Dataset Information

Detailed Molecular and Structural Analysis of Dual Emitter IrQ(ppy)2 Complex.

ABSTRACT: The molecular structure of the 8-hydroxyquinoline-bis (2-phenylpyridyl) iridium (IrQ(ppy)2) dual emitter organometallic compound is determined based on detailed 1D and 2D nuclear magnetic resonance (NMR), to identify metal-ligands coordination, isomerization and chemical yield of the desired compound. Meanwhile, the extended X-ray absorption fine structure (EXAFS) was used to determine the interatomic distances around the iridium ion. From the NMR results, this compound IrQ(ppy)2 exhibits a trans isomerization with a distribution of coordinated N-atoms in a similar way to facial Ir(ppy)3. The EXAFS measurements confirm the structural model of the IrQ(ppy)2 compound where the oxygen atoms from the quinoline ligands induce the splitting of the next-nearest neighboring C in the second shell of the Ir3+ ions. The high-performance liquid chromatography (HPLC), as a part of the detailed molecular analysis, confirms the purity of the desired IrQ(ppy)2 organometallic compound as being more than 95%, together with the progress of the chemical reactions towards the final compound. The theoretical model of the IrQ(ppy)2, concerning the expected bond lengths, is compared with the structural model from the EXAFS and XRD measurements.

SUBMITTER: Ciobotaru IC

PROVIDER: S-EPMC7178428 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Detailed Molecular and Structural Analysis of Dual Emitter IrQ(ppy)2 Complex.

Ciobotaru Iulia Corina IC Crisan Daniel Nicolae DN Šket Primoz P Ciobotaru Constantin Claudiu CC Polosan Silviu S

Materials (Basel, Switzerland) 20200401 7

The molecular structure of the 8-hydroxyquinoline-bis (2-phenylpyridyl) iridium (IrQ(ppy)2) dual emitter organometallic compound is determined based on detailed 1D and 2D nuclear magnetic resonance (NMR), to identify metal-ligands coordination, isomerization and chemical yield of the desired compound. Meanwhile, the extended X-ray absorption fine structure (EXAFS) was used to determine the interatomic distances around the iridium ion. From the NMR results, this compound IrQ(ppy)2 ...[more]

PMID: 32244686

Similar Datasets

Project description:Radio signal-based positioning in environments with complex propagation paths is a challenging task for classical positioning methods. For example, in a typical industrial environment, objects such as machines and workpieces cause reflections, diffractions, and absorptions, which are not taken into account by classical lateration methods and may lead to erroneous positions. Only a few data-driven methods developed in recent years can deal with these irregularities in the propagation paths or use them as additional information for positioning. These methods exploit the channel impulse responses (CIR) that are detected by ultra-wideband radio systems for positioning. These CIRs embed the signal properties of the underlying propagation paths that represent the environment. This article describes a feature-based localization approach that exploits machine-learning to derive characteristic information of the CIR signal for positioning. The approach is complete without highly time-synchronized receiver or arrival times. Various features were investigated based on signal propagation models for complex environments. These features were then assessed qualitatively based on their spatial relationship to objects and their contribution to a more accurate position estimation. Three datasets collected in environments of varying degrees of complexity were analyzed. The evaluation of the experiments showed that a clear relationship between the features and the environment indicates that features in complex propagation environments improve positional accuracy. A quantitative assessment of the features was made based on a hierarchical classification of stratified regions within the environment. Classification accuracies of over 90% could be achieved for region sizes of about 0.1 m 2 . An application-driven evaluation was made to distinguish between different screwing processes on a car door based on CIR measures. While in a static environment, even with a single infrastructure tag, nearly error-free classification could be achieved, the accuracy of changes in the environment decreases rapidly. To adapt to changes in the environment, the models were retrained with a small amount of CIR data. This increased performance considerably. The proposed approach results in highly accurate classification, even with a reduced infrastructure of one or two tags, and is easily adaptable to new environments. In addition, the approach does not require calibration or synchronization of the positioning system or the installation of a reference system.

Dataset Information

Detailed Molecular and Structural Analysis of Dual Emitter IrQ(ppy)2 Complex.

Publications

Detailed Molecular and Structural Analysis of Dual Emitter IrQ(ppy)<sub>2</sub> Complex.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets