Zobrazeno 1 - 10
of 5 052
pro vyhledávání: '"A. Klie"'
Autor:
Gemperline, Patrick T., Thind, Arashdeep S., Tang, Chunli, Sterbinsky, George E., Kiefer, Boris, Jin, Wencan, Klie, Robert F., Comes, Ryan B.
Perovskite oxides hetero-structures are host to a large number of interesting phenomena such as ferroelectricity and 2D-superconductivity. Ferroelectric perovskite oxides have been of significant interest due to their possible use in MOSFETs and FRAM
Externí odkaz:
http://arxiv.org/abs/2409.13066
Autor:
Wong, Joeson, Onizhuk, Mykyta, Nagura, Jonah, Thind, Arashdeep S., Bindra, Jasleen K., Wicker, Christina, Grant, Gregory D., Zhang, Yuxuan, Niklas, Jens, Poluektov, Oleg G., Klie, Robert F., Zhang, Jiefei, Galli, Giulia, Heremans, F. Joseph, Awschalom, David D., Alivisatos, A. Paul
We demonstrate nearly a microsecond of spin coherence in Er3+ ions doped in cerium dioxide nanocrystal hosts, despite a large gyromagnetic ratio and nanometric proximity of the spin defect to the nanocrystal surface. The long spin coherence is enable
Externí odkaz:
http://arxiv.org/abs/2406.07762
Annotated datasets are an essential ingredient to train, evaluate, compare and productionalize supervised machine learning models. It is therefore imperative that annotations are of high quality. For their creation, good quality management and thereb
Externí odkaz:
http://arxiv.org/abs/2405.11919
Autor:
Chen, Xinglong, Zhang, Junjie, Thind, A. S., Sharma, S., LaBollita, H., Peterson, G., Zheng, H., Phelan, D., Botana, A. S., Klie, R. F., Mitchell, J. F.
We report the discovery of a novel form of Ruddlesden-Popper (RP) oxide, which stands as the first example of long-range, coherent polymorphism in this class of inorganic solids. Rather than the well-known, uniform stacking of perovskite blocks ubiqu
Externí odkaz:
http://arxiv.org/abs/2312.06081
Data quality is crucial for training accurate, unbiased, and trustworthy machine learning models as well as for their correct evaluation. Recent works, however, have shown that even popular datasets used to train and evaluate state-of-the-art models
Externí odkaz:
http://arxiv.org/abs/2307.08153
Autor:
Zhou, Chenkun, Wang, Di, Lagunas, Francisco, Atterberry, Benjamin, Lei, Ming, Hu, Huicheng, Zhou, Zirui, Filatov, Alexander S., Jiang, De-en, Rossini, Aaron J., Klie, Robert F., Talapin, Dmitri V.
Two-dimensional (2D) transition-metal carbides and nitrides (MXenes) show impressive performance in applications, such as supercapacitors, batteries, electromagnetic interference shielding, or electrocatalysis. These materials combine the electronic
Externí odkaz:
http://arxiv.org/abs/2305.17566
Autor:
Klie, Jan-Christoph, Lee, Ji-Ung, Stowe, Kevin, Şahin, Gözde Gül, Moosavi, Nafise Sadat, Bates, Luke, Petrak, Dominic, de Castilho, Richard Eckart, Gurevych, Iryna
Many Natural Language Processing (NLP) systems use annotated corpora for training and evaluation. However, labeled data is often costly to obtain and scaling annotation projects is difficult, which is why annotation tasks are often outsourced to paid
Externí odkaz:
http://arxiv.org/abs/2304.12836
Autor:
Wang, Di, Zhou, Chenkun, Filatov, Alexander S., Cho, Wooje, Lagunas, Francisco, Wang, Mingzhan, Vaikuntanathan, Suriyanarayanan, Liu, Chong, Klie, Rober F., Talapin, Dmitri V.
Two-dimensional (2D) transition metal carbides and nitrides (MXenes) are a large family of materials actively studied for various applications, especially in the field of energy storage. To date, MXenes are commonly synthesized by etching the layered
Externí odkaz:
http://arxiv.org/abs/2212.08922
Publikováno v:
Computational Linguistics, Vol 50, Iss 3 (2024)
Externí odkaz:
https://doaj.org/article/9c98640f81324a218857826b18cb375e
Annotated data is an essential ingredient in natural language processing for training and evaluating machine learning models. It is therefore very desirable for the annotations to be of high quality. Recent work, however, has shown that several popul
Externí odkaz:
http://arxiv.org/abs/2206.02280