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How Certain Are the Reported Ionic Conductivities of Thiophosphate-Based Solid Electrolytes? An Interlaboratory Study
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  • Saneyuki Ohno*
    Saneyuki Ohno
    Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, Germany
    Center for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
    *Email: [email protected]
  • Tim Bernges
    Tim Bernges
    Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, Germany
    Center for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
    More by Tim Bernges
  • Johannes Buchheim
    Johannes Buchheim
    Institute for Technical Chemistry and Environmental Chemistry, Center for Energy and Environmental Chemistry Jena (CEEC Jena), Friedrich-Schiller-University Jena, 07743 Jena, Germany
  • Marc Duchardt
    Marc Duchardt
    Department of Chemistry, Philipps-Universität Marburg, Hans-Meerwein-Straße 4, D-35032 Marburg, Germany
  • Anna-Katharina Hatz
    Anna-Katharina Hatz
    Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, Germany
    Department of Chemistry, Ludwig-Maximilians-Universität (LMU), Butenandtstrasse 5-13, 81377 Munich, Germany
    Center for NanoScience, Schellingstrasse 4, 80799 Munich, Germany
  • Marvin A. Kraft
    Marvin A. Kraft
    Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, Germany
    Center for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
  • Hiram Kwak
    Hiram Kwak
    Department of Energy Engineering, Hanyang University, Seoul 04763, South Korea
    More by Hiram Kwak
  • Aggunda L. Santhosha
    Aggunda L. Santhosha
    Department of Chemistry, Humboldt-University Berlin, Brook-Taylor-Str. 2, 12489 Berlin, Germany
  • Zhantao Liu
    Zhantao Liu
    The Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 771 Ferst Drive, Atlanta, Georgia 30332-0245, United States
    More by Zhantao Liu
  • Nicolò Minafra
    Nicolò Minafra
    Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, Germany
    Center for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
  • Fumika Tsuji
    Fumika Tsuji
    Department of Applied Chemistry, Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 599-8531, Japan
    More by Fumika Tsuji
  • Atsushi Sakuda
    Atsushi Sakuda
    Department of Applied Chemistry, Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 599-8531, Japan
  • Roman Schlem
    Roman Schlem
    Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, Germany
    Center for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
    More by Roman Schlem
  • Shan Xiong
    Shan Xiong
    The Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 771 Ferst Drive, Atlanta, Georgia 30332-0245, United States
    More by Shan Xiong
  • Zhenggang Zhang
    Zhenggang Zhang
    Department of Chemistry, Humboldt-University Berlin, Brook-Taylor-Str. 2, 12489 Berlin, Germany
  • Philipp Adelhelm
    Philipp Adelhelm
    Department of Chemistry, Humboldt-University Berlin, Brook-Taylor-Str. 2, 12489 Berlin, Germany
  • Hailong Chen
    Hailong Chen
    The Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 771 Ferst Drive, Atlanta, Georgia 30332-0245, United States
    More by Hailong Chen
  • Akitoshi Hayashi
    Akitoshi Hayashi
    Department of Applied Chemistry, Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 599-8531, Japan
  • Yoon Seok Jung
    Yoon Seok Jung
    Department of Energy Engineering, Hanyang University, Seoul 04763, South Korea
  • Bettina V. Lotsch
    Bettina V. Lotsch
    Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, Germany
    Department of Chemistry, Ludwig-Maximilians-Universität (LMU), Butenandtstrasse 5-13, 81377 Munich, Germany
    Center for NanoScience, Schellingstrasse 4, 80799 Munich, Germany
    E-conversion, Lichtenbergstrasse 4a, 85748 Garching, Germany
  • Bernhard Roling
    Bernhard Roling
    Department of Chemistry, Philipps-Universität Marburg, Hans-Meerwein-Straße 4, D-35032 Marburg, Germany
  • Nella M. Vargas-Barbosa*
    Nella M. Vargas-Barbosa
    Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, Germany
    *Email: [email protected]
  • Wolfgang G. Zeier*
    Wolfgang G. Zeier
    Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, Germany
    Center for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
    *Email: [email protected]
Open PDFSupporting Information (1)

ACS Energy Letters

Cite this: ACS Energy Lett. 2020, 5, 3, 910–915
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https://doi.org/10.1021/acsenergylett.9b02764
Published February 28, 2020

Copyright © 2020 American Chemical Society. This publication is available under these Terms of Use.

