Analytische Chemie
Filtern
Erscheinungsjahr
Dokumenttyp
Sprache
- Englisch (1695)
- Deutsch (24)
- Mehrsprachig (3)
- Polnisch (1)
Referierte Publikation
- ja (1723) (entfernen)
Schlagworte
- Fluorescence (121)
- Quantum yield (76)
- Nanoparticles (56)
- Mechanochemistry (53)
- Sensor (49)
- Nanoparticle (46)
- XPS (44)
- Lifetime (43)
- Dye (41)
- Nano (41)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (544)
- 6 Materialchemie (361)
- 8 Zerstörungsfreie Prüfung (291)
- 6.3 Strukturanalytik (157)
- 1.2 Biophotonik (129)
- 6.1 Oberflächen- und Dünnschichtanalyse (124)
- 1.1 Anorganische Spurenanalytik (109)
- 1.9 Chemische und optische Sensorik (80)
- 8.0 Abteilungsleitung und andere (75)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (73)
Paper des Monats
- ja (29)
Terrestrial mud volcanoes are unique structures driven by tectonic pressure and fluids from the deep subsurface. These structures are mainly found in active tectonic zones, such as the area near the Los Bajos Fault in Trinidad. Here we report a chemical and microbiological characterization of three mud volcanoes, which included analyses of multiple liquid and solid samples from the mud volcanoes. Our study confirms previous suggestions that at least some of the mud volcano fluids are a mixture of deeper salt-rich water and surficial/precipitation water. No apparent water quality differences were found between sampling sites north and south of a major geological fault line. Microbiological analyses revealed diverse communities, both aerobic and anaerobic, including sulfate reducers, methanogens, carbon dioxide fixing and denitrifying bacteria. Several identified species were halophilic and likely derived from the deeper salt-rich subsurface water, while we also cultivated pathogenic species from the Vibrionaceae, Enterobacteriaceae, Shewanellaceae, and Clostridiaceae. These microorganisms were likely introduced into the mud volcano fluids both from surface water or shallow ground-water, and perhaps to a more minor degree by rain water. The identified pathogens are a major health concern that needs to be addressed.
The adsorption behavior of Platinum nanoparticles was studied for the as-received catalyst (under inert gas), under hydrogen and CO atmosphere using our newly designed in-situ cell. X-ray Absorption Spectroscopy (XAS) and Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) experiments were performed simultaneously with high data quality. Structural information and the type of adsorbate could be revealed via Extended X-ray Absorption Fine Structure (EXAFS) analysis, Dl X-ray Absorption Near Edge Structure analysis (Dl XANES) and in-situ DRIFTS. The as-received catalyst showed sub-surface oxygen and O(n-fold). Under CO atmosphere only CO(atop) was found. Reversible adsorbate induced changes of the Pt nanoparticle structure were derived from changes in the PtAPt coordination number and the corresponding bond distance. Under reducing conditions (H2, CO) a significant increase in both values occurred. Temperature dependent desorption of CO revealed a gradual shift from PtACO to PtAO. Reoxidation was clearly assigned to strong metal support interaction from the SiO2 support.
The mechanochemical formation of the ionic cocrystals of glucose (Glc) and sodium salts Glc2NaCl·H2O (1) and Glc2NaX (X = Br (2), I (3)) is presented. Products are formed by co-milling Glc with three sodium salts (NaCl, NaBr, NaI). The ionic cocrystals were obtained under both neat grinding and liquid-assisted grinding conditions, the later found to accelerate the reaction kinetics. The crystal structures of the ionic cocrystals (2) and (3) were solved from powder X-ray diffraction data. The structure solution contrasts with the structure of Glc2NaCl·H2O (1) where the electron density at three halide crystallographic sites is modeled as of being the intermediate between water molecule and a chloride ion. The reaction pathways of the three ionic cocrystals were investigated in real time using our tandem approach comprising a combination of in situ synchrotron powder X-ray diffraction and Raman spectroscopy. The results indicate the rapid formation of each cocrystal directly from their respective starting materials without any intermediate moiety formation. The products were further characterized by DTA-TG and elemental analysis.
