6.5 Synthese und Streuverfahren nanostrukturierter Materialien
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Small-angle scattering is an increasingly common method for characterizing particle ensembles in a wide variety of sample types and for diverse areas of application. SASfit has been one of the most comprehensive and flexible curve-fitting programs for decades, with many specialized tools for various fields. Here, a selection of enhancements and additions to the SASfit program are presented that may be of great benefit to interested and advanced users alike: (a) further development of the technical basis of the program, such as new numerical algorithms currently in use, a continuous integration practice for automated building and packaging of the software, and upgrades on the plug-in system for easier adoption by third-party developers; (b) a selection of new form factors for anisotropic scattering patterns and updates to existing form factors to account for multiple scattering effects; (c) a new type of a very flexible distribution called metalog [Keelin (2016). Decis. Anal. 13, 243–277], and regularization techniques such as the expectation-maximization method [Dempster et al. (1977). J. R. Stat. Soc. Ser. B (Methodological), 39, 1–22; Richardson (1972) J. Opt. Soc. Am. 62, 55; Lucy (1974). Astron. J. 79, 745; Lucy (1994). Astron. Astrophys. 289, 983–994], which is compared with fits of analytical size distributions via the non-linear least-squares method; and (d) new structure factors, especially for ordered nano- and meso-scaled material systems, as well as the Ornstein–Zernike solver for numerical determination of particle interactions and the resulting structure factor when no analytical solution is available, with the aim of incorporating its effects into the small-angle scattering intensity model used for fitting with SASfit.
A tool for merging and/or rebinning single or multiple datasets to achieve a lower point density with best possible statistics. highly scriptable, CLI, no GUI
Version 0.1: works but could do with a cleanup. Weighting by uncertainty currently always on, but should be optional for use as an azimuthal or radial averager
Efforts are rising in opening up science by making data more transparent and more easily available, including the data reduction and evaluation procedures and code. A strong foundation for this is the F.A.I.R. principle, building on Findability, Accessibility, Interoperability, and Reuse of digital assets, complemented by the letter T for trustworthyness of the data. Here, we have used data, which was made available by the Institute Laue-Langevin and can be identified using a DOI, to follow the F.A.I.R.+T. principle in extracting, evaluating and publishing triple axis data, recorded at IN3.
With Direct Laser Writing (DLW) maturing in all aspects as a manufacturing technology a toolset for quality assurance must be developed. In this work we want to introduce a first of its kind test artifact. Test artifacts are standardized 3D models with specific geometric feature to evaluate the performance of writing parameters. Test artifacts are already common in other 3D additive manufacturing technologies e.g. Selective Laser Melting. The test artifact introduced in this work was developed in particular to accommodate 1) the high geometrical resolution of DLW structures and 2) the limited possibilities to examine the resulting structure. Geometric accuracy, surface adhesion as well as confocal raman spectroscopy results were considered when evaluating the design of the test artifact. We will explain the individual features and design considerations of our DLW test artifact. The difference between two slicers, Cura and 3DPoli, and the implications on measured feature sizes and the general shape is quantified. The measured geometries are used to derive a general design guide for a specific combination of photoresist, laser power and scanning speed and to analyse the geometric accuracy of a structure produced using these guidelines.
Wide-range X-ray scattering datasets and analyses for all samples described in the 2020 publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup". These datasets are composed by combining multiple small-angle x-ray scattering and wide-angle x-ray scattering curves into a single dataset. They have been analyzed using McSAS to extract polydispersities and volume fractions. They have been collected using the MOUSE project (instrument and methodology).
Aqueous dispersions of polypropylene: towards referencematerials for nanoplastics characterization
(2022)
Plastic pollution in the environment is a rising concern for the health of our planet. The plastic litter that pollutes our environment leads to microplastic particles. They can be found (nearly) everywhere. The processes that lead to microplastic can also form nanoplastic particles, which have a size below 1 µm. Because of the small size they can penetrate tissue more easily. Only few risk assessment studies of nanoplastics were carried out so far.
Using polystyrene (PS) nanoparticles to test effects on organisms is easy because it is commercially available. However, this falls a little short, as the polyolefins i.e., polypropylene (PP) and polyethylene (PE), are produced in a larger proportion than PS. Moreover, these plastics are mainly used for disposable products, which means that they also account for a large proportion of plastic waste. Therefore, the percentage of polyolefins in environmental nanoplastic is presumably high. It is important to test the toxicological effects also with nanoplastics made of PP and PE to have more realistic results.
