https://scholar.dgist.ac.kr/handle/20.500.11750/249 2026-08-23T22:35:46Z 2026-08-23T22:35:46Z Ali, Shahzad Kim, Dongyun Khalid, Muhammad Zeeshan Gong, Eunhee Lee, Junho Slabon, Adam Yuan, Jiayin Huttula, Marko In, Su-Il https://scholar.dgist.ac.kr/handle/20.500.11750/60619 2026-08-19T02:40:12Z 2026-06-30T15:00:00Z

Title: Activation to Deactivation Dynamics of Cu-Embedded TiO2 for Solar CH4 Generation Author(s): Ali, Shahzad; Kim, Dongyun; Khalid, Muhammad Zeeshan; Gong, Eunhee; Lee, Junho; Slabon, Adam; Yuan, Jiayin; Huttula, Marko; In, Su-Il Abstract: Photocatalytic CO2 reduction is known to accelerate on surfaces with defects such as oxygen vacancies (Vo), undercoordinatedmetal atoms, and hydroxyl groups (OH − ). This is further boosted while these defects, Vo-coupled undercoordinated metal atoms,and proximal OH − , act synergistically. However, it is challenging to make atomic-level patterns of such structural arrangementsand monitor their activation anddeactivation pathways. Herein, we report single-atom hydroxylated-Cu in the vicinity of Ti atomthat triggers Vo generation owing to specific structural arrangements. It finally activates CO 2 by coordinative activation andeventually transforms CO2 to CH 4 through Cu–*CHO intermediate. Alongside the activation, deactivation of photocatalyst alsoproceeds, accompanied by the change in the binding environment of the Cu, generation of the oxidizing hydroxyl radicals, andphotocatalytically inactive carbonaceous species. This work outlines the efficacious role of Cu in CO2 reduction to CH 4 andprovides valuable insights into the activation and deactivation mechanisms.

2026-06-30T15:00:00Z Gong, Eunhee Kim, Hwapyong Hiragond, Chaitanya B. Lee, Jeonghyeon Goddard III, William A. In, Su-Il https://scholar.dgist.ac.kr/handle/20.500.11750/60613 2026-08-14T07:10:12Z 2026-08-31T15:00:00Z

Title: Experimental and Machine Learning-Assisted Discovery of 2D Materials for Hydrogen Evolution: From Fundamentals to Industrial Applications Author(s): Gong, Eunhee; Kim, Hwapyong; Hiragond, Chaitanya B.; Lee, Jeonghyeon; Goddard III, William A.; In, Su-Il Abstract: Water splitting to produce hydrogen is recognized as a green technology with significant potential to replace traditional non-renewable energy sources. Substantial progress has been made in the hydrogen evolution reaction (HER), with two-dimensional (2D) materials for both photocatalytic and electrocatalytic HER due to their unique structural features and favourable properties. Along with experimental materials design, the properties of the 2D materials have been complemented by computational methods such as density functional theory (DFT) over the past decade. However, these computational approaches face limitations in terms of time and cost efficiency. Consequently, data-driven approaches, particularly machine learning (ML), are emerging as powerful tools in materials science for identifying structure-activity relationships by learning from existing experimental and DFT calculation data. This review discusses the progress of 2D materials for hydrogen evolution, encompassing experimental advances, theoretical insights, and ML-assisted discovery. First, the fundamental principles of HER are examined, combining insights from photocatalysis and electrocatalysis. Next, an overview of 2D materials for HER is presented, including key challenges related to kinetics, stability, and scalability. Subsequently, ML strategies for 2D material discovery and screening are explored. Case studies on ML applications for various 2D photocatalysts and electrocatalysts, including graphene, g-C3N4, transition metal chalcogenides, MXenes, etc., are discussed. Finally, factors influencing large-scale applications and challenges associated with integrating materials science and ML approaches for HER are addressed.

2026-08-31T15:00:00Z Lee, Hyo Cheol In, Su-Il https://scholar.dgist.ac.kr/handle/20.500.11750/60230 2026-04-15T08:11:02Z 2025-12-31T15:00:00Z

Title: Next-Generation Quantum Dot Engineering for Photoelectrochemical Hydrogen Production: Insights From Artificial Intelligence-Assisted Approaches Author(s): Lee, Hyo Cheol; In, Su-Il Abstract: The transition to sustainable energy requires efficient technologies for solar-driven hydrogen production. Quantum dots (QDs), with size-tunable bandgaps and favorable interfacial properties, significantly enhance photoelectrochemical (PEC) water splitting by enabling broad-spectrum light harvesting, optimized band alignment, and improved charge separation. However, QD design strategies for PEC systems remain less developed compared to those for light-emitting diodes and solar cells, constrained by incomplete understanding of interfacial photophysics, limited exploration of low-dimensional nanocrystals (1D/2D), and the absence of AI-assisted optimization. This review provides a comprehensive overview of material design strategies for QDs in PEC hydrogen production, encompassing fundamental principles, established approaches, and recent advances in both heavy-metal-based and nontoxic systems. Particular attention is given to emerging paradigms such as dimensional control and AI-driven optimization, which enable predictive modeling, accelerated synthesis, and performance tuning beyond conventional trial-and-error methods. Finally, we address critical challenges—including stability, toxicity, and scalability—and outline future directions for achieving efficient, sustainable QD-based PEC systems suitable for practical and economically viable commercialization.

2025-12-31T15:00:00Z Kim, Hwapyong Kim, Ki Nam Lee, Sang-Hyeon Nam, Chang-Hoon Lee, Young-Sam In, Su-Il https://scholar.dgist.ac.kr/handle/20.500.11750/59989 2026-02-09T18:01:18Z 2025-12-31T15:00:00Z

Title: Hydrogen Evolution via Oxygen Tolerant [NiFe]-Hydrogenase Immobilized on TiO2 Nanotubes Author(s): Kim, Hwapyong; Kim, Ki Nam; Lee, Sang-Hyeon; Nam, Chang-Hoon; Lee, Young-Sam; In, Su-Il Abstract: [FeFe]-hydrogenase has been of great interest due to its high enzymatic activity for hydrogen evolution reactions (HERs). However, the big challenge of [FeFe]-hydrogenase is a significant performance degradation in aerobic conditions. On the other hand, [NiFe]-hydrogenase of E. coli has an oxygen tolerant property. Therefore, using [NiFe]-hydrogenase is an effective solution to avoid performance degradation in aerobic conditions. Herein, we extracted [NiFe]-hydrogenases from E. coli and immobilized them on the TiO2 nanotube (TNT) electrode prepared by pyrrole-based electropolymerization for application in aerobic conditions. As a result, we can confirm that [NiFe]-hydrogenases coated TNT electrode demonstrates the increased HER activity underaerobic condition than control samples in in-vitro activity test using methylene viologen and linear sweep voltammetry.

2025-12-31T15:00:00Z