Multi-Parameter Analysis of Nanoplastics in Flow: Taking Advantage of High Sensitivity and Time Resolution Enabled by Stimulated Raman Scattering.

Here, we demonstrate the detection of nanoplastics (NPLs) in flow with stimulated Raman scattering (SRS) for the first time. NPLs (plastic particles <1000 nm) have recently been detected in different environmental samples and personal care products. However, their characterization is still an analytical challenge. Multiple parameters, including size, chemical composition, and concentration (particle number and mass), need to be determined. In an earlier paper, online field flow fractionation (FFF)-Raman analysis with optical trapping was shown to be a promising tool for the detection of particles in this size range. SRS, which is based on the enhancement of a vibrational transition by the matching energy difference of two laser beams, would allow for much more sensitive detection and, hence, much shorter acquisition times compared to spontaneous Raman microspectroscopy (RM). Here, we show the applicability of SRS for the flow-based analysis of individual, untrapped NPLs. It was possible to detect polyethylene (PE), polystyrene (PS), and poly(methyl methacrylate) (PMMA) beads with diameters of 100-5000 nm. The high time resolution of 60.5 µs allows us to detect individual signals per particle and to correlate the number of detected particles to the injected mass concentration. Furthermore, due to the high time resolution, optically trapped beads could be distinguished from untrapped beads by their peak shapes. The SRS wavenumber settings add chemical selectivity to the measurement. Whereas optical trapping is necessary for the flow-based detection of particles by spontaneous RM, the current study demonstrates that SRS can detect particles in a flow without trapping. Additionally, the mean particle size could be estimated using the mean width (duration) and intensity of the SRS signals.

Towards a reference material for microplastics' number concentration-case study of PET in water using Raman microspectroscopy.

Increasing demand for size-resolved identification and quantification of microplastic particles in drinking water and environmental samples requires the adequate validation of methods and techniques that can be used for this purpose. In turn, the feasibility of such validation depends on the existence of suitable certified reference materials (CRM). A new candidate reference material (RM), consisting of polyethylene terephthalate (PET) particles and a water matrix, has been developed. Here, we examine its suitability with respect to a homogeneous and stable microplastic particle number concentration across its individual units. A measurement series employing tailor-made software for automated counting and analysis of particles (TUM-ParticleTyper 2) coupled with Raman microspectroscopy showed evidence of the candidate RM homogeneity with a relative standard deviation of 12% of PET particle counts involving particle sizes >30 µm. Both the total particle count and the respective sums within distinct size classes were comparable in all selected candidate RM units. We demonstrate the feasibility of production of a reference material that is sufficiently homogeneous and stable with respect to the particle number concentration.

Chemical Analysis of Microplastics and Nanoplastics: Challenges, Advanced Methods, and Perspectives.

Microplastics and nanoplastics have become emerging particulate anthropogenic pollutants and rapidly turned into a field of growing scientific and public interest. These tiny plastic particles are found in the environment all around the globe as well as in drinking water and food, raising concerns about their impacts on the environment and human health. To adequately address these issues, reliable information on the ambient concentrations of microplastics and nanoplastics is needed. However, micro- and nanoplastic particles are extremely complex and diverse in terms of their size, shape, density, polymer type, surface properties, etc. While the particle concentrations in different media can vary by up to 10 orders of magnitude, analysis of such complex samples may resemble searching for a needle in a haystack. This highlights the critical importance of appropriate methods for the chemical identification, quantification, and characterization of microplastics and nanoplastics. The present article reviews advanced methods for the representative mass-based and particle-based analysis of microplastics, with a focus on the sensitivity and lower-size limit for detection. The advantages and limitations of the methods, and their complementarity for the comprehensive characterization of microplastics are discussed. A special attention is paid to the approaches for reliable analysis of nanoplastics. Finally, an outlook for establishing harmonized and standardized methods to analyze these challenging contaminants is presented, and perspectives within and beyond this research field are discussed.

TUM-ParticleTyper 2: automated quantitative analysis of (microplastic) particles and fibers down to 1 [Formula: see text]m by Raman microspectroscopy.

