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1 August 2021 Deep learning enhanced digital holography for characterization of nanoparticles and soft matter
Daniel Midtvedt
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Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 1180410 (2021) https://doi.org/10.1117/12.2593718
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States
Abstract
Characterization of nanoparticles in their native environment plays a central role in a wide range of fields, from medical diagnostics and nanoparticle-enhanced drug delivery to nanosafety and environmental nanopollution assessment. I will present a label-free method to quantify size and refractive index of individual nanoparticles using two orders of magnitude shorter trajectories than required by standard methods, and without prior knowledge about the physicochemical properties of the medium. This is achieved through a weighted average convolutional neural network which analyzes holographic scattering images of single particles. I will demonstrate how deep learning enhanced holography opens up completely new possibilities to temporally characterize particle interactions and particle properties in complex environments.
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Daniel Midtvedt "Deep learning enhanced digital holography for characterization of nanoparticles and soft matter", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 1180410 (1 August 2021); https://doi.org/10.1117/12.2593718
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KEYWORDS
Nanoparticles
Particles
Digital holography
Refractive index
Holography
Diffusion
Holograms
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