Data Management Plan (DMP)

Plan Overview A Data Management Plan created using DMPonline Title: EcoRPCchem Creator:Elena Giglia Principal Investigator: Luca Quaglia Data Manager: Luca Quaglia Project Administrator: Luca Quaglia Affiliation: Other Funder: European Commission Template: Horizon Europe Template ORCID iD: 0000-0002-0793-8275 Project abstract: With the enforcement of EU regulations 2024/573, the production and usage of Tetrafluoroethane (R134a) has been strongly regulated. This gas is a key component in the gas mixture of Resistive Plate Chambers, a detector technology widely employed in highenergy physics. A potential, more environment-friendly, substitute for this gas is Tetrafluoropropene (HFO) and several promising HFO-based mixtures have been proposed. The long-term behavior (aging) of RPCs operated with these mixtures is typically studied by exposing several detectors flushed with an HFO-based gas mixture to a radioactive source and by studying the stability of the absorbed current and RPC performance over time. Experimental tests are crucial to spot and quantify aging effects, but can rarely provide an explanation for their origin. This requires a deeper understanding of the microscopical modifications of the materials induced by the HFO decomposition when exposed to irradiation. This project aims at breaking down the aging phenomena of several RPC components in their basic building blocks by comparing the chemical (EDX spectroscopy and SEM analyses) and electrical (resistivity) features of new and aged samples of RPC materials. The results of these analyses will be used to formulate a model to describe the observed effects and develop a simulation code, allowing for a systematic test of the aging properties of different HFO-based gas mixtures. I will carry out my research at the High Voltage Laboratory of the ETH Zurich University and at the Physics Department at the University of Torino, with the guidance of Prof. Christian Franck and Martino Gagliardi, leading experts on eco-friendly high-voltage gaseous insulation and RPC detectors respectively, while the chemical analyses will be performed at the CERN chemical laboratory. The data coming from these measurements will be saved and made publicly available in Zenodo, following the FAIR principles. The data analysis code will be developed using open source software and it will also be shared in a GitHub repository, to ensure analysis reproducibility and external verification of the results. Created using DMPonline. Last modified 16 December 2025 1 of 14 ID: 154277 Start date: 20-06-2025 End date: 19-06-2028 Last modified: 16-12-2025 Grant number / URL: 101199027 Created using DMPonline. Last modified 16 December 2025 2 of 14 EcoRPCchem Data Summary Will you re-use any existing data and what will you re-use it for? The project does not foresee the re-usage of existing data. It does, however, include the study of some samples obtained by a particle detector that has been exposed to some irradiation in the past few years (aged samples in the following). These materials have not been studied yet, so no data is available on them. Moreover, there are no third-party rights on these samples since I personally worked on them in the past and my current research group has accepted the proposal for these new studies. What types and formats of data will the project generate or re-use? MACRO TYPE TYPE FORMAT (ONGOING) FORMAT (PRESERVATION) EXPECTED SIZE SOFTWARE NEEDED? TEXTUAL Reports .doc .pdf <10 MB NO Raw spectra .txt /.dat .txt/dat <10 MB NO Current data .txt /.dat .txt/dat ~1 MB NO IMAGES SEM images .jpeg/.tif .jpeg/.tif ~1 GB NO LASER MICROSCOPE 2D surface profiles .vk4 .jpeg/.pdf ~10 GB YES CODE Data analysis codes .C/.cpp/.py .C/.cpp/.py < 500 kB NO Chemical analyses (performed by me at the ScopeM center at ETH) Two different chemical analyses will be performed: Energy Dispersive X-ray (EDS) to study the abundance of elements in a sample Scanning Electron Microscope (SEM) measurements to provide visual magnification of the samples The output data from the EDS will be a two column file where the first column represents the energy of the impinging particle while the second represents the intensity of the material response to the specific energy The second column will be plotted against the first, leading to the creation of several response spectra Each energy is related to a specific element and the intensity of the response is related to its concentration in the sample The SEM provides high-quality and high-magnification images of the tested samples for visual inspection studies A legend for the fields in the files and a README file will be provided for each dataset Electrical analyses (performed by me at the ETH High Voltage Laboratory) The output data from the electrical analyses is a value of circulating current as a function of time Two columns: current and time Created using DMPonline. Last modified 16 December 2025 3 of 14 Knowing the voltage applied by the instrument one can measure the resistivity and conductivity of the material under test Laser microscope These data refer to surface roughness measurements of the samples and they are saved in a proprietary format which can, nonetheless, be analyzed using the vk4-python-driver python library (developed by other users, hence not all the functionalities of the proprietary software are available) A pc with the license for the official program is available at ETH and it will be used to analyze the data Different sources of aging (performed by me at ETH) After characterizing the brand-new materials these will be aged in two different ways Material compatibility: the materials will be exposed to a given gas mixture and the