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In the past, δ26/24Mg measurements were referenced to NIST SRM 980, the initial zero of the δ26/24Mg scale. With the development of MC-ICPMS, the detection of small but measurable isotopic differences in different chips of SRM 980 became apparent. To solve this problem a suite of magnesium isotope reference materials, ERM-AE143, -AE144 and -AE145, has been certified in a first study by applying an ab initio calibration for absolute Mg isotope ratios without any a priori assumptions, a procedure which fulfils all requirements of a primary method of measurement. We could achieve for the first time measurement uncertainties for isotope amount ratios close to the typical precision of magnesium delta values, δ26/24Mg, which are at the 0.1 ‰ level (2SD). In addition, it was demonstrated that commonly used fractionation laws are invalid for correcting Mg isotope ratios in multi-collector ICPMS as they result in a bias which is not covered by its associated uncertainty. Depending on their type, fractionation laws create a bias up to several per mil, with the exponential law showing the smallest bias between 0.1 ‰ to 0.7 ‰.
With these isotope reference materials, it is possible to establish SI-traceability for magnesium delta measurements. To realize this, we organized a second study within which five expert laboratories participated to cross-calibrate all available magnesium isotope standards, which are NIST SRM 980, IRMM-009, ERM-AE143, ERM-AE144, ERM-AE145 and the standards DSM3 and Cambridge-1. The mean δ26/24Mg values for the individual iRMs, calculated from the laboratory means show 2 SD reproducibilities varying between 0.025 and 0.093 ‰. Propagated measurement uncertainties suggest a standard uncertainty of about 0.1‰ for δ26/24Mg determinations (2SD). Thus, SI traceability for magnesium isotope amount ratios and delta values is demonstrated to be established.
In the past, δ26/24Mg measurements were referenced to NIST SRM 980, the initial zero of the δ26/24Mg scale. With the development of MC-ICPMS, the detection of small but measurable isotopic differences in different chips of SRM 980 became apparent. To solve this problem a suite of magnesium isotope reference materials, ERM-AE143, -AE144 and -AE145, has been certified in a first study by applying an ab initio calibration for absolute Mg isotope ratios without any a priori assumptions, a procedure which fulfils all requirements of a primary method of measurement. We could achieve for the first time measurement uncertainties for isotope amount ratios close to the typical precision of magnesium delta values, δ26/24Mg, which are at the 0.1 ‰ level (2SD). In addition, it was demonstrated that commonly used fractionation laws are invalid for correcting Mg isotope ratios in multi-collector ICPMS as they result in a bias which is not covered by its associated uncertainty. Depending on their type, fractionation laws create a bias up to several per mil, with the exponential law showing the smallest bias between 0.1 ‰ to 0.7 ‰.
With these isotope reference materials, it is possible to establish SI-traceability for magnesium delta measurements. To realize this, we organized a second study within which five expert laboratories participated to cross-calibrate all available magnesium isotope standards, which are NIST SRM 980, IRMM-009, ERM-AE143, ERM-AE144, ERM-AE145 and the standards DSM3 and Cambridge-1. The mean δ26/24Mg values for the individual iRMs, calculated from the laboratory means show 2 SD reproducibilities varying between 0.025 and 0.093 ‰. Propagated measurement uncertainties suggest a standard uncertainty of about 0.1‰ for δ26/24Mg determinations (2SD). Thus, SI traceability for magnesium isotope amount ratios and delta values is demonstrated to be established.
Mixed copper and titanium hydride powder was hot-pressed and characterized by Carrier Gas Hot Extraction, XRay Diffraction, Thermal Gravimetric Analysis coupled with Mass Spectrometry, and Scanning Electron Microscopy.
The hot-pressed and five conventional samples were applied for calibration of hydrogen in Glow Discharge Optical Emission and Mass Spectrometry. Up to the introduction of 15 ng/s hydrogen the Emission yield model is useful in Glow Discharge Optical Emission Spectrometry. A correlation between saturation and even reversal of the emission yield of the spectral lines H121, H486 and H656 and low sputtering rates was found. Hydrogen effects exist for the spectral lines of Cu(II) 219 and Ti(I) 399. In Glow Discharge Mass Spectrometry, a linear dependency of the 1H ion current on the sputtered mass per time exists over the total range of hydrogen content investigated. Hydrogen effects also exist for the sensitivity of 48Ti and 63Cu. The sputtering rate of two-phase materials depends linearly on the sputtered mass per time of one phase, which allows the sputtering rate of two-phase materials with known composition to be predicted.
In all fluorescence-based techniques, the measured signals contain not only sample-related but also instrument-specific contributions, which limit the direct comparison of fluorescence data obtained e.g. on different devices or at different times and often hamper quantification. To rule out instrumentation as major source of variability of emission data, accepted fluorescence standards and procedures for the control of instrument specifications and long-term performance are required. For flow cytometry (FCM), a broad variety of fluorophore-stained polymer beads differing in emission wavelength and intensity is available for the testing of the alignment, sensitivity, and other parameters of FCM. These calibration tools are intended to facilitate the assessment of instrument performance to ensure reliable measurements and to improve the comparability of FCM experiments.
As a step towards an improved comparability of fluorescence data, with special emphasis on spectroscopic methods measuring nano- and micrometer-sized fluorescent objects, we are currently developing a set of fluorescent polystyrene (PS) beads loaded with luminophores from the certified BAM-Kit “Spectral fluorescent standards”, initially developed for the calibration of fluorescence spectrometers. Here, we present first results from studies of these fluorophore-loaded polymer beads. Moreover, new beads are made to supplement this kit by encapsulating near-infrared (NIR)-emissive luminophores in PS beads to cover the UV/VIS, and NIR wavelength range.
These beads are designed for calibration of flow cytometers and other fluorescence imaging systems to meet the increasing demand for reliable and comparable fluorescence data especially in strongly regulated areas like e.g. medical diagnostics.
