https://scholar.dgist.ac.kr/handle/20.500.11750/79 2026-04-24T20:36:47Z https://scholar.dgist.ac.kr/handle/20.500.11750/60197 Title: Surface-Interaction-Driven Polarity Switching in II-V Cd3P2 Colloidal Quantum Dots for Infrared Photodiodes Author(s): Tran, Ha-Chi V.; Shim, Doeun; Park, Youngsang; Choi, Mahnmin; Jeong, Hyeonjun; Bonifas, Guillaume; Ouyang, Liyan; Nayral, Celine; Delpech, Fabien; Kang, Joongoo; Jeong, Sohee Abstract: Colloidal quantum dots (CQDs) based on II-V semiconductors offer attractive optical absorption and carrier transport properties for infrared optoelectronics, yet their device-relevant electronic behavior remains poorly understood. In particular, Cd3P2 CQDs have been constrained by limited control over nanocrystal growth and carrier polarity. Here, a materials-to-device study establishes polarity control in Cd3P2 CQD solids for infrared photodiodes. Precise regulation of oleic acid (OA) concentration during synthesis yields monodisperse Cd3P2 CQDs with suppressed nanocrystal fusion and photoluminescence quantum yields up to 62 %. Electrical measurements reveal an oxygen-induced transition from n-type to p-type transport in Cd3P2 CQD films. Spectroscopic analysis and first-principles calculations indicate that adsorbed oxygen generates surface acceptor states that drive Fermi-level realignment. Building on these functional Cd3P2 CQD solids, a Cd3P2-based homojunction CQD photodiode is demonstrated, in which Cd3P2 functions as both the infrared absorber and a charge-selective layer. The resulting devices exhibit stable ambient operation, achieving a short-circuit current density of 18 mA cm(-2), an external quantum efficiency (EQE) of 24 %, and a fast temporal response of 23 ns under zero bias. These results identify surface-driven polarity control as a viable design strategy for II-V CQD optoelectronics and position Cd3P2 CQDs as a promising platform for low-power infrared conversion technologies. 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