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Minisymposium Presentation
Data - Driven Discovery of Fe(III) Based Spin-Crossover Systems
Presenter
Jordi Cirera (Barcelona, 1979) graduated in Chemistry from the University of Barcelona (UB, 2002) and received his doctorate with honors from the same university (2006). His first postdoctoral stage was at Stanford University (2007-2010) working on spectroscopic studies and theoretical modeling of copper mediated biogenesis in metalloproteins, with Prof. Edward I. Solomon. He underwent a second postdoctoral stage with Prof. Francesco Paesani (2012- 2014) at University of California, San Diego (UCSD), working in the development and implementation of new methodologies for the computational modeling of spin-crossover (SCO) processes in Metal-Organic Frameworks (MOFs). He has been visiting researcher at the Max-Planck Institute für Festköperforschung (MPG-FKF) in Stuttgart, and the Institut de Physique et Chimie des Materiaux (ICPMS) in Strasbourg, under the supervision of Prof. Jens Kortus, developing new methodologies to compute zero-field splitting parameters in transition metal complexes, which are key in the study of Single -Molecule Magnets. He has been awarded with several grants, including a FPU PhD grant (AP2002-2236), a grant for his first postdoctoral stage (2006BP-A10041), a Hellmann Fellowship Foundation grant for his second postdoctoral stage, and a Beatriu de Pinos/Marie Curie COFUND grant (2013BP-B00155). He has also been co-PI in the European Prace project SPINMOLSURF (15th Prace Call, project ID: 2016163898), and PI of the ComSwitch project (PID2020-115165GB-I00). He has been speaker at 44 national and international conferences (8 invited), and is co-author of 59 publications (h-index 29, total citations 5163, 14 as a corresponding author, one as a single author) and two book chapters (one as a single author). Dr. Cirera appears in the 2023 Stanford ranking of the top 2% influential scientist in his field (10.17632/btchxktzyw.6). He has conducted different teaching assignments within the Inorganic Chemistry area at the UB (around 1700h) and is also involved in two Erasmus mundus master programs (ChIR and TCCM). He has directed 9 final degree projects, and four master projects. He is also responsible for different scientific outreach activities, including the development of the ModMol© app in collaboration with Vysion, and is the PI of the Immersive Virtual Reality towards active chemistry learning project (2023PEDC-QUI/002). He was co-organizer of the IQTC-UB annual Symposium (2018 one awarded with 2370 for funding) and co-organizer of the FHI- AIMS workshop-2010 that took place in Barcelona (awarded with 32000 from CECAM and PSI-K networks). He participated in the Materials Networking project, partially funded within the EU Horizon 2020 research and innovation program (grant 692146). Currently he is a Ramón y Cajal researcher at the UB (RYC2018- 024692-I). He took a volunteer paternity leave of absence between 2011-2012, to allow his wife to continue with her academic career. His research focusses on the computational study of the transition temperature in SCO systems of different complexity, from molecules to clusters up to condensed phases, using a wide range of electronic structure methods that allow for an accurate calculation of such value. Understanding the changes in such parameter in terms of the electronic structure of the system allows for a tailored design of new systems with specific physical properties, thus accelerating the discovery of new functional materials that can operate at specific conditions.
Description
Spin-crossover (SCO) molecules exhibit bistability between two electronic states, switching in response to an external stimuli that alters the material properties. This makes SCO systems promising candidates for molecular-level based applications. The transition temperature (T1/2) marks the point where spin populations are equal, and is a key parameter in SCO systems. While Fe(II) compounds dominate the field, Fe(III)-based SCO systems offer advantages for technological applications. However, experimental data on Fe(III) systems is limited. Electronic structure methods, particularly density functional theory (DFT) calculations, help in the design of new Fe(III)-based SCO systems with targeted T1/2 values. Our results demonstrates that DFT calculations accurately reproduce experimental T1/2 values and enables broad ligand functionalization screening. Moreover, all observed trends can be explained through the underlying electronic structure of the system. These calculations provide with valuable guidelines for chemists when developing new SCO compounds with specific properties. Additionally, this method allow us to generate data that can be used to train machine learning (ML) models employing SOAPs descriptors for the automatic classification of Fe(III) based molecules into high-spin, low-spin, or spin-crossover categories. This approach enhances the predictive capabilities for new SCO materials, accelerating their design and application in technology.