Chromium(III) complexes can show phosphorescence from the spin-flip excited doublet states 2E/2T1 in the near-infrared with high photoluminescence quantum yields and extremely long lifetimes in the absence of dioxygen. The prototype molecular ruby, [Cr(ddpd)2]3+ (ddpd = N,N’-dimethyl-N,N’-dipyridine-2-ylpyridine-2,6-diamine), has a photoluminescence quantum yield and a luminescence lifetime of 13.7% and 1.1 ms in deaerated acetonitrile, respectively. However, its luminescence is strongly quenched by 3O2 via an efficient Dexter-type energy transfer process. To enable luminescence applications of molecular rubies in solution under aerobic conditions, we explored the potential of sterically demanding ddpd ligands to shield the chromium(III) center from O2 using steady state and time-resolved photoluminescence spectroscopy. The structures of the novel complexes with sterically demanding ligands were investigated by single crystal X-ray diffraction and quantum chemically by density functional theory calculations. The O2 sensitivity of the photoluminescence was derived from absolutely measured photoluminescence quantum yields and excited state lifetimes under inert and aerobic conditions and by Stern–Volmer analyses of these data. Optimal sterically shielded chromium(III) complexes revealed photoluminescence quantum yields of up to 5.1% and excited state lifetimes of 518 μs in air-saturated acetonitrile, underlining the large potential of this ligand design approach to broaden the applicability of highly emissive chromium(III) complexes.
Is it a parmesan cheese from Italy? Who painted the Mona Lisa? The determination of the place of origin is essential for consumer protection, detection of falsifications, and also to bring justice.
All the tangible possess an isotopic fingerprint. However, current technologies are too expensive. We work on the development of fast and low-cost optical instruments and methods for isotope analysis.
With the continuous release of anthropogenic pollutants into the environment, substantial risks for the human health arise. Concerning are especially persistent substances (e.g., PFAS) as they accumulate in food chains which inevitably result in the transgression of negative impact threshold levels. Environmental Analytical Chemsitry interfaces all disciplines of Risk Assessment. Therefore it is the important tool to identify, monitor, and remediate environmental pollutants. Based on the example of PFAS, a workflow to tackle environmental pollutants in a retro- and pro-spective way is shown. Within the project, the worldwide situation of environmental pollutants will be illustrated for the example of PFAS. As the major discipline to confront the problem, analytical chemistry will be shown as a key tool for contesting PFAS and creating safe-by-design materials in the future.
Rationale: Boron (B) is an essential micronutrient in plants and its isotope variations are used to gain insights into plant metabolism, which is important for crop plant cultivation. B isotope variations were used to trace intra‐plant fractionation mechanisms in response to the B concentration in the irrigation water spanning the
range from B depletion to toxic levels.
Methods: A fully validated analytical procedure based on multi‐collector inductively coupled plasma mass spectrometry (MC‐ICP‐MS), sample decomposition and B Matrix separation was applied to study B isotope fractionation. The Validation was accomplished by establishing a complete uncertainty budget and by applying reference materials, yielding expanded measurement uncertainties of 0.8‰ for pure boric acid solutions and ≤1.5‰ for processed samples. With this validated procedure SI traceable B isotope amount ratios were determined in plant reference materials for the first time.
Results: The B isotope compositions of Irrigation water and bell pepper samples suggest passive diffusion of the heavy 11B isotope into the roots during low to high B concentrations while uptake of the light 10B isotope was promoted during B depletion, probably by active processes. A systematic enrichment of the heavy 11B isotope in higher located plant parts was observed (average Δ11Bleaf‐roots = 20.3 ± 2.8‰ (1 SD)), possibly by a facilitated transport of the heavy 11B isotope to growing Meristems by B transporters.
Conclusions: The B isotopes can be used to identify plant metabolism in Response to the B concentration in the irrigation water and during intra‐plant B transfer. The large B isotope fractionation within the plants demonstrates the importance of
biological B cycling for the global B cycle.
Boron isotope fractionation in soil-plant systems and its influence on biogeochemical cycling
(2022)
Boron (B) is an essential mineral nutrient for higher plants. Although B plant nutrition is well studied, the B isotope fractionation at the soil-plant interface, within plant metabolism, and its influence on biogeochemical cycling is not fully understood. Boron concentrations and isotope variations (δ11B) of the dicotyledonous plants of Chenopodium album and Brassica napus and their growing soils along a climatic gradient were analyzed to decipher these unresolved issues of the B behavior. The boron concentrations and δ11B values show an increasing trend from roots to leaves for both plants, while a decreasing trend from flower to shell and to seed for Brassica napus. A large boron isotope fractionation occurs within the plants with median Δ11Bleaf-root ≈ +20‰, which is related to different boron transporters and transportation ways. Formation of borate dimerized rhamnogalacturonan II in cell and B(OH)3 transportation in xylem lead to heavier δ11B values from root to stem and leaf while B(OH)4 transportation in phloem lead to lighter δ11B values from flower to shell and seed. Although samples cover a distinct transect with systematically different climatic conditions, Δδ11B within the individual plant compartments and between the bulk plants and the soil available B do not show any systematic variation.
This suggests that B uptake from the soil into Chenopodium album and Brassica napus occurs without a distinct isotope fractionation at the soil-plant interface (median Δ11Bbulkplant-soil = 0.2‰) and plants are able to regulate boron uptake. Both the observed large B fractionation within plant and low or absent B isotope fractionation at the soil-plant interface may have profound implications for the biological and geological B cycle. If this observed boron behavior also exists in other plants, their litters would be an important source for exporting 11B-rich biological material from continental ecosystems via rivers to the global oceans. This may be helpful for the explanation of ocean B cycle and the increasing δ11B values over the Cenozoic.
Zearalenone (ZEN) and its sulfate and glucoside conjugates have been detected in (a broad variety of) food and feed commodities1. Both conjugated derivatives are formed as part of fungal or plant secondary metabolism and thus, belong to the group of modified mycotoxins2. After consumption of contaminated foodstuff, the conjugates can be hydrolyzed by human intestinal microbiota leading to liberation of ZEN that implies an underestimation of the true ZEN exposure. In order to include ZEN conjugates in routine analysis, as well as for toxicological investigation reliable standards are needed.