This publication is licensed for personal use by The American Chemical Society.

Copyright © 2020 American Chemical Society

Owing to highly conductive solid ionic conductors, all-solid-state batteries attract significant attention as promising next-generation energy storage devices. A lot of research is invested in the search for and optimization of solid electrolytes with higher ionic conductivity. However, a systematic study of interlaboratory reproducibility of measured ionic conductivities and activation energies is missing, making the comparison of absolute values in the literature challenging. In this Viewpoint, we perform an uncertainty evaluation via a round-robin approach using different Li-argyrodites exhibiting orders of magnitude different ionic conductivities as reference materials. Identical samples are distributed to different research laboratories, and the conductivities and activation barriers are measured by impedance spectroscopy. The results show large ranges of up to 4.5 mS cm–1 in the measured total ionic conductivity (1.3–5.8 mS cm–1 for the highest conducting sample, relative standard deviation 35–50% across all samples) and up to 128 meV for the activation barriers (198–326 meV, relative standard deviation 5–15% across all samples), presenting the necessity of a more rigorous methodology including further collaborations within the community and multiplicate measurements.

Fast ionic conductors such as lithium and sodium thiophosphates are currently being investigated for their possible application in all-solid-state batteries. (1,2) Recent research efforts have found a variety of Li+- and Na+-based materials such as the thiophosphates Li10+xM1–xP2+xS12 (M = Si, Ge, Sn), (3−8) Li2S–P2S5 glasses, (9−15) Li6PS5X (X = Cl, Br, I), (16−22) Na3PS4, (23−27) and Na11Sn2PS12. (11,28,29) These materials can exhibit ionic conductivities >1 mS cm–1, making them viable for solid-state battery applications. Throughout the literature, however, we can find a spread in the reported ionic conductivity and activation barrier values, even within the same class of materials. Whereas significant variations in the Li+ ionic transport has been reported as a function of batch variation, particle size, and synthesis procedure, and even due to local sample inhomogeneity, (30,31) to date, no rigorous study on the interlaboratory reproducibility of the ionic conductivity measurement via impedance spectroscopy has been performed. Inspired by the standardization and benchmarking efforts in other communities, e.g., photovoltaics, (32) in this Viewpoint we report a round robin study that considers the reproducibility of ionic conductivity measurements in superionic lithium thiophosphate solid electrolytes.

In this Viewpoint, we chose the lithium argyrodite Li6PS5X as an exemplary class of materials because it provides the possibility to establish statistical trends over several orders of magnitude in the ionic conductivity, ranging from 10–4 mS cm–1 up to a few millisiemens per centimeter. All test samples, namely, Li6.6P0.4Ge0.6PS5I, Li6PS5Cl, Li6PS5Br0.75I0.25, Li6PS5Br0.25I0.75, and Li6PS5I, here identified as samples 1, 2, 3, 4, and 5, respectively, were synthesized by the organizing group according to previous reports. (18,20) To obtain a sufficient amount of homogeneous powder (10 g), each composition was synthesized in multiple batches, followed by X-ray diffraction of each batch to confirm the sample purities (see Figure S1). The resulting sample powders were mixed and homogenized, such that each participating group received 1 g of identical test sample for each composition. Prior to the distribution, the ionic conductivity of all homogenized samples was measured by the organizing group to make sure that the values obtained were similar to previously reported values. All samples were supplied as powders to capture the influence of sample-preparation procedures (i.e., densification procedure, relative density, applied pressure during measurement, and pellet contacting method) on the reported ionic conductivities. Each group was asked to measure temperature-dependent impedance spectra on the supplied samples, including at room temperature (25 °C), using the standard measuring procedure within each lab. All groups were asked to provide the measured impedance spectra and Arrhenius behaviors upon heating (see Figures S2–S10) as well as report the calculated room-temperature conductivities and the activation barriers for all samples, without providing the fitting procedure in order to avoid revealing the identity of the different groups. Further details on the sample preparation and the methodology reported of each group (labeled A–H) are given in the Supporting Information (Tables S2–S10), which include applied pressure upon densification (pelletizing pressure) and during measurement, contacting method, contacting material (Au sputtered and stainless steel pressed), impedance analyzer, excitation voltage, temperature and frequency ranges, the cell constants, and employed powder masses. Hence, the statistical analysis presented here includes the measurement uncertainty of the employed impedance spectroscopy, the uncertainty in the cell constants, as well as the differences in sample preparation for the measurement itself and data analysis procedure.

