Hokkaido University · 에너지
이 교수의 연구실은 에너지 변환 및 저장 소재, 특히 태양광을 활용한 수소 생산과 리튬이온이온 배터리의 나노구조적 거동을 중심으로 연구를 진행하고 있습니다. 광촉매, 태양전지, 전기화학적 반응 메커니즘 등에서 나노구조 제어와 표면/계면 공학을 접목하여 고성능 소재를 설계합니다. 특히, 반도체-코캐탈리스트 계면의 상호작용, 리튬실리사이드의 조성 및 구조 변화, 광활성 물질의 구조-기능 관계 분석에 초점을 맞추고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
The structure and configuration of reaction centers, which dominantly govern the catalytic behaviors, often undergo dynamic transformations under reaction conditions, yet little is known about how to exploit these features to favor the catalytic functions. Here, we demonstrate a facile light activation strategy over a TiO<sub>2</sub>-supported Cu catalyst to regulate the dynamic restructuring of Cu active sites during low-temperature methanol steam reforming. Under illumination, the thermally de
Abstract An efficient water oxidation photocatalyst is imperative for the realization of artificial photosynthesis. Herein, a cooperative strategy is represented that enables 2D structure tailoring and lattice distortion engineering simultaneously over a BiVO 4 photocatalyst for efficient visible‐light‐driven oxygen evolution reaction (OER). Specifically, the lattice distortion engineering is achieved through the introduction of a sodium (Na + ) additive during the ion exchange process. Structur
Abstract Strong coupling between the Si photocathode and a low‐cost cocatalyst is of great significance for enhancing the photoelectrochemical hydrogen evolution. Here, a facile method is proposed to in situ assemble amorphous MoS x (a‐MoS x ) thin‐film onto a single crystal p‐Si through a self‐reduction mechanism to achieve strong coupling. In the process of self‐reduction, the (MoS 4 ) 2− anion is reduced to form a‐MoS x by the oxidation of H–Si to form SiO x , which is etched further to form
The sluggish transfer of electrons from a planar p-type Si (p-Si) semiconductor to a cocatalyst restricts the activity of photoelectrochemical (PEC) hydrogen evolution. To overcome such inefficiency, an elegant interphase of the semiconductor/cocatalyst is generally necessary. Hence, in this work, a NiS<sub>2</sub> /NiS heterojunction (NNH) is prepared in situ and applied to a planar p-Si substrate as a cocatalyst to achieve progressive electron transfer. The NNH/Si photocathode exhibits an onse
The composition of Li-Si alloys in a lithiated single crystal Si(111) was studied using windowless energy dispersive spectroscopy (EDS), scanning electron microscopy (SEM), and soft X-ray emission spectroscopy (SXES). The intensities of Li Kα and Si L2,3 were obtained after deconvolution of the windowless EDS spectra. The Li Kα, Si L2,3, and Si Kα intensity changes along a line scan revealed a clear layered structure with varied Li concentrations. The Li distribution in Li-Si alloys was obtained
As one of the major impurities in the organic electrolyte, HF can react with the alkali components in the solid electrolyte interphase (SEI), such as lithium alkoxide and lithium carbonate, to form more LiF-rich SEI. Here, the effects of HF on the lithiation behavior of the single crystal Si(111) anode were studied using scanning electron microscopy, soft X-ray emission spectroscopy, and windowless energy-dispersive X-ray spectroscopy. When the Li-Si alloy is formed in 1.0 M LiPF<sub>6</sub> in
Solar-driven photoelectrochemical (PEC) water splitting into hydrogen fuel is a promising avenue for renewable energy conversion to overcome energy crises and environmental concerns. Earth-abundant Si semiconductors with excellent light-harvesting capabilities are suitable photocathode candidates for the PEC hydrogen evolution reaction (HER), but suffer from intrinsic instability and sluggish kinetics. Extensive studies have demonstrated that surface/interface engineering can serve as an effecti
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Abstract. Wintertime low temperatures and snow cover usually diminish the friction coefficient of asphalt pavements, thereby elevating accident and congestion risks. Road surface temperature (RST) is an important parameter for maintaining traffic safety under extreme winter weather conditions, as it helps predict road icing events. Aiming to enhance the precision and robustness of RST prediction, this paper introduces a forecasting framework combining optimized Long Short-Term Memory (LSTM) arch