A comparative study on the performance of digital detector systems for high energy applications
(2014)
For cast components reaching or exceeding total material thicknesses of 150mm, high energy sources such as linear accelerators or Betatrons are required in order to obtain reasonable exposure times. In this study, the performance of digital detector systems, involving imaging plates (IP) and digital detector arrays (DDA), was evaluated with respect to the testing class B requirements as formulated in the standard EN ISO 17636-2. As a reference, traditional radiographic film and a Cobalt-60 source was used. With film exposures, testing class B was achieved with Co-60 and Betatron (7.5 MV) at longer exposure times. The preliminary results show that the testing class B was not obtained with the examined digital detector arrays (DDA) and the high resolution imaging plates (IP) , even at 40, 60 and 80 minutes exposure time with a 7.5 MV Betatron. Class A was achieved using high resolution imaging plates with optimized metal filters between object and IPs and a high resolution DDA with intermediate Cu filters. Class A was also achieved applying a DDA with lower basic spatial resolution than required by Table B.13 of EN ISO 17636-2, but using the compensation principle as described in this standard. The next generation of digital detector arrays might potentially be able to obtain class B performance with the expected spatial resolution and sensitivity improvements.
Trace element concentrations in gold grains from various geological units in South Africa were measured in situ by field emission-electron probe microanalysis (FE-EPMA), laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) and synchrotron micro X-ray fluorescence spectroscopy (SR-µ-XRF). This study assesses the accuracy, precision and detection limits of these mostly non-destructive analytical methods using certified reference materials and discusses their application in natural sample measurement. FE-EPMA point analyses yielded reproducible and discernible concentrations for Au and trace concentrations of S, Cu, Ti, Hg, Fe and Ni, with detection limits well below the actual concentrations in the gold. LA-ICP-MS analyses required larger gold particles (> 60 µm) to avoid contamination during measurement. Elements that measured above detection limits included Ag, Cu, Ti, Fe, Pt, Pd, Mn, Cr, Ni, Sn, Hg, Pb, As and Te, which can be used for geochemical characterisation and gold fingerprinting. Although LA-ICP-MS measurements had lower detection limits, precision was lower than FE-EPMA and SR-µ-XRF. The higher variability in absolute values measured by LA-ICP-MS, possibly due to micro-inclusions, had to be critically assessed. Non-destructive point analyses of gold alloys by SR-µ-XRF revealed Ag, Fe, Cu, Ni, Pb, Ti, Sb, U, Cr, Co, As, Y and Zr in the various gold samples. Detection limits were mostly lower than those for elements measured by FE-EPMA, but higher than those for elements measured by LA-ICP-MS.
This work addresses the identification of synthetic organic pigments (SOP) in eight modern reverse paintings on glass (1913–1946) by means of an in-situ multi-analytical approach. We combined the complementary properties of mobile Raman spectroscopy and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) to overcome the main disadvantages of each method: extensive band overlapping in DRIFT spectra and fluorescence problems in Raman spectra. A collection of DRIFTS reference spectra enables a precise pigment identification by DRIFTS and establishes this method as a serious non-destructive alternative for the identification of SOP. The group of β-naphthol pigments yielded valuable results for both methods, whereas synthetic alizarin (PR83) was preferentially detected by DRIFTS. Finally, uncommon triaryl carbonium pigments and two azo group-based yellows were identified in the paintings by means of Raman spectroscopy.
Metaproteomics, the study of the collective protein composition of multi-organism systems, provides deep insights into the biodiversity of microbial communities and the complex functional interplay between microbes and their hosts or environment. Thus, metaproteomics has become an indispensable tool in various fields such as microbiology and related medical applications. The computational challenges in the analysis of corresponding datasets differ from those of pure-culture proteomics, e.g., due to the higher complexity of the samples and the larger reference databases demanding specific computing pipelines. Corresponding data analyses usually consist of numerous manual steps that must be closely synchronized. With MetaProteomeAnalyzer and Prophane, we have established two open-source software solutions specifically developed and optimized for metaproteomics. Among other features, peptide-spectrum matching is improved by combining different search engines and, compared to similar tools, metaproteome annotation benefits from the most comprehensive set of available databases (such as NCBI, UniProt, EggNOG, PFAM, and CAZy). The workflow described in this protocol combines both tools and leads the user through the entire data analysis process, including protein database creation, database search, protein grouping and annotation, and results visualization. To the best of our knowledge, this protocol presents the most comprehensive, detailed and flexible guide to metaproteomics data analysis to date. While beginners are provided with robust, easy-to-use, state-of-the-art data analysis in a reasonable time (a few hours, depending on, among other factors, the protein database size and the number of identified peptides and inferred proteins), advanced users benefit from the flexibility and adaptability of the workflow.