Under ideal conditions, the impedance spectrum in a Nyquist representation of a polycrystalline solid electrolyte is characterized by two well-resolved semicircles and an electrode polarization. The higher-frequency semicircle would then describe the ionic transport in the grains, whereas the lower-frequency semicircle describes grain boundary contributions to the ionic transport. As is typically observed for Li+ conducting thiophosphates, bulk and grain boundary contributions in Li-argyrodites cannot be deconvoluted at room temperature (see Figures S2 – S10). (18,20) Therefore, in line with the different preparation and measurement procedures, the here-reported ionic conductivity values correspond to the total ionic conductivities of all samples and their corresponding activation barriers. Table S11 summarizes all of the reported values used for this statistical analysis.

The obtained room-temperature conductivities are statistically analyzed using the interquartile range (IQR) method, and the results are shown in Figure 1a as a box plot. Although we observe a large spread in the reported ionic conductivities for all samples (e.g., up to 4.5 mS cm–1 range for sample 1), we were not able to detect any outliers in any of the samples with the IQR method. In the case of samples 1 and 2, the median shows a skewness to lower and higher conductivity values, respectively, whereas for the lower-conducting samples 3, 4, and 5 we observe that the mean and the median are closer to one another. Moreover, the calculated median for the lower-conducting samples is close to the center of the IQR box, which suggests that the spread in the conductivity can be viewed as following a normal distribution. In the particular case of samples 1 and 2, based on this statistical analysis, the samples have very similar median total ionic conductivities, showing the difficulty in comparing different materials across laboratories.

Figure 1

Figure 1. (a) Box plots for the room-temperature total ionic conductivity for all samples in the study. (b) Percentile standard deviations and relative median error percentage for all samples. The relative median error was calculated assuming that the median represents the true total conductivity value, using

Because we do not know what the “true” total ionic conductivity of these samples is, it is challenging to assess the best-practice procedure for the statistical analysis. We can, however, use the different measures of central tendency (median and average) as reasonable estimates for the “true” total ionic conductivity, as well as the standard deviation of the ionic conductivity as the representative expected spread in these samples for the following discussion. It needs to be mentioned that the term “true” total ionic conductivity serves only as a statistical descriptor here; it does not imply that measured values of an individual group represent a “false” ionic conductivity. Note that although the ionic conductivities of all samples range over several orders of magnitude, the calculated average values are close to the median values, and high, but similar, percentages of the standard deviation are found within all samples (see Figure 1b). As the median of any data set is less influenced by extreme values, we take it as the better estimate for the “true” total ionic conductivity and use the calculated average to determine relative median errors for all samples (see Figure 1b). In doing so we observe that for samples with ionic conductivities <1 mS cm–1 this error is less than 10%, whereas in the case of the fastest conductor, the Li6.6P0.4Ge0.6PS5I sample, we obtain a much greater error of 22%.

In the case of the calculated activation barriers, we observe a similar spread in the reported values (see Figure 2). The IQR analysis reveals that in the case of the highest and lowest conducting samples, samples 1 and 5, respectively, one of the values with higher activation barrier is an outlier. Here, the median values for samples 3, 4, and 5 show a skewness to lower activation energies. Only in samples 1 and 2 do we observe that the mean and the median are closer to one another and more centered in the IQR box, again suggesting a normal distribution of the data. In spite of the spread, the percentile standard deviations and relative median errors are much smaller than those for the ionic conductivities, likely because the activation barrier is a parameter that is extracted from the slope of the Arrhenius plot and is therefore less sensitive to extreme values at specific temperatures. Nonetheless, even with the small deviation from the average, the values can correspond to a statistical range of up to 128 meV (198–326 meV). This large range of the activation barriers is significant considering that often values of the activation barriers are reported with a large number of significant figures and changes in series of solid solutions are often within this value of the spread. Moreover, these results suggest that direct comparisons between experimental and theoretically calculated activation barriers are not straightforward and similar values between them do not validate the theory or experimental results.

Figure 2

Figure 2. (a) Box plots for the activation barrier of all samples in the study. (b) Percentile standard deviations and relative median error percentage for all samples. The relative median error was calculated assuming that the median represents the true conductivity value, using .

