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Nina Andrejevic

Argonne National Laboratory · US
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Area of research
Materials Chemistry · Atomic and Molecular Physics, and Optics
Research interest
Research interests include Machine Learning in Materials Science, Topological Materials and Phenomena, X-ray Diffraction in Crystallography, and Graphene research and applications.
h-index
12
citations
680
works
56
NIH funding
primary concept
email

Recent publications

Virtual node graph neural network for full phonon prediction
Nature Computational Science 2024cited by 19position: middledoi
Topology stabilized fluctuations in a magnetic nodal semimetal
Nature Communications 2023cited by 16position: middledoi
Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning
Advanced Materials 2022cited by 6position: middledoi
Machine learning on neutron and x-ray scattering and spectroscopies
Chemical Physics Reviews 2021cited by 110position: middledoi
Direct Prediction of Phonon Density of States With Euclidean Neural Networks.
2021cited by 28position: middle
Topological signatures in nodal semimetals through neutron scattering
New Journal of Physics 2021cited by 4position: middledoi
Quantized thermoelectric Hall effect induces giant power factor in a topological semimetal
Nature Communications 2020cited by 88position: middledoi
Topological Singularity Induced Chiral Kohn Anomaly in a Weyl Semimetal
Physical Review Letters 2020cited by 44position: middledoi
Editors' Choice—Connecting Fuel Cell Catalyst Nanostructure and Accessibility Using Quantitative Cryo-STEM Tomography
Journal of The Electrochemical Society 2018cited by 150position: middledoi
Theory of electron–phonon–dislon interacting system—toward a quantized theory of dislocations
DSpace@MIT (Massachusetts Institute of Technology) 2017cited by 18position: middle
Theory of Electron-Phonon-Dislon Interacting System - Toward a Quantized Theory of Dislocations
arXiv (Cornell University) 2017cited by 0position: middledoi
Multicomponent Nanomaterials with Complex Networked Architectures from Orthogonal Degradation and Binary Metal Backfilling in ABC Triblock Terpolymers
Journal of the American Chemical Society 2015cited by 78position: middledoi

Grants

No grants ingested yet.

Frequent collaborators

Mingda Li · IIT@MIT10 papers (2017–2024)Thanh Nguyen · Massachusetts Institute of Technology6 papers (2020–2023)Zhantao Chen · Massachusetts Institute of Technology4 papers (2021–2023)Nathan C. Drucker · Massachusetts Institute of Technology4 papers (2021–2024)Ahmet Alatas · California Institute of Technology4 papers (2020–2023)Yoichiro Tsurimaki · Massachusetts Institute of Technology4 papers (2017–2021)J. A. Fernandez‐Baca · University of Tennessee at Knoxville3 papers (2020–2023)Fei Han · National University of Singapore3 papers (2020–2023)Shengxi Huang · Massachusetts Institute of Technology3 papers (2020–2023)Songxue Chi · University of Maryland, College Park3 papers (2020–2023)Zhiwei Ding · National University of Singapore3 papers (2020–2021)Gang Chen · Xi'an Railway Survey and Design Institute3 papers (2017–2022)Quynh T. Thanh Nguyen · Massachusetts Institute of Technology3 papers (2020–2023)Tongtong Liu · IIT@MIT3 papers (2021–2023)Ricardo Pablo‐Pedro · Massachusetts Institute of Technology3 papers (2020–2021)Tom Hogan · University of California, Santa Barbara2 papers (2020–2023)Anuj Apte · University of Chicago2 papers (2020–2021)G. D. Mahan · Massachusetts Institute of Technology2 papers (2017–2017)Qichen Song · Massachusetts Institute of Technology2 papers (2022–2024)David A. Muller · Cornell University2 papers (2015–2018)
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