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About OptimalSensing LLC

OptimalSensing is a research-focused company developing new algorithms and hardware that work in tandem to observe phenomena that are not observable with existing technology. The primary application area is currently (scanning) transmission electron microscopy (S/TEM).
Many of the most important processes in materials engineering and biology/medicine occur by the movement of atoms—such as the storing of charge in Li-ion batteries and drug interactions with cells to cure disease. Understanding and controlling the way that atoms move will lead to new technologies that address the major global challenges of energy, defense, and human health. The ability to see atoms as they move is a key enabler for understanding and control of materials and biological processes. Although aberration-corrected S/TEM can routinely acquire atomic resolution images, these images typically require a large radiation dose applied under extremely stable environmental conditions. Atomic resolution is currently a…

Latest Posts

A Sub-Sampled Approach to Extremely Low-Dose STEM

Bridging Zirconia Nodes within a Metal-Organic Framework via Catalytic Ni-Hydroxo Clusters to Form Heterobimetallic Nanowires

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

Variational Autoencoder for Deep Learning of Images, Labels and Captions

Implementing an accurate and rapid sparse sampling approach for low-dose atomic resolution STEM imaging

The Impact of Li Grain Size on Coulombic Efficiency in Li Batteries

Learning Weight Uncertainty With Stochastic Gradient MCMC for Shape Classification

A Deep Generative Deconvolutional Image Model

Applying compressive sensing to TEM video: a substantial frame rate increase on any camera

The potential for Bayesian compressive sensing to significantly reduce electron dose in high-resolution STEM images