PtyRANNOSAUR: Ptychography with Robust Artificial Neural Networks Optimized for Subangstrom Accuracy and Ultrafast Reconstruction
- DOI
- 10.1021/acs.nanolett.6c03513
- Published
- 2026-10-22
- Container
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/acs.nanolett.6c03513,
title = {PtyRANNOSAUR:
Ptychography with Robust Artificial
Neural Networks Optimized for Subangstrom Accuracy and Ultrafast Reconstruction},
author = {Kieran Loehr and Rahim Raja and Xiaochuan Ding and Jeffrey Huang and Gillian Nolan and Sang hyun Bae and Bryan K. Clark and Pinshane Y. Huang},
year = {2026},
journal = {Nano Letters},
doi = {10.1021/acs.nanolett.6c03513},
url = {https://doi.org/10.1021/acs.nanolett.6c03513}
}RIS
TY - JOUR TI - PtyRANNOSAUR: Ptychography with Robust Artificial Neural Networks Optimized for Subangstrom Accuracy and Ultrafast Reconstruction AU - Kieran Loehr AU - Rahim Raja AU - Xiaochuan Ding AU - Jeffrey Huang AU - Gillian Nolan AU - Sang hyun Bae AU - Bryan K. Clark AU - Pinshane Y. Huang PY - 2026 JO - Nano Letters DO - 10.1021/acs.nanolett.6c03513 UR - https://doi.org/10.1021/acs.nanolett.6c03513 ER -
APA
Loehr, K., Raja, R., Ding, X., Huang, J., Nolan, G., Bae, S. H., Clark, B. K., & Huang, P. Y. (2026). PtyRANNOSAUR: Ptychography with Robust Artificial Neural Networks Optimized for Subangstrom Accuracy and Ultrafast Reconstruction. Nano Letters. https://doi.org/10.1021/acs.nanolett.6c03513
Source records
- crossref · retrieved 2026-11-09T23:13:13.962Z