Stepwise modification of the methyl groups at the α positions of BODIPY 1 was used for preparation of a series of mono- (2, 4, and 6) and diferrocene (3) substituted donor-acceptor dyads in which the organometallic substituents are fully conjugated with the BODIPY π system. All donor-acceptor complexes have strong absorption in the NIR region and quenched steady-state fluorescence, which can be partially restored upon oxidation of organometallic group(s). X-ray crystallography of complexes 2-4 and 6 confirms the nearly coplanar arrangement of the ferrocene groups and the BODIPY π system. Redox properties of the target systems were studied using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). It was found that the first oxidation process in all dyads is ferrocene centered, while the separation between the first and the second ferrocene-centered oxidation potentials in diferrocenyl-containing dyad 3 is ∼150 mV. The density functional theory-polarized continuum model (DFT-PCM) and time-dependent (TD) DFT-PCM methods were used to investigate the electronic structure as well as explain the UV-vis and redox properties of organometallic compounds 2-4 and 6. TDDFT calculations allow for assignment of the charge-transfer and π → π* transitions in the target compounds. The excited state dynamics of the parent BODIPY 1 and dyads 2-4 and 6 were investigated using time-resolved transient spectroscopy. In all organometallic dyads 2-4 and 6 the initially excited state is rapidly quenched by electron transfer from the ferrocene ligand. The lifetime of the charge-separated state was found to be between 136 and 260 ps and demonstrates a systematic dependence on the electronic structure and geometry of BODIPYs 2-4 and 6.

Noncovalent π-π interactions between chloroboron subphthalocyanine (1), 2,3-subnaphthalocyanine (3), 1,4,8,11,15,18-(hexathiophenyl)subphthalocyanine (4), or 4-tert-butylphenoxyboron subphthalocyanine (2) with C and C fullerenes were studied by UV-vis and steady-state fluorescence spectroscopy, as well as mass (APCI, ESI, and CSI) spectrometry. Mass spectrometry experiments were suggestive of relatively weak interaction energies between compounds 1-4 and fullerenes. The formation of a new weak charge-transfer band in the NIR region was observed in solution only for subphthalocyanine 4 when titrated with C and C fullerenes. Molecular structures of the subphthalocyanines 2 and 4 as well as cocrystallite of 4 with C fullerene (4···C) were studied using X-ray crystallography. One of the C fullerenes in the crystal structure of 4···C was found in the concave region between two subphthalocyanine cores, while the other three fullerenes are aligned above individual isoindole fragments of the aromatic subphthalocyanine. The excited-state dynamics in noncovalent assemblies were studied by transient absorption spectroscopy. The time-resolved photophysics data suggest that only electron-rich subphthalocyanine 4 can facilitate an electron-transfer to C or C fullerenes, while no electron-transfer from the photoexcited receptors 1-3 to fullerenes was observed in UV-vis and transient spectroscopy experiments. DFT calculations using the CAM-B3LYP exchange-correlation functional and the 6-31+G(d) basis set allowed an estimation of interaction energies for the noncovalent 1:1 and 1:2 (fullerene:subphthalocyanine) complexes. Theoretical data suggest that the weak (∼3.5-10.5 kcal/mol) van der Waals-type interaction energies tend to increase with an increase of the electron density at the subphthalocyanine core with compound 4 being the best platform for noncovalent interactions with fullerenes. DFT calculations also indicate that 1:2 (fullerene:subphthalocyanine) noncovalent complexes are more stable than the corresponding 1:1 assemblies.

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A complete pipeline system for constructing language processing models that can be used to process multiple practical detection tasks of language structures of clinical records is presented.

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This paper presents ongoing research in clinical information extraction. This work introduces a new genre of text which are not well-written, noise prone, ungrammatical and with much cryptic content. A corpus of clinical progress notes drawn form an Intensive Care Service has been manually annotated with more than 15000 clinical named entities in 11 entity types. This paper reports on the challenges involved in creating the annotation schema, and recognising and annotating clinical named entities. The information extraction task has initially used two approaches: a rule based system and a machine learning system using Conditional Random Fields (CRF). Different features are investigated to assess the interaction of feature sets and the supervised learning approaches to establish the combination best suited to this data set. The rule based and CRF systems achieved an F-score of 64.12% and 81.48% respectively.