For identification of plastic items from surface sampling, a subset of 38.4% (total: 1075) of all items from field LK and 100% (total: 314) of items from field HB were analysed with a with a Tensor 37 FTIR spectrometer (BrukerOptics GmbH) combined with a Platinum-ATR-unit (BrukerOptics GmbH). Each item was measured after 16 background scans by 16 sample scans (spectral resolution: 4 cm−1 in a wavenumber range of 4000–400 cm−1). Spectra identification was carried out with the internal OPUS 7.0 (BrukerOptics GmbH) database, showing average OPUS-HIT ratios of 619.3 (LK) and 601.9 (HB). For microplastics from soil samples, a subset of 35.4% (total: 99) particles was analysed with a µFTIR spectrometer (Lumos II, BrukerOptics GmbH) with 30 background and 30 sample scans (spectral resolution: 4 cm−1 in a wavenumber range of 4000–680 cm−1). µFTIR spectra were identified using spectra correlation via OpenSpecy59 (link), resulting in an average r2 of 0.84. Each plastic item or microplastic particle, regardless of the spectrometric analysis, was classified according to its visual surface characteristics (particle type, surface form and surface degradation)60 (link). Statistical operations were performed in Microsoft Excel 2021 (Microsoft), and R (R Core Team, 2020), using RStudio (Version 3.4.1; RStudio Inc.). Spatial data analysis and processing was performed in QGIS61 .
Lumos 2
Manufactured by Bruker
Sourced in United States
The LUMOS II is a Fourier Transform Infrared (FTIR) Microscope system designed for high-performance infrared spectroscopic imaging and analysis. The core function of the LUMOS II is to provide researchers and analysts with a powerful tool for non-destructive chemical characterization and visualization of microscopic samples.
Automatically generated - may contain errors
Lab products found in correlation
Evo ls10, by Zeiss (2 mentions)
Opus 7, by Bruker (1 mentions)
Tensor 37 ftir spectrometer, by Bruker (1 mentions)
Platinum atr unit, by Bruker (1 mentions)
Hyperion 3000, by Bruker (1 mentions)
K alpha, by Thermo Fisher Scientific (1 mentions)
Gemini 500, by Zeiss (1 mentions)
Sodium hydroxide (naoh), by Thermo Fisher Scientific (1 mentions)
Ethanol, by Thermo Fisher Scientific (1 mentions)
Methanol, by Thermo Fisher Scientific (1 mentions)
Aniline, by Thermo Fisher Scientific (1 mentions)
Su8010, by Hitachi (1 mentions)
Isopropyl alcohol, by Thermo Fisher Scientific (1 mentions)
Nicl2, by Thermo Fisher Scientific (1 mentions)
Cucl2 2h2o, by Thermo Fisher Scientific (1 mentions)
Jsm 6480lv, by JEOL (1 mentions)
D8 advance eco, by Bruker (1 mentions)
8 protocols using lumos 2
1
Identification of Plastic Items and Microplastics
2
Spectroscopic Analysis of Titanium Alloys
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Kazarian and Chan in their work [26 (link)] point out that FT-IR is one of the best methods for analyzing materials for medical applications, including biomaterials and pharmaceuticals. FT-IR spectroscopy is used for the identification and quantitative analysis of chemical compounds or their mixtures, and the determination of physicochemical properties, e.g., the determination of molecular structure and its transformation by reaction, reaction kinetics, or intramolecular dynamics. Samples can be in any state of aggregation.
Titanium alloy surfaces were scanned with an infrared spectrometer (LUMOS II, Bruker Optics, Ettlingen, Germany) under reflection mode with an analyzed surface of 900 μm × 900 μm, with step 100 μm. The spectral resolution is 4 cm−1, and 60 scans are acquired on each measurement point. The spectrometer is equipped with a TE-MCT detector and gold mirror as a reference. External reflection was used as the acquisition mode.
Titanium alloy surfaces were scanned with an infrared spectrometer (LUMOS II, Bruker Optics, Ettlingen, Germany) under reflection mode with an analyzed surface of 900 μm × 900 μm, with step 100 μm. The spectral resolution is 4 cm−1, and 60 scans are acquired on each measurement point. The spectrometer is equipped with a TE-MCT detector and gold mirror as a reference. External reflection was used as the acquisition mode.
