ESR study of persistent thioaminyls, N-(arylthio)-3,5-di-tert-butylphenylaminyls

Miura, Yozo; Yamamoto, Akifumi; Katsura, Yosuke; Kinoshita, Masayoshi

doi:10.1021/jo01307a028

Cited by 30 publications

(6 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These values are similar to those of the monoradicals quoted above. 77 Some of the ESR parameters of the radicals discussed above are listed in Table 1.…”

Section: Open-chain Systemsmentioning

confidence: 99%

Electron spin resonance spectroscopy of free radicals containing sulphur linked to nitrogen

Preston¹,

Sutcliffe²

1990

Magnetic Reson in Chemistry

View full text Add to dashboard Cite

There is an abundance of information on closed-shell compounds containing sulphur linked to nitrogen; much less, of course, is known about free radicals containing this moeity. This review describes the wide variety of these radicals, their remarkable stability, the characteristic values of their ESR parameters, their electronic structures and their potential applications.KEY WORDS Electron spin resonance spectroscopy Free radicals Sulphur-nitrogen-containing free radicals 14N hyperfine interactions 33S hyperfine interactions powder spectra

show abstract

“…These values are similar to those of the monoradicals quoted above. 77 Some of the ESR parameters of the radicals discussed above are listed in Table 1.…”

Section: Open-chain Systemsmentioning

confidence: 99%

Electron spin resonance spectroscopy of free radicals containing sulphur linked to nitrogen

Preston¹,

Sutcliffe²

1990

Magnetic Reson in Chemistry

View full text Add to dashboard Cite

show abstract

“…We curated a brand-new test set with 64 charge-neutral, doublet-spin organic semiconducting radicals. In particular, we selected 19 carbon-based radicals (C-1 through C-19), − two polyaromatic hydrocarbon-based radicals (PAH-20 and PAH-21), , 13 nitrogen-based radicals (N-22 through N-34), − six nitrogen–oxygen-based radicals (NO-35 through NO-40), − and eight aryl oxygen-based radicals (ArO-41 through ArO-48) − to benchmark values of E abs . We also selected 16 carbon-based radicals (C-49 through C-64) ,,,− to benchmark values of E fl .…”

Section: Methodsmentioning

confidence: 99%

Accurate Electronic and Optical Properties of Organic Doublet Radicals Using Machine Learned Range-Separated Functionals

Ju,

Shen,

French

et al. 2024

J. Phys. Chem. A

View full text Add to dashboard Cite

Luminescent organic semiconducting doublet-spin radicals are unique and emergent optical materials because their fluorescent quantum yields (Φ fl ) are not compromised by the spinflipping intersystem crossing (ISC) into a dark high-spin state. The multiconfigurational nature of these radicals challenges their electronic structure calculations in the framework of singlereference density functional theory (DFT) and introduces room for method improvement. In the present study, we extended our earlier development of ML-ωPBE [J. Phys. Chem. Lett., 2021, 12, 9516−9524], a range-separated hybrid (RSH) exchange−correlation (XC) functional constructed using the stacked ensemble machine learning (SEML) algorithm, from closed-shell organic semiconducting molecules to doublet-spin organic semiconducting radicals. We assessed its performance for a new test set of 64 doublet-spin radicals from five categories while placing all previously compiled 3926 closed-shell molecules in the new training set. Interestingly, ML-ωPBE agrees with the nonempirical OT-ωPBE functional regarding the prediction of the molecule-dependent range-separation parameter (ω), with a small mean absolute error (MAE) of 0.0197 a 0 −1 , but saves the computational cost by 2.46 orders of magnitude. This result demonstrates an outstanding domain adaptation capacity of ML-ωPBE for diverse organic semiconducting species. To further assess the predictive power of ML-ωPBE in experimental observables, we also applied it to evaluate absorption and fluorescence energies (E abs and E fl ) using linearresponse time-dependent DFT (TDDFT), and we compared its behavior with nine popular XC functionals. For most radicals, ML-ωPBE reproduces experimental measurements of E abs and E fl with small MAEs of 0.299 and 0.254 eV, only marginally different from those of OT-ωPBE. Our work illustrates a successful extension of the SEML framework from closed-shell molecules to doublet-spin radicals and will open the venue for calculating optical properties for organic semiconductors using single-reference TDDFT.

show abstract

“…In particular, we addressed a greater and more worthwhile question about domain adaption: are we able to reproduce the success of ML-ωPBE on radicals? Herein we performed a similar performance assessment for ML-ωPBE based on 64 new species, including 35 carbon-based radicals (C), 19, 2 polyaromatic hydrocarbon-based radicals (PAH), 63,198 13 nitrogen-based radicals (N), [199][200][201][202][203][204][205][206][207] 6 nitrogen-oxygen-based radicals (NO), [208][209][210][211][212][213] and 8…”

Section: Doublet Radicalsmentioning

confidence: 99%

Accurate Electronic and Optical Properties of Organic Doublet Radicals Using Machine Learned Range-Separated Functionals

Shen

French

et al. 2023

Preprint

View full text Add to dashboard Cite

Luminescent organic semiconducting doublet-spin radicals are unique and emergent optical materials because their fluorescent quantum yields (Φfl) are not compromised by spin-flipping intersystem crossing (ISC) into any dark high-spin states. The multi-configurational nature of radical electronic structures challenges computational studies in the framework of single-reference density functional theory (DFT) and introduces room for method improvement. In the present study, we extended our earlier development of a machine-learned range-separated hybrid functional, referred to as ML-ωPBE, from closed-shell molecules to doublet-spin radicals, and assessed its performance for the original training set of 3,926 organic semiconducting molecules and an external test set of 64 organic semiconducting radicals from five categories. Interestingly, for this external test set, ML-ωPBE reproduced the optimal value of ω, the molecule-dependent range-separation parameter, from the first-principles OT-ωPBE functional with a small mean absolute error (MAE) of 0.0197 a0−1 and with a significant save of computational cost by 2.46 orders of magnitude. This result demonstrated excellent generalizability and transferability of ML-ωPBE among a variety of organic semiconducting species. To further assess the predictive power of ML-ωPBE on organic semiconducting radicals, we also compared its performance on experimentally measurable absorption and fluorescence energies (Eabs’s and Efl’s), evaluated using time-dependent DFT (TDDFT), with nine conventional functionals. ML-ωPBE reproduced experimental Eabs’s and Efl’s for most radicals in questions, with small MAEs of 0.222 and 0.121 eV, marginally worse from OT-ωPBE. Our work not only illustrated a successful extension of stacked ensemble machine learning (SEML) framework from closed-shell molecules to open-shell doublet-spin radicals, but also opened the venue for the calculations of optical properties these using single-reference TDDFT.

show abstract

ESR study of persistent thioaminyls, N-(arylthio)-3,5-di-tert-butylphenylaminyls

Cited by 30 publications

References 5 publications

Electron spin resonance spectroscopy of free radicals containing sulphur linked to nitrogen

Electron spin resonance spectroscopy of free radicals containing sulphur linked to nitrogen

Accurate Electronic and Optical Properties of Organic Doublet Radicals Using Machine Learned Range-Separated Functionals

Accurate Electronic and Optical Properties of Organic Doublet Radicals Using Machine Learned Range-Separated Functionals

Contact Info

Product

Resources

About