Accurate quantification of small microplastics in environmental and food samples is a prerequisite for studying their potential hazard. Knowledge of numbers, size distributions and polymer type for particles and fibers is particularly relevant in this respect. Raman microspectroscopy can identify particles down to 1 [Formula: see text]m in diameter. Here, a fully automated procedure for quantifying microplastics across the entire defined size range is presented as the core of the new software TUM-ParticleTyper 2. This software implements the theoretical approaches of random window sampling and on-the-fly confidence interval estimation during ongoing measurements. It also includes improvements to image processing and fiber recognition (when compared to the previous software TUM-ParticleTyper for analysis of particles/fibers [Formula: see text] [Formula: see text]m), and a new approach to adaptive de-agglomeration. Repeated measurements of internally produced secondary reference microplastics were evaluated to assess the precision of the whole procedure.

Physicochemical characterization and quantification of nanoplastics: applicability, limitations and complementarity of batch and fractionation methods.

A comprehensive physicochemical characterization of heterogeneous nanoplastic (NPL) samples remains an analytical challenge requiring a combination of orthogonal measurement techniques to improve the accuracy and robustness of the results. Here, batch methods, including dynamic light scattering (DLS), nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (TRPS), transmission electron microscopy (TEM), and scanning electron microscopy (SEM), as well as separation/fractionation methods such as centrifugal liquid sedimentation (CLS) and field-flow fractionation (FFF)-multi-angle light scattering (MALS) combined with pyrolysis gas chromatography mass spectrometry (pyGC-MS) or Raman microspectroscopy (RM) were evaluated for NPL size, shape, and chemical composition measurements and for quantification. A set of representative/test particles of different chemical natures, including (i) polydisperse polyethylene (PE), (ii) (doped) polystyrene (PS) NPLs, (iii) titanium dioxide, and (iv) iron oxide nanoparticles (spherical and elongated), was used to assess the applicability and limitations of the selected methodologies. Particle sizes and number-based concentrations obtained by orthogonal batch methods (DLS, NTA, TRPS) were comparable for monodisperse spherical samples, while higher deviations were observed for polydisperse, agglomerated samples and for non-spherical particles, especially for light scattering methods. CLS and TRPS offer further insight with increased size resolution, while detailed morphological information can be derived by electron microscopy (EM)-based approaches. Combined techniques such as FFF coupled to MALS and RM can provide complementary information on physical and chemical properties by online measurements, while pyGC-MS analysis of FFF fractions can be used for the identification of polymer particles (vs. inorganic particles) and for their offline (semi)quantification. However, NPL analysis in complex samples will continue to present a serious challenge for the evaluated techniques without significant improvements in sample preparation.

Fructobacillus cardui sp. nov., isolated from a thistle (Carduus nutans) flower.

A Fructobacillus strain was isolated from the flower of a nodding thistle (Carduus nutans) collected in Bavaria, Germany. The strain is Gram-positive, rod-shaped, non-motile, non-sporulating, catalase- and oxidase-negative, and facultatively anaerobic. Growth can be detected at 10-37 °C and pH 4 to 9. The genome size is about 1.56 Mbp and the G+C content is 43.76 mol%. Assignment to the genus Fructobacillus was done by average nucleotide identity (ANI), 16S rRNA gene sequence and multilocus sequence analyses. Calculations of ANI and digital DNA-DNA hybridization values indicate a novel species with Fructobacillus tropaeoli DSM 23246T (93.58% ANI and 57.9 % dDDH) being its closest relative. Therefore, a new species named Fructobacillus cardui sp. nov. with TMW 2.2452T (=DSM 113480T=CECT 30515T) as type strain is proposed.

Multi-element stable isotope Raman microspectroscopy of bacterial carotenoids unravels rare signal shift patterns and single-cell phenotypic heterogeneity.

