Real-time 4D tracking of airborne virus-laden droplets and aerosols

Abstract

There is currently no real-time airborne virus tracking method, hindering the understanding of rapid virus changes and associated health impacts. Nano-digital in-line holographic microscopy (Nano-DIHM) is a lensless technology that can directly obtain the interference patterns of objects by recording the scattered light information originating from the objects. Here, we provide evidence for real-time physicochemical tracking of virus-laden droplets and aerosols in the air using desktop label-free Nano-DIHM. The virus interference patterns, as single and ensemble particles, were imaged by the Nano-DIHM with 32.5 ms resolution. The next-generation Stingray and Octopus software was used to automate object detection, characterization and classification from the recorded holograms. The detection system was demonstrated to detect active MS2 bacteriophages, inactivated SARS-CoV-2 and RNA fragments, and an MS2 mixture with metallic and organic compounds. This work demonstrates the feasibility of using Nano-DIHM to provide rapid virus detection to improve transmission management in real time.

Nanoplastics in Water: Artificial Intelligence-Assisted 4D Physicochemical Characterization and Rapid In Situ Detection

“…This observation can be explained by the formation of magnetite clusters in different sizes and structures, which agrees with the manual reconstruction observations (Figures S7). Such results also suggest the potential of AI-assisted nano-DIHM in investigating the physical processes and transformation mechanisms of diverse particles/clusters in the environment …”

“…Such results also suggest the potential of AI-assisted nano-DIHM in investigating the physical processes and transformation mechanisms of diverse particles/clusters in the environment. 35 …”

“…We implement an additional convolution–deconvolution route in the coding of the software to improve the resolution for detecting nanosized particles . The particle size measured from manual reconstructions is determined based on the full width at half-maximum of the peak from the intensity crosscut . Additional information and schematic illustration of the principle of DIHM are in Note S2 and Figure S1.…”

“… 31 The particle size measured from manual reconstructions is determined based on the full width at half-maximum of the peak from the intensity crosscut. 35 Additional information and schematic illustration of the principle of DIHM are in Note S2 and Figure S1 .…”

“…Such results also suggest the potential of AI-assisted nano-DIHM in investigating the physical processes and transformation mechanisms of diverse particles/clusters in the environment. 35 Nevertheless, it should be noted that the automation yields only particle size >1 μm mainly due to the tendency of the algorithm to overestimate the particle size. For instance, the size of studied PE and PS nanoplastics is between 100 and 800 nm, but the software measures ∼1.1−1.8 μm for most plastic particles.…”