Because the reported conductivities correspond to total conductivities, one may expect an influence of the densification behavior or resulting relative pellet densities. While nearly 100% relative densities can be achieved in oxide ceramic-based materials via sintering, the mechanical soft nature of the thiophosphate-based electrolytes often leads to densities between 80 and 90% by pressing at ambient temperature. In this study a comparison of the reported ionic conductivities against the densification (pelletizing pressure) pressure, the relative pellet density, the excitation voltage, the cell constant, and pellet thickness show no strong apparent trend in all samples (Figures S11–S20). As an example, Figure 3 shows the absence of clear trends for the ionic conductivity and the activation barrier of sample 2 as a function of pelletizing pressure and cell constant. Although there is no apparent trend as a function of cell constants, a qualitative trend of increasing conductivity with the relative density of the pellet can be observed. However, the trend seen as a function of relative density is not correlated to the pelletizing pressure; that is, a higher relative density is not obtained at higher pelletizing pressures. In addition, whereas no clear influence of the contacting material was identified, an increasing conductivity with increasing applied pressure during measurement was found. This trend does not hold for the Au sputtered samples that were measured without external pressure, indicating the influence of the pressing conditions for pellet preparation on the measured ionic conductivity. These results highlight the effect of sample preparation to the microstructure of the sample and its influence on the measured conductivity. However, it should be noted that the trend with relative densities is not universally observed for all the samples and is less prominent in lower-conducting samples as seen in Figures S11–S20, adding the difficulty of assessing the underlying mechanism of the here-observed variations.

Figure 3

Figure 3. Spread in the total ionic conductivities and activation barriers of sample 2 as a function of various experimental parameters. The dashed line represents the average value and the shaded area the standard deviation from the average.

The absence of universal trends among all the samples on one of the experimental parameters suggests a convolution of influences due to the differences in measurement setups and measurement approaches. One potential reason for the larger discrepancies at high ionic conductivities is the lack of a well-resolved semicircle. In this study, only the samples with a lower ionic conductivity show well-resolved semicircles. An experimental approach for modulating the overall resistance is to change the cell constant (thickness of the pellet divided by the area of the electrode) and with it using enough amount of sample. Note that although changing the cell constant may help to resolve the relevant features in the impedance spectra, the cell constant itself has no influence on the intrinsic conductivity of the material; that is, when normalizing the impedance spectra to the cell constant, the same intercept in the real impedance axis will be obtained. In other words, larger thicknesses will change only the total resistance but not the time constant and frequency range of the occurring transport processes, and a deconvolution of bulk and grain boundaries may be possible only at low temperatures. (33) This may be particularly important in highly conducting samples that lead to low measured resistances in which the influence of the microstructure and resulting grain resistances and microstructure may be more prominent, in comparison to the highly resistive samples. The increasing conductivity with pressure of the stainless-steel contacts, as well as the observed variation as a function of relative densities, in contrast to the values obtained by the Au sputtered samples that do not exhibit any external pressure during measurement, additionally underscores the importance of proper contact between particles, as well as with the electrodes.

To show the influence and beneficial approach of low-temperature measurements, one of the participating groups has the experimental capabilities to perform impedance measurements at temperatures down to −120 °C. At these much lower temperatures it is often possible to separate the grain impedance from the total ionic conductivity. (33)Figure S21 shows the conductivity versus inverse temperature behavior for a representative sample 2 measured to such low temperatures as well as a representative impedance spectrum of sample 2 measured at −100 °C. At temperatures below −75 °C, it is possible to resolve the grain conductivity contributions to the impedance spectrum. Upon fitting and extrapolating the data of grain conductivity versus inverse temperature, the extrapolated line of best fit can estimate the upper-bound values of the reported room-temperature total ionic conductivities in this study. These results underscore, again, the effects of sample microstructure on the ionic conductivity and how under the right measurement conditions it is possible to discriminate between bulk and microstructure effects.

Considering the spread in the obtained conductivities and activation barriers, a few conclusions may be drawn. A larger relative median error can be clearly seen in the samples that exhibit high ionic conductivities >1 mS cm–1 likely due to the convergence of different occurring processes that lead to unresolved processes, which cannot be deconvoluted without a low-temperature measurement.