Herein, we present an easy and repeatable method to prepare an aqueous dispersion of polypropylene nanoplastics (nano-PP). They are stabilized electrostatically, resulting in a strongly negative zeta potential of -43 mV (± 2 mV) and making no surfactant necessary to keep the dispersion stable.
The size and the size distribution were determined via Dynamic Light Scattering (DLS) and gives a hydrodynamic diameter of 180.5 nm (± 5.8 nm) and a PDI of 0.084 (± 0.023).
Finally, ca. 480 bottles of the dispersion with a volume of 10 mL each were prepared to serve as a potential reference material for further testing of detection methods or risk assessments.
The separation of colloidal nanocrystals from their original synthesis medium is an essential process step towards their application, however, the costs on a preparative scale are still a constraint. A new combination of approaches for the purification of hydrophobic Quantum Dots is presented, resulting in an efficient scalable process in regard to time and solvent consumption, using common laboratory equipment and low-cost materials. The procedure is based on a combination of solvent-induced adhesion and solid phase extraction. The platform allows the transition from manual handling towards automation, yielding an overall purification performance similar to one conventional batch precipitation/centrifugation step, which was investigated by thermogravimetry and gas chromatography. The distinct miscibility gaps between surfactants used as nanoparticle capping agents, original and extraction medium are clarified by their phase diagrams, which confirmed the outcome of the flow chemistry process. Furthermore, the solubility behavior of the Quantum Dots is put into context with the Hansen solubility parameters framework to reasonably decide upon appropriate solvent types.
Plastic debris in micron and nanometer scale pollutes the nature all over the world. The potential dangers of these pollutants remain unpredictable. While risk assessment studies on microplastic are already popular, nanoplastic has not yet reached the same focus of investigation. The reason for this difference is simple: There is a “methodological gap” in the analytics of plastic particles with a diameter smaller than 1 µm. Submicron and nano plastic particles are currently not detectable in environmental matrices. Therefore, it is important for researchers to have a well-characterized nanoplastic material, that serves as a reference for nanoplastic found in nature.
Our aim was to synthesize nanoplastics made from the most common used plastics, starting with polypropylene (PP). We found an easy way to form nanoparticles consisting of PP (nano-PP), adapting and improving the method presented for polystyrene (PS). PP was dispersed to acetone and then transferred to water. No additional surfactant is needed to obtain a dispersion which is stable for more than 35 weeks. The
The success of forming nanoplastics and their size was detected via scattering methods, predominantly dynamic light scattering (DLS). To examine the good stability of the nanoparticles, zeta potential measurements were performed, which revealed zeta potentials of -30 to -40 mV.
This method is repeatable and well suited to produce reference material, as which we propose our prepared particles, based on a homogeneity study, that we performed, following the ISO Guide 35 for reference materials.
Plastic debris in micron and nanometer scale pollutes the nature all over the world. The potential dangers of these pollutants remain unpredictable. While risk assessment studies on microplastics are already popular, nanoplastic has not yet reached the same focus of investigation. The reason for this difference is simple: There is a "methodological gap" in the analytics of plastic particles with a diameter smaller than 1 µm. Submicron and nanoplastic particles are currently not detectable in environmental matrices. Therefore, it is important for researchers to have a well-characterized nanoplastic material, that serves as a reference for nanoplastics found in nature.
Our aim was to synthesize nanoplastics made from the most common used plastics such as polypropylene (PP). We found an easy way to form nanoparticles consisting of PP (nano-PP), adapting and improving the method presented for polystyrene (PS). Nano-PP was formed via a top-down method where the polymer was dispersed to acetone and then transferred to water. No additional surfactant is needed to obtain a dispersion which is stable for more than 35 weeks.
The success of forming nanoplastics and their size was detected via scattering methods, predominantly dynamic light scattering (DLS). The chemical analysis of the nanoplastics was performed via Fourier Transform Infrared spectroscopy. To examine the good stability of the nanoparticles, zeta potential measurements were performed, which revealed zeta potentials of -30 to -40 mV.
An extremely brief summary of what X-ray scattering can do for you (X-ray scattering encompasses small-angle X-ray scattering (SAXS), and wide-angle X-ray scattering (WAXS/XRD), amongst others). See my other videos for more detailed explanations on sample selection, data correction, data analysis, etc.
How much do we, the small-angle scatterers, influence the results of an investigation? What uncertainty do we add by our human diversity in thoughts and approaches, and is this significant compared to the uncertainty from the instrumental measurement factors?
After our previous Round Robin on data collection, we know that many laboratories can collect reasonably consistent small-angle scattering data on easy samples1. To investigate the next, human component, we compiled four existing datasets from globular (roughly spherical) scatterers, each exhibiting a common complication, and asked the participants to apply their usual methods and toolset to the quantification of the results https://lookingatnothing.com/index.php/archives/3274).