The objective of the present study was to develop a simple and economic method for biosynthesis of ZEN conjugates. Preceding experiments on the biotransformation of ZEN by Rhizopus and Aspergillus species showed a mixed metabolite formation3. Therefore, these known ZEN conjugating fungal strains were screened for their potential to selectively synthesize the ZEN derivatives ZEN-14-sulfate (Z14S), ZEN-14-glucoside (Z14G) and ZEN-16-glucoside (Z16G). The screening was conducted by adding ZEN to liquid fungal cultures. Cultivation conditions and ZEN incubation time were varied. All media samples were analyzed for metabolite formation by HPLC-MS/MS. Z14S was exclusively formed by A. oryzae. Under optimized conditions a specific biosynthesis of Z14G by R. oryzae and Z16G by R. oligosporus was achieved. After liquid-liquid-extraction and preparative chromatographic cleanup 1H-NMR purities of ≥ 73% for Z14S, ≥ 82% for Z14G and ≥ 50% for Z16G were obtained. In addition, a consecutive biosynthesis was developed by first using Fusarium graminearum for ZEN biosynthesis on rice based liquid medium. After inactivation of Fusarium the subsequent conjugation reaction was conducted utilizing Aspergillus and Rhizopus species under the various optimized conditions.
In this study an easy and cost-efficient biosynthesis for Z14S, Z14G and Z16G was developed. The developed biosynthesis could be also used for other metabolites like ZEL conjugates. Our results of the in vitro screening indicate also the formation of a ZEL-glucoside and α ZEL-sulfate as major metabolites by R. oryzae. In sum, under optimized cultivation conditions fungi can be easily utilized for a targeted and stereospecific synthesis of ZEN conjugates.
Zearalenone (ZEN) and its phase II sulfate and glucoside metabolites have been detected in food and feed commodities. After consumption, the conjugates can be hydrolyzed by the human intestinal microbiota leading to liberation of ZEN that implies an underestimation of the true ZEN exposure. To include ZEN conjugates in routine analysis, reliable standards are needed, which are currently not available. Thus, the aim of the present study was to develop a facilitated biosynthesis of ZEN-14-sulfate, ZEN-14-glucoside and ZEN-16-glucoside. A metabolite screening was conducted by adding ZEN to liquid fungi cultures of known ZEN conjugating Aspergillus and Rhizopus strains. Cultivation conditions and ZEN incubation time were varied. All media samples were analyzed for metabolite formation by HPLC-MS/MS. In addition, a consecutive biosynthesis was developed by using Fusarium graminearum for ZEN biosynthesis with subsequent conjugation of the toxin by utilizing Aspergillus and Rhizopus species. ZEN-14-sulfate (yield: 49%) is exclusively formed by Aspergillus oryzae. ZEN-14-glucoside (yield: 67%) and ZEN-16-glucoside (yield: 39%) are formed by Rhizopus oryzae and Rhizopus oligosporus, respectively. Purities of ≥73% ZEN-14-sulfate, ≥82% ZEN-14-glucoside and ≥50% ZEN-16-glucoside were obtained by 1H-NMR. In total, under optimized cultivation conditions, fungi can be easily utilized for a targeted and regioselective synthesis of ZEN conjugates.
BioPIC - Integration of Biosensors based on Photonic Integrated Circuits by Local-Backside Etching
(2020)
Silicon photonic sensors are promising candidates for lab-on-a-chip solutions with versatile applications and scalable production prospects using complementary metal-oxide semiconductor (CMOS) fabrication methods. However, the widespread use has been hindered because the sensing area adjoins optical and electrical components making packaging and sensor handling challenging. In this work, a local back-side release of the photonic sensor is employed, enabling a separation of the sensing area from the rest of the chip. This approach allows preserving the compatibility of photonic integrated circuits in the front-end of line and metal interconnects in the back-end of line.
An increasing number of (bio)analytical techniques rely on multiparametric analyses and the measurement of a very small number of emitters. While the former implies encoding or labeling by means of easily distinguishable properties like luminescence color or lifetime in conjunction with high-throughput optical-spectroscopic methods such as flow cytometry, the latter requires methods suitable for the characterization of the optical properties of single emitters. Here, we present the use of fluorescence correlation spectroscopy (FCS) for the relative determination of the key parameter photoluminescence quantum yield [5] and first results from flow cytometry measurements in the time-domain with a custom-designed instrument with luminescence lifetime analysis capability.
Biophotonics and analytics - Photoluminescence properties of nanocrystals and surface group analysis
(2018)
Correlating the photoluminescence (PL) properties of nanomaterials like semiconductor nanocrystals (QDs) and upconversion nanocrystals (UCNPs) assessed in ensemble studies and at the single particle level and studying their surface chemistry is increasingly relevant for applications of these nanomaterials in the life and material sciences. Here we present a comparison of the spectroscopic properties of ensembles and single nanocrystalline emitters and simple methods for the quantification of functional groups and ligands on particle surfaces. The overall goal of this study was to derive particle architectures and surface chemistries well suited for spectroscopic and microscopic applications.
An immunohistochemical method is described to visualize the distribution of metallothioneins 1/2 (MT 1/2) and metallothionein 3 (MT 3) in human ocular tissue. It is making use of (a) antibodies conjugated to gold nanoclusters (AuNCs) acting as labels, and (b) laser ablation (LA) coupled to inductively coupled plasma – mass spectrometry (ICP-MS).Water-soluble fluorescent AuNCs (with an average size of 2.7 nm) were synthesized and then conjugated to antibody by carbodiimide coupling. The surface of the modified AuNCs was then blocked with hydroxylamine to avoid nonspecific interactions with biological tissue. Immunoassays for MT 1/2 and MT 3 in ocular tissue sections (5 μm thick) from two post mortem human donors were performed. Imaging studies were then performed by fluorescence using confocal microscopy, and LA-ICP-MS was performed in the retina to measure the signal for gold. Signal amplification by the >500 gold atoms in each nanocluster allowed the antigens (MT 1/2 and MT 3) to be imaged by LA-ICP-MS using a laser spot size as small as 4 μm. The image patterns found in retina are in good agreement with those obtained by conventional fluorescence immunohistochemistry which was used as an established reference method.
