Structure and Conductivity Correlation in NASICON Based Na3Al2P3O12 Glass: Effect of Na2SO4

Mandal, Indrajeet; Chakraborty, Saswata; Ghosh, Manasi; Dey, Krishna Kishor; Annapurna, K.; Allu, Amarnath R.

doi:10.3389/fmats.2021.802379

Cited by 4 publications

(6 citation statements)

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“…This clearly indicates that Na 2 SO 4 has a positive impact on conductivity for concentration >5 mol %. Several studies in the literature have reported that the addition of Na 2 SO 4 in phosphate glasses enhances the conductivity value. ,− Na 2 SO 4 decomposed in a glass structure and formed isolated SO 4 2– anions and Na + cations. Additionally, these large SO 4 2– anions accumulated in the channel regions surrounded by Na + cations.…”

Section: Resultsmentioning

confidence: 99%

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: 99%

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

et al. 2023

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“…Even at 10 A g −1 , its capacity still reaches 321 mAh g −1 . According to the simulation results, the amorphous Fe 2 O 3 has a much lower intercalation energy of 1.82 eV compared with crystal Fe 2 O 3 [111] Copyright 2022, Frontiers Media S.A. b) Structure of pure NaPO 3 , 80NaPO 3 -20AlF 3 , and 60NaPO 3 -40AlF 3 glasses. Reproduced with permission.…”

Section: Non-glass Ams For Sodium Batteriesmentioning

confidence: 96%

“…The DC‐conductivity change in Na 3 Al 2 P 3 O 12 (Na 2 O‐Al 2 O 3 ‐P 2 O 5 ) glass caused by substituting Na 2 SO 4 for Al 2 O 3 was measured to identify the factors influencing the ionic conductivity. [ 111 ] Raman spectroscopy results show that increasing the Na 2 SO 4 content can increase the fraction of isolated SO 4 2− units, which are charge compensated by sodium‐ion ( Figure a). Magic‐angle spinning (MAS)‐NMR results further indicate that increasing the Na 2 SO 4 content also increases the content of nonbridging oxygens.…”

Section: Am‐based Batteriesmentioning

confidence: 99%

“…XANES analysis further demonstrates that Al@a-Al has a higher energy value than that of pure Al, indicating poor periodicity (Figure 12e). Analysis of the radial distribution function (RDF) shows that the nearest and the second nearest neighboring peaks -306 mAh g −1 at 2 A g −1 1000 cycles Anode of LIBs [ 26a] Lithium storage structure evolution T g = 563 K [ 223] ZIF-62 glass (Zn) E = 5.2, 𝜈 = 0.343 K Ic = 0.104 𝛾 = 0.82 [ 224] --T g = 593 K [ 225] 𝜅 = 0.130 [33] ZIF-4 glass (Zn) -L i + conductivity is 0.161 mS cm −1 (303 K), ZIF-4 based electrolyte [ 26b] Lithium transfer stability T g = 570 K [ 225] 𝜅 = 0.115 [33] Li 2 S-B 2 S 3 -LiI-SiO 2 glass -L i + conductivity is 2.1 mS cm −1 (RT) [53] Lithium transfer stability -Li 2 S-P 2 S 5 glass E = 18.5, H = 1.9 K Ic = 0.23 [52] Li + conductivity at 10 −1 mS cm −1 level [ 226] Lithium transfer stability -Amorphous polymer -Li + conductivity is about 0.36 mS cm −1 (RT) [25] Lithium transfer stability Thermal stability (652 K) [ 111] Sodium transfer stability -…”

Section: Ams For Other Types Of Batteriesmentioning

confidence: 99%

“…(a) Structure and Raman spectra of Na 2 SO 4 on Na 3 Al 2 P 3 O 12 glasses. Reproduced with permission [111]. Copyright 2022, Frontiers Media S.A. b) Structure of pure NaPO 3 , 80NaPO 3 -20AlF 3 , and 60NaPO 3 -40AlF 3 glasses.…”

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Amorphous Materials for Lithium‐Ion and Post‐Lithium‐Ion Batteries

Ding,

Ji,

Yue

et al. 2023

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Lithium‐ion and post‐lithium‐ion batteries are important components for building sustainable energy systems. They usually consist of a cathode, an anode, an electrolyte, and a separator. Recently, the use of solid‐state materials as electrolytes has received extensive attention. The solid‐state electrolyte materials (as well as the electrode materials) have traditionally been overwhelmingly crystalline materials, but amorphous (disordered) materials are gradually emerging as important alternatives because they can increase the number of ion storage sites and diffusion channels, enhance solid‐state ion diffusion, tolerate more severe volume changes, and improve reaction activity. To develop superior amorphous battery materials, researchers have conducted a variety of experiments and theoretical simulations. This review highlights the recent advances in using amorphous materials (AMs) for fabricating lithium‐ion and post‐lithium‐ion batteries, focusing on the correlation between material structure and properties (e.g., electrochemical, mechanical, chemical, and thermal ones). We review both the conventional and the emerging characterization methods for analyzing AMs and present the roles of disorder in influencing the performances of various batteries such as those based on lithium, sodium, potassium, and zinc. Finally, we describe the challenges and perspectives for commercializing rechargeable AMs‐based batteries.

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