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DOE OSTI · 2556880

Database of Nonaqueous Proton-Conducting Materials

Cassady, Harrison J. [Michigan State University, East Lansing, MI (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000264531762)·Martin, Emeline [Michigan State University, East Lansing, MI (United States); University of Michigan, Ann Arbor, MI (United States)]·Liu, Yifan [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000151020552)·Bhattacharya, Debjyoti [Pennsylvania State University, University Park, PA (United States)]·Rochow, Maria F. [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000234867038)·Dyer, Brock A. [Ursinus College, Collegeville, PA (United States)]·Reinhart, Wesley F. [Pennsylvania State University, University Park, PA (United States)] (ORCID:0000000172562123)·Cooper, Valentino R. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000167144410)·Hickner, Michael A. [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000222527626)
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Abstract

This work presents the assembly of 48 papers, representing 74 different compounds and blends, into a machine-readable database of nonaqueous proton-conducting materials. SMILES was used to encode the chemical structures of the molecules, and we tabulated the reported proton conductivity, proton diffusion coefficient, and material composition for a total of 3152 data points. The data spans a broad range of temperatures ranging from -70 to 260 °C. To explore this landscape of nonaqueous proton conductors, DFT was used to calculate the proton affinity of 18 unique proton carriers. The results were then compared to the activation energy derived from fitting experimental data to the Arrhenius equation. It was found that while the widely recognized positive correlation between the activation energy and proton affinity may hold among closely related molecules, this correlation does not necessarily apply across a broader range of molecules. This work serves as an example of the potential analyses that can be conducted using literature data combined with emerging research tools in computation and data science to address specific materials design problems.

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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRYBiological databasesElectrical conductivityImpuritiesMaterialsMoleculesPythonacid-dopeddatabaseimidazolenonaqueous moleculesproton conductivityproton exchange membranesmall molecules

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Cassady, Harrison J. [Michigan State University, East Lansing, MI (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000264531762), Martin, Emeline [Michigan State University, East Lansing, MI (United States); University of Michigan, Ann Arbor, MI (United States)], Liu, Yifan [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000151020552), Bhattacharya, Debjyoti [Pennsylvania State University, University Park, PA (United States)], Rochow, Maria F. [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000234867038), Dyer, Brock A. [Ursinus College, Collegeville, PA (United States)], Reinhart, Wesley F. [Pennsylvania State University, University Park, PA (United States)] (ORCID:0000000172562123), Cooper, Valentino R. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000167144410), Hickner, Michael A. [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000222527626). 2025-03-09. Database of Nonaqueous Proton-Conducting Materials. https://doi.org/10.1021/acsami.4c22618

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