An immunohistochemical method is described to visualize the distribution of metallothioneins 1/2 (MT 1/2) and metallothionein 3 (MT 3) in human ocular tissue. It is making use of (a) antibodies conjugated to gold nanoclusters (AuNCs) acting as labels, and (b) laser ablation (LA) coupled to inductively coupled plasma – mass spectrometry (ICP-MS). Water-soluble fluorescent AuNCs (with an average size of 2.7 nm) were synthesized and then conjugated to antibody by carbodiimide coupling. The surface of the modified AuNCs was then blocked with hydroxylamine to avoid nonspecific interactions with biological tissue. Immunoassays for MT 1/2 and MT 3 in ocular tissue sections (5 μm thick) from two post mortem human donors were performed. Imaging studies were then performed by fluorescence using confocal microscopy, and LA-ICP-MS was performed in the retina to measure the signal for gold. Signal amplification by the >500 gold atoms in each nanocluster allowed the antigens (MT 1/2 and MT 3) to be imaged by LA-ICP-MS using a laser spot size as small as 4 μm. The image patterns found in retina are in good agreement with those obtained by conventional fluorescence immunohistochemistry which was used as an established reference method.
Referenzmaterialien sind entscheidend für die Qualitätssicherung von Laboratorien. Diese nutzen Referenzmaterialien unter anderem zur Validierung von Messverfahren und zur Kalibrierung von Geräten. Dabei ist zu beachten, dass zertifizierte Merkmalswerte stets eine gewisse Unsicherheit aufweisen. Die Ermittlung dieser Unsicherheitsbeiträge ist Gegenstand des Artikels. Des Weiteren wird ein Vorgehen beschrieben, wie die Unsicherheit von Messverfahren mit Hilfe eines Referenzmaterials bestimmt werden kann.
Referenzmaterialien sind unter anderem ein wichtiges Werkzeug zur Qualitätskontrolle von Messungen bestimmter Merkmalswerte. Dabei ist zu berücksichtigen, dass zertifizierte Merkmalswerte immer eine gewisse Unsicherheit haben. Die Ermittlung dieser Unsicherheitsbeiträge ist Gegenstand des Vortrags. Referenzmaterialien sind gleichzeitig ein wertvolles Werkzeug zur Ermittlung der Unsicherheit von Messverfahren und -Analysen unbekannter Proben. Die Vorgehensweise bei der Ermittlung der Messunsicherheit mit Hilfe eines Referenzmaterials wird beschrieben.
The use of benchtop-NMR instruments is constantly increasing during the recent years. Advantages of being affordable, portable and easy-to-operate without the need for trained staff make them especially interesting for industrial applications in quality control. However, applications of NMR spectroscopy as an online PAT tool are still very rare but offer a huge potential for process optimization and control. A key task to exploit this potential is hardware field integration of the lab-instruments in a rough environment of a chemical plant. Additionally, developments in automation and data evaluation are mandatory to ensure a robust unattended operation with low maintenance requirements. Here, we show an approach of a fully automated analyzer enclosure considering explosion safety, field communication, as well as environmental conditions in the field.
Temperature sensitivity is still a limitation of benchtop-NMR instruments in flow applications. Recent developments of manufacturers allow for limited operation at static temperature levels, however, a dynamic system for continuous operation is still not available. Using a prototype system offering a larger bore, active temperature shielding studies with thermostated air were performed evaluating the performance.
Automated data evaluation of NMR spectra using a modular indirect hard modeling (IHM) approach showed good results and flexibility. A second data analysis approach based on artificial neural networks (ANN) was evaluated.Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously, offering new ways to simultaneously evaluating large numbers of different models.
The study, dedicated to Beautiful Pietàs conserved in South Tyrol (Northern Italy), aims to establish, for the first time, a connection between Austroalpine raw materials and the high-fired gypsum mortars constituting the Gothic figure groups in question. The origin and chronology of this stylistically and qualitatively differing ensemble have been subject of art historical debate for nearly a century. The discourse is dominated by three main hypotheses: itinerary of an Austrian artist versus itinerary of the work of art created in an artist’s workshop in Austria versus itinerary of the stylistic vocabulary via graphical or three-dimensional models. The comparison of the δ34S values and the 87Sr/86Sr ratios of the gypsum mortars and Austroalpine sulphate deposits (in a compilation of own reference samples and literature data) points to the exploitation of sediments in the Salzkammergut and possibly also in the evaporite district of the Eastern Calcareous Alps, thus evidencing the import of the sculptures and not the activities of local South Tyrolean or itinerant artists. Two geochronological units are distinguishable: The Pietà in the Church St. Martin in Göflan can be assigned to Upper Permian raw material, whereas the metrologically consistent sculptures in the Church of Our Lady of the Benedictine Abbey Marienberg and in the Chapel St. Ann in Mölten correlate with deposits of the Early Triassic (or the Lower-Middle Triassic transition). The medieval gypsum mortars also differ in their mineralogical characteristics, i.e. in their geologically related minor components, as in the first case, characterised by a significant proportion of primary anhydrite, natural carbonate impurities mainly consist of calcite (partly converted to lime-lump-like aggregates), whereas in the second group dolomite (or rather its hydration products after pyrometamorphic decomposition) predominates, accompanied by celestine, quartz and potassium feldspar. The Pietà in the Cathedral Maria Himmelfahrt in Bozen turned out to be made of Breitenbrunn calcareous sandstone (Leitha Mountains, Burgenland, Austria), which is why the sample is not considered in the geochemical analysis.
Accreditation of analytical methods, either according to GxP or ISO regulations, requires a comprehensive quality management system. General quality documents are often already in place, which need to be extended by method-specific documentation. In this presentation we like to show an idea of a modular set of standard operating procedures (SOP) specifically developed meeting the requirements for quantitative NMR. The future goal is to collaborate with different accreditated NMR laboratories to compile a universal set of SOP and other quality documents that can be modified and used as a starting point for developing your own quality system for applications of qNMR in a regulated environment.
Back Deposition of Titanium Oxides under Laser Ablation of Titanium: Simulation and Experiment
(2022)
Titanium is widely used in medicine for implants and prostheses, thanks to its high biocompatibility, good mechanical properties, and high corrosion resistance. Pure titanium, however, has low wear resistance and may release metallic titanium into surrounding tissues. Structuring and coating its surface with oxide layers are necessary for high wear resistance and improved biocompatibility. In this work, a combination of theoretical and experimental methods was used to study processes responsible for deposition of titanium oxides during ablation of titanium in air.
