Weighing nanoparticles in solution at the attogram scale
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Olcum-2014-Weighing nanoparticl.pdf
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1.17 MB
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Checksum (MD5)
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Author(s)
Olcum, Selim
Cermak, Nathan
Wasserman, Steven Charles
Christine, Kathleen
Atsumi, Hiroshi
Payer, Kristofor Robert
Shen, Wenjiang
Lee, Jungchul
Belcher, Angela M.
Bhatia, Sangeeta N.
Date Issued
January 2014
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Olcum, S., N. Cermak, S. C. Wasserman, K. S. Christine, H. Atsumi, K. R. Payer, W. Shen, et al. “Weighing Nanoparticles in Solution at the Attogram Scale.” Proceedings of the National Academy of Sciences 111, no. 4 (January 28, 2014): 1310–1315.
Version
Final published version
Abstract
Physical characterization of nanoparticles is required for a wide range of applications. Nanomechanical resonators can quantify the mass of individual particles with detection limits down to a single atom in vacuum. However, applications are limited because performance is severely degraded in solution. Suspended micro- and nanochannel resonators have opened up the possibility of achieving vacuum-level precision for samples in the aqueous environment and a noise equivalent mass resolution of 27 attograms in 1-kHz bandwidth was previously achieved by Lee et al. [(2010) Nano Lett 10(7):2537–2542]. Here, we report on a series of advancements that have improved the resolution by more than 30-fold, to 0.85 attograms in the same bandwidth, approaching the thermomechanical noise limit and enabling precise quantification of particles down to 10 nm with a throughput of more than 18,000 particles per hour. We demonstrate the potential of this capability by comparing the mass distributions of exosomes produced by different cell types and by characterizing the yield of self-assembled DNA nanoparticle structures.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Microsystems Technology Laboratories
Koch Institute for Integrative Cancer Research at MIT
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/pnas.1318602111
