefits and interfacial recombination losses, defining important design limitations for hybrid perovskite optoelectronic devices. © 2026 Elsevier B.V. 2026-05-01T00:00:00Z https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/36180 Title: Synthesis of functional chalcogenide materials for memory/sensing devices and their integration into artificial sensory systems Authors: Liu, Pengfei; Heo, Jae Won; Bong, Hyeonmin; Choe, Jinsik; Lee, Huiyoung; Lee, Won-Kyu; Kim, Myung-Gil; Son, Donghee; Kang, Joohoon; Eom, Taeyong; Park, Sungjin; Kim, In Soo Abstract: With distinctive phase-change and switching properties, chalcogenide materials have emerged as critical components in various cutting-edge technologies. This review attempts to provide an overview of chalcogenide materials, from their fundamental properties to their diverse applications with focus on memory and sensing technologies, which are indispensable components in human-like electronic artificial sensory systems. After reviewing the synthesis and application of chalcogenide materials with respect to dimensionality, we focus on the key advances in (1) memory devices, including phase-change memory (PCM), ovonic threshold switching (OTS) selectors, and selector-only memory (SOM), and (2) sensing devices, including optical sensors, gas sensors, and neuromorphic sensors. Emphasis will be given on how chalcogenide materials can be integrated into next-generation systems, such as wearable platforms, artificial intelligence, and neuromorphic/quantum computing systems, to meet the growing demands for high-performance memory and multi-functional sensing. We also provide an overview of emerging research trends as well as a comprehensive perspective on the current status of research on chalcogenides. Finally, we attempt to provide insights into how chalcogenides can continue to drive technological breakthroughs in both memory and sensing applications while shaping the future landscape of intelligent systems, smart sensing platforms, and sustainable technology development. 2026-04-01T00:00:00Z