The combination of single-cell Raman microspectroscopy (SCRM) and stable isotope probing (SIP) enables in situ tracking of carbon or hydrogen fluxes into microorganisms at the single-cell level. Therefore, it has high potential for the analysis of metabolic processes and biogeochemical cycles. However, especially for high throughput applications such as imaging or cell sorting, it is hampered by low Raman scattering intensities (and therefore long acquisition times). In order to overcome these limitations, this study brings forward a systematic investigation of Resonance Raman (RR) enhanced SCRM for SIP of bacterial carotenoids. Dynamic carbon uptake from 13C-glucose was successfully monitored and quantified utilizing 13C stable isotope-induced red-shifts of RR signals. High single-cell phenotypic heterogeneity was revealed in terms of carbon uptake and, unlike in previous studies, clear evidence for de novo synthesis of carotenoids was found. For the first time, hydrogen uptake into carotenoids was systematically investigated by deuterium labeling (providing a direct probe for metabolic activity of single cells). In carotenoid single-cell Resonance Raman (SCRR) spectra, a unique pattern of signal red-shifts and apparent blue-shifts was observed and quantitatively evaluated. Finally, a novel combined approach for simultaneous monitoring of carbon and hydrogen uptake revealed complementary effects in carotenoid SCRR spectra that can be analyzed in parallel. Overall, it was shown that the high RR intensity, simplicity of spectral features and straightforward signal processing make microbial carotenoids an ideal target for quantitative multi-element SIP, with great potential for high throughput applications.

Which particles to select, and if yes, how many? : Subsampling methods for Raman microspectroscopic analysis of very small microplastic.

Micro- and nanoplastic contamination is becoming a growing concern for environmental protection and food safety. Therefore, analytical techniques need to produce reliable quantification to ensure proper risk assessment. Raman microspectroscopy (RM) offers identification of single particles, but to ensure that the results are reliable, a certain number of particles has to be analyzed. For larger MP, all particles on the Raman filter can be detected, errors can be quantified, and the minimal sample size can be calculated easily by random sampling. In contrast, very small particles might not all be detected, demanding a window-based analysis of the filter. A bootstrap method is presented to provide an error quantification with confidence intervals from the available window data. In this context, different window selection schemes are evaluated and there is a clear recommendation to employ random (rather than systematically placed) window locations with many small rather than few larger windows. Ultimately, these results are united in a proposed RM measurement algorithm that computes confidence intervals on-the-fly during the analysis and, by checking whether given precision requirements are already met, automatically stops if an appropriate number of particles are identified, thus improving efficiency. To provide quality control in the MP quantification by Raman microspectroscopy, a window subsampling and bootstrap protocol is presented, which can provide confidence intervals that enable the assessment of the reliability of the data. This is brought together with a proposed on-the-fly algorithm that assesses the precision during the measurement and stops at the optimal point.

Analysis of microplastics in drinking water and other clean water samples with micro-Raman and micro-infrared spectroscopy: minimum requirements and best practice guidelines.

Microplastics are a widespread contaminant found not only in various natural habitats but also in drinking waters. With spectroscopic methods, the polymer type, number, size, and size distribution as well as the shape of microplastic particles in waters can be determined, which is of great relevance to toxicological studies. Methods used in studies so far show a huge diversity regarding experimental setups and often a lack of certain quality assurance aspects. To overcome these problems, this critical review and consensus paper of 12 European analytical laboratories and institutions, dealing with microplastic particle identification and quantification with spectroscopic methods, gives guidance toward harmonized microplastic particle analysis in clean waters. The aims of this paper are to (i) improve the reliability of microplastic analysis, (ii) facilitate and improve the planning of sample preparation and microplastic detection, and (iii) provide a better understanding regarding the evaluation of already existing studies. With these aims, we hope to make an important step toward harmonization of microplastic particle analysis in clean water samples and, thus, allow the comparability of results obtained in different studies by using similar or harmonized methods. Clean water samples, for the purpose of this paper, are considered to comprise all water samples with low matrix content, in particular drinking, tap, and bottled water, but also other water types such as clean freshwater.

Nanoplastic Analysis by Online Coupling of Raman Microscopy and Field-Flow Fractionation Enabled by Optical Tweezers.

Nanoplastic pollution is an emerging environmental concern, but current analytical approaches are facing limitations in this size range. However, the coupling of nanoparticle separation with chemical characterization bears potential to close this gap. Here, we realize the hyphenation of particle separation/characterization (field-flow fractionation (FFF), UV, and multiangle light scattering) with subsequent chemical identification by online Raman microspectroscopy (RM). The problem of low Raman scattering was overcome by trapping particles with 2D optical tweezers. This setup enabled RM to identify particles of different materials (polymers and inorganic) in the size range from 200 nm to 5 µm, with concentrations in the order of 1 mg/L (109 particles L-1). The hyphenation was realized for asymmetric flow FFF and centrifugal FFF, which separate particles on the basis of different properties. This technique shows potential for application in nanoplastic analysis, as well as many other fields of nanomaterial characterization.

