Combined Machine Learning, Computational, and Experimental Analysis of the Iridium(III) Complexes with Red to Near-Infrared Emission

Various coordination complexes have been the subject of experimental and theoretical studies in recent decades because of their fascinating photophysical properties. In this work, a combined experimental and computational approach was applied to investigate the optical properties of monocationic Ir­...

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Published inThe journal of physical chemistry letters Vol. 15; no. 2; pp. 471 - 480
Main Authors Karuth, Anas, Casanola-Martin, Gerardo M., Lystrom, Levi, Sun, Wenfang, Kilin, Dmitri, Kilina, Svetlana, Rasulev, Bakhtiyor
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 18.01.2024
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ISSN1948-7185
1948-7185
DOI10.1021/acs.jpclett.3c02533

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Abstract Various coordination complexes have been the subject of experimental and theoretical studies in recent decades because of their fascinating photophysical properties. In this work, a combined experimental and computational approach was applied to investigate the optical properties of monocationic Ir­(III) complexes. An interpretative machine learning-based quantitative structure–property relationship (ML/QSPR) model was successfully developed that could reliably predict the emission wavelength of the Ir­(III) complexes and provide a foundation for the theoretical evaluation of the optical properties of Ir­(III) complexes. A hypothesis was proposed to explain the differences in the emission wavelengths between structurally different individual Ir­(III) complexes. The efficacy of the developed model was demonstrated by high R 2 values of 0.84 and 0.87 for the training and test sets, respectively. It is worth noting that a relationship between the N–N distance in the diimine ligands of the Ir­(III) complexes and emission wavelengths is detected. This effect is most probably associated with a degree of distortion in the octahedral geometry of the complexes, resulting in a perturbed ligand field. This combined experimental and computational approach shows great potential for the rational design of new Ir­(III) complexes with the desired optical properties. Moreover, the developed methodology could be extended to other transition-metal complexes.
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Various coordination complexes have been the subject of experimental and theoretical studies in recent decades because of their fascinating photophysical properties. In this work, a combined experimental and computational approach was applied to investigate the optical properties of monocationic Ir(III) complexes. An interpretative machine learning-based quantitative structure-property relationship (ML/QSPR) model was successfully developed that could reliably predict the emission wavelength of the Ir(III) complexes and provide a foundation for the theoretical evaluation of the optical properties of Ir(III) complexes. A hypothesis was proposed to explain the differences in the emission wavelengths between structurally different individual Ir(III) complexes. The efficacy of the developed model was demonstrated by high values of 0.84 and 0.87 for the training and test sets, respectively. It is worth noting that a relationship between the N-N distance in the diimine ligands of the Ir(III) complexes and emission wavelengths is detected. This effect is most probably associated with a degree of distortion in the octahedral geometry of the complexes, resulting in a perturbed ligand field. This combined experimental and computational approach shows great potential for the rational design of new Ir(III) complexes with the desired optical properties. Moreover, the developed methodology could be extended to other transition-metal complexes.
Various coordination complexes have been the subject of experimental and theoretical studies in recent decades because of their fascinating photophysical properties. In this work, a combined experimental and computational approach was applied to investigate the optical properties of monocationic Ir(III) complexes. An interpretative machine learning-based quantitative structure-property relationship (ML/QSPR) model was successfully developed that could reliably predict the emission wavelength of the Ir(III) complexes and provide a foundation for the theoretical evaluation of the optical properties of Ir(III) complexes. A hypothesis was proposed to explain the differences in the emission wavelengths between structurally different individual Ir(III) complexes. The efficacy of the developed model was demonstrated by high R2 values of 0.84 and 0.87 for the training and test sets, respectively. It is worth noting that a relationship between the N-N distance in the diimine ligands of the Ir(III) complexes and emission wavelengths is detected. This effect is most probably associated with a degree of distortion in the octahedral geometry of the complexes, resulting in a perturbed ligand field. This combined experimental and computational approach shows great potential for the rational design of new Ir(III) complexes with the desired optical properties. Moreover, the developed methodology could be extended to other transition-metal complexes.Various coordination complexes have been the subject of experimental and theoretical studies in recent decades because of their fascinating photophysical properties. In this work, a combined experimental and computational approach was applied to investigate the optical properties of monocationic Ir(III) complexes. An interpretative machine learning-based quantitative structure-property relationship (ML/QSPR) model was successfully developed that could reliably predict the emission wavelength of the Ir(III) complexes and provide a foundation for the theoretical evaluation of the optical properties of Ir(III) complexes. A hypothesis was proposed to explain the differences in the emission wavelengths between structurally different individual Ir(III) complexes. The efficacy of the developed model was demonstrated by high R2 values of 0.84 and 0.87 for the training and test sets, respectively. It is worth noting that a relationship between the N-N distance in the diimine ligands of the Ir(III) complexes and emission wavelengths is detected. This effect is most probably associated with a degree of distortion in the octahedral geometry of the complexes, resulting in a perturbed ligand field. This combined experimental and computational approach shows great potential for the rational design of new Ir(III) complexes with the desired optical properties. Moreover, the developed methodology could be extended to other transition-metal complexes.
Various coordination complexes have been the subject of experimental and theoretical studies in recent decades because of their fascinating photophysical properties. In this work, a combined experimental and computational approach was applied to investigate the optical properties of monocationic Ir­(III) complexes. An interpretative machine learning-based quantitative structure–property relationship (ML/QSPR) model was successfully developed that could reliably predict the emission wavelength of the Ir­(III) complexes and provide a foundation for the theoretical evaluation of the optical properties of Ir­(III) complexes. A hypothesis was proposed to explain the differences in the emission wavelengths between structurally different individual Ir­(III) complexes. The efficacy of the developed model was demonstrated by high R 2 values of 0.84 and 0.87 for the training and test sets, respectively. It is worth noting that a relationship between the N–N distance in the diimine ligands of the Ir­(III) complexes and emission wavelengths is detected. This effect is most probably associated with a degree of distortion in the octahedral geometry of the complexes, resulting in a perturbed ligand field. This combined experimental and computational approach shows great potential for the rational design of new Ir­(III) complexes with the desired optical properties. Moreover, the developed methodology could be extended to other transition-metal complexes.
Author Lystrom, Levi
Karuth, Anas
Casanola-Martin, Gerardo M.
Kilin, Dmitri
Kilina, Svetlana
Rasulev, Bakhtiyor
Sun, Wenfang
AuthorAffiliation Department of Chemistry and Biochemistry
Coatings and Polymeric Materials
North Dakota State University
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Snippet Various coordination complexes have been the subject of experimental and theoretical studies in recent decades because of their fascinating photophysical...
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SubjectTerms Chemistry
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Physical Insights into Materials and Molecular Properties
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Title Combined Machine Learning, Computational, and Experimental Analysis of the Iridium(III) Complexes with Red to Near-Infrared Emission
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