Summary
Metal-organic frameworks (MOFs) are composed of metal ions coordinated with organic ligands to form porous structures with high surface areas, making them suitable for a wide range of industrial applications. For instance, MOFs exhibit sensitivity to various molecules and gases due to their high surface area and tailored pores. As such, they can be employed in gas sensors for detecting volatile organic compounds, environmental pollutants, and toxic gases, enabling important applications in environmental monitoring and industrial safety. Despite the incredible success of MOFs as a sensing strategy and sequestration agent, only macroscopic quantities of segregated compounds can be effectively sensed. My project SEnsing with QUantum OrganometallIc frAmeworks (SEQUOIA) will pave the way to the exploitation of quantum sensing for the detection of traces of gases/pollutants in air and water by exploring the potential of MOFs decorated with molecular quantum sensors. Quantum sensing is an emerging area of quantum information science that enables the measurement of physical properties using quantum objects (qubits). Quantum sensors are far more precise than their classical counterpart, potentially allowing them to probe a vast range of physical properties, from magnetic fields to gravity, with unprecedented sensitivity. In particular, molecular qubits represent one of the latest frontiers of spin-based quantum sensors, where long spin coherence times are combined with chemical versatility and the possibility to tailor molecular structures in order to tune the sensor’s properties and tailor sensor-target interactions. SEQUOIA will bring together a diverse set of advanced simulation techniques such as quantum chemistry, machine learning and ab initio spin relaxation theory to deliver an unprecedented computational characterization of the properties of MOFs in realistic environments and thus provide a blueprint for the realization of this cutting-edge technology.
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| Web resources: | https://cordis.europa.eu/project/id/101151501 |
| Start date: | 01-10-2024 |
| End date: | 30-09-2026 |
| Total budget - Public funding: | - 215 534,00 Euro |
Cordis data
Original description
Metal-organic frameworks (MOFs) are composed of metal ions coordinated with organic ligands to form porous structures with high surface areas, making them suitable for a wide range of industrial applications. For instance, MOFs exhibit sensitivity to various molecules and gases due to their high surface area and tailored pores. As such, they can be employed in gas sensors for detecting volatile organic compounds, environmental pollutants, and toxic gases, enabling important applications in environmental monitoring and industrial safety. Despite the incredible success of MOFs as a sensing strategy and sequestration agent, only macroscopic quantities of segregated compounds can be effectively sensed. My project SEnsing with QUantum OrganometallIc frAmeworks (SEQUOIA) will pave the way to the exploitation of quantum sensing for the detection of traces of gases/pollutants in air and water by exploring the potential of MOFs decorated with molecular quantum sensors. Quantum sensing is an emerging area of quantum information science that enables the measurement of physical properties using quantum objects (qubits). Quantum sensors are far more precise than their classical counterpart, potentially allowing them to probe a vast range of physical properties, from magnetic fields to gravity, with unprecedented sensitivity. In particular, molecular qubits represent one of the latest frontiers of spin-based quantum sensors, where long spin coherence times are combined with chemical versatility and the possibility to tailor molecular structures in order to tune the sensor’s properties and tailor sensor-target interactions. SEQUOIA will bring together a diverse set of advanced simulation techniques such as quantum chemistry, machine learning and ab initio spin relaxation theory to deliver an unprecedented computational characterization of the properties of MOFs in realistic environments and thus provide a blueprint for the realization of this cutting-edge technology.Status
SIGNEDCall topic
HORIZON-MSCA-2023-PF-01-01Update Date
24-11-2024
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