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DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

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4,961 to 4,970 of 92,174 Results
Ti_12_S1.tab
Aug 25, 2026 - Replication Data for: Fluorine incorporation in nominally anhydrous minerals: insights from density functional theory and high-pressure experiments
Tabular Data - 4.4 KB - 2 Variables, 173 Observations - UNF:6:qlZL98ywL3qHpWx4+/qi6g==
Ti_12_S2_kk.tab
Aug 25, 2026 - Replication Data for: Fluorine incorporation in nominally anhydrous minerals: insights from density functional theory and high-pressure experiments
Tabular Data - 47.4 KB - 2 Variables, 1868 Observations - UNF:6:nXl2Fr1+5LBBS6qq0IAcKQ==
Ti_12_S2.tab
Aug 25, 2026 - Replication Data for: Fluorine incorporation in nominally anhydrous minerals: insights from density functional theory and high-pressure experiments
Tabular Data - 4.4 KB - 2 Variables, 173 Observations - UNF:6:lfto8A6gXPYg4Xer7yMFnA==
Ti8.csv
Aug 25, 2026 - Replication Data for: Fluorine incorporation in nominally anhydrous minerals: insights from density functional theory and high-pressure experiments
Comma Separated Values - 64.2 KB - MD5: d104b9f0e85eec137e44e390996408c6
TS16_spectrum3.csv
Aug 25, 2026 - Replication Data for: Fluorine incorporation in nominally anhydrous minerals: insights from density functional theory and high-pressure experiments
Comma Separated Values - 80.7 KB - MD5: 63a78989104e6a55a256be36d0bf683d
TS16_spectrum4.csv
Aug 25, 2026 - Replication Data for: Fluorine incorporation in nominally anhydrous minerals: insights from density functional theory and high-pressure experiments
Comma Separated Values - 80.5 KB - MD5: 6af5abd119cdf9997db889ffaec742d6
TEO Jun Hao Brendan(Nanyang Technological University)
Aug 25, 2026Asian School of the Environment (ASE)
approximate_cons_models_100_3.dat
Aug 20, 2026 - Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Fixed Field Text Data - 123.9 MB - MD5: 7cd2b57371973cec17482efe4baa38af
Approximate consumer models using simulation data
readme.md
Aug 20, 2026 - Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Markdown Text - 738 B - MD5: 99dac3f6c8b4464ca698e66431bfa302
Documentation
Readme
real_consumer_models_100.dat
Aug 20, 2026 - Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Fixed Field Text Data - 310.9 MB - MD5: 82fd6c3d135cd8fc988d120f3d9dfa80
Actual models used for evaluation
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