Surface-enhanced Raman spectroscopy of microorganisms: limitations and applicability on the single-cell level.

Detection and characterization of microorganisms is essential for both clinical diagnostics and environmental studies. An emerging technique to analyse microbes at single-cell resolution is surface-enhanced Raman spectroscopy (surface-enhanced Raman scattering: SERS). Optimised SERS procedures enable fast analytical read-outs with specific molecular information, providing insight into the chemical composition of microbiological samples. Knowledge about the origin of microbial SERS signals and parameter(s) affecting their occurrence, intensity and/or reproducibility is crucial for reliable SERS-based analyses. In this work, we explore the feasibility and limitations of the SERS approach for characterizing microbial cells and investigate the applicability of SERS for single-cell sorting as well as for three-dimensional visualization of microbial communities. Analyses of six different microbial species (an archaeon, two Gram-positive bacteria, three Gram-negative bacteria) showed that for several of these organisms distinct features in their SERS spectra were lacking. As additional confounding factor, the physiological conditions of the cells (as influenced by e.g., storage conditions or deuterium-labelling) were systematically addressed, for which we conclude that the respective SERS signal at the single-cell level is strongly influenced by the metabolic activity of the analysed cells. While this finding complicates the interpretation of SERS data, it may on the other hand enable probing of the metabolic state of individual cells within microbial populations of interest.

Are We Speaking the Same Language? Recommendations for a Definition and Categorization Framework for Plastic Debris.

The accumulation of plastic litter in natural environments is a global issue. Concerns over potential negative impacts on the economy, wildlife, and human health provide strong incentives for improving the sustainable use of plastics. Despite the many voices raised on the issue, we lack a consensus on how to define and categorize plastic debris. This is evident for microplastics, where inconsistent size classes are used and where the materials to be included are under debate. While this is inherent in an emerging research field, an ambiguous terminology results in confusion and miscommunication that may compromise progress in research and mitigation measures. Therefore, we need to be explicit on what exactly we consider plastic debris. Thus, we critically discuss the advantages and disadvantages of a unified terminology, propose a definition and categorization framework, and highlight areas of uncertainty. Going beyond size classes, our framework includes physicochemical properties (polymer composition, solid state, solubility) as defining criteria and size, shape, color, and origin as classifiers for categorization. Acknowledging the rapid evolution of our knowledge on plastic pollution, our framework will promote consensus building within the scientific and regulatory community based on a solid scientific foundation.

Stable-isotope Raman microspectroscopy for the analysis of soil organic matter.

We examined the potential of stable-isotope Raman microspectroscopy (SIRM) for the evaluation of differently enriched 13C-labeled humic acids as model substances for soil organic matter (SOM). The SOM itself can be linked to the soil water holding capacity. Therefore, artificial humic acids (HA) with known isotopic compositions were synthesized and analyzed by means of SIRM. By performing a pregraphitization, a suitable analysis method was developed to cope with the high fluorescence background. Results were verified against isotope ratio mass spectrometry (IRMS). The limit of quantification was 2.1 × 10-1 13C/C tot for the total region and 3.2 × 10-2 13C/C tot for a linear correlation up to 0.25 13C/C tot. Complementary nanoscale secondary ion mass spectrometry (NanoSIMS) analysis indicated small-scale heterogeneity within the dry sample material, even though-owing to sample topography and occurring matrix effects-obtained values deviated in magnitude from those of IRMS and SIRM. Our study shows that SIRM is well-suited for the analysis of stable isotope-labeled HA. This method requires no specific sample preparation and can provide information with a spatial resolution in the micrometer range. Graphical abstract Analysis of the isotopic composition of humic acids by Raman microspectroscopy in combination with isotope ratio mass spectrometry and nanoscale secondary ion mass spectrometry.

Raman microspectroscopy, surface-enhanced Raman scattering microspectroscopy, and stable-isotope Raman microspectroscopy for biofilm characterization.

