Classification of diverse plastic samples by LIBS and Raman data fusion

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F24%3APU151298" target="_blank" >RIV/00216305:26210/24:PU151298 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0142941824000916" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0142941824000916</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.polymertesting.2024.108414" target="_blank" >10.1016/j.polymertesting.2024.108414</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of diverse plastic samples by LIBS and Raman data fusion

Popis výsledku v původním jazyce

The plastic production and usage in the world is steadily increasing. This leads to increased amounts of plastic waste. Most of the waste could be potentially recycled, but only 14 % of plastic waste is recycled. In order to increase the share of recycling in plastic waste management, the recycling process should be completely automated. The problematic part of sorting is being solved by either manual (labor-intensive) or spectroscopy-based (still in development) methods. In this work, we propose the data fusion of Laser-Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy as a fast, robust, and reliable way to sort/classify any potential polymer material. The sample set of this work consists of several types of polymers in clear, colored, and even mixture versions. So far, no LIBS/Raman classification works involved all these categories in one experiment. Additionally, the low and medium level of data fusion is discussed, and the performance is compared. By using LIBS and Raman data fusion method and both linear and nonlinear chemometric techniques, increased accuracy reaching more than 98 % in the classification of investigated plastic samples was achieved, which was a significant improvement when compared with singular methods classification accuracy.

Název v anglickém jazyce

Classification of diverse plastic samples by LIBS and Raman data fusion

Popis výsledku anglicky

The plastic production and usage in the world is steadily increasing. This leads to increased amounts of plastic waste. Most of the waste could be potentially recycled, but only 14 % of plastic waste is recycled. In order to increase the share of recycling in plastic waste management, the recycling process should be completely automated. The problematic part of sorting is being solved by either manual (labor-intensive) or spectroscopy-based (still in development) methods. In this work, we propose the data fusion of Laser-Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy as a fast, robust, and reliable way to sort/classify any potential polymer material. The sample set of this work consists of several types of polymers in clear, colored, and even mixture versions. So far, no LIBS/Raman classification works involved all these categories in one experiment. Additionally, the low and medium level of data fusion is discussed, and the performance is compared. By using LIBS and Raman data fusion method and both linear and nonlinear chemometric techniques, increased accuracy reaching more than 98 % in the classification of investigated plastic samples was achieved, which was a significant improvement when compared with singular methods classification accuracy.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10406 - Analytical chemistry

Projekt

<a href="/cs/project/FW06010042" target="_blank" >FW06010042: Výzkum a vývoj pokročilého interakčního vakuového systému pro laserovou spektroskopii</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

POLYMER TESTING

ISSN

0142-9418

e-ISSN

1873-2348

Svazek periodika

134

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

17

Strana od-do

„“-„“

Kód UT WoS článku

001231301700002

EID výsledku v databázi Scopus

2-s2.0-85190336166