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10.1021/acs.nanolett.0c04230 http://scihub22266oqcxt.onion/10.1021/acs.nanolett.0c04230 33283521!ä!33283521 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Nano+Lett 2021 ; 21 (1): 651-657 Nephropedia Template TP {{tp|p=33283521|t=2021. Three-Dimensional Analysis of Particle Distribution on Filter Layers inside N95 Respirators by Deep Learning |pdf=|usr=}}{{33283521}} gab.com Text Three-Dimensional Analysis of Particle Distribution on Filter Layers inside N95 Respirators by Deep Learning JO: Nano Lett http://www.kidney.de/pget.php?&tw=1&pmid=33283521 #FOAvip The global COVID-19 pandemic has changed many aspects of daily lives. Wearing personal protective equipment, especially respirators (face masks), has become common for both the public and medical professionals, proving to be effective in preventing spread of the virus. Nevertheless, a detailed understanding of respirator filtration-layer internal structures and their physical configurations is lacking. Here, we report three-dimensional (3D) internal analysis of N95 filtration layers via X-ray tomography. Using deep learning methods, we uncover how the distribution and diameters of fibers within these layers directly affect contaminant particle filtration. The average porosity of the filter layers is found to be 89.1%. Contaminants are more efficiently captured by denser fiber regions, with fibers <1.8 mum in diameter being particularly effective, presumably because of the stronger electric field gradient on smaller diameter fibers. This study provides critical information for further development of N95-type respirators that combine high efficiency with good breathability. Twit Text FOAVip Three-Dimensional Analysis of Particle Distribution on Filter Layers inside N95 Respirators by Deep Learning ????Nano Lett http://www.kidney.de/pget.php?&tw=1&pmid=33283521 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33283521 #FOAvip English Wikipedia <ref>{{Cite pmid|33283521}}</ref> Three-Dimensional Analysis of Particle Distribution on Filter Layers inside N95 Respirators by Deep Learning #MMPMID33283521 Lee HR; Liao L; Xiao W; Vailionis A; Ricco AJ; White R; Nishi Y; Chiu W; Chu S; Cui Y Nano Lett 2021[Jan]; 21 (1): 651-657 PMID33283521show ga The global COVID-19 pandemic has changed many aspects of daily lives. Wearing personal protective equipment, especially respirators (face masks), has become common for both the public and medical professionals, proving to be effective in preventing spread of the virus. Nevertheless, a detailed understanding of respirator filtration-layer internal structures and their physical configurations is lacking. Here, we report three-dimensional (3D) internal analysis of N95 filtration layers via X-ray tomography. Using deep learning methods, we uncover how the distribution and diameters of fibers within these layers directly affect contaminant particle filtration. The average porosity of the filter layers is found to be 89.1%. Contaminants are more efficiently captured by denser fiber regions, with fibers <1.8 mum in diameter being particularly effective, presumably because of the stronger electric field gradient on smaller diameter fibers. This study provides critical information for further development of N95-type respirators that combine high efficiency with good breathability. |*Pandemics/prevention & control[MESH] |Air Microbiology[MESH] |COVID-19/*prevention & control/transmission/virology[MESH] |Deep Learning[MESH] |Filtration/statistics & numerical data[MESH] |Humans[MESH] |Imaging, Three-Dimensional[MESH] |Microscopy, Electron, Scanning[MESH] |N95 Respirators/standards/statistics & numerical data/*virology[MESH] |Nanoparticles/ultrastructure[MESH] |Particle Size[MESH] |Polypropylenes[MESH] |Porosity[MESH] |SARS-CoV-2/*ultrastructure[MESH] |Textiles/virology[MESH]Three-Dimensional Analysis of Particle Distribution on Filter Layers i(epmc).pdf DeepDyve Pubget Overpricing