Automated Author ProfileCoccia, Giulio
Institute for Photonics and Nanotechnologies (IFN) CNR, 20133 Milano, Italy
Coccia, Giulio
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Data repository for: Determining Strain Components in a Diamond Waveguide from Zero-Field ODMR Spectra of NV- Center Ensembles ‘Raw_data.txt' contains the data as collected from ODMR experiments. The first column represents the microwave frequency, while the subsequent columns contain counts for positions 1 to 47, as detailed in the Supplementary Material (Sec II).'Preprocessed_data.txt' includes the preprocessed data, as described in both the main text (Sec II.B) and the Supplementary Material (Sec II). The format of this data is consistent with that described above.Acknowledgements:This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ITN project LasIonDef (GA no. 956387). MG acknowledges support from the National Science Centre (Poland) under Grant No. 2015/18/E/ST3/00583. DW acknowledges financial support by the Science Foundation Ireland (SFI) under grants nos. 18/RP/16190 and 22/PATH-S/10656. AJB and JPH acknowledge the financial support provided by EPSRC via Grant No. EP/T017813/1 and EP/03982X/1. VB acknowledges the support of the Alexander von Humboldt Foundation. AB gratefully acknowledges financial contribution from MAECI, "Italy-Israel joint programme - 2023 scientific track" within the project PRECIOUSMRI. SME is thankful for the support from the projects QuantDia (FISR2019-05178) and PNRR PE0000023 NQSTI funded by MUR (Ministero dell'Università e della Ricerca). MG, DW, and PM acknowledge support from the Alexander von Humboldt Foundation in the framework of the Research Group Linkage Programme funded by the German Federal Ministry of Education and Research.
Authors
- Alam, M. Sahnawaz ;
- Gorrini, Federico ;
- Gawełczyk, Michał ;
- Wigger, Daniel ;
- Coccia, Giulio ;
- Guo, Yanzhao ;
- Shahbazi, Sajedeh ;
- Bharadwaj, Vibhav ;
- Kubanek, Alexander ;
- Ramponi, Roberta ;
- Barclay, Paul E ;
- Bennett, Anthony J. ;
- Hadden, John P. ;
- Bifone, Angelo ;
- Eaton, Shane M. ;
- Machnikowski, Paweł
Data repository for: Determining Strain Components in a Diamond Waveguide from Zero-Field ODMR Spectra of NV- Center Ensembles ‘Raw_data.txt' contains the data as collected from ODMR experiments. The first column represents the microwave frequency, while the subsequent columns contain counts for positions 1 to 47, as detailed in the Supplementary Material (Sec II).'Preprocessed_data.txt' includes the preprocessed data, as described in both the main text (Sec II.B) and the Supplementary Material (Sec II). The format of this data is consistent with that described above.Acknowledgements:This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ITN project LasIonDef (GA no. 956387). MG acknowledges support from the National Science Centre (Poland) under Grant No. 2015/18/E/ST3/00583. DW acknowledges financial support by the Science Foundation Ireland (SFI) under grants nos. 18/RP/16190 and 22/PATH-S/10656. AJB and JPH acknowledge the financial support provided by EPSRC via Grant No. EP/T017813/1 and EP/03982X/1. VB acknowledges the support of the Alexander von Humboldt Foundation. AB gratefully acknowledges financial contribution from MAECI, "Italy-Israel joint programme - 2023 scientific track" within the project PRECIOUSMRI. SME is thankful for the support from the projects QuantDia (FISR2019-05178) and PNRR PE0000023 NQSTI funded by MUR (Ministero dell'Università e della Ricerca). MG, DW, and PM acknowledge support from the Alexander von Humboldt Foundation in the framework of the Research Group Linkage Programme funded by the German Federal Ministry of Education and Research.
Authors
- Alam, M. Sahnawaz ;
- Gorrini, Federico ;
- Gawełczyk, Michał ;
- Wigger, Daniel ;
- Coccia, Giulio ;
- Guo, Yanzhao ;
- Shahbazi, Sajedeh ;
- Bharadwaj, Vibhav ;
- Kubanek, Alexander ;
- Ramponi, Roberta ;
- Barclay, Paul E ;
- Bennett, Anthony J. ;
- Hadden, John P. ;
- Bifone, Angelo ;
- Eaton, Shane M. ;
- Machnikowski, Paweł