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Unpigmented HDPE jerrycans filled with nitric acid (55%) and water respectively had been exposed to outdoor conditions for one Berlin summer season. As both liquids underwent equal temperature progression, exposure effects of UV radiation and nitric acid as well as of their combination can be separated and compared. On the basis of various property changes after these exposures, synergistic action is evaluated and compared to a damaged Intermediate Bulk Container (IBC) from a transport accident.
It is found that carbonyl formation goes along with lightness increase in color measurement due to microcracking and with a worsening in mechanical behavior, all of them showing synergistic effects of UV and nitric acid exposure. In contrast, embedding nitrogen compounds goes along with yellowing of the material but cannot be correlated to oxidation.
The reason for intensified damaging is the decomposition of the 55-percent nitric acid and formation of nitrogen oxides even at ambient temperatures, caused by UV radiation. Thus, damaging effects become similar to those caused by fuming nitric acid exposure at temperatures above 60 °C, with the result of strong oxidative degradation of the polyethylene.
In contrast, exclusive exposure to the 55-percent nitric acid at 40 °C does not cause any failure.
It can therefore be assumed that also the damaged IBC had been exposed to both UV radiation and nitric acid, probably outdoors.
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.
Electron backscatter diffraction (EBSD) images of extruded pure aluminum were statistically analyzed to investigate creep-induced subgrain structures after applying two different levels of creep stress, corresponding to the power law (PL) and power-law breakdown (PLB) regimes. Kernel average misorientation analysis of EBSD measurements revealed 2D morphologies, which were subdivided by a multi-step segmentation procedure into subgranular arrangements. Various descriptors were employed to characterize the “subgrains” quantitatively, including their size, shape, spatial arrangement, and crystallographic orientation. In particular, the analysis of the orientations of subgrains was conducted by neglecting rotations around the loading axis. This approach facilitated the individual investigation of the {001} and {111} subgrain families with respect to the loading axis for two investigated stress levels plus a reference specimen. For the PL regime, the statistical analysis of subgrain descriptors computed from segmented image data revealed a similar degree of strain accumulation for {111} and {001} subgrains. In contrast, for the PLB regime, the analyzed descriptors indicate that {111} subgrains tend to accumulate significantly more strain than {001} ones. These observations suggest that the mechanisms leading to PLB may be associated with strain localization dependent on intergranular stress, hindering the recovery process within {111} grains.
The properties of nanomaterials are influenced not only by their chemical composition but also by physical properties (such as size, geometry and crystal structure). For the reliable determination and assessment of behaviour and effects of nanomaterials as well as for the determination of the exposure of humans and environment a comprehensive physical-chemical characterization of nanomaterials is essential. This is an important prerequisite to identify them as nanomaterials and to interpret and compare test results and - in future – to forecast interaction and effects of nanomaterials.
In 2006, the OECD launched a sponsorship program for the testing of nanomaterials in which 11 nanomaterials were thoroughly investigated using a variety of methods. The aim of the project was, among other things, to find out where problems occur and where there are gaps in the measurement and test procedures and where are changes required. An important outcome of the sponsorship program was the finding that the OECD Test Guidelines should in several cases be extended to the specific needs in testing of nanomaterials. The existing standardized test methods of the OECD for physical-chemical characterization have not been developed for nanomaterials in particular. A high demand for an extension of the test guidelines was identified. Germany complied with the OECD's request in 2017 and has agreed to extend the “Test Guideline on Particle Size Distribution / Fiber Length and Diameter Distributions Test Guideline” for Manufactured Nanomaterials (MN). UBA commissioned BAM and BAuA with the preparation of the Test Guideline. The aim of the project is the development of a harmonized test protocol for a valid and reproducible determination of particle size and size distribution which is one of the most relevant physical-chemical properties for MNs.
Different measuring methods provide different results for the size distribution of the particles. This is caused by the different measuring principles of the methods. Each method measures a specific parameter that ultimately determines particle size. First, the measured quantity differs for each method (Scattered light intensity, 2D image / projection, electric mobility, etc.). Second, the calculated diameters of the MN may differ (Feret Diameter, Area Projection, Mobility Diameter, Aerodynamic Diameter, Hydrodynamic Diameter). Third, a measuring method provides a size distribution which is measured either mass-based, surface-based or number-based. A conversion between the results requires additional parameters and thus possibly increases the measurement error.
In addition to the technical differences, the individual parameters are strongly influenced by the structure and material of the nanoparticles. For example, a surface functionalization can lead to very different results in the size distribution. The suitability of measurement methods differs with the material of the MN. As a result, two very different results can be measured for the particle size distribution using two different methods, which are nevertheless both correct. Several large projects in recent years therefore concluded that nanomaterials should be characterized by at least two complementary method. Imaging techniques are regarded as one of these methods for the characterization, the complementary methods are supposed to be statistical methods.
The different results for the size distribution of nanomaterials become problematic for the registration of new MN. A comparable and reproducible size distribution is a prerequisite for a standardized registration. In the future, the particle size distribution in the EU will also decide on the classification of a substance as a nanomaterial or as a non-nanomaterial. Especially in borderline cases, a standardized and comparable measurement methodology is therefore essential.
The new OECD test guideline will address the following four main steps in the determination of the length and width distributions of fibers: sample preparation, image acquisition, data evaluation and uncertainty analysis. As the sample preparation has to be optimized for each material, general quality criteria will be given in the protocol. For full visibility of a fiber the appropriate resolution has to be chosen. In the data evaluation the length and diameter of each fiber will be determined concurrently to allow for application of different regulatory definitions. The quality of the results critically depends on the sample preparation as well as the data evaluation. In this step the classification rules have to be formulated and followed accurately in order to optimize reproducibility of the method. The SOP will be validated in an international round robin test, which is planned for 2018/2019.
The OECD test guidelines (TGs) for testing chemicals have been widely used for regulatory purposes all over the world since the establishment of the Mutual Acceptance of Data (MAD) principle in 1984. This MAD principle ensures that, if a chemical is tested under the Good Laboratory Practice (GLP) conditions accordingly to an OECD TG, the data should be accepted in all OECD countries. The TGs have been developed, harmonized, internationally validated (round robin tests) and adopted by OECD countries to be used for the physical-chemical characterisation, fate estimation, and hazard identification for risk assessment of various chemicals. In addition to the TGs, OECD Guidance Documents (GDs) usually provide guidance on how to use TGs and how to interpret the results. These GDs do not have to be fully experimentally validated, and hence they are not under MAD, but they are based on relevant published scientific research.
But are the existing TGs and the related GDs applicable and adequate for the regulatory testing of nanomaterials? In general, for nanomaterials it is accepted that most of the "endpoints" or more precisely measurement variables are applicable. However, for some endpoints new or amended TGs are needed. In addition, several GDs are needed to give more precise advice on the test performance in order to gain regulatory relevant data on nanomaterials.