simple chemical reactivity between gas and material will be studied Plasma-induced aging: the materials will be exposed to the same gas mixture and this time the gas will be ionized using a plasma source and the effect of bombardment with electrons and ions will be studies Methodology The analyses will be carried out on different slabs and on different samples (different spatial regions on each slab). The slabs numbered 1 to 6 are the "virgin" samples (1,2,3,4,5 all come from the same Bakelite sheet while 6 is from a different one) while slab 7 and 8 are the ones already coming from previous aging studies. More specifically: Slabs 1-2: "old" Bakelite no linseed oil (material compatibility and plasma-assisted aging) Slabs 3-4-5: "old" Bakelite with linseed oil (material compatibility and plasma-assisted aging) Slab 6: "new" Bakelite with linseed oil (comparison with the samples coming from "aged" detector) Slab 7: anode of aged RPC detector Slab 8: cathode of aged RPC detector Slab 9-10: "old" Bakelite, no linseed oil for reference measurements of PDC Different sample size is required for the chemical and electrical analyses. In general, more than one sample per slab can be obtained and more slabs will be subjected to the same aging in order to accumulate some statistics for the data analysis. Moreover, some samples from a slab are used as reference and other samples from the same slab are used for the exposure and the measurements after the aging. File naming scheme is as follows: ├── Slab_1 │ ├── S1_B0 (no aging) │ │ ├── laserMicroscope_xxx.vk4 │ │ ├── ... │ │ └── laserMicroscope_yyy.vk4 │ │ │ ├── S1_B1 (no aging) │ │ ├── SEM_image_1.tif │ │ ├── ... │ │ ├── SEM_image_x.tif │ │ ├── EDX_spectra_1.txt │ │ ├── ... │ │ └── EDX_spectra_n.txt │ │ │ ├── S1_B2 (after material compatibility studies) Created using DMPonline. Last modified 16 December 2025 4 of 14 │ │ ├── laserMicroscope_xxx.vk4 │ │ ├── ... │ │ └── laserMicroscope_yyy.vk4 │ │ │ ├── S1_B3 (after material compatibility studies) │ │ ├── SEM_image_1.tif │ │ ├── ... │ │ ├── SEM_image_x.tif │ │ ├── EDX_spectra_1.txt │ │ ├── ... │ │ └── EDX_spectra_n.txt │ │ │ ├── S1_B4 (after plasma-assisted aging) │ │ ├── laserMicroscope_xxx.vk4 │ │ ├── ... │ │ └── laserMicroscope_yyy.vk4 │ │ │ ├── S1_B5 (after plasma-assisted aging) │ │ ├── SEM_image_1.tif │ │ ├── ... │ │ ├── SEM_image_x.tif │ │ ├── EDX_spectra_1.txt │ │ ├── ... │ │ └── EDX_spectra_n.txt │ │ │ ├── Slab_2 │ ├── S2_B0 (before aging) │ │ ├── PDC_measurements_1.txt │ │ ├── PDC_measurements_2.txt │ │ ├── ... │ │ └── PDC_measurements_n.txt │ │ │ ├── Slab_4 │ ├── S3_B0 (after plasma-assisted aging) │ │ ├── PDC_measurements_1.txt │ │ ├── PDC_measurements_2.txt │ │ ├── ... │ │ └── PDC_measurements_n.txt │ ├── Slab_3 │ ├── S3_B0 (after material compatibility studies) │ │ ├── PDC_measurements_1.txt │ │ ├── PDC_measurements_2.txt │ │ ├── ... │ │ └── PDC_measurements_n.txt And a similar structure will be used for all samples. A dedicated database is maintained in order to easily associate each sample to its "origin" and different type of aging. One can notice that, for some samples, only the PDC measurement is foreseen; this is because the size of the sample needed for this measurement is much larger than what is needed for the SEM analyses so the samples are only used for PDC. Created using DMPonline. Last modified 16 December 2025 5 of 14 What is the purpose of the data generation or re-use and its relation to the objectives of the project? Not applicable. What is the expected size of the data that you intend to generate or re-use? See the Table reported in Section 1.2 There are no costs foreseen for data storage as every record is < 50GB. What is the origin/provenance of the data, either generated or re-used? The data will be generated by me, using the instruments of the High Voltage Laboratory or the ScopeM laboratory at ETH. To whom might your data be useful ('data utility'), outside your project? Data will be useful to the whole community of researchers using Resistive Plate Chambers (RPCs) as well as to other scientists interested in material compatibility and aging studies with the new, ecofriendly, gas alternatives. FAIR data 2.1. Making data findable, including provisions for metadata: Will data be identified by a persistent identifier? I have created a community in Zenodo to share publicly the data (https://zenodo.org/communities/ecorpcchem). Each record in Zenodo get its own DOI ensuring findability. I have created a repository in GitHub to share the open source code developed to carry out the data analysis (https://github.com/lucaquaglia15/EcoRPCchem). Although GitHub itself does not provide a DOI for the code, one can use Zenodo to archive a repository on GitHub and issue a DOI for the archive. 2.1. Making data findable, including provisions for metadata: Will rich metadata be provided to allow discovery? What metadata will be created? What disciplinary or general standards will be followed? In case metadata standards do not exist in your discipline, please outline what type of metadata will be created and how. Examples of metadata from the discipline Created using DMPonline. Last modified 16 December 2025 6 of 14 Date and time of the measurements Instrument type and measuring conditions (lens used, image resolution, detector used, scale, pressure, field of view, tilt) Examples of metadata created by myself (scheme will be deposited in FAIRsharing) Legend and labels in the spectra Name of the samples and their origin/treatment/storage conditions Search keywords Different machines will be used by the lab to perform the chemical analyses: Scanning Electron Microscope (SEM), equipped with Schottky field emission gun (FEG) ETD, LFD, GSED