Liu, Yinqiao, Jiang, Xue, Zhao, Jijun, and Hu, Ming. Electronic charge density as a fast approach for predicting Li-ion migration pathways in superionic conductors with first-principles level precision. Retrieved from https://par.nsf.gov/biblio/10230373. Computational Materials Science 192.C Web. doi:10.1016/j.commatsci.2021.110380.

Liu, Yinqiao, Jiang, Xue, Zhao, Jijun, & Hu, Ming. Electronic charge density as a fast approach for predicting Li-ion migration pathways in superionic conductors with first-principles level precision. Computational Materials Science, 192 (C). Retrieved from https://par.nsf.gov/biblio/10230373. https://doi.org/10.1016/j.commatsci.2021.110380

Liu, Yinqiao, Jiang, Xue, Zhao, Jijun, and Hu, Ming. "Electronic charge density as a fast approach for predicting Li-ion migration pathways in superionic conductors with first-principles level precision". Computational Materials Science 192 (C). Country unknown/Code not available. https://doi.org/10.1016/j.commatsci.2021.110380. https://par.nsf.gov/biblio/10230373.

@article{osti_10230373,
place = {Country unknown/Code not available}, title = {Electronic charge density as a fast approach for predicting Li-ion migration pathways in superionic conductors with first-principles level precision}, url = {https://par.nsf.gov/biblio/10230373}, DOI = {10.1016/j.commatsci.2021.110380}, abstractNote = {}, journal = {Computational Materials Science}, volume = {192}, number = {C}, author = {Liu, Yinqiao and Jiang, Xue and Zhao, Jijun and Hu, Ming}, editor = {null} }