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「科研費ウェブサイトコレクション」を更新しました。
今月の特集「New Archived Websites」を掲載(2023年8月1日)
from 国立国会図書館インターネット資料収集保存事業(WARP)-新着情報 (2023/8/1 0:00:00)
from 国立国会図書館インターネット資料収集保存事業(WARP)-新着情報 (2023/8/1 0:00:00)
2023年8月の特集「New Archived Websites」を掲載しました。
【電話番号】0242-55-1122(代表)
Magnetic bubble crystal in tetragonal magnets
from Hokkaido University Collection of Scholarly and Academic Papers (2023/7/26 0:00:00)
from Hokkaido University Collection of Scholarly and Academic Papers (2023/7/26 0:00:00)
Title: Magnetic bubble crystal in tetragonal magnetsAuthors: Hayami, Satoru; Kato, YasuyukiAbstract: A magnetic bubble crystal is a two-dimensional soliton lattice consisting of multiple spin-density waves similar to a magnetic skyrmion crystal. Nevertheless, the emergence of the bubble crystal with a collinear spin texture is rare compared to that of the skyrmion crystal with a noncoplanar spin texture. Here, we theoretically report the stabilization mechanisms of the bubble crystal in tetragonal magnets. By performing numerical calculations based on an efficient steepest descent method for an effective spin model with magnetic anisotropy and multiple spin interactions in momentum space on a two-dimensional square lattice, we construct magnetic-field-temperature phase diagrams for various sets of model parameters. We find that the bubble crystal is stabilized at finite temperatures near the skyrmion crystal by an easy-axis anisotropic two-spin interaction. Through a detailed analysis, ...
Forecasting coal power plant retirement ages and lock-in with random forest regression
from Kyoto University Research Information Repository (2023/7/14 9:00:00)
from Kyoto University Research Information Repository (2023/7/14 9:00:00)
タイトル: Forecasting coal power plant retirement ages and lock-in with random forest regression著者: Edianto, Achmed; Trencher, Gregory; Manych, Niccolò; Matsubae, Kazuyo抄録: Averting dangerous climate change requires expediting the retirement of coal-fired power plants (CFPPs). Given multiple barriers hampering this, here we forecast the future retirement ages of the world’s CFPPs. We use supervised machine learning to first learn from the past, determining the factors that influenced historical retirements. We then apply our model to a dataset of 6, 541 operating or under-construction units in 66 countries. Based on results, we also forecast associated carbon emissions and the degree to which countries are locked in to coal power. Contrasting with the historical average of roughly 40 years over 2010–2021, our model forecasts earlier retirement for 63% of current CFPP units. This results in 38% less emissions than if assuming historical retirement trends. However, the l ...
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Title: 規約
Title: もくじ
Title: 表紙・裏表紙
2023年6月の月間アクセスランキングを掲載しました。
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