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Nicholas Wagner
Nicholas Wagner
Graduate Student, Northwestern University
Verified email at u.northwestern.edu - Homepage
Title
Cited by
Cited by
Year
Symbolic regression in materials science
Y Wang, N Wagner, JM Rondinelli
MRS Communications 9 (3), 793-805, 2019
1962019
Theory-guided machine learning in materials science
N Wagner, JM Rondinelli
Frontiers in Materials 3, 28, 2016
1572016
Electrochemical cycling of sodium-filled silicon clathrate
NA Wagner, R Raghavan, R Zhao, Q Wei, X Peng, CK Chan
ChemElectroChem 1 (2), 2014
422014
Type I clathrates as novel silicon anodes: An electrochemical and structural investigation
Y Li, R Raghavan, NA Wagner, SK Davidowski, L Baggetto, R Zhao, ...
Advanced Science 2 (6), 1500057, 2015
342015
Database, features, and machine learning model to identify thermally driven metal–insulator transition compounds
AB Georgescu, P Ren, AR Toland, S Zhang, KD Miller, DW Apley, ...
Chemistry of Materials 33 (14), 5591-5605, 2021
312021
Discovery of complex oxides via automated experiments and data science
L Yang, JA Haber, Z Armstrong, SJ Yang, K Kan, L Zhou, MH Richter, ...
Proceedings of the National Academy of Sciences 118 (37), e2106042118, 2021
272021
Learning from correlations based on local structure: Rare-earth nickelates revisited
N Wagner, D Puggioni, JM Rondinelli
Journal of Chemical Information and Modeling 58 (12), 2491-2501, 2018
202018
Property control from polyhedral connectivity in oxides
N Wagner, R Seshadri, JM Rondinelli
Physical Review B 100 (6), 064101, 2019
122019
Symbolic regression in materials science. MRS Commun 9 (3): 793–805
Y Wang, N Wagner, JM Rondinelli
72019
A Database and Machine Learning Model to Identify Thermally Driven Metal-Insulator Transition Compounds
AB Georgescu, P Ren, AR Toland, EA Olivetti, N Wagner, JM Rondinelli
arXiv preprint arxiv:2010.13306, 2020
22020
Platform Infrastructure for Agile Software Estimation
NA Wagner
Acquisition Research Program, 2022
2022
A Machine Learning Model and Database for The Identification of New Metal-Insulator Transition Compounds
AB Georgescu, P Ren, A Toland, N Wagner, E Olivetti, J Rondinelli
APS March Meeting Abstracts 2021, S44. 006, 2021
2021
Erratum to: Symbolic regression in materials science—CORRIGENDUM
Y Wang, N Wagner, JM Rondinelli
MRS Communications 9, 1370-1370, 2019
2019
Corrigendum: Symbolic regression in materials science (MRS Communications (2019) 9 (793
Y Wang, N Wagner, JM Rondinelli
MRS Communications 9 (4), 1370, 2019
2019
Data Science for Design of Functional Materials
NA Wagner
Northwestern University, 2019
2019
A Classifier for Metal-Insulator Transitions
N Wagner, J Rondinelli
APS March Meeting Abstracts 2019, A18. 007, 2019
2019
Exploring the RNiO3 and RVO3 Phase Diagrams with Data Analytics
N Wagner, D Puggioni, J Rondinelli
APS March Meeting Abstracts 2018, S12. 007, 2018
2018
Controlling Elastic Properties in Perovskites with Polyhedral Connectivity
N Wagner, J Rondinelli
APS March Meeting Abstracts 2017, S32. 005, 2017
2017
Controlling Spin Ordering in Rare-Earth Perovskite Vanadates
N Wagner, J Rondinelli
APS March Meeting Abstracts 2016, Y6. 012, 2016
2016
Structural and Electrochemical Performance of Ternary Type-I Clathrate As Anode Materials for Lithium-Ion Batteries
Y Li, R Raghavan, N Wagner, C Chan
Electrochemical Society Meeting Abstracts 226, 252-252, 2014
2014
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