PMID- 37893340
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20231031
IS  - 2072-666X (Print)
IS  - 2072-666X (Electronic)
IS  - 2072-666X (Linking)
VI  - 14
IP  - 10
DP  - 2023 Oct 5
TI  - A Novel Approach for Identifying Nanoplastics by Assessing Deformation Behavior 
      with Scanning Electron Microscopy.
LID - 10.3390/mi14101903 [doi]
LID - 1903
AB  - As plastic production continues to increase globally, plastic waste accumulates 
      and degrades into smaller plastic particles. Through chemical and biological 
      processes, nanoscale plastic particles (nanoplastics) are formed and are expected 
      to exist in quantities of several orders of magnitude greater than those found 
      for microplastics. Due to their small size and low mass, nanoplastics remain 
      challenging to detect in the environment using most standard analytical methods. 
      The goal of this research is to adapt existing tools to address the analytical 
      challenges posed by the identification of nanoplastics. Given the unique and 
      well-documented properties of anthropogenic plastics, we hypothesized that 
      nanoplastics could be differentiated by polymer type using spatiotemporal 
      deformation data collected through irradiation with scanning electron microscopy 
      (SEM). We selected polyvinyl chloride (PVC), polyethylene terephthalate (PET), 
      and high-density polyethylene (HDPE) to capture a range of thermodynamic 
      properties and molecular structures encompassed by commercially available 
      plastics. Pristine samples of each polymer type were chosen and individually 
      milled to generate micro and nanoscale particles for SEM analysis. To test the 
      hypothesis that polymers could be differentiated from other constituents in 
      complex samples, the polymers were compared against proxy materials common in 
      environmental media, i.e., algae, kaolinite clay, and nanocellulose. Samples for 
      SEM analysis were prepared uncoated to enable observation of polymer deformation 
      under set electron beam parameters. For each sample type, particles approximately 
      1 microm in diameter were chosen, and videos of particle deformation were recorded 
      and studied. Blinded samples were also prepared with mixtures of the 
      aforementioned materials to test the viability of this method for identifying 
      near-nanoscale plastic particles in environmental media. Based on the evidence 
      collected, deformation patterns between plastic particles and particles present 
      in common environmental media show significant differences. A computer vision 
      algorithm was also developed and tested against manual measurements to improve 
      the usefulness and efficiency of this method further.
FAU - Stine, Jared S
AU  - Stine JS
AUID- ORCID: 0000-0001-6179-5669
AD  - School of Chemical, Biological and Environmental Engineering, Oregon State 
      University, Corvallis, OR 97331, USA.
AD  - Department of Environmental and Molecular Toxicology, Oregon State University, 
      Corvallis, OR 97331, USA.
FAU - Aziere, Nicolas
AU  - Aziere N
AUID- ORCID: 0000-0003-0780-5349
AD  - School of Electrical Engineering and Computer Science, Oregon State University, 
      Corvallis, OR 97331, USA.
FAU - Harper, Bryan J
AU  - Harper BJ
AUID- ORCID: 0000-0003-1359-8446
AD  - Department of Environmental and Molecular Toxicology, Oregon State University, 
      Corvallis, OR 97331, USA.
FAU - Harper, Stacey L
AU  - Harper SL
AUID- ORCID: 0000-0001-7043-7097
AD  - School of Chemical, Biological and Environmental Engineering, Oregon State 
      University, Corvallis, OR 97331, USA.
AD  - Department of Environmental and Molecular Toxicology, Oregon State University, 
      Corvallis, OR 97331, USA.
LA  - eng
GR  - 1935018, 1935028/National Science Foundation/
PT  - Journal Article
DEP - 20231005
PL  - Switzerland
TA  - Micromachines (Basel)
JT  - Micromachines
JID - 101640903
PMC - PMC10609349
OTO - NOTNLM
OT  - SEM
OT  - detection
OT  - machine learning
OT  - microplastics
OT  - polymers
COIS- The authors declare no conflict of interest.
EDAT- 2023/10/28 11:43
MHDA- 2023/10/28 11:44
PMCR- 2023/10/05
CRDT- 2023/10/28 01:09
PHST- 2023/09/02 00:00 [received]
PHST- 2023/09/27 00:00 [revised]
PHST- 2023/10/04 00:00 [accepted]
PHST- 2023/10/28 11:44 [medline]
PHST- 2023/10/28 11:43 [pubmed]
PHST- 2023/10/28 01:09 [entrez]
PHST- 2023/10/05 00:00 [pmc-release]
AID - mi14101903 [pii]
AID - micromachines-14-01903 [pii]
AID - 10.3390/mi14101903 [doi]
PST - epublish
SO  - Micromachines (Basel). 2023 Oct 5;14(10):1903. doi: 10.3390/mi14101903.