3,071 to 3,080 of 8,021 Results
Oct 12, 2023 - SG Academies South-East Asia Fellowship (SASEAF) Programme
Gagus, 2023, "Related data for: SG Academies South-East Asia Fellowship (SASEAF) Programme", https://doi.org/10.21979/N9/CVT2WB, DR-NTU (Data), V1
Data for Singapore academies south-east Asia fellowship programme |
ZIP Archive - 258.4 MB -
MD5: b49f62106046b1ffde21dcc85c02d202
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Oct 11, 2023 - ACS Applied Energy Materials
Ahmed, Mahmoud; Nguyen, Thi Hiep; Zhang, Mengyuan; Halevi, Oded; Abdi, Fatwa F.; Magdassi, Shlomo; Wong, Lydia Helena, 2023, "Replication Data for: Enhancing Photoelectrochemical Performance of the Printed Nanoporous FeVO4 Photoanode by Dual-Layer CoOx–CoPi Catalysts", https://doi.org/10.21979/N9/AJJSHR, DR-NTU (Data), V1
Raw data for the article titled "Enhancing Photoelectrochemical Performance of the Printed Nanoporous FeVO4 Photoanode by Dual-Layer CoOx–CoPi Catalysts" |
application/vnd.ms-powerpoint.presentation.macroEnabled.12 - 3.5 MB -
MD5: 842b8f6442437e96670788fdee894871
Raw data for article titled: Photoelectrochemical Performance of the Printed Nanoporous FeVO4 Photoanode by Dual-Layer CoOx−CoPi Catalysts.pptm |
Oct 11, 2023Mahmoud Ahmed
The dataset contains the raw data for the paper published in ACS Applied Energy Materials titled as: Enhancing Photoelectrochemical Performance of the Printed Nanoporous FeVO4 Photoanode by Dual-Layer CoOx–CoPi Catalysts (21 Jul 2023) |
Oct 10, 2023 - Project: Catalyst design principle in low temperature methane activation and conversion through machine learning
Liu, Jiyuan, 2023, "Related Data for: Catalyst design principle in low temperature methane activation and conversion through machine learning", https://doi.org/10.21979/N9/2MGYW2, DR-NTU (Data), V1
data for Catalyst design principle in low temperature methane activation and conversion through machine learning |
Oct 10, 2023 -
Related Data for: Catalyst design principle in low temperature methane activation and conversion through machine learning
Compressed Archive - 2.8 GB -
MD5: aafb7389af46f8134a5f12ed37174348
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Oct 10, 2023 -
Related Data for: Catalyst design principle in low temperature methane activation and conversion through machine learning
Compressed Archive - 373.2 MB -
MD5: ce4d1cd8049296c23c32693dc4266f19
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Oct 10, 2023LI Shuzhou
data for project "Catalyst design principle in low temperature methane activation and conversion through machine learning" |