Additionally, these lithium thiophosphate electrolytes are highly sensitive to atmosphere and, while structurally and chemically comparable, differences in glovebox atmospheres (H2O and O2 content, as well as solvents present) as well as during measurement may interfere with a comparability between groups. Furthermore, pressing in these materials is needed, and a certain degree of microstructural relaxation may occur after pellet consolidation and contacting, making the “sample history” a possible factor in the observed spread. Nevertheless, the large range and uncertainty in the reproducibility of the conductivity and activation barriers suggest the need to adopt a more rigorous approach in the field, as often minor improvements in activation barriers and conductivities are deemed significant.

First, it seems reasonable that for future studies showing changing conductivities and activation barriers, e.g. as a result from isovalent and aliovalent substitutions, measurements in triplicate are necessary, and an accurate description of sample consolidation, contacting, and measurement conditions is needed. Here, three different samples of the same composition should be measured with different cell constants (changing thicknesses as the diameter is often restricted in the cell setup), in order to change the overall cell resistance and report an average value and their respective standard deviations. Measurements at low temperatures to deconvolute processes seems crucial; (33) however, this is often restricted by experimental setups. While the recommendation of triplicate measurements seems trivial, it is not often reported in the literature despite the fact that these triplicates may help to produce more realistic uncertainties in obtained ionic conductivities and activation barriers. While the measurement of triplicates does not fully alleviate the large range that was found throughout the groups, it can provide more meaningful information on qualitative changes in the ionic transport within studies for solid solutions. In the future, measurement standards and standard materials for measurement setup validation may be needed.

Second, especially within this mechanically soft class of materials, there seems to be an influence of the pressure under measurement when measured in press cells (see Figure 3). Therefore, it may be needed to report ionic conductivities as a function of the external pressure applied.

Third, when novel electrolytes with high ionic conductivities >1 mS cm–1 are reported, we suggest sending samples to a collaborative group to corroborate the obtained ionic conductivities.

Fourth, a comparison of experimental conductivity values with diffusion coefficients obtained by nuclear magnetic resonance and with it calculations of Haven ratios may be subject to a large uncertainty based on the experimental range in obtained conductivities. While Haven ratios are often used to explain correlation effects, (34) comparing different measurement techniques may not be very meaningful in extracting information about correlation effects in these systems.

Fifth, often theoretical calculations are internally validated by reproduction of experimental activation barriers. Despite a smaller relative median error, the larger range of up to 128 meV in the experimentally obtained activation barriers suggests that a direct comparison between experiment and theory alone should not be used to validate theoretical nor experimental results.

Overall, within the field of superionic conductors a more rigorous approach for reporting results, including the experimental conditions and triplicate measurements, will be needed to better understand and reliably design solid electrolytes for the use in solid-state batteries.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsenergylett.9b02764.

  • Synthesis procedure of all samples and X-ray diffraction results; all experimental measurement conditions of the different data sets along with their statistical analysis; measured impedance spectra and Arrhenius plots as well as the comparison of the transport properties against possible sample preparation and measurement influences (PDF)

