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CORDIS - EU research results
CORDIS

Program for Research and Innovation on Micro and Nanotechnology for Sensors

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Data Management Plan (DMP) (opens in new window)

The detailed Data Management Plan for FAIR (Findable, Accessible, Interoperable and Reusable) research data will be implemented by month of the project following the FAIR Principle and provide the complete research data life cycle, describing the types of research data that will be generated or collected during the project, the standards that will be used, how the research data will be preserved and what parts of the datasets will be shared for verification or reuse.

Training program for Fostering Research Management, Administration and Innovation skills (opens in new window)

This document describes in detail the content of the training programs & Tutorials for the Fostering Research Management, Administration and Innovation skills WP. The suitable training programme will be developped on the base of the assessment and the analysis of the current situation of CRMN.

Quality assurance plan (opens in new window)

This document will include the guiding principles and measures for correct procedures

Plan for dissemination and exploitation including communication activities (opens in new window)

This document will provide the plan for communication and Dissemination actions. In addition it will provide a Communication Guide and a description of the communications activities.

Publications

Effect of Different PVDF Thicknesses as Coating on PCB-based Interdigital Capacitance Structure (opens in new window)

Author(s): Fatma Khayat, Salma Bizid, Mohamed Hadj Said, Mounir Mansour, Fares Tounsi, Ayoub Hadj Said, Olfa Kanoun
Published in: 2025 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2025
Publisher: IEEE
DOI: 10.1109/I2MTC62753.2025.11079079

Chemically Treated Polyimide Film Modified by Liquid Phase Epitaxially Grown HKUST-1 MOFs for Electrochemical Sensing Applications (opens in new window)

Author(s): Amir Mrayeh, Oumayma Otay, Ge Shi, Tianqi Lu, Anurag Adiraju, Salma Bizid, Olfa Kanoun, Ayoub Haj Said
Published in: 2024 International Workshop on Impedance Spectroscopy (IWIS), 2025
Publisher: IEEE
DOI: 10.1109/IWIS63047.2024.10847152

Plasma-Treated Polyimide Film Modified by Liquid Epitaxially Grown HKUST-1 MOFs for Sensing Application (opens in new window)

Author(s): Oumayma Otay, Amir Mrayeh, Ge Shi, Tianqi Lu, Anurag Adiraju, Salma Bizid, Olfa Kanoun, Ayoub Haj Said
Published in: 2024 International Workshop on Impedance Spectroscopy (IWIS), 2025
Publisher: IEEE
DOI: 10.1109/IWIS63047.2024.10847257

Sensitivity Characterization of ZIF-8 Metal-Organic Framework Coated on an IDT for Ethanol Detection (opens in new window)

Author(s): Fatma Khayat, Mohamed Hadj Said, Tianqi Lu, Salma Bizid, Mounir Mansour, Fares Tounsi, Ayoub Haj Said, Olfa Kanoun
Published in: 2025 International Workshop on Impedance Spectroscopy (IWIS), 2026
Publisher: IEEE
DOI: 10.1109/IWIS69004.2025.11339419

Laser-Induced Synthesis of ZnO-Functionalized Graphene Electrodes from Imidazolate-Based MOFs for Electrochemical Applications (opens in new window)

Author(s): Amir Mrayeh, Tianqi Lu, Salma Bizid, Anurag Adiraju, Olfa Kanoun, Ayoub Haj Said
Published in: 2025 International Workshop on Impedance Spectroscopy (IWIS), 2026
Publisher: IEEE
DOI: 10.1109/IWIS69004.2025.11339386

Innovative Trinuclear Copper(I)-Based Metal–Organic Framework: Synthesis, Characterization, and Application in Laser-Induced Graphene Supercapacitors (opens in new window)

Author(s): Hiba Toumia, Yu Kyoung Ryu, Habiba Zrida, Alicia De Andrés, María Belén Gómez-Mancebo, Natalia Brea Núñez, Fernando Borlaf, Ayoub Haj Said, Javier Martinez
Published in: Nanomaterials, Issue 16, 2026, ISSN 2079-4991
Publisher: MDPI AG
DOI: 10.3390/NANO16030155

A hybrid DFT–machine learning approach for fast HOMO–LUMO gap prediction in naphthalene diimide MOF linkers (opens in new window)

Author(s): Sofiene Achour, Zied Hosni, Bahoueddine Tangour, Ayoub Haj Said
Published in: Materials Chemistry and Physics, Issue 357, 2026, ISSN 0254-0584
Publisher: Elsevier BV
DOI: 10.1016/J.MATCHEMPHYS.2026.132345

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