It is shown that preconditioning of experimental X‐ray computed tomography (XCT) data is critical to achieve high‐precision segmentation scores. The challenging experimental XCT datasets and deep convolutional neural networks (DCNNs) are used that are trained with low‐resemblance synthetic XCT data. The material used is a 6‐phase Al–Si metal matrix composite‐reinforced with ceramic fibers and particles. To achieve generalization, in our past studies, specific data augmentation techniques were proposed for the synthetic XCT training data. In addition, two toolsets are devised: (1) special 3D DCNN architecture (3D Triple_UNet), slicing the experimental XCT data from multiple views (MultiView Forwarding), the i.S.Sy.Da.T.A. iterative segmentation algorithm, and (2) nonlocal means (NLM) conditioning (filtering) for the experimental XCT data. This results in good segmentation Dice scores across all phases compared to more standard approaches (i.e., standard UNet architecture, single view slicing, standard single training, and NLM conditioning). Herein, the NLM filter is replaced with the deep conditioning framework BAM SynthCOND introduced in a previous publication, which can be trained with synthetic XCT data. This leads to a significant segmentation precision increase for all phases. The proposed methods are potentially applicable to other materials and imaging techniques.
Lake Magadi, East African Rift Valley, is a hyperalkaline and saline soda lake highly enriched in Na+, K+, CO32–, Cl–, HCO3–, and SiO2 and depleted in Ca2+ and Mg2+, where thick evaporite deposits and siliceous sediments have been forming for 100 000 years. The hydrogeochemistry and the evaporite deposits of soda lakes are subjects of growing interest in paleoclimatology, astrobiology, and planetary sciences. In Lake Magadi, different hydrates of sodium carbonate/bicarbonate and other saline minerals precipitate. The precipitation sequence of these minerals is a key for understanding the hydrochemical evolution, the paleoenvironmental conditions of ancient evaporite deposits, and industrial crystallization. However, accurate determination of the precipitation sequence of these minerals was challenging due to the dependency of the different hydrates on temperature, water activity, pH and pCO2, which could induce phase transformation and secondary mineral precipitation during sample handling. Here, we report a comprehensive methodology applied for monitoring the evaporitic mineral precipitation and hydrochemical evolution of Lake Magadi. Evaporation and mineral precipitations were monitored by using in situ video microscopy and synchrotron X-ray diffraction of acoustically levitated droplets. The mineral patterns were characterized by ex situ Raman spectroscopy, X-ray diffraction, and scanning electron microscopy. Experiments were coupled with thermodynamic models to understand the evaporation and precipitation-driven hydrochemical evolution of brines. Our results closely reproduced the mineral assemblages, patterns, and textural relations observed in the natural setting. Alkaline earth carbonates and fluorite were predicted to precipitate first followed by siliceous sediments. Among the salts, dendritic and acicular trona precipitate first via fractional crystallization─reminiscent of grasslike trona layers of Lake Magadi. Halite/villiaumite, thermonatrite, and sylvite precipitate sequentially after trona from residual brines depleted in HCO3–. The precipitation of these minerals between trona crystals resembles the precipitation process observed in the interstitial brines of the trona layers. Thermonatrite precipitation began after trona equilibrated with the residual brines due to the absence of excess CO2 input. We have shown that evaporation and mineral precipitation are the major drivers for the formation of hyperalkaline, saline, and SiO2-rich brines. The discrepancy between predicted and actual sulfate and phosphate ion concentrations implies the biological cycling of these ions. The combination of different in situ and ex situ methods and modeling is key to understanding the mineral phases, precipitation sequences, and textural relations of modern and ancient evaporite deposits. The synergy of these methods could be applicable in industrial crystallization and natural brines to reconstruct the hydrogeochemical and hydroclimatic conditions of soda lakes, evaporite settings, and potentially soda oceans of early Earth and extraterrestrial planets.
An auto-validation tool for the reliability quantification of materials integrated fiber Bragg grating (FBG) strain sensors have been developed and tested. The FBG strain sensor was jacketed with a magnetostrictive layer based on iron-nickel which, when excited by a specific magnetic field, adds an artificial strain to the sensor. The fixed relationship between magnetic induction and wavelength shift of the FBG strain sensor characterizes the bond strength and adhesion between the sensor and the surrounding structure. Due to an easily applicable magnetic field, it is possible to validate the sensor performance in a non-contact, fast way without disturbing the data-acquisition process.