TY - JOUR A1 - Fink, Friedrich A1 - Emmerling, Franziska A1 - Falkenhagen, Jana T1 - Identification and Classification of Technical Lignins by means of Principle Component Analysis and k-Nearest Neighbor Algorithm JF - Chemistry-Methods N2 - The characterization of technical lignins is a key step for the efficient use and processing of this material into valuable chemicals and for quality control. In this study 31 lignin samples were prepared from different biomass sources (hardwood, softwood, straw, grass) and different pulping processes (sulfite, Kraft, organosolv). Each lignin was analysed by attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy. Statistical analysis of the ATR-FT-IR spectra by means of principal component analysis (PCA) showed significant differences between the lignins. Hence, the samples can be separated by PCA according to the original biomass. The differences observed in the ATR-FT-IR spectra result primarily from the relative ratios of the p-hydroxyphenyl, guaiacyl and syringyl units. Only limited influence of the pulping process is reflected by the spectral data. The spectra do not differ between samples processed by Kraft or organosolv processes. Lignosulfonates are clearly distinguishable by ATR-FT-IR from the other samples. For the classification a model was created using the k-nearest neighbor (k NN) algorithm. Different data pretreatment steps were compared for k=1…20. For validation purposes, a 5-fold cross-validation was chosen and the different quality criteria Accuracy (Acc), Error Rate (Err), Sensitivity (TPR) and specificity (TNR) were introduced. The optimized model for k=4 gives values for Acc = 98.9 %, Err = 1.1 %, TPR = 99.2 % and TNR = 99.6 %. KW - Classification KW - PCA KW - K-nearest neighbor KW - FT-IR KW - Technical lignin PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-533855 DO - https://doi.org/10.1002/cmtd.202100028 VL - 1 IS - 8 SP - 350 EP - 396 PB - Wiley-VCH GmbH AN - OPUS4-53385 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Sobol, Oded T1 - Observations of the deuterium distribution and the structural changes in standard and lean duplex stainless steels by ToF-SIMS and EBSD N2 - Duplex (DSS) and austenitic stainless steels (ASS) are frequently used in many energy related applications. The duplex grade is considered to have outstanding mechanical properties as well as good corrosion resistance. The austenitic phase combines high ductility, even at low temperatures, with sufficient strength, and therefore such materials are applied in storage and transport of high-pressure hydrogen. During service in acidic environments large amounts of hydrogen can ingress into the microstructure and induce many changes in the mechanical properties of the steel. Embrittlement of steels by hydrogen remains unclear even though this topic has been intensively studied for several decades. The reason for that lies in the inability to validate the proposed theoretical models in the sub-micron scale. Among the very few available methods nowadays, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) enables a highly accurate mapping of hydrogen in the microstructure in a spatial resolution below 100 nm. In the present work ToF-SIMS was used as a main tool in order to investigate the effect of deuterium on a duplex microstructure of lean and standard DSSs during and after the electrochemical charging process. Electrochemical charging simulates the service of a component in acidic environments under conditions of cathodic protection that are commonly applied to prevent corrosion reactions. ToF-SIMS after multivariate data analysis (MVA) was combined with high resolution topographic images and electron back-scattered diffraction (EBSD) data to characterize the structural changes. It was observed that the ferritic phase was affected almost identical in all steels whereas in the austenitic phase significant differences were obtained in the lean duplex in comparison to the standard DSS. The obtained results have been compared to similar investigations on a AISI 304L austenitic stainless steel. The advantage of the combined techniques is reflected by the ability to correlate the hydrogen distribution in the microstructure and the resulted phase transformation. T2 - Third International Conference on Metals & Hydrogen CY - Ghent, Belgien DA - 29.05.2018 KW - Data-fusion KW - ToF-SIMS KW - PCA KW - DSS KW - LDX KW - EBSD PY - 2018 AN - OPUS4-45094 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Heinrich, Thomas A1 - Müller, Anja A1 - Schneider, Markus A1 - Sparnacci, Katja A1 - Unger, Wolfgang T1 - Chemical characterisation and classification of (Core-Shell) nanoparticles using PCA assisted ToF-SIMS N2 - The analysis of nanomaterials is currently an important task - especially in case of risk assessment – as the properties of these material class are not well understood and their growing use