https://scholar.dgist.ac.kr/handle/20.500.11750/27 2026-10-10T16:47:54Z https://scholar.dgist.ac.kr/handle/20.500.11750/60904 Title: Equilibrium-driven decarbonylative multi-deuteration enables access to highly deuterated carbon frameworks Author(s): Lee, Jiin; Park, Taejun; Park, Jeong Eun; Moon, Hye Won; Lee, Sunggi Abstract: Deuterium incorporation is a powerful strategy for modulating metabolic stability and probing reaction mechanisms. However, existing approaches based on defunctionalization or hydrogen-deuterium exchange are typically limited to mono-deuteration or suffer from poor site selectivity, restricting access to multi-deuterated carbon centers. Herein, we report a cost-effective strategy for decarbonylative multi-deuteration of aldehydes by integrating polar alpha-deuteration, thiyl radical-mediated hydrogen atom transfer (HAT), and decarbonylative deuteration. A key feature of this approach is an equilibrium-controlled radical-polar process, in which multiple reversible steps are directed toward productive pathways through irreversible trapping of alkyl radicals. The method employs inexpensive, commercially available reagents and exhibits a broad substrate scope encompassing primary, secondary, and tertiary aldehydes, including structurally complex substrates. This strategy provides a practical platform for the synthesis of highly deuterated carbon frameworks, offering new opportunities for isotopic labeling and medicinal chemistry. 2026-08-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60891 Title: Lessons from α-RuCl3 for pursuing quantum spin liquid physics in atomically thin materials Author(s): Ojeda-Aristizabal Claudia; Zheng Xiaohu; Xu Changsong; Nussinov Zohar; Motome Yukitoshi; Banerjee Arnab; Tsen Adam W.; Knap Michael; Du Rui-Rui; Joshi Gajadhar; Mounce Andy; Kim Youngwook; Hunt Benjamin M.; Shcherbakov Dmitry; Zhou Boyi; Jing Ran; Liu Mengkun; Zhao Hui; Claassen Martin; Erten Onur; Chen Yong P.; Henriksen Erik A. Abstract: Quantum spin liquids can arise from Kitaev magnetic interactions, and exhibit fractionalized excitations with the potential for a topological form of quantum computation. This review surveys recent experimental and theoretical progress on the pursuit of phenomena related to Kitaev magnetism in layered and exfoliatable materials, which offer numerous opportunities to apply powerful techniques from the field of atomically thin materials. We primarily focus on the antiferromagnetic Mott insulator alpha-RuCl3, which exhibits Kitaev couplings and is readily exfoliated to single- or few-layer sheets, and thus serves as a test bed for developing probes of Kitaev phenomena in atomically thin materials and devices. We introduce the Kitaev model and how it is realized in alpha-RuCl3 and other material candidates; and cover alpha-RuCl3 synthesis and fabrication into van der Waals heterostructure devices. A key discovery is a work-function-mediated charge transfer that heavily dopes both the alpha-RuCl3 and proximate materials, and can enhance Kitaev interactions by up to 50%. We further discuss a wide range of recent results in electronic transport and optical and tunneling spectroscopies of alpha-RuCl3 devices. The experimental techniques and theoretical insights developed for alpha-RuCl3 establish a framework for discovering and engineering superior two-dimensional Kitaev materials that may ultimately realize elusive quantum spin liquid phases. 2026-06-30T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60887 Title: Optimization of MuMax3 by Using Claude Code: A CUDA-Graph-Based Case Study in AI-Assisted Performance Engineering Author(s): You, Chun-Yeol Abstract: MuMax3 is a widely used open-source GPU-accelerated micromagnetic simulator whose computational core - CUDA kernels and cuFFT-based demagnetization convolutions - has changed little since its original release. We report a case study in which an agentic large-language-model coding assistant (Claude Code, Anthropic) was used, under continuous human supervision, to profile and optimize this mature CUDA/Go codebase. Profiling with NVIDIA Nsight Systems revealed that for small and medium grids (64 & times;64 & times;1 to 256 & times;256 & times;1 cells), 75-79 % of step time is spent in CPU-side cuLaunchKernel driver calls rather than in GPU computation, because every solver step launches roughly 27 kernels sequentially on a single CUDA stream. Building on this finding, we implemented a "split-graph" execution strategy: the time-step-independent torque-evaluation kernel sequences of each solver stage are captured once as CUDA Graphs and replayed via cudaGraphLaunch, while the time-step-dependent update, error estimate, and adaptive-step-size logic remain ordinary stream-ordered calls. The optimization is exposed transparently through Run()/Steps(), guarded by a compatibility check (constant excitation, zero thermal field, no custom field terms, time-independent material parameters, mesh size below a tunable threshold) that falls back silently to the original code path when violated. Across five solvers (Heun, RK23, RK45DP, RK56, Backward Euler), the optimization yields up to 5.4 & times; throughput for a 64 & times;64 & times;1 grid with a fixed time step, 2.4-3.6 & times; for adaptive time-stepping, decreasing smoothly to approximate to 1.0 & times; near 10(6) cells, essentially independent of which physical field terms (exchange, anisotropy, DMI) are active. All results were verified bit-for-bit identical (ndiff=0) against the unmodified code, and the full 176-script mumax3 regression suite passes with zero failures. We discuss the workflow itself - including three episodes in which the assistant autonomously diagnosed and corrected its own defects - as a template for AI-assisted optimization of legacy scientific HPC codes. 2026-05-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60884 Title: Development of a Three-Axis Planar Hall Magnetoresistance Sensor Using a Superparamagnetic Nanoparticle-Based Flux Guide Author(s): Jeon, Changyeop; Kim, Mijin; Kim, Keonmok; Lim, Byeonghwa; Nayak, Bibhutibhusan; Jung, Youngdo; Lee, Bo- Yeon; Jeon, Taehyeong; Kim, Jinwoo; Oh, Sunjong; Kim, CheolGi Abstract: Accurate perception of 3D magnetic fields is essential for advanced spatial awareness in motion tracking and robotics. However, conventional magnetoresistance sensors typically lack out-of-plane sensitivity. Magnetic flux guides have been employed to redirect out-of-plane fields into the sensor plane, yet ferromagnetic flux guides introduce unwanted hysteresis, necessitating complex reset mechanisms that hinder miniaturization. Here, we present a highly sensitive 3D planar Hall magnetoresistance (PHMR) sensor integrated with a superparamagnetic nanoparticle-based flux guide (SPMFG). Crucially, microstructural tunability via field-assisted curing allows for application-specific optimization between precision and sensitivity. Randomly dispersed configurations provide strictly hysteresis-free operation (similar to 0 mT), whereas vertically aligned nanoparticle chains (Chain MFG) significantly amplify flux redirection efficiency. Although chain alignment introduces a small but finite residual hysteresis (0.3 mT), it achieves a 40% magnetic field conversion ratio and a threefold enhancement in z-axis sensitivity. This architectural flexibility bypasses the need for auxiliary coils, enabling a compact, power-efficient system realized through scalable inkjet printing. The platform's versatility is further demonstrated by a multi-axis force-sensing module capable of independently resolving normal and shear forces. This work establishes a practical platform bridging vector magnetometry and tactile sensing for next-generation wearable and human-machine interface applications. 2026-08-31T15:00:00Z