Single-particle multi-element fingerprinting (spMEF) using inductively-coupled plasma time-of-flight mass spectrometry (ICP-TOFMS) to identify engineered nanoparticles against the elevated natural background in soils. Issue 2 (19th January 2017)
- Record Type:
- Journal Article
- Title:
- Single-particle multi-element fingerprinting (spMEF) using inductively-coupled plasma time-of-flight mass spectrometry (ICP-TOFMS) to identify engineered nanoparticles against the elevated natural background in soils. Issue 2 (19th January 2017)
- Main Title:
- Single-particle multi-element fingerprinting (spMEF) using inductively-coupled plasma time-of-flight mass spectrometry (ICP-TOFMS) to identify engineered nanoparticles against the elevated natural background in soils
- Authors:
- Praetorius, Antonia
Gundlach-Graham, Alexander
Goldberg, Eli
Fabienke, Willi
Navratilova, Jana
Gondikas, Andreas
Kaegi, Ralf
Günther, Detlef
Hofmann, Thilo
von der Kammer, Frank - Abstract:
- Abstract : This novel single-particle multi-element fingerprinting (spMEF) method makes it possible to discriminate engineered and natural nanoparticles in complex matrices. Abstract : The discrimination of engineered nanoparticles (ENPs) from the natural geogenic background is one of the preeminent challenges for assessing their potential implications. At low ENP concentrations, most conventional analytical techniques are not able to take advantage of inherent differences ( e.g. in terms of composition, isotopic signatures, element ratios, structure, shape or surface characteristics) between ENPs and naturally occurring nanoscale particles (NNPs) of similar composition. Here, we present a groundbreaking approach to overcome these limitations and enable the discrimination of man-made ENPs from NNPs through simultaneous detection of multiple elements on an individual particle level. This new analytical approach is accessible by an inductively-coupled plasma time-of-flight mass spectrometer (ICP-TOFMS) operated in single-particle mode. Machine learning is employed to classify ENPs and NNPs based on their unique elemental fingerprints and quantify their concentrations. We demonstrate the applicability of this single-particle multi-element fingerprinting (spMEF) method by distinguishing engineered cerium oxide nanoparticles (CeO2 ENPs) from natural Ce-containing nanoparticles (Ce-NNPs) in soils at environmentally relevant ENP concentrations, orders of magnitude below the naturalAbstract : This novel single-particle multi-element fingerprinting (spMEF) method makes it possible to discriminate engineered and natural nanoparticles in complex matrices. Abstract : The discrimination of engineered nanoparticles (ENPs) from the natural geogenic background is one of the preeminent challenges for assessing their potential implications. At low ENP concentrations, most conventional analytical techniques are not able to take advantage of inherent differences ( e.g. in terms of composition, isotopic signatures, element ratios, structure, shape or surface characteristics) between ENPs and naturally occurring nanoscale particles (NNPs) of similar composition. Here, we present a groundbreaking approach to overcome these limitations and enable the discrimination of man-made ENPs from NNPs through simultaneous detection of multiple elements on an individual particle level. This new analytical approach is accessible by an inductively-coupled plasma time-of-flight mass spectrometer (ICP-TOFMS) operated in single-particle mode. Machine learning is employed to classify ENPs and NNPs based on their unique elemental fingerprints and quantify their concentrations. We demonstrate the applicability of this single-particle multi-element fingerprinting (spMEF) method by distinguishing engineered cerium oxide nanoparticles (CeO2 ENPs) from natural Ce-containing nanoparticles (Ce-NNPs) in soils at environmentally relevant ENP concentrations, orders of magnitude below the natural background. … (more)
- Is Part Of:
- Environmental science. Volume 4:Issue 2(2017)
- Journal:
- Environmental science
- Issue:
- Volume 4:Issue 2(2017)
- Issue Display:
- Volume 4, Issue 2 (2017)
- Year:
- 2017
- Volume:
- 4
- Issue:
- 2
- Issue Sort Value:
- 2017-0004-0002-0000
- Page Start:
- 307
- Page End:
- 314
- Publication Date:
- 2017-01-19
- Subjects:
- Environmental sciences -- Periodicals
Nanotechnology -- Periodicals
620.505 - Journal URLs:
- http://pubs.rsc.org/en/journals/journalissues/en ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/c6en00455e ↗
- Languages:
- English
- ISSNs:
- 2051-8153
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3791.618000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 290.xml