Joshua L. Vincent

TL;DR: In this paper, the dynamic characteristics of a Pt/CeO2 system at the atomic level for the water gas shift (WGS) reaction were investigated and the synergistic effects of metal-support bonding at the perimeter region were revealed.

TL;DR: In this article, electron microscopy was employed to visualize the structural dynamics occurring at and near Pt/CeO2 interfaces during CO oxidation and showed that the catalytic turnover frequency correlates with fluxional behavior that destabilizes the supported Pt particle, marks an enhanced rate of oxygen vacancy creation and annihilation, and leads to increased strain and reduction in the CeO2 support surface.

TL;DR: An Unsupervised Deep Video Denoiser (UDVD1), a CNN architecture designed to be trained exclusively with noisy data, is proposed and the performance of UDVD is comparable to the supervised state-of-the-art, even when trained only on a single short noisy video.

TL;DR: A simulation-based denoising (SBD) framework, in which CNNs are trained on simulated images, which outperforms existing techniques by a wide margin on a simulated benchmark dataset, as well as on real data.

TL;DR: An approach based on the log-likelihood ratio test that provides a quantitative measure of the agreement between the noisy observation and the atomic-level structure in the network-denoised image is developed.