3
Distinguishing Particles Using μFTIR
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μFTIR analysis was performed using FTIR spectroscopy on a microscope (LUMOS II, Bruker Optics, MA, USA) equipped with a 32 × 32 pixel focal plane array (FPA) detector. IR images were acquired in transmission mode at a spectral resolution of 12 cm−1 within a spectral range from 3800 to 900 cm−1, utilizing one scan time. μFTIR was specifically employed to distinguish particles that might be erroneously identified as PE using Raman spectroscopy.
4
FTIR Hyperspectral Image Analysis
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Figure 1 depicts close-up views of a collection of
eight samples from different matrices in order to show the broad applicability
and robustness of the RDF model for various environmental application
scenarios.Figure 1 a–c represent well-studied data sets from the literature.
See for example Hufnagl and Lohninger39 (link) and Wander et al.40 (link) for comparison.Figure 1 h represents a sea
salt sample which was measured using a Bruker Lumos II. All other
data sets have been measured using a Bruker Hyperion 3000. Complete
views of the filters are available inFigures S3–S10 .
Without applying any filter substrate detection, the classification
of an image of 1000 × 1000 pixels requires about 20–25
min assuming 20 polymer classes (see Hufnagl et al.9 (link) for experimental details and used hardware). This computation
time can be reduced to less than 10 min by using the above-mentioned
statistical detection technique to exclude pixels from the background
for the following reasons. As can be seen inFigures S3– S10 , the samples’ particles will cover only
a small circular portion of the filter surface. As the measured FTIR
image is rectangular, the particles therefore usually cover less than
50% of all the pixels. By excluding the pixels which can be attributed
to the background, a significant reduction of computation time can
thus be achieved.
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eight samples from different matrices in order to show the broad applicability
and robustness of the RDF model for various environmental application
scenarios.
See for example Hufnagl and Lohninger39 (link) and Wander et al.40 (link) for comparison.
salt sample which was measured using a Bruker Lumos II. All other
data sets have been measured using a Bruker Hyperion 3000. Complete
views of the filters are available in
Without applying any filter substrate detection, the classification
of an image of 1000 × 1000 pixels requires about 20–25
min assuming 20 polymer classes (see Hufnagl et al.9 (link) for experimental details and used hardware). This computation
time can be reduced to less than 10 min by using the above-mentioned
statistical detection technique to exclude pixels from the background
for the following reasons. As can be seen in
a small circular portion of the filter surface. As the measured FTIR
image is rectangular, the particles therefore usually cover less than
50% of all the pixels. By excluding the pixels which can be attributed
to the background, a significant reduction of computation time can
thus be achieved.
5
Comprehensive Surface Characterization of Nanostructured Materials
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The chemical composition
and morphology of the obtained surfaces were characterized using scanning
electron microscopy (SEM, Zeiss EVO LS10), FE-SEM (field emission
scanning electron microscopy) (Zeiss Gemini 500), and energy-dispersive
spectroscopy (EDS, Bruker). Before imaging, a thin layer of gold was
sputter-coated onto the samples. ImageJ software was used to determine
the size distribution of the nanoparticles on surfaces from SEM images.
The surface chemical composition of the nanostructures was analyzed
using X-ray photoelectron spectroscopy (XPS, K-alpha, Thermo Scientific)
with a monochromatic Al Kα X-ray source (1486.7 eV). Thin-film
XRD analysis was performed with a diffraction meter (Panalytical Empyrean)
operating at 40 kV and 30 mA using a Cu Kα radiation source.
Finally, an FTIR microspectrometer (LUMOS II, Bruker) was used to
analyze the IR spectrum of bacteria on the surfaces.
and morphology of the obtained surfaces were characterized using scanning
electron microscopy (SEM, Zeiss EVO LS10), FE-SEM (field emission
scanning electron microscopy) (Zeiss Gemini 500), and energy-dispersive
spectroscopy (EDS, Bruker). Before imaging, a thin layer of gold was
sputter-coated onto the samples. ImageJ software was used to determine
the size distribution of the nanoparticles on surfaces from SEM images.
The surface chemical composition of the nanostructures was analyzed
using X-ray photoelectron spectroscopy (XPS, K-alpha, Thermo Scientific)
with a monochromatic Al Kα X-ray source (1486.7 eV). Thin-film
XRD analysis was performed with a diffraction meter (Panalytical Empyrean)
operating at 40 kV and 30 mA using a Cu Kα radiation source.
Finally, an FTIR microspectrometer (LUMOS II, Bruker) was used to
analyze the IR spectrum of bacteria on the surfaces.
