Toshie Yaguchi | Searcharxiv

arXiv2024

Denoising Low-dose Images Using Deep Learning of Time Series Images

Digital image devices have been widely applied in many fields, including scientific imaging, recognition of individuals, and remote sensing. As the application of these imaging technologies to autonomous driving and measurement, image noise generated when observation cannot be performed with a sufficient dose has become a major problem. Machine learning denoise technology is expected to be the solver of this problem, but there are the following problems. Here we report, artifacts generated by machine learning denoise in ultra-low dose observation using an in-situ observation video of an electron microscope as an example. And as a method to solve this problem, we propose a method to decompose a time series image into a 2D image of the spatial axis and time to perform machine learning denoise. Our method opens new avenues accurate and stable reconstruction of continuous high-resolution images from low-dose imaging in science, industry, and life.

cs.CV↗

arXiv2021

Observing and modeling the sequential pairwise reactions that drive solid-state ceramic synthesis

Solid-state synthesis from powder precursors is the primary processing route to advanced multicomponent ceramic materials. Designing ceramic synthesis routes is usually a laborious, trial-and-error process, as heterogeneous mixtures of powder precursors often evolve through a complicated series of reaction intermediates. Here, we show that phase evolution from multiple precursors can be modeled as a sequence of pairwise interfacial reactions, with thermodynamic driving forces that can be efficiently calculated using ab initio methods. Using the synthesis of the classic high-temperature superconductor YBa$_2$Cu$_3$O$_{6+x}$ (YBCO) as a representative system, we rationalize how replacing the common BaCO$_3$ precursor with BaO$_2$ redirects phase evolution through a kinetically-facile pathway. Our model is validated from in situ X-ray diffraction and in situ microscopy observations, which show rapid YBCO formation from BaO$_2$ in only 30 minutes. By combining thermodynamic modeling with in situ characterization, we introduce a new computable framework to interpret and ultimately design synthesis pathways to complex ceramic materials.

cond-mat.mtrl-sci↗