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DTSTAMP:20250822T115805Z
LOCATION:Room 5.2A17
DTSTART;TZID=Europe/Stockholm:20250618T090000
DTEND;TZID=Europe/Stockholm:20250618T093000
UID:submissions.pasc-conference.org_PASC25_sess148_msa203@linklings.com
SUMMARY:Data - Driven Discovery of Fe(III) Based Spin-Crossover Systems
DESCRIPTION:Jordi Cirera, Jordi Ribas-Arino, and Daniel Vidal Ramon (Unive
 rsity of Barcelona)\n\nSpin-crossover (SCO) molecules exhibit bistability 
 between two electronic states, switching in response to an external stimul
 i that alters the material properties. This makes SCO systems promising  c
 andidates for molecular-level based applications. The transition temperatu
 re (T1/2) marks the point where spin populations are equal, and is a key p
 arameter in SCO systems. While Fe(II) compounds dominate the field, Fe(III
 )-based SCO systems offer advantages for technological applications. Howev
 er, experimental data on Fe(III) systems is limited. Electronic structure 
 methods, particularly density functional theory (DFT) calculations, help i
 n the design of new Fe(III)-based SCO systems with targeted T1/2 values. O
 ur results demonstrates that DFT calculations accurately reproduce experim
 ental T1/2 values and enables broad ligand functionalization screening. Mo
 reover, all observed trends can be explained through the underlying electr
 onic structure of the system. These calculations provide with valuable gui
 delines for chemists when developing new SCO compounds with specific prope
 rties. Additionally, this method allow us to generate data that can be use
 d to train machine learning (ML) models employing SOAPs descriptors for th
 e 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 applicat
 ion in technology.\n\nDomain: Chemistry and Materials\n\nSession Chair: Ma
 rco Lattuada (Universiity of Fribourg)\n\n
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