2022
DOI: 10.1016/j.ccr.2022.214684
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Basic structural modifications for improving the practical properties of BODIPY

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Cited by 60 publications
(30 citation statements)
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References 140 publications
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“…Various deep red to NIR chromophores/fluorophores such as squaraine, [19][20][21] azo, [22][23][24] styryl, [25][26][27] perylene, [28][29][30] BODIPY, [31][32][33] aza-BODIPY, [32,34,35] cyanine, [36][37][38] coumarin, [39,40] and xanthene [41][42][43] are reported having either absorption or emission or both lying in the deep-red to NIR. A few such fluorophores are presented in Figure 1.…”
Section: Types Of Deep Red To Nir Chromophores/fluorophoresmentioning
confidence: 99%
“…Various deep red to NIR chromophores/fluorophores such as squaraine, [19][20][21] azo, [22][23][24] styryl, [25][26][27] perylene, [28][29][30] BODIPY, [31][32][33] aza-BODIPY, [32,34,35] cyanine, [36][37][38] coumarin, [39,40] and xanthene [41][42][43] are reported having either absorption or emission or both lying in the deep-red to NIR. A few such fluorophores are presented in Figure 1.…”
Section: Types Of Deep Red To Nir Chromophores/fluorophoresmentioning
confidence: 99%
“…[6][7][8] This variety of physicochemical properties of BODIPYs can be achieved through the accessible route of molecular structure modification. [9][10][11][12][13] For example, the introduction of aryl substituents along the periphery of the BODIPY core leads to a red shift of the absorption and emission maxima, allowing us to use BODIPYs in the ''phototherapeutic window'' region. 12,14 Another example is the halogenation of BODIPYs that realizes promising photosensitizers for cancer photodynamic therapy, using their ability to generate singlet oxygen.…”
Section: Introductionmentioning
confidence: 99%
“…In this regard, the methods based on machine learning (ML) are an attractive alternative. Gao et al suggested a method based on DNN (Deep Neural Network) combining the chemical environment descriptors and the structural descriptors calculated by DFT to predict 1 H/ 13 C NMR chemical shifts of organic molecules. 26 Gerrard et al developed a methodology based on Impression (Intelligent Machine PREdiction of Shift and Scalar information Of Nuclei) KRR (Kernel Ridge Regression) to predict the 15 N NMR chemical shift.…”
Section: Introductionmentioning
confidence: 99%
“…2 Due to the ease of structural modification based on BODIPY derivatives, it is possible to obtain luminophores that absorb and emit in almost the entire spectral range. 3 Such a set of practically significant physicochemical properties allows the use of dyes in this class in various fields, including molecular sensorics, 4,5 medical diagnostics, [6][7][8] biochemistry, [9][10][11][12] etc.…”
Section: Introductionmentioning
confidence: 99%