Biofilms represent the predominant form of microbial life on our planet. These aggregates of microorganisms, which are embedded in a matrix formed by extracellular polymeric substances, may colonize nearly all interfaces. Detailed knowledge of microorganisms enclosed in biofilms as well as of the chemical composition, structure, and functions of the complex biofilm matrix and their changes at different stages of the biofilm formation and under various physical and chemical conditions is relevant in different fields. Important research topics include the development and improvement of antibiotics and medical devices and the optimization of biocides, antifouling strategies, and biological wastewater treatment. Raman microspectroscopy is a capable and nondestructive tool that can provide detailed two-dimensional and three-dimensional chemical information about biofilm constituents with the spatial resolution of an optical microscope and without interference from water. However, the sensitivity of Raman microspectroscopy is rather limited, which hampers the applicability of Raman microspectroscopy especially at low biomass concentrations. Fortunately, the resonance Raman effect as well as surface-enhanced Raman scattering can help to overcome this drawback. Furthermore, the combination of Raman microspectroscopy with other microscopic techniques, mass spectrometry techniques, or particularly with stable-isotope techniques can provide comprehensive information on monospecies and multispecies biofilms. Here, an overview of different Raman microspectroscopic techniques, including resonance Raman microspectroscopy and surface-enhanced Raman scattering microspectroscopy, for in situ detection, visualization, identification, and chemical characterization of biofilms is given, and the main feasibilities and limitations of these techniques in biofilm research are presented. Future possibilities of and challenges for Raman microspectroscopy alone and in combination with other analytical techniques for characterization of complex biofilm matrices are discussed in a critical review. Graphical Abstract Applicability of Raman microspectroscopy for biofilm analysis.

Microplastic in Aquatic Ecosystems.

The contamination of marine and freshwater ecosystems with plastic, and especially with microplastic (MP), is a global ecological problem of increasing scientific concern. This has stimulated a great deal of research on the occurrence of MP, interaction of MP with chemical pollutants, the uptake of MP by aquatic organisms, and the resulting (negative) impact of MP. Herein, we review the major issues of MP in aquatic environments, with the principal aims 1) to characterize the methods applied for MP analysis (including sampling, processing, identification and quantification), indicate the most reliable techniques, and discuss the required further improvements; 2) to estimate the abundance of MP in marine/freshwater ecosystems and clarify the problems that hamper the comparability of such results; and 3) to summarize the existing literature on the uptake of MP by living organisms. Finally, we identify knowledge gaps, suggest possible strategies to assess environmental risks arising from MP, and discuss prospects to minimize MP abundance in aquatic ecosystems.

The origin of the band at around 730 cm(-1) in the SERS spectra of bacteria: a stable isotope approach.

Raman microspectroscopy is an emerging tool to analyze the molecular and isotopic composition of single microbial cells. It can be used to achieve an in situ understanding of metabolic processes. Due to the low sensitivity of the Raman effect, surface-enhanced Raman scattering (SERS) is utilized to enhance the Raman signal. The SERS spectra of bacteria are usually characterized by a pronounced band at around 730 cm(-1), which is assigned to glycosidic ring vibrations or to adenine or even to CH2 deformation in different studies. In order to clarify the origin of this band, we employed a stable isotope approach and performed a SERS analysis of Escherichia coli bacteria using in situ prepared Ag nanoparticles. The cells were grown on unlabeled ((12)C, (14)N) and labeled ((13)C, (15)N) carbon and nitrogen sources in different combinations. The SERS band of the stable isotope labeled microorganisms showed a characteristic red-shift in the SERS spectra, which solely depends on the isotopic composition. It was therefore possible to confidently assign this band to adenine-related compounds. Furthermore, by utilizing the fingerprint area of single-cell SERS spectra as the input for the principal component analysis, one can clearly differentiate between E. coli bacteria incorporating different stable isotopes.

Exploring the Potential of Stable Isotope (Resonance) Raman Microspectroscopy and Surface-Enhanced Raman Scattering for the Analysis of Microorganisms at Single Cell Level.