The deposition process was modeled via the Navier-Stokes equations that accounted for the material removal and accumulation of the deposit on the ablation surface. The chemical part was based on the equilibrium model embedded into the hydrodynamic code. Simulations showed that the most active zone of production of condensed titanium oxides were at plasma periphery whereas a zone of strong condensation of titanium metal was above the molten pool.
In experiment, a pulsed Yb fiber laser was scanned across a titanium surface. The temperature and composition of the plasma were inferred from plasma emission spectra. The post-ablation surface was analyzed by SEM, TEM, STEM, AFM, and XRD.
The developed model well reproduced the main features of experimental data. It was concluded that the deposition of condensed metal oxides from the plasma is a principal mechanism of formation of nanoporous oxide layer on the metal surface. The method of surface structuring and modification by nanosecond laser ablation can be developed into a useful technology that may find applications in medicine, photonics, and other areas.
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds, and the segmented images can be used for automatically extracting and calculating various other particle size and shape descriptors.
The development of an automated miniaturized analytical system that allows for the rapid monitoring of carbamazepine (CBZ) levels in serum and wastewater is proposed. Molecular recognition of CBZ was achieved through its selective interaction with microbeads carrying anti-CBZ antibodies. The proposed method combines the advantages of the micro-bead injection spectroscopy and of the flow-based platform lab-on-valve for implementation of automatic immunosorbent renewal, rendering a new recognition surface for each sample. The sequential (or simultaneous) perfusion of CBZ and the horseradish peroxidase-labelled CBZ through the microbeads is followed by real-time on-column Monitoring of substrate (3,30,5,50-tetramethylbenzidine) oxidation by colorimetry. The evaluation of the initial oxidation rate and also the absorbance value at a fixed time point provided a linear response versus the logarithm of the CBZ concentration. Under the selected assay conditions, a single analysis was completed after only 11 min, with a quantification range between 1.0 and 50 µg L⁻¹. Detection of CBZ levels in undiluted wastewater samples was feasible after a simple filtration step while good recoveries were attained for spiked certified human serum, analyzed without sample clean-up.
The overall interest in nanotoxicity, triggered by the increasing use of nanomaterials in the material and life sciences, and the synthesis of an ever increasing number of new functional nanoparticles calls for standardized test procedures1,2 and for efficient approaches to screen the potential genotoxicity of these materials. Aiming at the development of fast and easy to use, automated microscopic methods for the determination of the genotoxicity of different types of nanoparticles, we assess the potential of the fluorometric γH2AX assay for this purpose. This assay, which can be run on an automated microscopic detection system, relies on the detection of DNA double strand breaks as a sign for genotoxicity3. Here, we provide first results obtained with broadly used nanomaterials like CdSe/CdS and InP/ZnS quantum dots as well as iron oxide, gold, and polymer particles of different surface chemistry with previously tested colloidal stability and different cell lines like Hep-2 and 8E11 cells, which reveal a dependence of the genotoxicity on the chemical composition as well as the surface chemistry of these nanomaterials. These studies will be also used to establish nanomaterials as positive and negative genotoxicity controls or standards for assay performance validation for users of this fluorometric genotoxicity assay. In the future, after proper validation, this microscopic platform technology will be expanded to other typical toxicity assays.
The isotopic analysis of lithium is also relevant to the study of geological phenomena.1 In this work we propose improvements to the method for the isotopic analysis of lithium using a high-resolution continuum source atomic absorption spectrometer (HR-CS-AAS) coupled to a double echelle modular spectrometer (DEMON). 2 This tool for isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←2 2S electronic transition around 670.788 nm. The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm. For the training of the algorithm (XGBoost), a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol-1 was used. Subsequently, the procedure was validated of a set of stock chemicals (Li2CO3, LiNO3, LiCl and LiOH) and a BAM candidate reference material, the cathode material LiNi1/3Mn1/3Co1/3O2 (NMC111). Finally, the ML model was applied to the set of geological samples, previously digested, for the determination of their isotope ratio. The optical resolution was improved from 140,000 to 790,000 to better deconvolution the lithium isotopic components in the atomic spectrum. And the method was compared with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). The results are metrologically comparable.
Asymmetrically bridged aroyl-S,N-ketene acetals and aroyl-S,N-ketene acetal multichromophores can be readily synthesized in consecutive three-, four-, or five-component syntheses in good to excellent yields by several successive Suzuki-couplings of aroyl-S,N-ketene acetals and bis(boronic)acid esters. Different aroyl-S,N-ketene acetals as well as linker molecules yield a library of 23 multichromophores with substitution and linker pattern-tunable emission properties. This allows control of different communication pathways between the chromophores and of aggregation-induced emission (AIE) and energy transfer (ET) properties, providing elaborate aggregation-based fluorescence switches.
To investigate the imaging performance of an elastin-specific molecular magnetic resonance imaging (MRI) probe with respect to the extracellular matrix (ECM) in an experimental hepatic cancer model. Twelve rabbits with hepatic VX2 tumors were examined using 3 T MRI 14, 21, and 28 days after tumor implantation for two subsequent days (gadobutrol, day 1; elastin-specific probe, day 2). The relative enhancement (RE) of segmented tumor regions (central and margin) and the peritumoral matrix was calculated using pre-contrast and delayed-phase T1w sequences. MRI measurements were correlated to histopathology and element-specific and spatially resolved mass spectrometry (MS). Mixed-model analysis was performed to assess the performance of the elastin-specific probe. In comparison to gadobutrol, the elastin probe showed significantly stronger RE, which was pronounced in the tumor margin (day 14–28: P ≤ 0.007). In addition, the elastin probe was superior in discriminating between tumor regions (χ2(4) = 65.87; P < 0.001). MRI-based measurements of the elastin probe significantly correlated with the ex vivo elastinstain (R = .84; P <0 .001) and absolute gadolinium concentrations (ICP-MS: R = .73, P <0 .01). LA-ICP-MS imaging confirmed the colocalization of the elastin-specific probe with elastic fibers. Elastin-specific molecular MRI is superior to non-specific gadolinium-based contrast agents in imaging the ECM of hepatic tumors and the peritumoral tissue.