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Author Information

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  • Corresponding Authors
    • Saneyuki Ohno - Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, GermanyCenter for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, GermanyOrcidhttp://orcid.org/0000-0001-8192-996X Email: [email protected]
    • Nella M. Vargas-Barbosa - Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, GermanyOrcidhttp://orcid.org/0000-0002-6357-017X Email: [email protected]
    • Wolfgang G. Zeier - Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, GermanyCenter for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, GermanyOrcidhttp://orcid.org/0000-0001-7749-5089 Email: [email protected]
  • Authors
    • Tim Bernges - Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, GermanyCenter for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
    • Johannes Buchheim - Institute for Technical Chemistry and Environmental Chemistry, Center for Energy and Environmental Chemistry Jena (CEEC Jena), Friedrich-Schiller-University Jena, 07743 Jena, Germany
    • Marc Duchardt - Department of Chemistry, Philipps-Universität Marburg, Hans-Meerwein-Straße 4, D-35032 Marburg, Germany
    • Anna-Katharina Hatz - Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, GermanyDepartment of Chemistry, Ludwig-Maximilians-Universität (LMU), Butenandtstrasse 5-13, 81377 Munich, GermanyCenter for NanoScience, Schellingstrasse 4, 80799 Munich, Germany
    • Marvin A. Kraft - Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, GermanyCenter for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
    • Hiram Kwak - Department of Energy Engineering, Hanyang University, Seoul 04763, South Korea
    • Aggunda L. Santhosha - Department of Chemistry, Humboldt-University Berlin, Brook-Taylor-Str. 2, 12489 Berlin, GermanyOrcidhttp://orcid.org/0000-0002-2422-2703
    • Zhantao Liu - The Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 771 Ferst Drive, Atlanta, Georgia 30332-0245, United States
    • Nicolò Minafra - Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, GermanyCenter for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
    • Fumika Tsuji - Department of Applied Chemistry, Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 599-8531, Japan
    • Atsushi Sakuda - Department of Applied Chemistry, Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 599-8531, JapanOrcidhttp://orcid.org/0000-0002-9214-0347
    • Roman Schlem - Institute of Physical Chemistry, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 17, D-35392 Giessen, GermanyCenter for Materials Research (LaMa), Justus-Liebig-University Giessen, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
    • Shan Xiong - The Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 771 Ferst Drive, Atlanta, Georgia 30332-0245, United States
    • Zhenggang Zhang - Department of Chemistry, Humboldt-University Berlin, Brook-Taylor-Str. 2, 12489 Berlin, Germany
    • Philipp Adelhelm - Department of Chemistry, Humboldt-University Berlin, Brook-Taylor-Str. 2, 12489 Berlin, GermanyOrcidhttp://orcid.org/0000-0003-2439-8802
    • Hailong Chen - The Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 771 Ferst Drive, Atlanta, Georgia 30332-0245, United StatesOrcidhttp://orcid.org/0000-0001-8283-2860
    • Akitoshi Hayashi - Department of Applied Chemistry, Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 599-8531, JapanOrcidhttp://orcid.org/0000-0001-9503-5561
    • Yoon Seok Jung - Department of Energy Engineering, Hanyang University, Seoul 04763, South KoreaOrcidhttp://orcid.org/0000-0003-0357-9508
    • Bettina V. Lotsch - Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, GermanyDepartment of Chemistry, Ludwig-Maximilians-Universität (LMU), Butenandtstrasse 5-13, 81377 Munich, GermanyCenter for NanoScience, Schellingstrasse 4, 80799 Munich, GermanyE-conversion, Lichtenbergstrasse 4a, 85748 Garching, GermanyOrcidhttp://orcid.org/0000-0002-3094-303X
    • Bernhard Roling - Department of Chemistry, Philipps-Universität Marburg, Hans-Meerwein-Straße 4, D-35032 Marburg, GermanyOrcidhttp://orcid.org/0000-0001-7383-1495
  • Notes
    Views expressed in this Viewpoint are those of the authors and not necessarily the views of ACS.
    The authors declare no competing financial interest.

Acknowledgments

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The research was supported by the Federal Ministry of Education and Research (BMBF) within the project FESTBATT under Grant Numbers 03XP0117A and 03XP0177B. S.O. gratefully acknowledges the Alexander von Humboldt Foundation for financial support through a Postdoctoral Fellowship. P.A. acknowledges support within the research unit Hy-NIB (2017 FGR 0055) funded by the ESF/Thuringia. S.X., Z.L., and H.C. acknowledge the financial support of the U.S. National Science Foundation under Grant Number 1706723.

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ACS Energy Letters

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https://doi.org/10.1021/acsenergylett.9b02764
Published February 28, 2020

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  • Figure 1

    Figure 1. (a) Box plots for the room-temperature total ionic conductivity for all samples in the study. (b) Percentile standard deviations and relative median error percentage for all samples. The relative median error was calculated assuming that the median represents the true total conductivity value, using

    Figure 2

    Figure 2. (a) Box plots for the activation barrier of all samples in the study. (b) Percentile standard deviations and relative median error percentage for all samples. The relative median error was calculated assuming that the median represents the true conductivity value, using .

    Figure 3

    Figure 3. Spread in the total ionic conductivities and activation barriers of sample 2 as a function of various experimental parameters. The dashed line represents the average value and the shaded area the standard deviation from the average.

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    • Synthesis procedure of all samples and X-ray diffraction results; all experimental measurement conditions of the different data sets along with their statistical analysis; measured impedance spectra and Arrhenius plots as well as the comparison of the transport properties against possible sample preparation and measurement influences (PDF)


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