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Enhancing Singlet Oxygen Generation in Conjugates of Silicon Nanocrystals and Organic Photosensitizers.

ABSTRACT: Silicon nanocrystals (SiNCs) are regarded as a green and environmentally friendly material when compared with other semiconductor nanocrystals. Ultra-small SiNCs (with the size 4.6-5.2 nm) demonstrate strong UV absorption and photoluminescence in the near infrared (NIR) range with the high photoluminescence quantum yield (PLQY) up to 60%. In contrast to nanoporous silicon, ultra-small SiNCs do not possess an intrinsic ability to generate singlet oxygen (1O2). However, we demonstrate that SiNC-dye conjugates synthesized via microwave assistant hydrosilylation reaction produce 1O2 with moderate quantum yield (??) up to 27% in cyclohexane. These interesting results were obtained via measurements of singlet oxygen phosphorescence at 1,270 nm. SiNCs play an important role in the production of singlet oxygen as SiNCs harvest UV and blue radiation and transfer absorbed energy to a triplet state of the attached dyes. It increases the population of the triplet states and leads to the enhancement of the singlet oxygen generation. Simultaneously, the SiNC-dye conjugates demonstrate NIR luminescence with the PLQY up to 22%. Thus, the luminescence behavior and photosensitizing properties of the SiNC-dye conjugates can attract interest as a new multifunctional platform in the field of bio-applications.

SUBMITTER: Beri D

PROVIDER: S-EPMC7379910 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Enhancing Singlet Oxygen Generation in Conjugates of Silicon Nanocrystals and Organic Photosensitizers.

Beri Deski D Jakoby Marius M Busko Dmitry D Richards Bryce S BS Turshatov Andrey A

Frontiers in chemistry 20200717

Silicon nanocrystals (SiNCs) are regarded as a green and environmentally friendly material when compared with other semiconductor nanocrystals. Ultra-small SiNCs (with the size 4.6-5.2 nm) demonstrate strong UV absorption and photoluminescence in the near infrared (NIR) range with the high photoluminescence quantum yield (PLQY) up to 60%. In contrast to nanoporous silicon, ultra-small SiNCs do not possess an intrinsic ability to generate singlet oxygen (<sup>1</sup>O<sub>2</sub>). However, we de ...[more]

PMID: 32766208

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Project description:Heavy-atom-free sensitizers forming long-living triplet excited states via the spin-orbit charge transfer intersystem crossing (SOCT-ISC) process have recently attracted attention due to their potential to replace costly transition metal complexes in photonic applications. The efficiency of SOCT-ISC in BODIPY donor-acceptor dyads, so far the most thoroughly investigated class of such sensitizers, can be finely tuned by structural modification. However, predicting the triplet state yields and reactive oxygen species (ROS) generation quantum yields for such compounds in a particular solvent is still very challenging due to a lack of established quantitative structure-property relationship (QSPR) models. In this work, the available data on singlet oxygen generation quantum yields (ΦΔ ) for a dataset containing >70 heavy-atom-free BODIPY in three different solvents (toluene, acetonitrile, and tetrahydrofuran) were analyzed. In order to build reliable QSPR model, a series of new BODIPYs were synthesized that bear different electron donating aryl groups in the meso position, their optical and structural properties were studied along with the solvent dependence of singlet oxygen generation, which confirmed the formation of triplet states via the SOCT-ISC mechanism. For the combined dataset of BODIPY structures, a total of more than 5000 quantum-chemical descriptors was calculated including quantum-chemical descriptors using density functional theory (DFT), namely M06-2X functional. QSPR models predicting ΦΔ values were developed using multiple linear regression (MLR), which perform significantly better than other machine learning methods and show sufficient statistical parameters (R=0.88-0.91 and q2 =0.62-0.69) for all three solvents. A small root mean squared error of 8.2 % was obtained for ΦΔ values predicted using MLR model in toluene. As a result, we proved that QSPR and machine learning techniques can be useful for predicting ΦΔ values in different media and virtual screening of new heavy-atom-free BODIPYs with improved photosensitizing ability.

Dataset Information

Enhancing Singlet Oxygen Generation in Conjugates of Silicon Nanocrystals and Organic Photosensitizers.

Publications

Enhancing Singlet Oxygen Generation in Conjugates of Silicon Nanocrystals and Organic Photosensitizers.

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