Atherosclerosis is a progressive inflammatory vascular disease characterized by endothelial dysfunction and plaque burden. Extracellular matrix (ECM)-associated plasma proteins play an important role in disease development. Our magnetic resonance imaging (MRI) study investigates the feasibility of using two different molecular MRI probes for the simultaneous assessment of ECM-associated intraplaque albumin deposits caused by endothelial damage and progressive inflammation in atherosclerosis. Male apolipoprotein E-deficient (ApoE-/-)-mice were fed a high-fat diet (HFD) for 2 or 4 months. Another ApoE-/--group was treated with pravastatin and received a HFD for 4 months. T1- and T2*-weighted MRI was performed before and after albumin-specific MRI probe (gadofosveset) administration and a macrophage-specific contrast agent (ferumoxytol). Thereafter, laser ablation inductively coupled plasma mass spectrometry and histology were performed. With advancing atherosclerosis, albumin-based MRI signal enhancement and ferumoxytol-induced signal loss areas in T2*-weighted MRI increased. Significant correlations between contrast-to-noise-ratio (CNR) post-gadofosveset and albumin stain (R2 = 0.78, p < 0.05), and signal loss areas in T2*-weighted MRI with Perls’ Prussian blue stain (R2 = 0.83, p < 0.05) were observed. No interference of ferumoxytol with gadofosveset enhancement was detectable. Pravastatin led to decreased inflammation and intraplaque albumin. Multi-target MRI combining ferumoxytol and gadofosveset is a promising method to improve diagnosis and treatment monitoring in atherosclerosis.
Luminescent semiconductor quantum dots (QDs) are frequently used in the life and material sciences as reporter for bioimaging studies and as active components in devices such as displays, light-emitting diodes, solar cells, and sensors. Increasing concerns regarding the use of toxic elements like cadmium and lead, and hazardous organic solvents during QD synthesis have meanwhile triggered the search for heavy-metal free QDs using green chemistry syntheses methods. Interesting candidates are ternary AgInS2 (AIS) QDs that exhibit broad photoluminescence (PL) bands, large effective Stokes shifts, high PL quantum yields (PL QYs), and long PL lifetimes, which are particularly beneficial for applications such as bioimaging, white light-emitting diodes, and solar concentrators. In addition, these nanomaterials can be prepared in high quality with a microwave-assisted (MW) synthesis in aqueous solution. The homogeneous heat diffusion and instant temperature rise of the MW synthesis enables a better control of QD nucleation and growth and thus increases the batch-to-batch reproducibility. In this study, we systematically explored the MW synthesis of AIS/ZnS QDs by varying parameters such as the order of reagent addition, precursor concentration, and type of stabilizing thiol ligand, and assessed their influence on the optical properties of the resulting AIS/ZnS QDs. Under optimized synthesis conditions, water-soluble AIS/ZnS QDs with a PL QY of 65% and excellent colloidal and long-term stability could be reproducible prepared.
To establish the SI traceability of the element content w(Hg) of a gravimetrically prepared 1 g/kg mercury solution, the latter was compared to a primary reference solution by means of high accuracy inductively coupled plasma optical emission spectrometry (ICP OES) measurements. For this purpose, the ICP OES bracketing method previously described [1] was improved to yield a relative expanded uncertainty of the mercury element content of Urel(w(Hg)) = 0.5 % (with k = 2) associated with the comparison of two monoelemental solutions. In case of mercury, such a small uncertainty was achieved for the first time. Before, in general, such small uncertainties were only reported applying isotope dilution methods performed with MC-ICP-MS. However, for mercury solutions at this concentration range, several dilution steps are necessary to prepare the samples for ID-MC-ICP-MS. The sum of the uncertainty contributions stemming from the dilution steps, as well as the intrinsic difficulties of measuring mercury at low concentrations, result in an overall uncertainty of the ICP-MS measurements, which is comparable to or even larger than those, achieved with the ICP OES method applied. We will present details of the sample preparation as well as of the dedicated ICP OES measurement approach, which were crucial to achieve such a small measurement uncertainty.
The newly developed method was successfully applied in the context of the development and production of elemental solution chemical reference standards (CRS), which are distributed by the EDQM. The CRS are intended to support measurements required by the European Pharmacopoeia, which has recently incorporated a new international guideline for the control of elemental impurities in medicinal products.
Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are valuable analytical and quality control methods for most industrial chemical processes as they provide information on the concentrations of individual compounds and by-products. These processes are traditionally carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been realized to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra, to train an ANN with better prediction performance and speed than state-of-the-art analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Arraying of single cells for mass spectrometric analysis is a considerable bioanalytical challenge. In this study, we employ a novel single cell arraying technology for quantitative analysis and isotopic fingerprinting by laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS). The single cell arraying approach is based on a piezo-acoustic microarrayer with software for automated optical detection of cells within the piezo dispense capillary (PDC) prior to arraying. Using optimized parameters, single cell occupancy of >99%, high throughput (up to 550 cells per hour), and a high cell recovery of >66% is achieved. LA-ICP-TOF-MS is employed to detect naturally occurring isotopes in the whole mass range as fingerprints of individual cells. Moreover, precise quantitative determination of metal-containing cell dyes is possible down to contents of ∼100 ag using calibration standards which were produced using the same arrayer.
The visualization of index-of-refraction (IoR) distribution is one of the common methods to investigate fluid flow or pressure fields. While schlieren and shadowgraphy imaging techniques are widely accepted, their inherent limitations often lead to difficulties in elucidating the IoR distribution and extracting the true IoR information from the resulting images. While sophisticated solutions exist, the IoR-gradient-to-image was achieved by purposely introducing a commonly avoided “defect” into the optical path of a conventional coincident schlieren/shadowgraphy setup; the defect is a combination of slight defocusing and the use of non-conjugate optical components. As such, the method presented in this work is referred to as defocusing shadowgraphy, or DF-shadowgraphy. While retaining the ease of a conventional schlieren/shadowgraphy geometry, this DF approach allows direct visualization of complicated resonant acoustic fields even without any data processing. For instance, the transient acoustic fields of a common linear acoustic resonator and a two-dimensional one were directly visualized without inversion. Moreover, the optical process involved in DF-shadowgraphy was investigated from a theoretical perspective. A numerical solution of the sophisticated impulse response function was obtained, which converts the phase distortion into intensity distributions. Based on this solution, the IoRs of various gas streams (e.g., CO2 and isopropanol vapor) were determined from single images.