in everyday life. The rather high surface area of these objects renders their interactions significantly different to their corresponding bulk. Thus, the surface’s chemical composition must be investigated to get a better understanding and prediction of the nanomaterials’ behaviour. ToF-SIMS and XPS have proven to be powerful tools to determine the general chemical composition. The superior surface sensitivity of ToF-SIMS furthermore allows us to study mainly the utmost atomic layers and thus gives us an idea of possible interactions involved. Supported by multivariate data analysis such as principal component analysis (PCA), the method can also be used for sub-classification of different materials using slight differences in surface chemistry. Here, we present data of the analysis of Hyflon®-polystyrene core-shell nanoparticles which can be used as a model system due to the known preparation and a rather good chemical as well as physical separation of core and shell. Principle component analysis (PCA) will be used to detect the influence of sample preparation and for a better separation of different samples. This is achieved by measurement of a statistically relevant set of samples for every particle sample. We acquired surface spectra under static SIMS conditions with Bi32+ and analysed the resulting spectra by PCA. The carefully selected and refined peaks allow a reasonable categorization and further a reliable allocation of blank feeds. In detail, the fluorine containing, organic fragments are an indication for a heterogeneous shell that has errors. Furthermore, results on Au nanoparticles with and without an antibody shell are presented. ToF-SIMS imaging is desired to be implemented for single particle detection as well. T2 - SIMS-Europe CY - Münster, Germany DA - 16.09.2018 KW - Nanoparticles KW - ToF-SIMS KW - XPS KW - PCA KW - Titania KW - Core-Shell PY - 2018 AN - OPUS4-46249 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Heinrich, Thomas A1 - Schneider, Markus A1 - Schäpe, Kaija A1 - Unger, Wolfgang A1 - Stockmann, Jörg M. T1 - Classification of engineered Titania nanomaterials via surface analysis using principal component analysis (PCA) assisted Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) N2 - Due to the growing number of engineered nanomaterials (NM) the need for a reliable risk assessment for these materials is today bigger than ever before. Especially the nanomaterial’s surface or shell directly interacts with its environment and therefore is a crucial factor for NM’ toxicity or functionality. Especially, titania is one of the NM with the greatest technological importance. It is used for a large number of applications and can be found in food, cosmetics, glasses, mirrors, paints to mention only a few. In 2012, experts estimate[d] the annual European nano-titania production or utilization at an amount of more than 10,000 t. Great progress has been achieved in the area of NM investigation and characterization during the past decade. A variety of publications provide information about technological innovation as well as hazard potential, which means the potential risk on human health and ecosystems. However, enhanced data harmonization and well-defined standards for nanomaterial analysis, could significantly improve the reliability of such studies which often suffers from varying methods, parameters and sample preparations. To develop a suitable approach for the NM’s risk assessment, the ACEnano project aims at establishing a toolbox of verified methods. The size of this well-structured European project allows to handle even those big challenges like data harmonization and standardization. Due to its powerful combination of superior surface sensitivity and lateral resolution down to the Nano regime, ToF-SIMS could become one of these toolbox methods. Supported by multivariate data analysis such as principal component analysis (PCA), the method can be used for sub-classification of nanomaterial families using slight differences in surface chemistry. Here, we show a PCA supported classification of titania nanoparticles from various sources (NIST, JRC, BAM) with ToF-SIMS. Parameters like size, shell, pre-preparation and crystal system cause variance in the data and allow us to distinguish the species from each other. Moreover, this variance in the data also occurs and can be used for investigation when we compare our measurements of particle ensembles with those of grown titania films. The carefully selected and refined peaks allow a reasonable particle categorization and further a reliable allocation of blank feeds, which introduces a promising approach for NM characterization in the context of NM risk assessment. T2 - SIMS-Europe CY - Münster, Germany DA - 16.09.2018 KW - Nanoparticles KW - ToF-SIMS KW - XPS KW - PCA KW - Titania PY - 2018 AN - OPUS4-46250 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -