Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Kireeva, Natalia
and
Pervov, Vladislav S.
2017.
Materials space of solid-state electrolytes: unraveling chemical composition–structure–ionic conductivity relationships in garnet-type metal oxides using cheminformatics virtual screening approaches.
Physical Chemistry Chemical Physics,
Vol. 19,
Issue. 31,
p.
20904.
Dimiduk, Dennis M.
Holm, Elizabeth A.
and
Niezgoda, Stephen R.
2018.
Perspectives on the Impact of Machine Learning, Deep Learning, and Artificial Intelligence on Materials, Processes, and Structures Engineering.
Integrating Materials and Manufacturing Innovation,
Vol. 7,
Issue. 3,
p.
157.
Chen, D.
and
Torquato, S.
2018.
Designing disordered hyperuniform two-phase materials with novel physical properties.
Acta Materialia,
Vol. 142,
Issue. ,
p.
152.
Seko, Atsuto
Toyoura, Kazuaki
Muto, Shunsuke
Mizoguchi, Teruyasu
and
Broderick, Scott
2018.
Progress in nanoinformatics and informational materials science.
MRS Bulletin,
Vol. 43,
Issue. 9,
p.
690.
Broderick, Scott R.
Kumar, Aakash
Oni, Adedapo A.
LeBeau, James M.
Sinnott, Susan B.
and
Rajan, Krishna
2018.
Discovering chemical site occupancy- modulus correlations in Ni based intermetallics via statistical learning methods.
Computational Condensed Matter,
Vol. 14,
Issue. ,
p.
8.
Torquato, S.
and
Chen, D.
2018.
Multifunctionality of particulate composites via cross-property maps.
Physical Review Materials,
Vol. 2,
Issue. 9,
Mullis, Adam S.
Broderick, Scott R.
Binnebose, Andrea M.
Peroutka-Bigus, Nathan
Bellaire, Bryan H.
Rajan, Krishna
and
Narasimhan, Balaji
2019.
Data Analytics Approach for Rational Design of Nanomedicines with Programmable Drug Release.
Molecular Pharmaceutics,
Vol. 16,
Issue. 5,
p.
1917.
Burnett, T. L.
and
Withers, P. J.
2019.
Completing the picture through correlative characterization.
Nature Materials,
Vol. 18,
Issue. 10,
p.
1041.
Withers, Philip J
and
Burnett, Timothy L
2019.
Rich multi-dimensional correlative imaging.
IOP Conference Series: Materials Science and Engineering,
Vol. 580,
Issue. 1,
p.
012014.
Kireeva, Natalia
and
Pervov, Vladislav S.
2020.
Materials Informatics Screening of Li‐Rich Layered Oxide Cathode Materials with Enhanced Characteristics Using Synthesis Data.
Batteries & Supercaps,
Vol. 3,
Issue. 5,
p.
427.
Echlin, McLean P.
Burnett, Timothy L.
Polonsky, Andrew T.
Pollock, Tresa M.
and
Withers, Philip J.
2020.
Serial sectioning in the SEM for three dimensional materials science.
Current Opinion in Solid State and Materials Science,
Vol. 24,
Issue. 2,
p.
100817.
Mianroodi, Jaber Rezaei
H. Siboni, Nima
and
Raabe, Dierk
2021.
Teaching solid mechanics to artificial intelligence—a fast solver for heterogeneous materials.
npj Computational Materials,
Vol. 7,
Issue. 1,
Zhang, Hongbin
2021.
High-throughput design of magnetic materials.
Electronic Structure,
Vol. 3,
Issue. 3,
p.
033001.
Jiao, Pengcheng
2021.
Emerging artificial intelligence in piezoelectric and triboelectric nanogenerators.
Nano Energy,
Vol. 88,
Issue. ,
p.
106227.
Kireeva, Natalia
and
Solov'ev, Vitaly P.
2021.
Machine learning analysis of microwave dielectric properties for seven structure types: The role of the processing and composition.
Journal of Physics and Chemistry of Solids,
Vol. 156,
Issue. ,
p.
110178.
Jivani, Devyani
and
Wodo, Olga
2022.
Skeletal-based microstructure representation and featurization through descriptors.
Computational Materials Science,
Vol. 214,
Issue. ,
p.
111668.
Mianroodi, Jaber Rezaei
Rezaei, Shahed
Siboni, Nima H.
Xu, Bai-Xiang
and
Raabe, Dierk
2022.
Lossless multi-scale constitutive elastic relations with artificial intelligence.
npj Computational Materials,
Vol. 8,
Issue. 1,
Kireeva, Natalia
Tsivadze, Aslan Yu.
and
Pervov, Vladislav S.
2023.
Predicting Ionic Conductivity in Thin Films of Garnet Electrolytes Using Machine Learning.
Batteries,
Vol. 9,
Issue. 9,
p.
430.
Kireeva, Natalia
and
Tsivadze, Aslan Yu.
2024.
Novelty detection in the design of synthesis of garnet-structured solid electrolytes.
Journal of Solid State Chemistry,
Vol. 334,
Issue. ,
p.
124669.
Kireeva, Natalia
Pervov, Vladislav S.
and
Tsivadze, Aslan Yu.
2024.
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,
Vol. 231,
Issue. ,
p.
112591.