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RESEARCH PAPER · Solid State Ionics · 2023

Modeling ionic conductivity and activation energy in garnet-structured solid electrolytes: The role of composition, grain boundaries and processing

Natalia V. Kireeva, Aslan Yu. Tsivadze, Vladislav S. Pervov

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16 direct citing papers in this saved network. Explore the next layer with second-order citations.

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Modeling ionic conductivity and activation energy in garnet-structured solid electrolytes: The role of composition, grain boundaries and processingOriginalPredicting Ionic Conductivity in Thin Films of Garnet Electrolytes Using Machine Learning13Machine learning-based evaluation of functional characteristics of Li-rich layered oxide cathode materials using the data of XPS and XRD spectra16Novelty Detection in the Design of Synthesis of Energy Storage Materials: a Case Study of Garnet-Structured Solid Electrolytes1Novelty detection in the design of synthesis of garnet-structured solid electrolytes6Oxide ceramics of A2M3O12 family with negative and close-to-zero thermal expansion coefficients: Machine learning-based modeling of functional characteristics12Structure factors dictate the ionic conductivity and chemical stability for cubic garnet-based solid-state electrolyte9The Key Role of Grain Boundary Dynamics in Revolutionizing the Potential of Solid Electrolytes28Materials advancements in solid-state inorganic electrolytes for highly anticipated all solid Li-ion batteries97Input Consistency Regularization for Modeling Negative Thermal Expansion Characteristics of A2M3O12 Family of Compounds0Input Consistency Regularization of Experimental Data for Modeling Functional Characteristics of A2M3O12${\rm A}_{2} {\rm M}_{3} {\rm O}_{12}$ Family of Compounds0Deep desalination of ash water from coal to methanol gasification: Coupling fluidized-bed crystallization technology and rocking-chair capacitive deionization1Defect and Interface Engineering in Li‐Ion Batteries0Machine learning pipelines for the design of solid-state electrolytes30Data-driven approaches for functional ceramics3Machine Learning Guided Design of Doped Lithium Lanthanum Zirconium Oxide ( LLZO ) for Improved Performance0Automatic Generation of Inorganic Solid‐State Electrolytes via Unified Multi‐Modal Network0

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16 direct citing papers saved.

  1. Predicting Ionic Conductivity in Thin Films of Garnet Electrolytes Using Machine Learning

    Batteries · 2023-08-22

    Natalia V. Kireeva, Aslan Yu. Tsivadze, Vladislav S. Pervov

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  2. Machine learning-based evaluation of functional characteristics of Li-rich layered oxide cathode materials using the data of XPS and XRD spectra

    Computational Materials Science · 2023-10-30

    Natalia V. Kireeva, Vladislav S. Pervov, Aslan Yu. Tsivadze

    Read original paper ↗ ·

  3. Novelty Detection in the Design of Synthesis of Energy Storage Materials: a Case Study of Garnet-Structured Solid Electrolytes

    ChemRxiv · 2024-01-09

    Natalia V. Kireeva, Aslan Yu. Tsivadze

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  4. Novelty detection in the design of synthesis of garnet-structured solid electrolytes

    Journal of Solid State Chemistry · 2024-03-21

    Natalia V. Kireeva, Aslan Yu. Tsivadze

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  5. Oxide ceramics of A2M3O12 family with negative and close-to-zero thermal expansion coefficients: Machine learning-based modeling of functional characteristics

    Journal of Alloys and Compounds · 2024-04-08

    Natalia V. Kireeva, Aslan Yu. Tsivadze

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  6. Structure factors dictate the ionic conductivity and chemical stability for cubic garnet-based solid-state electrolyte

    Chinese Chemical Letters · 2024-04-29

    Jingyu Shi, Xiaofeng Wu, Yutong Chen, Yi Hang Zhang, Xiangyan Hou, Ruike Lv, Junwei Liu, Mengpei Jiang, Keke Huang, Shouhua Feng

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  7. The Key Role of Grain Boundary Dynamics in Revolutionizing the Potential of Solid Electrolytes

    Advanced Functional Materials · 2024-06-18

    Yangyang Wang, Charlotte Thomas, Kaitlin Garman, Hwangsun Kim, Zonghai Chen, Miaofang Chi, Chunmei Ban

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  8. Materials advancements in solid-state inorganic electrolytes for highly anticipated all solid Li-ion batteries

    Energy storage materials · 2024-07-11

    Nafeesa Sarfraz, Nosheen Kanwal, Muzahir Ali, Kashif Ali, Ali Hasnain, Muhammad Ashraf, Muhammad Ayaz, Jerosha Ifthikar, Shahid Ali, Abdulmajeed Hendi, Nadeem Baig, Muhammad Fahad Ehsan, Syed Shaheen Shah, Rizwan Khan, Ibrahim Khan

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  9. Input Consistency Regularization for Modeling Negative Thermal Expansion Characteristics of A2M3O12 Family of Compounds

    ChemRxiv · 2024-08-28

    Natalia V. Kireeva, Aslan Yu. Tsivadze

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  10. Input Consistency Regularization of Experimental Data for Modeling Functional Characteristics of A2M3O12${\rm A}_{2} {\rm M}_{3} {\rm O}_{12}$ Family of Compounds

    Advanced Theory and Simulations · 2025-04-22

    Natalia V. Kireeva, Aslan Yu. Tsivadze

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  11. Deep desalination of ash water from coal to methanol gasification: Coupling fluidized-bed crystallization technology and rocking-chair capacitive deionization

    Desalination · 2025-05-10

    Fengyu Ren, Chenlin Zhang, Chong Zhao, Jinyi Luan, Ziyang Chen, Xinmiao Zhang

    Read original paper ↗ ·

  12. Defect and Interface Engineering in Li‐Ion Batteries

    Unknown journal · 2025-10-17

    Jesús Adrián Díaz‐Real

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  13. Machine learning pipelines for the design of solid-state electrolytes

    Materials Horizons · 2025-11-15

    Vinamr Jain, Zhilong Wang, Fengqi You

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  14. Data-driven approaches for functional ceramics

    Materials Science and Engineering R Reports · 2026-04-01

    Jincheng Qin, Faqiang Zhang, Mingsheng Ma, Yongxiang Li, Zhifu Liu

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  15. Machine Learning Guided Design of Doped Lithium Lanthanum Zirconium Oxide ( LLZO ) for Improved Performance

    Energy Storage · 2026-05-19

    Bernice Ngwi Abraham, Elvis Twumasi, Desmond Edem Primus Klenam, Tabiri Kwayie Asumadu, Abdulhakeem Bello, Vitalis Chioh Anye, N. A. Burnham, Rodica Neamtu, Winston Oluwole Soboyejo

    Read original paper ↗ ·

  16. Automatic Generation of Inorganic Solid‐State Electrolytes via Unified Multi‐Modal Network

    Small · 2026-10-08

    Yihong Liu, Jinjiang Liang, Zheng Wang, Mohamed Ait Tamerd, Jielun Huang, Renyuan Zhang, Wei Liu, Menghao Yang

    Read original paper ↗ ·
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