Kinetic fragility and structure of lithium borophosphate glasses analysed by 1D/2D NMR
文献情報
Laura Muñoz-Senovilla, Gregory Tricot, Francisco Muñoz
The macroscopic and high temperature properties of lithium borophosphate glasses were determined in this contribution. Our data, obtained on 50Li2O–xB2O3–(50−x)P2O5 glasses, confirm a continuous and linear increase of the glass transition temperature with the B/P substitution but show a two-domain evolution of the kinetic fragility with a steep decrease in the low B2O3 region (0 ≤ x ≤ 10) followed by a moderate increase for higher B2O3 contents. In order to understand this different behaviour, the glass structure was investigated in detail using 1D and 2D 11B/31P correlation solid state nuclear magnetic resonance. The local and medium orders of borate units were determined by 1D MAS-NMR, 2D 11B DQSQ- and 11B(31P) D-HMQC NMR experiments. The latter NMR technique was also used to deeply interpret the 1D 31P MAS-NMR spectra. Altogether the data allow (i) highlighting of the presence of four borate and seven phosphate units, (ii) evaluation of the number of homopolar POP and mixed POB linkages, and (iii) contribute to a better understanding of the Tg and kinetic fragility evolution.
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.














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