Enhancement of Optical Telecommunication Bands: Pr3+-Doped Halide Phosphate Glasses Display Broadband NIR Photoluminescence Emission.

In the optical energy gap, visible and near-IR emission of halide phosphate glasses with a composition of 40P2O5-30ZnO-20LiCl-10BaF2 in mol% doped with 3.5 × 104 ppm Pr2O3, referred to as PZLBPr, were synthesized. The UV-VIS-NIR and spectroscopic properties of these glasses were also predicted. The current glasses had broadband emission photoluminescence covering a wavelength range of 1250 to 1700 nm when excited at 455 nm. These bands for near-infrared emission luminescence relate to the transitions 1G4 → 3H5, 1D2 → 1G4, and 3H4 → 3F3, 3F4 in the optical telecommunication window. The significant PL emission wideband was caused by the radiative transition from Pr3+: 1D2 to 1G4. At 445 nm excitation, these glasses exhibited emission bands that corresponded to blue/reddish orange spectral ranges in visible ranges. The prepared glass has a high lasing quality factor (Ω4/Ω6 = 0.9), high optical energy (4.72 eV), and quantum efficiency = 87.3% with FWHM = 156 nm of transition emission from the 1D2 → 1G4 level. As a result, broadband near infrared optical amplifiers can be fabricated from the prepared glasses.

The Structure of Gd3+-Doped Li2O and K2O Containing Aluminosilicate Glasses from Molecular Dynamics Simulations.

Understanding the atomic structure of glasses is critical for developing new generations of materials with important technical applications. In particular, the local environment of rare-earth ions and their distribution and clustering is of great relevance for applications of rare earth-containing glasses in photonic devices. In this work, the structure of Gd2O3 doped lithium and potassium aluminosilicate glasses is investigated as a function of their network modifier oxide (NMO-Li2O, K2O) to aluminum oxide ratio using molecular dynamics simulations. The applied simulation procedure yields a set of configurations, the so-called inherent structures, of the liquid state slightly above the glass transition temperature. The generation of a large set of inherent structures allows a statistical sampling of the medium-range order of the Gd3+ ions with less computational effort compared to other simulation methods. The resulting medium-range atomic structures of network former and modifier ions are in good agreement with experimental results and simulations of similar glasses. It was found that increasing NMO/Al ratio increases the network modifier coordination number with non-bridging oxygen sites and reduces the overall stability of the network structure. The fraction of non-bridging oxygen sites in the vicinity of Gd3+ ions increases considerably with decreasing field strength and increasing concentration of the network modifier ions. These correlations could be confirmed even if the simulation results of alkaline earth aluminosilicate glasses are added to the analysis. In addition, the structure predictions generally indicate a low driving force for the clustering of Gd3+. Here, network modifier ions of large ionic radii reduce the probability of Gd-O-Gd contacts.

Atomistic Descriptors for Machine Learning Models of Solubility Parameters for Small Molecules and Polymers.

Descriptors derived from atomic structure and quantum chemical calculations for small molecules representing polymer repeat elements were evaluated for machine learning models to predict the Hildebrand solubility parameters of the corresponding polymers. Since reliable cohesive energy density data and solubility parameters for polymers are difficult to obtain, the experimental heat of vaporization ΔHvap of a set of small molecules was used as a proxy property to evaluate the descriptors. Using the atomistic descriptors, the multilinear regression model showed good accuracy in predicting ΔHvap of the small-molecule set, with a mean absolute error of 2.63 kJ/mol for training and 3.61 kJ/mol for cross-validation. Kernel ridge regression showed similar performance for the small-molecule training set but slightly worse accuracy for the prediction of ΔHvap of molecules representing repeating polymer elements. The Hildebrand solubility parameters of the polymers derived from the atomistic descriptors of the repeating polymer elements showed good correlation with values from the CROW polymer database.

Structure Prediction of Rare Earth Doped BaO and MgO Containing Aluminosilicate Glasses⁻the Model Case of Gd2O3.

The medium-range atomic structure of magnesium and barium aluminosilicate glasses doped with Gd2O3 as a model rare earth oxide is elucidated using molecular dynamics simulations. Our structure models rationalize the strong dependence of the luminescence properties of the glasses on their chemical composition. The simulation procedure used samples' atomic configurations, the so-called inherent structures, characterizing configurations of the liquid state slightly above the glass transition temperature. This yields medium-range atomic structures of network former and modifier ions in good agreement with structure predictions using standard simulated annealing procedures. However, the generation of a large set of inherent structures allows a statistical sampling of the medium-range order of Gd3+ ions with less computational effort compared to the simulated annealing approach. It is found that the number of Si-bound non-bridging oxygen in the vicinity of Gd3+ considerably increases with growing ionic radius and concentration of network-modifier ions. In addition, structure predictions indicate a low driving force for clustering of Gd3+, yet no precise correlation between the atomic structure and luminescence lifetimes can be conclusively established. However, the structure models provided in this study can serve as a starting point for future quantum mechanical simulations to shed a light on the relation between the atomic structure and optical properties of rare earth doped aluminosilicate glasses.