Bioanalytical, diagnostic, and security applications require the fast and sensitive determination of a steadily increasing number of analytes or events in parallel in a broad variety of detection formats and increased sensitivities. This – flanked by recent technical advancements and the availability of simple to use, commercial time-resolved photoluminescence measuring devices at reasonable costs - calls for the exploitation of the species- and environment-specific photoluminescence parameter luminescence lifetime. In this context, time-resolved photoluminescence measurements of different classes of molecular and nanocrystalline emitter and luminescent particles in different time windows are presented and examples for applications such as lifetime multiplexing and barcoding in conjunction with fluorescence lifetime imaging microscopy (FLIM) and flow cytometry are given.
An alternative method for lithium isotope analysis by using high-resolution atomic absorption spectrometry (HR-CS-AAS) is proposed herein. This method is based on monitoring the isotope shift of approximately 15 pm for the electronic transition 22P←22S at around the wavelength of 670.8 nm, which can be measured by state-of-the-art HR-CS-AAS. Isotope analysis can be used for (i) the traceable determination of Li concentration and (ii) isotope amount ratio analysis based on a combination of HR-CS-AAS and spectral data analysis by machine learning (ML).
In the first case, the Li spectra are described as the linear superposition of the contributions of the respective isotopes, each consisting of a spin-orbit doublet, which can be expressed as Gaussian components with constant spectral position and width and different relative intensity, reflecting the isotope ratio in the sample. Precision was further improved by using lanthanum as internal spectral standard. The procedure has been validated using human serum-certified reference materials. The results are metrologically comparable and compatible with the certified values.
In the second case, for isotope amount ratio analysis, a scalable tree boosting ML algorithm (XGBoost) was employed and calibrated using a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol mol−1. The training ML model was validated with certified reference materials. The procedure was applied to the isotope amount ratio determination of a set of stock chemicals and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. These determinations were compared with those obtained by MC-ICP-MS and found to be metrologically comparable and compatible. The residual bias was −1.8‰, and the precision obtained ranged from 1.9‰ to 6.2‰. This precision was sufficient to resolve naturally occurring variations. The NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification to assess its suitability for technical applications. The results obtained were metrologically compatible with each other.
Two calibration-free LIBS techniques are used for the quantitative analysis of synthetic cement samples: the CF-LIBS based on the Boltzmann plot method and the Monte Carlo (MC) LIBS based on the iterative spectrum fitting. In CF-LIBS, the inverse problem is solved, i.e. the elemental concentrations are determined by the reconstruction of plasma parameters from spectra. The MC-LIBS technique solves the direct problem by finding the highest correlation between the model-generated and experimental spectrum. The accuracy of both calibration-free LIBS methods suffers from factors such as inaccurately determined instrumental function, the deviation of experimental plasma from the mathematical model used, not taking into account the collection geometry and from the uncertainty of spectroscopic data. Therefore, the both calibration-free LIBS approaches are applied to synthetic spectra which perfectly suit the mathematical model of the method. This test yields the accuracy of both the approaches for the ideal case. In addition, the accuracy of both methods is investigated for non-isothermal plasma, because real laser-induced plasma often has high gradients in temperature. Both methods assume an isothermal plasma.
Two calibration-free (CF) LIBS approaches are used for the quantitative analysis of cement samples: the CF-LIBS based on the Boltzmann plot method and the Monte Carlo (MC) LIBS based on the iterative spectrum fitting. In CF-LIBS, the inverse problem is solved, i.e. the elemental concentrations are determined by the reconstruction of plasma parameters from spectra. The MC-LIBS technique solves the direct problem by finding the highest correlation between the model-generated and experimental spectrum. The accuracy of both calibration-free LIBS methods suffers from factors such as inaccurately determined instrumental function, the deviation of experimental plasma from the mathematical model used, not taking into account the collection geometry, and from the uncertainty of spectroscopic data. The both calibration-free LIBS approaches are first applied to synthetic spectra which perfectly suit the mathematical model of the method, i.e. the model of the uniform, isothermal, and stationary plasma. This test yields the accuracy of both the approaches for the ideal case. In addition, the accuracy of both the methods is investigated for non-uniform and non-isothermal plasma, because real laser-induced plasma often has high gradients in temperature and particle number densities. Finally, both calibration-free LIBS approaches are applied to experimental spectra obtained from cement samples. The figures of merits of two approaches are compared when working with both synthetic and experimental spectra.
Spatial Heterodyne Spectroscopy (SHS) is a spectrometric technique that combines both dispersive and interferometric features into a customizable instrument. The Basis of SHS is a Michelson interferometer with its mirrors replaced by diffraction gratings and with no moving parts. The output signal from SHS is the interferogram, which is recorded with a 1D or 2D pixel array detector. The spatial periodicity of the fringes on the interferogram is a function of the wavelength of the diffracted light. Using the Fast Fourier Transform, the original optical spectrum that enters SHS is retrieved. The light that is analyzed by SHS can come from a variety of sources. In our work, we used Raman scattering and Laser-Induced Plasma to perform quantitative and qualitative analyses. Figure 1 compares the performance of the SHS with that of high Resolution echelle and portable low-resolution asymmetrically crossed Czerny-Turner spectrometers (OO in Fig.1). The analyzed light came from the plasma induced on a stainless-steel reference material. The SHS exhibits the resolution comparable to that of the echelle spectrometer used, about 8000. Due to a high throughput of the SHS (theoretically, ~200 times higher than that of grating instruments), the number of spectra needed to be accumulated for comparable signal-to-noise ratios is much smaller than in the case of the echelle and comparable to OO spectrometers.
Examples of Raman SHS applied to several pure liquids are given in Fig. 2. Raman SHS was used in three different settings: (i) for classification of six types of oils, (ii) for univariate/multivariate analysis of binary mixture cyclohexane-isopropanol, and (iii) for multivariate analysis of glycerol solution in water. For the last two settings, chemometric analysis of the spectra yielded linear calibration plots over the range 1-90% of concentrations of isopropanol in cyclohexane, and 0.5-10% of glycerol in water.
