{"@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": ["006:55"], "contactPoint": {"fn": "Thomas Cleveland", "hasEmail": "mailto:thomas.cleveland@nist.gov"}, "description": "Lipid nanoparticles (LNPs) were prepared as described (https://doi.org/10.1038/s42003-021-02441-2) using the lipids DLin-KC2-DMA, DSPC, cholesterol, and PEG-DMG2000 at mol ratios of 50:10:38.5:1.5. RNA was not included and LNPs were ejected into pH 4 and pH 7.4 buffer after microfluidic assembly. To prepare samples for imaging, 3 \u03bcL of LNP formulation was applied to holey carbon grids (Quantifoil, R3.5/1, 200 mesh copper). Grids were then incubated for 30 s at 298 K and 100% humidity before blotting and plunge-freezing into liquid ethane using a Vitrobot Mark IV (Thermo Fisher Scientific). Grids were imaged at 200 kV using a Talos Arctica system equipped with a Falcon 3EC detector (Thermo Fisher Scientific). A nominal magnification of 45,000x was used, corresponding to images with a pixel count of 4096x4096 and a calibrated pixel spacing of 0.223 nm. Micrographs were collected as dose-fractionated \"movies\" at nominal defocus values between -1 and -3 \u03bcm, with 10 s total exposures consisting of 66 frames with a total electron dose of 12,000 electrons per square nanometer. Movies were motion-corrected using MotionCor2 (https://doi.org/10.1038/nmeth.4193), resulting in flattened micrographs suitable for downstream particle segmentation. Images were manually segmented into particle and non-particle regions. Segmentation masks and their corresponding images are deposited in this data set.", "distribution": [{"downloadURL": "https://data.nist.gov/od/ds/ark:/88434/mds2-4063/LNPs_low_pH_v1.0.zip", "mediaType": "application/zip"}, {"downloadURL": "https://data.nist.gov/od/ds/ark:/88434/mds2-4063/LNPs_low_pH_v1.0.zip.sha256", "mediaType": "text/plain"}, {"downloadURL": "https://data.nist.gov/od/ds/ark:/88434/mds2-4063/LNPs_neutralized_v1.0.zip", "mediaType": "application/zip"}, {"downloadURL": "https://data.nist.gov/od/ds/ark:/88434/mds2-4063/LNPs_neutralized_v1.0.zip.sha256", "mediaType": "text/plain"}, {"downloadURL": "https://data.nist.gov/od/ds/ark:/88434/mds2-4063/readme_v1.0.txt", "mediaType": "text/plain"}, {"downloadURL": "https://data.nist.gov/od/ds/ark:/88434/mds2-4063/readme_v1.0.txt.sha256", "mediaType": "text/plain"}], "identifier": "ark:/88434/mds2-4063", "issued": "2026-03-30", "keyword": ["AI", "CTF", "Contrast transfer function", "Cryo-EM", "Drug delivery", "KC2", "LNP", "Lipid", "ML", "TEM", "augmentation", "electron microscopy", "machine learning", "nanoparticle", "segmentation"], "language": ["en"], "license": "https://www.nist.gov/open/license", "modified": "2026-02-23 00:00:00", "programCode": ["006:045"], "publisher": {"@type": "org:Organization", "name": "National Institute of Standards and Technology"}, "theme": ["Bioscience:Biomaterials", "Information Technology:Data and informatics", "Manufacturing:Biomanufacturing", "Nanotechnology:Nanobiotechnology"], "title": "A CTF-Based Data Augmentation Method for the Segmentation of Lipid Nanoparticles in Cryo-EM"}