Effect of Na2SO4 substitution for Na2O on the structural and electrical properties of a sodium borophosphate glass

Sadok, Khouloud Hadj; Haouari, Mohamed; Gallot‐Lavallée, Olivier; Ouada, H. Ben

doi:10.1016/j.jallcom.2018.11.203

Cited by 17 publications

(9 citation statements)

References 64 publications

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“…Additionally, these large SO 4 2– anions accumulated in the channel regions surrounded by Na + cations. K. H. Sadok et al, in their investigation of borophosphate glasses, also observe a similar increasing trend of the conductivity value by raising the Na 2 SO 4 concentration. They explain that as the Na + cations surrounded by large-size SO 4 2– anions face the shallow potential wall, this leads to an increase in the mobility of Na + cations connected to SO 4 2– anions.…”

Section: Resultsmentioning

confidence: 56%

Machine Learning-Assisted Design of Na-Ion-Conducting Glasses

et al. 2023

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As an alternative to liquid electrolytes, all-solid-state sodium-ion batteries are receiving significant attention due to their potential for improved safety and efficiency. Here, we propose a combined experimental and machine learning (ML) approach for discovering glass electrolytes while also providing insights into the role of different glass components. Specifically, we experimentally prepare and measure the ionic conductivity of 27 glass compositions of the sodium aluminophosphate glass family. Further, we train ML models on this dataset to predict the ionic conductivity, which exhibits excellent agreement with the experimental results. We interpret the composition–conductivity relationship learned by the ML model using Shapely additive explanations (SHAP), which reveals the role played by the glass components in governing the conductivity. Employing these observations, glass compositions with improved conductivity values are predicted and experimentally validated. The results corroborate the insights from SHAP analysis and enable optimized glass formulations in real-world experiments. This demonstrates how ML tools can significantly accelerate the discovery of Na-ion-conducting glass electrolytes.

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Section: Resultsmentioning

confidence: 56%

Machine Learning-Assisted Design of Na-Ion-Conducting Glasses

et al. 2023

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“…Therefore, the ionic conductivity variation maintains the proportional relation with the concentration of sulfate in sulfate glasses. This hypothesis has been proved in several studies. ,, For example, Ganguli et al have found that increasing the Li 2 SO 4 content from 0 to 30 mol % at a constant Li 2 O/P 2 O 5 molar ratio in the Li 2 SO 4 –Li 2 O–P 2 O 5 system increases the conductivity by almost 2 orders of magnitude.…”

Section: Introductionmentioning

confidence: 80%

“…Immense research activity recently focuses on understanding the sodium-ion dynamics in glass network structures, thereby achieving high ionic conductivity at room temperature (>10 –3 S/cm). − It has been found that the chemical components and the network structure of glass highly influence sodium-ion dynamics. For example, in aluminosilicate glasses, the bond strength of sodium with nonbridging oxygen (NBO) of silica tetrahedral is stronger than that of sodium with bridging oxygen (BO) shared between alumina and silica tetrahedral. , NBOs around sodium create a deep local potential well for the sodium cations and increase the energy barriers, which obviously decrease diffusion.…”

Section: Introductionmentioning

confidence: 99%

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Role of Sodium-Ion Dynamics and Characteristic Length Scales in Ion Conductivity in Aluminophosphate Glasses Containing Na₂SO₄

et al. 2022

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Achieving high ion conductivity in glass-based Na-ion conducting materials for their applications as solid electrolytes in batteries is still challenging owing to the vague knowledge on the factors governing Na-ion dynamics. In the present study, an attempt has been made to identify the factors affecting the sodium-ion dynamics through structure and conductivity property correlation for the 37.5Na2O–37.5P2O5–15Al2O3–10NaF (FS-0; mol %) glass system with varied concentrations of Na2SO4. 31P, 27Al, and 23Na MAS NMR (magic-angle spinning nuclear magnetic resonance) and Raman spectroscopy are employed to assess the structural modifications, and impedance spectroscopy is used to measure the variations in ionic conductivity on the addition of Na2SO4 in the FS-0 glass. Raman spectra and MAS NMR analysis indicate that the quantity of P–O–Na bonds and sulfate (SO4 2–) units surrounded by sodium increase with increasing Na2SO4 concentration. Impedance analysis reveals that the conductivity of FS-0 glass enhances by 1 order with the addition of 6 mol % Na2SO4. We identify from the ac-conductivity spectral analysis that the concentration of charge carriers and the critical hopping length of mobile cations increase with the addition of 6 mol % Na2SO4. Overall, we reveal that the structural modifications, Na-ion concentration, and the shallower potential well that is created for sodium due to its interaction with the nearest neighboring cations affect the Na-ion dynamics. The information obtained from the present study certainly helps to optimize the chemical composition of glasses demonstrating high ionic conductivity.

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“…Majority of scientific reports dealing with the glass transition kinetics focus on the activation energy of this process. [21][22][23][24][25][26][27][28][29][30] It is indeed the most important parameter, as it determines the position of the glass transition phenomenon with respect to the temperature axis and describes its shift/evolution with experimental conditions (temperature T, heating or cooling rate q + / q -, applied stress, etc.). One of the other proposed meanings of the activation energy of structural relaxation is its similarity with the activation energy of viscous flow in the corresponding temperature region [31,32] the idea is based on the concept of the structural relaxation movements being mechanistically (on the atomic level) similar to the structural changes associated with the flow of the matter.…”

Section: Introductionmentioning

confidence: 99%

Correlation between the activation energies of structural relaxation and viscous flow for BaO–P2O5–Al2O3 glasses

Svoboda

Chromčíková

Hruška

et al. 2020

Journal of Non-Crystalline Solids

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Effect of Na2SO4 substitution for Na2O on the structural and electrical properties of a sodium borophosphate glass

Cited by 17 publications

References 64 publications

Machine Learning-Assisted Design of Na-Ion-Conducting Glasses

Machine Learning-Assisted Design of Na-Ion-Conducting Glasses

Role of Sodium-Ion Dynamics and Characteristic Length Scales in Ion Conductivity in Aluminophosphate Glasses Containing Na₂SO₄

Correlation between the activation energies of structural relaxation and viscous flow for BaO–P2O5–Al2O3 glasses

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Effect of Na2SO4 substitution for Na2O on the structural and electrical properties of a sodium borophosphate glass

Cited by 17 publications

References 64 publications

Machine Learning-Assisted Design of Na-Ion-Conducting Glasses

Machine Learning-Assisted Design of Na-Ion-Conducting Glasses

Role of Sodium-Ion Dynamics and Characteristic Length Scales in Ion Conductivity in Aluminophosphate Glasses Containing Na2SO4

Correlation between the activation energies of structural relaxation and viscous flow for BaO–P2O5–Al2O3 glasses

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Role of Sodium-Ion Dynamics and Characteristic Length Scales in Ion Conductivity in Aluminophosphate Glasses Containing Na₂SO₄