文献
J-GLOBAL ID:201802264070931579
整理番号:18A0575537
機械学習を用いたけい酸塩ガラスの溶解速度の予測【Powered by NICT】
Predicting the dissolution kinetics of silicate glasses using machine learning
著者 (6件):
Anoop Krishnan N.M.
(Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India)
,
Mangalathu Sujith
(Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA)
,
Smedskjaer Morten M.
(Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark)
,
Tandia Adama
(Science and Technology Division, Corning Incorporated, Corning, New York 14831, USA)
,
Burton Henry
(Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA)
,
Bauchy Mathieu
(Physics of AmoRphous and Inorganic Solids Laboratory (PARISlab), Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA)
資料名:
Journal of Non-Crystalline Solids
(Journal of Non-Crystalline Solids)
巻:
487
ページ:
37-45
発行年:
2018年
JST資料番号:
D0642A
ISSN:
0022-3093
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)