PMID- 29525562
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20180424
LR  - 20180424
IS  - 1873-3557 (Electronic)
IS  - 1386-1425 (Linking)
VI  - 198
DP  - 2018 Jun 5
TI  - A hierarchical classification approach for recognition of low-density (LDPE) and 
      high-density polyethylene (HDPE) in mixed plastic waste based on short-wave 
      infrared (SWIR) hyperspectral imaging.
PG  - 115-122
LID - S1386-1425(18)30197-5 [pii]
LID - 10.1016/j.saa.2018.03.006 [doi]
AB  - The aim of this work was to recognize different polymer flakes from mixed plastic 
      waste through an innovative hierarchical classification strategy based on 
      hyperspectral imaging, with particular reference to low density polyethylene 
      (LDPE) and high-density polyethylene (HDPE). A plastic waste composition 
      assessment, including also LDPE and HDPE identification, may help to define 
      optimal recycling strategies for product quality control. Correct handling of 
      plastic waste is essential for its further "sustainable" recovery, maximizing the 
      sorting performance in particular for plastics with similar characteristics as 
      LDPE and HDPE. Five different plastic waste samples were chosen for the 
      investigation: polypropylene (PP), LDPE, HDPE, polystyrene (PS) and polyvinyl 
      chloride (PVC). A calibration dataset was realized utilizing the corresponding 
      virgin polymers. Hyperspectral imaging in the short-wave infrared range 
      (1000-2500nm) was thus applied to evaluate the different plastic spectral 
      attributes finalized to perform their recognition/classification. After exploring 
      polymer spectral differences by principal component analysis (PCA), a 
      hierarchical partial least squares discriminant analysis (PLS-DA) model was built 
      allowing the five different polymers to be recognized. The proposed methodology, 
      based on hierarchical classification, is very powerful and fast, allowing to 
      recognize the five different polymers in a single step.
CI  - Copyright (c) 2018 Elsevier B.V. All rights reserved.
FAU - Bonifazi, Giuseppe
AU  - Bonifazi G
AD  - Department of Chemical Engineering Materials & Environment (DICMA), Sapienza 
      University of Rome, Rome, Italy.
FAU - Capobianco, Giuseppe
AU  - Capobianco G
AD  - Department of Chemical Engineering Materials & Environment (DICMA), Sapienza 
      University of Rome, Rome, Italy.
FAU - Serranti, Silvia
AU  - Serranti S
AD  - Department of Chemical Engineering Materials & Environment (DICMA), Sapienza 
      University of Rome, Rome, Italy. Electronic address: silvia.serranti@uniroma1.it.
LA  - eng
PT  - Journal Article
DEP - 20180303
PL  - England
TA  - Spectrochim Acta A Mol Biomol Spectrosc
JT  - Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
JID - 9602533
OTO - NOTNLM
OT  - Hierarchical PLS-DA
OT  - High density polyethylene (HDPE)
OT  - Hyperspectral imaging
OT  - Low density polyethylene (LDPE)
OT  - Plastic waste
OT  - Polymers
OT  - Recycling
EDAT- 2018/03/12 06:00
MHDA- 2018/03/12 06:01
CRDT- 2018/03/12 06:00
PHST- 2017/09/08 00:00 [received]
PHST- 2018/02/18 00:00 [revised]
PHST- 2018/03/02 00:00 [accepted]
PHST- 2018/03/12 06:00 [pubmed]
PHST- 2018/03/12 06:01 [medline]
PHST- 2018/03/12 06:00 [entrez]
AID - S1386-1425(18)30197-5 [pii]
AID - 10.1016/j.saa.2018.03.006 [doi]
PST - ppublish
SO  - Spectrochim Acta A Mol Biomol Spectrosc. 2018 Jun 5;198:115-122. doi: 
      10.1016/j.saa.2018.03.006. Epub 2018 Mar 3.