6
Synthesis and Characterization of Graphene-Aniline Composites
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Aniline (ANI) was obtained from ACROS Organics™ and was purified before use. Analytical-grade graphene (Production code: ANT-GNPs-160101, bulk density of 0.015 g mL−1, diameter of 10–20 μm, thickness <5 nm, C content ≥99%) were purchased from Applied Nano Technology Joint Stock Company (ANTECH, Vietnam). CuCl2·2H2O (99%) and NiCl2 (98%) were obtained from Acros Organics. Sodium hydroxide (NaOH, 98%), methanol (MeOH, 99.9%), ethanol (EtOH, 99%), isopropyl alcohol (IPA), acetone, sulfuric acid (H2SO4, 99%) were supplied by Fisher, Scientific. Electrochemical experiments were on Gamry Interface 1010T system, using a FTO working electrode (resistance of 8 Ωm cm−1, thickness of 2.2 mm, Dyesol, Australia), with a platinum sheet as the counter electrode, and Ag/AgCl in 3.5 M KCl electrode as the reference. Fourier transform infrared spectra (FTIR) were collected with Bruker LUMOS II; field-emission scanning electron microscopic (FE-SEM) and high resolution transmission electron microscopic images were analyzed using JEOL JSM-6480LV and Multipurpose 200 kV JEM 2100 JEOL respectively; energy-dispersive X-ray spectroscope (EDS) was obtained with Hitachi SU-8010; Raman spectrometer was collected using Jobin Yvon Labram 300; X-ray diffractometer was done with D8 Advance Eco, Bruker.
7
FT-IR Spectroscopy for Material Identification
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The samples were measured using FT-IR spectroscopy on an FT-IR microscope (LUMOS II, Bruker Optics, Billerica, MA, USA) equipped with a 32 × 32 pixel Focal Plane Array detector. The infrared (IR) images were measured in transmission mode at a spectral resolution of 12 cm−1 within a spectral range from 4000 to 700 cm−1 and by one scan. Before IR imaging, a photograph of the sample was taken to visualize any changes in the morphology of the particle surface. Data analyses were conducted using siMPle, freeware that is capable of rapid MP material detection and that has an algorithm that compares the IR spectrum of the sample with a reference spectrum within the database, thereby allocating the material with probability scores.
8
Comprehensive Surface Characterization
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To determine the surface wettability,
the contact angle (CA) and the sliding angle (SA) were measured with
an optical tensiometer (Attension, Theta Lite). CA and SA were measured
at three different locations using water droplets of 5 and 10 μL,
respectively. The reported results are arithmetic averages obtained
from these three measurements. The surface morphology of samples was
imaged via a scanning electron microscope (SEM) (Zeiss EVO LS10) at
25 kV. Surface topography was examined with a profilometer (Bruker-DektakXT).
Before measurements, the sample surface was coated with a thin layer
of gold via sputtering. The chemical composition was characterized
via FTIR using the ATR mode (LUMOS II, Bruker) and X-ray photoelectron
spectroscopy (XPS). For the XPS measurements, a Thermo Scientific
K-Alpha spectrometer with a monochromatic Al Kα source (1486.7
eV) was used. The XPS data were calibrated against adventitious C
1s. The thermal property of the materials was investigated via differential
scanning calorimetry (DSC, METTLER1). Specifically, 4–7 mg
of the sample was placed in an aluminum pan and heated to 200 °C,
equilibrated for 5 min, and then cooled to room temperature. The heating
and cooling rate was 10 °C/min.
the contact angle (CA) and the sliding angle (SA) were measured with
an optical tensiometer (Attension, Theta Lite). CA and SA were measured
at three different locations using water droplets of 5 and 10 μL,
respectively. The reported results are arithmetic averages obtained
from these three measurements. The surface morphology of samples was
imaged via a scanning electron microscope (SEM) (Zeiss EVO LS10) at
25 kV. Surface topography was examined with a profilometer (Bruker-DektakXT).
Before measurements, the sample surface was coated with a thin layer
of gold via sputtering. The chemical composition was characterized
via FTIR using the ATR mode (LUMOS II, Bruker) and X-ray photoelectron
spectroscopy (XPS). For the XPS measurements, a Thermo Scientific
K-Alpha spectrometer with a monochromatic Al Kα source (1486.7
eV) was used. The XPS data were calibrated against adventitious C
1s. The thermal property of the materials was investigated via differential
scanning calorimetry (DSC, METTLER1). Specifically, 4–7 mg
of the sample was placed in an aluminum pan and heated to 200 °C,
equilibrated for 5 min, and then cooled to room temperature. The heating
and cooling rate was 10 °C/min.
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