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In the presented research, the high potential and abilities of secondary ion mass spectrometry (ToF-SIMS) to detect and locally map the hydrogen distribution in two types of duplex stainless steels are shown. The research validates certain proposed mechanisms by combining ToF-SIMS with high-resolution scanning electron microscopy and electron-backscattered diffraction. The combination of data from several techniques on the same region was conducted in this field for the first time by applying data treatment of the ToF-SIMS raw data and data fusion approach. This powerful combination of methods allows reviewing of the occurring processes related to hydrogen assisted cracking. The step beyond the state of the art in this field was gained here by developing permeation and mechanical loading experiments within the ToF-SIMS during chemometric imaging of the hydrogen distribution in the microstructure. The research presents the necessary correlation between the hydrogen distribution and the resulted structural changes, the diffusion behavior in a duplex microstructure and stress induced diffusion of hydrogen by applying external load at the microscale.
BAM and Division 6.1
(2018)
Among the very few techniques to localize hydrogen (H) at the microscale in steels, Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was proven to be a reliable tool. The necessity to detect hydrogen stems from its deleterious effects in metals, that are often used as structural components and to obtain better understanding of the underlying metallurgical mechanisms of hydrogen embrittlement (HE) which are still unclear.
Austenitic stainless steels are nowadays commonly used in a wide variety of application, from hydrogen transport and storage facilities to petrochemical and offshore applications where they are exposed to aggressive environments and therefore prone to HE. One of the greater risks in the austenitic class is the embrittlement of the material due to the instability of the γ austenite and its transformation into a brittle α martensitic phase. This transformation takes place due to the local stresses that are induced by the uptake of hydrogen during service. Nonetheless, it was shown that this transformation can occur as an artefact during SIMS analysis itself where Cs-sputtering is necessary not only to remove surface contaminations but mainly to enhance H/D secondary ion yield.
In the following contribution we show the influence of different sputtering conditions on AISI 304L austenitic stainless steel in order to distinguish the artefact from the hydrogen induced transformation. The material was charged electrochemically in a deuterium based electrolyte. Deuterium (D) must be in these experiments as a replacement for hydrogen which cannot be used because adsorbed hydrogen superimposes hydrogen originating from charging the sample in the SIMS images. ToF-SIMS analyses were conducted by ToF SIMS IV (IONTOF GmbH, Münster, Germany). The experiments were carried out on deuterium charged and non-charged samples. The structural characterization was carried out by SEM and EBSD examinations before and after charging, both with a Leo Gemeni 1530VP field-emission scanning electron microscope and a Zeiss Supra 40 instrument (Carl Zeiss Microscopy GmbH, Oberkochen, Germany). The results showed that the use of 1keV Cs+ beam induces stacking faults while higher sputter beam energies results in γ→α transformation.
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.
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.
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. 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’ behavior. 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 the interactions involved.
Here, we present initial data on 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. Furthermore, results on Au nanoparticles with and without an antibody shell are presented. Principle component analysis (PCA) will be used to detect the influence of sample preparation and for a better separation of different samples. ToF-SIMS imaging is desired to be implemented for single particle detection as well.
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.
The reduction of harmful emissions to the environment is one of the most urgent challenges of our time. To achieve this goal, it is inevitable to shift from using fossil fuels to renewable energy sources. Within this transition, hydrogen can play a key role serving as fuel in transportation and as means for energy storage.
The storage and transport of hydrogen using austenitic stainless steels as the infrastructure, as well as the use of these grades in hydrogen containing aggressive environments, remains problematic. The degradation of the mechanical properties and the possibility of phase transformation by ingress and accumulation of hydrogen are the main drawbacks. Advanced studies of the behaviour of hydrogen in austenite is necessary to fully understand the occurring damage processes. This knowledge is crucial for the safe use of components in industry and transportation facilities of hydrogen.
A powerful tool for depicting the distribution of hydrogen in steels, with high accuracy and resolution, is time-of-flight secondary ion mass spectrometry (ToF-SIMS). We here present a comprehensive research on the hydrogen degradation processes in AISI 304L based on electrochemical charging and subsequent ToF-SIMS experiments. To obtain furthermore information about the structural composition and cracking behaviour, electron-backscattered diffraction (EBSD) and scanning electron microscopy (SEM) were performed afterwards. All the gathered data was treated employing data fusion, thus creating a thorough portrait of hydrogen diffusion and its damaging effects in AISI 304L.
Specimens were charged with deuterium instead of hydrogen. This necessity stems from the difficulty to separate between artificially charged hydrogen and traces existing in the material or adsorbed from the rest gas in the analysis chamber. Similar diffusion and permeation behaviour, as well as solubility, allow nonetheless to draw onclusions from the experiments.
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. 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’ behavior. 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 layer and thus gives us an idea of the interactions involved. Here, we present initial data on 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. Furthermore, principle component analysis (PCA) will be used to detect the influence of sample preparation and for a better separation of different samples. ToF-SIMS imaging is desired to be implemented for single particle detection as well.
The analysis of nanomaterials is current an important task - especially in case of risk assessment, as the properties of these material class are not well understood currently. The rather high surface area of these objects renders their interactions significantly different to their corresponding bulk. Thus, the surfaces chemical composition has to be investigated to get a better understanding and prediction of the nanomaterials' behavior. ToF-SIMS has proven as a powerful tool to determine said chemical composition. Its superior surface sensitivity allows us to study mainly the utmost atomic layer and therefore gives us an idea of the interactions involved. Here, we show first result from the validation of the method for the analysis of polystyrene and gold nanoparticles. ToF-SIMS will be compared to other methods like XPS, T-SEM or REM. Furthermore, principle component analysis (PCA) will be used to detect the influence of different sample preparation performed by an innovative microfluidic device. ToF-SIMS imaging is desired to be implemented for single particle detection as well.