Raman microspectroscopy is a prime tool to characterize the molecular and isotopic composition of microbial cells. However, low sensitivity and long acquisition times limit a broad applicability of the method in environmental analysis. In this study, we explore the potential, the applicability, and the limitations of stable isotope Raman microspectroscopy (SIRM), resonance SIRM, and SIRM in combination with surface-enhanced Raman scattering (SERS) for the characterization of single bacterial cells. The latter two techniques have the potential to significantly increase sensitivity and decrease measurement times in SIRM, but to date, there are no (SERS-SIRM) or only a limited number (resonance SIRM) of studies in environmental microbiology. The analyzed microorganisms were grown with substrates fully labeled with the stable isotopes (13)C or (2)H and compounds with natural abundance of atomic isotopes ((12)C 98.89% or (1)H 99.9844%, designated as (12)C or (1)H, respectively). Raman bands of bacterial cell compounds in stable isotope-labeled microorganisms exhibited a characteristic red-shift in the spectra. In particular, the sharp phenylalanine band was found to be an applicable marker band for SIRM analysis of the Deltaproteobacterium strain N47 growing anaerobically on (13)C-naphthalene. The study of G. metallireducens grown with (13)C- and (2)H-acetate showed that the information on the chromophore cytochrome c obtained by resonance SIRM at 532 nm excitation wavelength can be successfully complemented by whole-organism fingerprints of bacteria cells achieved by regular SIRM after photobleaching. Furthermore, we present here for the first time the reproducible SERS analysis of microbial cells labeled with stable isotopes. Escherichia coli strain DSM 1116 cultivated with (12)C- or (13)C-glucose was used as a model organism. Silver nanoparticles synthesized in situ were applied as SERS media. We observed a reproducible red-shift of an adenine-related marker band from 733 to 720 cm(-1) in SERS spectra for (13)C-labeled cells. Additionally, Raman measurements of (12)C/(13)C-glucose and -phenylalanine mixtures were performed to elucidate the feasibility of SIRM for nondestructive quantitative and spatially resolved analysis. The performed analysis of isotopically labeled microbial cells with SERS-SIRM and resonance SIRM paves the way toward novel approaches to apply Raman microspectroscopy in environmental process studies.

Label-Free in Situ Discrimination of Live and Dead Bacteria by Surface-Enhanced Raman Scattering.

Techniques to distinguish between live and dead bacteria in a quantitative manner are in high demand in numerous fields including medical care, food safety, and public security as well as basic science research. This work demonstrates new nanostructures (silver nanoparticles coating bacteria structure, Bacteria@AgNPs) and their utility for rapid counting of live and dead bacteria by surface-enhanced Raman scattering (SERS). We found that suspensions containing Gram-negative organisms as well as AgNPs give strong SERS signals of live bacteria when generated selectively on the particle surface. However, almost no SERS signals can be detected from Bacteria@AgNPs suspensions containing dead bacteria. We demonstrate successful quantification of different percentages of dead bacteria both in bulk liquid and on glass surfaces by using SERS mapping on a single cell basis. Furthermore, different chemicals have been used to elucidate the mechanism involved in this observation. Finally, we used the Bacteria@AgNPs method to detect antibiotic resistance of E. coli strains against several antibiotics used in human medicine.

Photoinduced C-C reactions on insulators toward photolithography of graphene nanoarchitectures.

On-surface chemistry for atomically precise sp(2) macromolecules requires top-down lithographic methods on insulating surfaces in order to pattern the long-range complex architectures needed by the semiconductor industry. Here, we fabricate sp(2)-carbon nanometer-thin films on insulators and under ultrahigh vacuum (UHV) conditions from photocoupled brominated precursors. We reveal that covalent coupling is initiated by C-Br bond cleavage through photon energies exceeding 4.4 eV, as monitored by laser desorption ionization (LDI) mass spectrometry (MS) and X-ray photoelectron spectroscopy (XPS). Density functional theory (DFT) gives insight into the mechanisms of C-Br scission and C-C coupling processes. Further, unreacted material can be sublimed and the coupled sp(2)-carbon precursors can be graphitized by e-beam treatment at 500 °C, demonstrating promising applications in photolithography of graphene nanoarchitectures. Our results present UV-induced reactions on insulators for the formation of all sp(2)-carbon architectures, thereby converging top-down lithography and bottom-up on-surface chemistry into technology.