for Secondary Electron, BSDE, GAD for backscattered electrons and EDAC Octane Super for Energy-dispersive X-ray spectroscopy (EDX) Software: FEI Maps, Ametek-EDAX TEAM, OIM, Genesis Focused Ion Beam (FIB)/SEM Zeiss XB540 with Secondary Electron Secondary Ion (SESI), Energy Selective Backscattered (ESB) and Back Scattered Detector (BSD) detector. KEYENCE laser microscope from VK-X3000 series For what concerns the electrical characterization of the samples, the following will be used: An apparatus to measure the polarization-depolarization currents flowing through the materials and, using the ASTM D257-14 and IEC 62631-3-2 standards, it allows the computation of both the surface and the bulk resistivity of the sample 2.1. Making data findable, including provisions for metadata: Will search keywords be provided in the metadata to optimize the possibility for discovery and then potential reuse? Appropriate search keywords will be provided in the metadata, a detailed research of a controlled dictionary is ongoing on FAIRsharing. 2.1. Making data findable, including provisions for metadata: Will metadata be offered in such a way that it can be harvested and indexed? Zenodo allows harvesting via OAI-PMH protocol. 2.2. Making data accessible - Repository: Will the data be deposited in a trusted repository? The data will be deposited in Zenodo. This repository is managed by CERN and OpenAIRE, and it is well-known within the scientific community, and connects with many other tools within the open science ecosystem such as ORCID and GitHub. It is also non-profit and fulfills the qualitative conditions set by various funders. Zenodo is trusted by OpenAIRE because the data will be stored safely for the future in CERN’s Data Centre for as long as CERN exists (see Section 4.4). Created using DMPonline. Last modified 16 December 2025 7 of 14 2.2. Making data accessible - Repository: Have you explored appropriate arrangements with the identified repository where your data will be deposited? Several arrangements have been explored and eventually the choice landed upon Zenodo, whose FAIR policies can be found here. 2.2. Making data accessible - Repository: Does the repository ensure that the data is assigned an identifier? Will the repository resolve the identifier to a digital object? According to policy of Zenodo: (meta)data are assigned a globally unique and persistent identifier A DOI is issued to every published record on Zenodo The DOI is a top-level and a mandatory field in the metadata of each record 2.2. Making data accessible - Data: Will all data be made openly available? If certain datasets cannot be shared (or need to be shared under restricted access conditions), explain why, clearly separating legal and contractual reasons from intentional restrictions. Note that in multi-beneficiary projects it is also possible for specific beneficiaries to keep their data closed if opening their data goes against their legitimate interests or other constraints as per the Grant Agreement. The project will work according to the principle "as open as possible, as closed as necessary". Raw spectra, PDC data and laser microscopy images will be made immediately available on Zenodo. Other types of data will be made available as soon as the analysis is completed and validated. 2.2. Making data accessible - Data: If an embargo is applied to give time to publish or seek protection of the intellectual property (e.g. patents), specify why and how long this will apply, bearing in mind that research data should be made available as soon as possible. Not applicable. 2.2. Making data accessible - Data: Will the data be accessible through a free and standardized access protocol? According to the Zenodo policy: The protocol is open, free, and universally implementable OAI-PMH and REST are open, free and universal protocols for information retrieval on the web Metadata for individual records as well as record collections are harvestable using the OAIPMH protocol by the record identifier and the collection name. Created using DMPonline. Last modified 16 December 2025 8 of 14 Metadata is also retrievable through the public REST API 2.2. Making data accessible - Data: If there are restrictions on use, how will access be provided to the data, both during and after the end of the project? No restriction will be applied. 2.2. Making data accessible - Data: How will the identity of the person accessing the data be ascertained? Not applicable. 2.2. Making data accessible - Data: Is there a need for a data access committee (e.g. to evaluate/approve access requests to personal/sensitive data)? Not applicable. 2.2. Making data accessible - Metadata: Will metadata be made openly available and licenced under a public domain dedication CC0, as per the Grant Agreement? If not, please clarify why. Will metadata contain information to enable the user to access the data? A CC0 licence will be associated to the data in Zenodo. Reuse should be credited as follows: [Dataset name, created by Luca Quaglia, available at [DOI], date accession] 2.2. Making data accessible - Metadata: How long will the data remain available and findable? Will metadata be guaranteed to remain available after data is no longer available? According to the policy of Zenodo: Data and metadata will be retained for the lifetime of the repository. This is currently the lifetime of the host laboratory CERN, which currently has an experimental programme defined for the next 20 years at least. Metadata are accessible, even when the data are no longer available Metadata are stored in high-availability database servers at CERN, which are separate to the data itself. Created using DMPonline. Last modified 16 December 2025 9 of 14