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Fang C, Sobhani Z, Zhang X, Gibson CT, Tang Y, Naidu R. Identification and visualisation of microplastics/ nanoplastics by Raman imaging (ii): Smaller than the diffraction limit of laser? Water Res 2020; 183:116046. [PMID: 32629180 DOI: 10.1016/j.watres.2020.116046] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 06/05/2020] [Accepted: 06/11/2020] [Indexed: 06/11/2023]
Abstract
We recently reported (Sobhani et al., 2020) that when a confocal Raman microscope imaged a nanoplastic with the diameter of 100 nm, the imaging lateral size was 300-400 nm, due to the diffraction limit of the laser spot. In this study, we examine the lateral intensity distribution of the Raman signal emitted by nanoplastics (diameters ranging ∼30-600 nm) within the excitation laser spot. We find that the Raman emission intensity, similar to the excitation power density distributed within a laser spot, also follows a lateral Gaussian distribution. To image and visualise individual nanoplastics, we (i) decrease the mapping pixel size, in a hope to generate an image with high-resolution and simultaneously to pick up items from the "blind point". We can then either (ii) offset the colour to intentionally image only the high-intensity portion of the Raman signal (emitted from the centre of the laser spot), to localise the exact position of the nanoplastic; or (iii) categorise the imaged nanoplastics to different groups via their Raman intensity, to simultaneously and separately visualise large nanoplastics/strong Raman signals, medium nanoplastics and small nanoplastics, in an effort to avoid the shielding and overlooking of weak signals. We (iv) also cross-check multi-images simultaneously mapped at two or three characteristic peaks via either a logic-OR or a logic-AND algorithm. Thus the imaging uncertainty can be significantly reduced from a statistical point of view.
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Affiliation(s)
- Cheng Fang
- Global Centre for Environmental Remediation (GCER), University of Newcastle, Callaghan, NSW, 2308, Australia; Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), University of Newcastle, Callaghan, NSW, 2308, Australia.
| | - Zahra Sobhani
- Global Centre for Environmental Remediation (GCER), University of Newcastle, Callaghan, NSW, 2308, Australia
| | - Xian Zhang
- Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Christopher T Gibson
- Flinders Institute for NanoScale Science and Technology, College of Science and Engineering, Flinders University, South Australia, 5042, Australia; Flinders Microscopy and Microanalysis, College of Science and Engineering, Flinders University, Bedford Park, 5042, Australia
| | - Youhong Tang
- Flinders Institute for NanoScale Science and Technology, College of Science and Engineering, Flinders University, South Australia, 5042, Australia
| | - Ravi Naidu
- Global Centre for Environmental Remediation (GCER), University of Newcastle, Callaghan, NSW, 2308, Australia; Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), University of Newcastle, Callaghan, NSW, 2308, Australia
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