Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Andrejevic, Nina"'
Autor:
Andrejevic, Nina, Zhou, Tao, Zhang, Qingteng, Narayanan, Suresh, Cherukara, Mathew J., Chan, Maria K. Y.
Publikováno v:
npj Comput Mater 10, 225 (2024)
Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex dynamics is
Externí odkaz:
http://arxiv.org/abs/2311.14196
Autor:
Andrejevic, Nina
Neutron and photon scattering and spectroscopy represent two fundamental categories of characterization techniques used to interrogate materials’ structural and dynamical properties at atomic to mesoscopic length scales. As advances at scientific u
Externí odkaz:
https://hdl.handle.net/1721.1/143296
Autor:
Okabe, Ryotaro, Chotrattanapituk, Abhijatmedhi, Boonkird, Artittaya, Andrejevic, Nina, Fu, Xiang, Jaakkola, Tommi S., Song, Qichen, Nguyen, Thanh, Drucker, Nathan, Mu, Sai, Liao, Bolin, Cheng, Yongqiang, Li, Mingda
The structure-property relationship plays a central role in materials science. Understanding the structure-property relationship in solid-state materials is crucial for structure design with optimized properties. The past few years witnessed remarkab
Externí odkaz:
http://arxiv.org/abs/2301.02197
Autor:
Chen, Zhantao, Shen, Xiaozhe, Andrejevic, Nina, Liu, Tongtong, Luo, Duan, Nguyen, Thanh, Drucker, Nathan C., Kozina, Michael E., Song, Qichen, Hua, Chengyun, Chen, Gang, Wang, Xijie, Kong, Jing, Li, Mingda
One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate mode-based transport information. Although recent advances in computation lead to mode-based information, it is hindered by unknown defects
Externí odkaz:
http://arxiv.org/abs/2202.06199
Autor:
Andrejevic, Nina, Chen, Zhantao, Nguyen, Thanh, Fan, Leon, Heiberger, Henry, Zhou, Ling-Jie, Zhao, Yi-Fan, Chang, Cui-Zu, Grutter, Alexander, Li, Mingda
Polarized neutron reflectometry is a powerful technique to interrogate the structures of multilayered magnetic materials with depth sensitivity and nanometer resolution. However, reflectometry profiles often inhabit a complicated objective function l
Externí odkaz:
http://arxiv.org/abs/2109.08005
Autor:
Drucker, Nathan C., Nguyen, Thanh, Han, Fei, Luo, Xi, Andrejevic, Nina, Zhu, Ziming, Bednik, Grigory, Nguyen, Quynh T., Chen, Zhantao, Nguyen, Linh K., Williams, Travis J., Stone, Matthew B., Kolesnikov, Alexander I., Chi, Songxue, Fernandez-Baca, Jaime, Hogan, Tom, Alatas, Ahmet, Puretzky, Alexander A., Geohegan, David B., Huang, Shengxi, Yu, Yue, Li, Mingda
The interplay between strong electron correlation and band topology is at the forefront of condensed matter research. As a direct consequence of correlation, magnetism enriches topological phases and also has promising functional applications. Howeve
Externí odkaz:
http://arxiv.org/abs/2103.08489
Autor:
Chen, Zhantao, Andrejevic, Nina, Drucker, Nathan, Nguyen, Thanh, Xian, R Patrick, Smidt, Tess, Wang, Yao, Ernstorfer, Ralph, Tennant, Alan, Chan, Maria, Li, Mingda
Publikováno v:
Chem. Phys. Rev. 2, 031301 (2021)
Neutron and X-ray scattering represent two state-of-the-art materials characterization techniques that measure materials' structural and dynamical properties with high precision. These techniques play critical roles in understanding a wide variety of
Externí odkaz:
http://arxiv.org/abs/2102.03024
Autor:
Nguyen, Thanh, Tsurimaki, Yoichiro, Pablo-Pedro, Ricardo, Bednik, Grigory, Liu, Tongtong, Apte, Anuj, Andrejevic, Nina, Li, Mingda
Publikováno v:
New J. Phys. 24, 013016 (2022)
Topological nodal semimetals are known to host a variety of fascinating electronic properties due to the topological protection of the band-touching nodes. Neutron scattering, despite its power in probing elementary excitations, has not been routinel
Externí odkaz:
http://arxiv.org/abs/2101.04046
Autor:
Chen, Zhantao, Andrejevic, Nina, Smidt, Tess, Ding, Zhiwei, Chi, Yen-Ting, Nguyen, Quynh T., Alatas, Ahmet, Kong, Jing, Li, Mingda
Publikováno v:
Advanced Science 202004214 (2021)
Machine learning has demonstrated great power in materials design, discovery, and property prediction. However, despite the success of machine learning in predicting discrete properties, challenges remain for continuous property prediction. The chall
Externí odkaz:
http://arxiv.org/abs/2009.05163