https://scholar.dgist.ac.kr/handle/20.500.11750/79 2026-04-04T18:06:20Z https://scholar.dgist.ac.kr/handle/20.500.11750/60021 Title: Theory of slidetronics in ferroelectric van der Waals layers Author(s): Lee, Byeoksong; Lee, Minki; Kang, Joongoo Abstract: Ferroelectricity can emerge in vertically stacked two-dimensional materials even when their constituent monolayers are nonferroelectric. In these sliding ferroelectrics, polarization switching is driven by small lateral displacements between layers. Here, we develop a comprehensive materials design framework for slidetronics founded on a symmetry principle: any sliding-induced polarization change from a state P to P' can be equivalently described by applying an appropriate point-group operator, or "generator" G, to the entire system, such that P' = GP. This generator-based framework classifies all possible sliding-induced transformations, establishes the necessary symmetry conditions for switchable polarization components, and provides design strategies for realizing targeted switching behaviors. A central result is that complete polarization inversion is symmetry forbidden in bilayers but becomes possible in multilayers. First-principles calculations confirm these predictions, revealing novel phenomena including dipole-locked ferroelectricity in cellulose bilayers, in-plane switching in As2S3-based systems, and full polarization reversal in a PdSe2 trilayer. 2025-11-30T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/59855 Title: 포인트 클라우드 시스템 표현을 위한 디스크립터 생성 방법 및 그 장치 Author(s): 하현욱; 강준구 Abstract: 본 발명의 일실시예는 포인트 클라우드 시스템의 디스크립터를 생성하는 방법에 있어서, 상기 포인트 클라우드 시스템의 포인트들을 가우시안 분포로 변환하여 연속성을 보장하는 가우시안 스무딩 단계와, 상기 가우시안 스무딩 처리된 포인트 클라우드 데이터를 푸리어 변환하여 주파수 도메인에서의 특성 함수를 추출하는 단계와, 상기 푸리어 변환된 데이터를 기반으로 특성 함수 S(k)와 T(k)를 추출하는 단계와, 상기 추출된 특성 함수 S(k)와 T(k)를 기저함수 세트에 투영하여 벡터로 변환하는 단계와, 상기 변환된 벡터에 대해 회전 정규화를 수행하여 회전에 불변하는 특성을 부여하는 단계를 포함하며, 상기 특성 함수 S(k)는 주파수 공간에서 포인트 클라우드의 분포 크기에 비례하는 양으로써 포인트 클라우드에 존재하는 모든 두 점의 조합(two-body)을 나타내며, 상기 특성 함수 T(k)는 주파수 공간에서의 고차 통계적 특성을 나타내는 양으로 포인트 클라우드에 존재하는 모든 세 점의 조합(three-body)으로부터 계산되는 함수이다. https://scholar.dgist.ac.kr/handle/20.500.11750/59351 Title: Topological Machine Learning Unveils Hidden Reaction Pathways in Nanocrystal Synthesis Author(s): Lee, Byeoksong; Choi, Mahnmin; Shin, Jibin; Ha, Hyunwook; Shim, Doeun; Jeong, Sohee; Kang, Joongoo Abstract: Uncovering reaction pathways from analytical data such as UV-vis spectra remains a central challenge in nanocrystal synthesis, where transient and ill-defined intermediates complicate mechanistic analysis. Conventional approaches, reliant on manual spectral feature extraction and expert interpretation, are prone to bias and often overlook critical events. Here we present a machine learning framework that integrates transformer-based data augmentation with topological manifold learning to objectively elucidate reaction pathways directly from raw, high-dimensional spectroscopic data. The key insight is that the topology of the data manifold reflects the structure of the underlying reaction pathway. Applied to ex-situ UV-vis data sets of indium arsenide nanocrystal synthesis, this approach reconstructs the complete reaction landscape, identifying previously unreported metastable intermediates and revealing how chemical additives modulate intermediate formation to steer pathway selection. Broadly adaptable to diverse analytical data, this topological learning framework provides a generalizable strategy for mechanistic discovery and predictive control in complex chemical systems. 2025-11-30T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/58965 Title: Targeted Selenite Adsorption Using Defective Fe-BTC: Effective in Acidic and Alkaline Conditions Author(s): Byun, Asong; Lee, Byeoksong; Jeong, Yujin; Kang, Joongoo; Park, Jinkyu; Park, Jinhee Abstract: Amorphous Fe-BTC, characterized by entirely defective metal nodes, has been employed for the effective adsorption of toxic selenite anions from aqueous solutions. Remarkably, Fe-BTC maintains high adsorption efficiency across a broad pH range (2-12), achieving a maximum adsorption capacity of 491 mg g-1, ranking among the highest recorded for adsorbents, including MOFs. The adsorption process involves distinct chemical interactions depending on pH: weak and variable interactions under acidic conditions (pH 2) and strong, diverse coordination modes under alkaline conditions (pH 11). Notably, the strong coordination ability of selenite ensures high selectivity over selenate and competing anions such as Cl-, NO2-, NO3-, CO32-, SO42-, and PO43-. The abundance of metal defects endows Fe-BTC with superior adsorption capacity compared to crystalline Fe-MOF, MIL-100(Fe). This study provides a comparative analysis of selenite adsorption on Fe-BTC under acidic and alkaline conditions, emphasizing pH-dependent adsorption mechanisms and their implications for designing effective adsorbents for toxic species removal. 2025-08-31T15:00:00Z