The antimicrobial photodynamic approach has been demonstrated as an efficient and sustainable process for the eradication of microbial pathogens. In this work, silica-coated Magnetite nanoparticles (NPs) were used as carriers of glycosylated porphyrins and phthalocyanines. Their subsequent cationization
resulted in the production of stable antimicrobial photosensitizing materials, effective against E. coli. Suspensions of the photocatalysts in water present bimodal size distributions formed by big clusters and small NPs with hydrodynamic diameters between 8 and 38 nm. The presence of small NPs in the suspensions is related to an effective photodynamic inactivation (PDI) of E. coli cells. Glycosylation of the PS showed a positive effect on the PDI performance, which could be related to a higher accumulation of the photocatalyst over the bacterial cell membrane. In addition, these biocidal agents proved to be photostable and their photoactive performance decreased only between 23% and 28% upon 5 PDI cycles, mostly because of the loss of material between cycles, which makes them promising materials for water disinfection purposes.
The primary screening of hybridoma cells is a time-critical and laborious step during the development of monoclonal antibodies. Often critical errors occur in this phase, which supports the notion that the generation of monoclonal antibodies with hybridoma technology is difficult to control and hence a risky venture. We think that it is crucial to improve the screening process to eliminate most of the immanent deficits of the conventional approach. With this new microarray-based procedure, several advances could be achieved: Selectivity for excellent binders, high throughput, reproducible signals, avoidance of misleading avidity (multivalency) effects, and simultaneous performance of competition experiments. The latter can directly be used to select clones of desired cross-reactivity properties. In this paper, a model system with two excellent clones against carbamazepine, two weak clones and blank supernatant has been designed to examine the effectiveness of the new system. The excellent clones could be detected largely independent of the IgG concentration, which is unknown during the clone screening since the determination and subsequent adjustment of the antibody concentration is not possible in most cases. Furthermore, in this approach, the enrichment, isolation, and purification of IgG for characterization is not necessary. Raw cell culture supernatant can be used directly, even when fetal calf serum (FCS) or other complex media had been used. In addition, an improved method for the oriented antibody-immobilization on epoxy-silanized slides is presented. Based on the results of this model system, we conclude that this approach should be preferable to most other protocols leading to many of false positives, causing expensive and lengthy confirmation steps to weed out the poor clones.
Probe 1, which contains an anilinopyridine chromophore and an azaoxa macrocyclic subunit, presented an absorption band centered at 340 nm in acetonitrile. Addition of Fe(III), Cr(III) and Hg(II) induced the growth of a new absorption band at 430 nm (with color change from colorless to yellow), whereas in the presence of Cu(II), Zn(II) and Pb(II), less marked changes were observed. The color changes observed upon addition of Fe(III), Cr(III) and Hg(II) were ascribed to the formation of 1:1 stoichiometry complexes with probe 1. Coordination of Fe(III), Cr(III) and Hg(II) with the pyridine fragment of 1 induced an enhancement of the charge transfer character accompanied with a marked bathochromic shift that was reflected in a color change from colorless to yellow. The strength of the interaction between probe 1 and Fe(III) cation was modulated upon interaction with anions. Of all the anions tested, only cyanide was able to induce the bleaching of the yellow 1·Fe(III) complex solution. This bleaching was ascribed to
the formation of 1·Fe(III)-CN complex that restored, to some extent, the optical features of the free probe allowing the chromogenic sensing of cyanide. Besides, 1·Fe(III) complex was used to detect
cyanide in acetonitrile-water 90:10 v/v mixtures with good recoveries.
Functional nanomaterials (NM) of different size, shape, chemical composition, and surface chemistry are of increasing relevance for many key technologies of the twenty-first century. This includes polymer and silica or silica-coated nanoparticles (NP) with covalently bound surface groups, semiconductor quantum dots (QD), metal and metal oxide NP, and lanthanide-based NP with coordinatively or electrostatically bound ligands, as well as surface-coated nanostructures like micellar encapsulated NP. The surface chemistry can significantly affect the physicochemical properties of NM, their charge, their processability and performance, as well as their impact on human health and the environment. Thus, analytical methods for the characterization of NM surface chemistry regarding chemical identification, quantification, and accessibility of functional groups (FG) and surface ligands bearing such FG are of increasing importance for quality control of NM synthesis up to nanosafety. Here, we provide an overview of analytical methods for FG analysis and quantification with special emphasis on bioanalytically relevant FG broadly utilized for the covalent attachment of biomolecules like proteins, peptides, and oligonucleotides and address methodand material-related challenges and limitations. Analytical techniques reviewed include electrochemical titration methods, optical assays, nuclear magnetic resonance and vibrational spectroscopy, as well as X-ray based and thermal analysis methods, covering the last 5–10 years. Criteria for method classification and evaluation include the need for a signal-generating label, provision of either the total or derivatizable number of FG, need for expensive instrumentation, and suitability for process and production control during NM synthesis and functionalization.
Working towards a comprehensive understanding of introduction pathways, number, and fate of micro¬plastics in the environment, suitable analytical methods are a precondition. Micro-spectroscopic methods are probably the most widely used techniques. Besides their ability to measure single spectra of a particle or fiber, most modern FTIR- and Raman microscopes are also capable of two-dimensional imaging. This is very appealing to microplastics research because it allows to simultaneously characterize the analytes chemically as well as their size (distribution) and shape.
Two-dimensional imaging on extensive sample areas with FTIR-micros¬copes is facilitated by focal plane array (FPA) detectors resulting in large data sets comprised of up to several million spectra. With numbers too large for manual inspection of each individual spectrum, automated data evaluation is inevitable. Identifying different polymers based on the comparison with known reference spectra (library search) has proven to be a suitable approach. For that purpose, FTIR-spectra of common plastics can be collected to create an individual reference library.
To Supplement this ‘targeted analysis’, looking for known substances via library search, an exploratory approach was tested. Principal component analysis (PCA) proved to be a helpful tool to drastically reduce the size of the data set while maintaining the significant information. Subsequently, cluster analysis was used to find groups of similar spectra. Spectra found in different clusters could be assigned to different polymer types. The variation observed within clusters gives a hint on chemical variability of microplastics of the same polymer found in the sample. Spectra labeled according to the respective cluster/polymer type were used to build a classification model which allowed to quickly predict the polymer type based on the FTIR spectrum. Classification was tested on a second, independent data set and results were compared to the spectral library search procedure.