https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/677 2026-07-24T15:09:42Z 2026-07-24T15:09:42Z Park, Seungjoo Lee, Hyunmin Vu, Thanh Van Kang, Youngjong https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/219159 2026-07-15T05:00:15Z 2026-10-01T00:00:00Z

Title: Chaotrope-assisted aqueous depolymerization of polycarbonate with spontaneous catalyst regeneration Authors: Park, Seungjoo; Lee, Hyunmin; Vu, Thanh Van; Kang, Youngjong Abstract: Aqueous chemical recycling of condensation polymers represents an ideal pathway for a circular economy, yet its implementation is severely hindered by the profound hydrophobic barrier at the polymer-water interface. Herein, we report a chaotropic salt-assisted aqueous depolymerization system that overcomes this limitation. We demonstrate that chaotropic ions (e.g., guanidinium) enhance wetting and polymer-water interfacial accessibility of hydrophobic polycarbonate (PC), thereby enabling efficient depolymerization over an Fe/MgO catalyst under mild conditions (100°C, 1 atm). While conventional batch recycling leads to catalyst deactivation via densification of carbonate species, we discovered that transitioning to an in situ one-pot sequential-feeding process promotes carbonate-mediated surface renewal and improves long-term catalyst stability. Detailed structural analysis reveals that the reaction-derived carbonate ions drive the selective surface segregation of iron species, forming active Fe2O3 nanoparticles on the catalyst exterior. This process effectively turns the typically detrimental phase transformation into a beneficial surface renewal mechanism. Consequently, the system achieved long-term stability (>10 days) processing a cumulative polymer load exceeding 100 times the catalyst mass with quantitative conversion and high monomer yield.

2026-10-01T00:00:00Z Jeong, Haeseong Peerapattana, Jomjai Yang, Seung Jee Chung, Hoeil https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218422 2026-07-08T11:00:18Z 2026-09-01T00:00:00Z

Title: Augmentation of vibrational spectroscopic datasets using local covariance-based sampling in latent space to make prediction models that are more tolerant to spectral variations caused by the physical properties of samples Authors: Jeong, Haeseong; Peerapattana, Jomjai; Yang, Seung Jee; Chung, Hoeil Abstract: An augmentation strategy for vibrational spectroscopic datasets using local covariance-based sampling in latent space is investigated to build a prediction model that is more tolerant to the spectral variation of samples caused by their physical properties. The strategy is based on the expansion of an original training dataset by adding newly generated spectra that go beyond the boundary of the original domain and the use of the expanded dataset for modeling. In this way, the generated spectra in the expanded domain emulate variations in the spectra caused by the physical properties of the sample. A data augmentation method that simultaneously leverages the capabilities of the Synthetic Minority Oversampling Technique (SMOTE) and the Mixup, called Local Covariance-based Augmentation (LoCA), is developed. To evaluate the utility of LoCA, Raman spectra of paracetamol tablets with four different packing densities and near-infrared (NIR) spectra of bovine serum albumin (BSA) powder samples with three different particle sizes are employed. The incorporation of LoCA-generated spectra for training is effective in building models for predicting the paracetamol and BSA concentrations that are more tolerant to variations in the spectra induced by differences in packing density and particle size, respectively. In overall, LoCA combining the local geometry-awareness of SMOTE and the input–output joint interpolation of Mixup for the augmentation in a latent space is beneficial to secure accuracy for vibrational spectroscopic analysis of solid samples under variation of their physical presentations.

2026-09-01T00:00:00Z Ahn, Su Min Lee, Seongho Lee, Ga-Been Natarajan, Logeshwaran Ravichandran, Balaji Kim, Nam Dong Kim, Sung-Soo Baek, Kitae Kang, Joonhee Yun, Hongseok Lee, Young Jun https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/211329 2026-03-18T02:30:29Z 2026-08-01T00:00:00Z

Title: Hydroxyl-blocking lignin-derived carbon catalysts for selective and durable hydrogen peroxide electrosynthesis Authors: Ahn, Su Min; Lee, Seongho; Lee, Ga-Been; Natarajan, Logeshwaran; Ravichandran, Balaji; Kim, Nam Dong; Kim, Sung-Soo; Baek, Kitae; Kang, Joonhee; Yun, Hongseok; Lee, Young Jun Abstract: Metal-free oxygen-functionalized carbon materials are promising electrocatalysts for selective hydrogen peroxide (H2O2) production via the two-electron oxygen reduction reaction (ORR). However, precisely controlling oxygen moieties while maintaining scalability remains challenging. Herein, we present a scalable and sustainable Friedel-Crafts reaction-assisted carbonization strategy that converts lignin into oxygen-tunable carbon catalysts for efficient H2O2 electrosynthesis. Electrochemical measurements reveal a strong correlation between carbonization temperature, oxygen speciation, and catalytic performance. Specifically, carbonyl and carboxyl groups enhance H2O2 selectivity, while hydroxyl groups suppress H2O2 formation by preferentially binding O* intermediates. Density functional theory corroborates these findings, indicating that carbonyl and carboxyl groups favor the two-electron pathway. Accordingly, selective blocking of hydroxyl groups achieves > 95 % H2O2 selectivity, a production rate of 575.5 mmol g(cat)(-1) h(-1) at 0.4 V-RHE, and stable operation for 40 h. This renewable, low-cost platform couples mechanistic control with scalable synthesis, potentially enabling decentralized H2O2 generation in on-site disinfection and wastewater treatment.

2026-08-01T00:00:00Z Parrey, Khursheed Ahmad Ayranci, Rukiye Choi, Hyosung Ak, Metin https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/217785 2026-07-02T02:30:22Z 2026-08-01T00:00:00Z

Title: Electrochemical Design of Reduced Graphene Oxide Supported Polyaniline-Metal Oxide Nanocomposites for Supercapacitor Applications Authors: Parrey, Khursheed Ahmad; Ayranci, Rukiye; Choi, Hyosung; Ak, Metin Abstract: Hybrid nanocomposites that integrate conducting polymers, metal oxides, and carbon frameworks offer a promising strategy for high-performance supercapacitor electrodes. In this work, reduced graphene oxide–supported polyaniline/metal oxide (ZnO, Fe2O3, and ZnFe2O4) nanocomposites were prepared and systematically investigated. The surface morphology, chemical composition, and structural and optical properties of the synthesized composites were systematically investigated using FE-SEM/EDX, AFM, UV–vis spectroscopy, and FTIR spectroscopy. Electrochemical performance was evaluated by cyclic voltammetry and electrochemical impedance spectroscopy, revealing typical pseudocapacitive behavior arising from synergistic faradaic contributions of PANI and metal oxides. Among the electrodes studied, rGO-supported PANI/ZnFe2O4 composite exhibited the best performance, delivering a competitive gravimetric specific capacitance of 294.13 F g−1, an energy density of 163.5 Wh kg−1, and a power density of 3658.5 W kg−1, along with a capacitance retention of about 81% after 2000 cycles at a scan rate of 50 mV/s. The superior performance is attributed to the combined effects of improved conductivity from rGO, enhanced redox activity from the bimetal oxide, and reduced charge-transfer resistance, as confirmed by impedance analysis. These results demonstrate the combined interaction among rGO, PANI, and metal oxide nanoparticles, highlighting rGO-supported PANI/metal oxide composites as a highly promising platform for the development of high-performance supercapacitor electrodes.

2026-08-01T00:00:00Z