Metrics
896 Downloads

DATADOI on multidistsiplinaarne avatud repositoorium teadusandmete jagamiseks ja avaldamiseks, mis põhineb avatud lähtekoodiga Dataverse tarkvaral.

Andmed tuleks talletada selle asutuse kollektsiooni, millega vähemalt üks kaasautoritest on seotud. DATADOI sisaldab praegu institutsionaalseid kollektsioone Tartu Ülikoolile, Tallinna Ülikoolile, Estonian Business Schoolile ja Eesti Teadusagentuurile.

Kui sobivat kollektsiooni veel ei ole, võtke ühendust DATADOI meeskonnaga aadressil datadoi@datadoi.ee.


DATADOI is a multidisciplinary open repository for sharing and publishing research data, based on the open-source Dataverse software.

Data should be deposited in the institutional collection assigned to the institution with which at least one of the contributors is affiliated. DATADOI currently includes institutional collections for the University of Tartu, Tallinn University, Estonian Business School, and the Estonian Research Council.

If a suitable collection does not yet exist, please contact the DATADOI team at datadoi@datadoi.ee.

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

751 to 760 of 3,476 Results
ZIP Archive - 1.0 GB - MD5: 7aa7e5b30cb367884c06234ba988d6f3
Pre ja posttest salvestused enne ja pärast hääldustreeningut
HTML - 10.1 KB - MD5: 1d30e678c5267a9adb15f8110c241929
2026. aasta migratsiooni käigus varasemast DataDOI süsteemist üle kantud kasutusstatistika kajastab tegevust eelmises DSpace-põhises süsteemis ega näita Dataverse’i uusi kasutusandmeid. Usage statistics carried over from the previous DataDOI system as part of the 2026 migration reflect activity in the former DSpace-based system and do not represent...
Plain Text - 1014 B - MD5: 20a832f9cf440f122bb265fc334fc6d9
README
Jun 11, 2024 - Füüsika andmed
Baloglu, Ahmet Burak; Kodu, Margus; Kozlova, Jekaterina; Kahro, Tauno; Jaaniso, Raivo, 2024, "Graphene-mediated blister-based laser-induced forward transfer of thin and ultra-thin ZrO2", https://doi.org/10.23673/RE-468, DATADOI, V1
The dataset includes data from both the manuscript and the supplementary materials of the original paper, which shares the same title as this dataset. Blister-based laser-induced forward transfer (BB-LIFT) is a promising high precision and resolution printing technique for the fast, solvent- and mask-free transfer of functional layered materials on...
TIFF Image - 2.8 MB - MD5: 56ccb7a9fdbb1cba63977a9a88927dad
HR-SEM of a donor substrate coated with 30 nm ZrO2 - after the BB-LIFT - 1
TIFF Image - 2.8 MB - MD5: 7c10913c12e4eeab77bd9f0896804309
HR-SEM of a donor substrate coated with 30 nm ZrO2 - after the BB-LIFT - 2
TIFF Image - 2.8 MB - MD5: 2a8eb24eb1e24c862cc09d1a1c4cc933
HR-SEM of a donor substrate coated with 30 nm ZrO2 - after the BB-LIFT - 3
TIFF Image - 2.8 MB - MD5: b28c671a3ec07a20e3b88d0befc90653
HR-SEM of a donor substrate coated with 30 nm ZrO2 - after the BB-LIFT - only ZrO2 layer removed
TIFF Image - 2.8 MB - MD5: 5113d2ff8fb83fc43ef295a2871fab39
HR-SEM of a donor substrate coated with 30 nm ZrO2 - after the BB-LIFT - graphene layer removed
TIFF Image - 2.8 MB - MD5: 0283391accbc24cd6176cc7cafe884d4
HR-SEM of a donor substrate coated with 30 nm ZrO2 - after the BB-LIFT - 4
Add Data

Sign up or log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.