Predicting the dissolution kinetics of silicate glasses by topology-informed machine learning

Han Liu, Tony Zhang, N. M. Anoop Krishnan, Morten Mattrup Smedskjær, Joseph V. Ryan, Stephane Gin, Mathieu Bauchy

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OriginalsprogEngelsk
Artikelnummer32
Tidsskriftnpj Materials Degradation
Vol/bind3
Antal sider12
ISSN2397-2106
DOI
StatusUdgivet - 29 aug. 2019

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Liu, Han ; Zhang, Tony ; Krishnan, N. M. Anoop ; Smedskjær, Morten Mattrup ; Ryan, Joseph V. ; Gin, Stephane ; Bauchy, Mathieu. / Predicting the dissolution kinetics of silicate glasses by topology-informed machine learning. I: npj Materials Degradation. 2019 ; Bind 3.
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title = "Predicting the dissolution kinetics of silicate glasses by topology-informed machine learning",
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year = "2019",
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Predicting the dissolution kinetics of silicate glasses by topology-informed machine learning. / Liu, Han; Zhang, Tony; Krishnan, N. M. Anoop; Smedskjær, Morten Mattrup; Ryan, Joseph V.; Gin, Stephane; Bauchy, Mathieu.

I: npj Materials Degradation, Bind 3, 32, 29.08.2019.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Predicting the dissolution kinetics of silicate glasses by topology-informed machine learning

AU - Liu, Han

AU - Zhang, Tony

AU - Krishnan, N. M. Anoop

AU - Smedskjær, Morten Mattrup

AU - Ryan, Joseph V.

AU - Gin, Stephane

AU - Bauchy, Mathieu

PY - 2019/8/29

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DO - 10.1038/s41529-019-0094-1

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VL - 3

JO - npj Materials Degradation

JF - npj Materials Degradation

SN - 2397-2106

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ER -