Accompanying the datasets was a modicum of accompanying information to help with the interpretation of the data, similar to what we normally receive from our collaborators. More than 30 participants reported back with volume fractions, mean sizes and size distribution widths of the particle populations in the samples, as well as information on their self-assessed level of experience and years in the field.
While the Round Robin is still underway (until the 25th of April, 2022), the initial results already show significant spread in the results. Some of these are due to the variety in interpretation of the meaning of the requested parameters, as well as simple human errors, both of which are easy to correct for. Nevertheless, even after correcting for these differences in understanding, a significant spread remains. This highlights an urgent challenge to our community: how can we better help ourselves and our colleagues obtain more reliable results, how could we take the human factor out of the equation, so to speak?
In this talk, we will introduce the four datasets, their origins and challenges. Hot off the press, we will summarize the anonymized, quantified results of the Data Analysis Round Robin. (Incidentally, we will also see if a correlation exists between experience and proximity of the result to the median). Lastly, potential avenues for improving our field will be offered based on the findings, ranging from low-effort yet somehow controversial improvements, to high-effort foundational considerations.
Measuring an X-ray scattering pattern is relatively easy, but measuring a steady stream of high-quality, useful patterns requires significant effort and good laboratory organization.
Such laboratory organization can help address the reproducibility crisis in science, and easily multiply the scientific output of a laboratory, while greatly elevating the quality of the measurements. We have demonstrated this for small- and wide-angle X-ray scattering in the MOUSE project (Methodology Optimization for Ultrafine Structure Exploration).
With the MOUSE, we have combined a comprehensive and highly automated laboratory workflow with a heavily modified X-ray scattering instrument. This combination allows us to collect fully traceable scattering data, within a well-documented, FAIR-compliant data flow (akin to what is found at the more automated synchrotron beamlines). With two full-time researchers, our lab collects and interprets thousands of datasets, on hundreds of samples, for dozens of projects per year, supporting many users along the entire process from sample selection and preparation, to the analysis of the resulting data.
This talk will briefly introduce the foundations of X-ray scattering, present the MOUSE project, and will highlight the proven utility of the methodology for materials science. Upgrades to the methodology will also be discussed, as well as possible avenues for transferring this holistic methodology to other instruments
A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm.
Post-assembly modifications are efficient tools to adjust colloidal features of block copolymer (BCP) particles. However, existing methods often address particle shape, morphology, and chemical functionality individually. For simultaneous control, we transferred the concept of seeded polymerization to phase separated BCP particles. Key to our approach is the regioselective polymerization of (functional) monomers inside specific BCP domains. This was demonstrated in striped PS-b-P2VP ellipsoids. Here, polymerization of styrene preferably occurs in PS domains and increases PS lamellar thickness up to 5-fold. The resulting asymmetric lamellar morphology also changes the particle shape, i.e., increases the aspect ratio. Using 4-vinylbenzyl azide as co-monomer, azides as chemical functionalities can be added selectively to the PS domains. Overall, our simple and versatile method gives access to various multifunctional BCP colloids from a single batch of pre-formed particles.
Thin polymer films are of vital importance due to their low production costs and wide range of applications in sensors, electronics, and coatings. Their geometry is ideal for the study of confinement effects, specifically one-dimensional confinement, on the thermodynamic properties and segmental dynamics of polymers. For this investigation, films of PC are prepared on both glass and silica substrates to measure the dielectric and calorimetric behavior as a function of film thickness. The methodology consists of broadband dielectric spectroscopy (BDS), ellipsometry, and atomic force microscopy (AFM). Using ellipsometry, the glass transition shows an increase with decreasing film thickness. Compared to a previous investigation of PC where dilatometry was used, an increase in PC was seen, but now only at thicknesses below 20 nm. Therefore, the critical thickness of PC, where the bulk-like layer no longer percolates through the film, is dependent on the method probing the glass transition. The dielectric behavior shows a deviation from bulk behavior with decreasing film thickness, although still showing a Vogel-Fulcher-Tammann (VFT) temperature dependence for all films. The influence of the adsorbed layer on the molecular mobility was also addressed.
Designing the shape and size of catalyst particles, and their interfacial charge, at the nanometer scale can radically change their performance. We demonstrate this with ceria nanoparticles. In aqueous media, nanoceria is a functional mimic of haloperoxidases, a group of enzymes that oxidize organic substrates, or of peroxidases that can degrade reactive oxygen species (ROS) such as H2O2 by oxidizing an organic substrate. We show that the chemical activity of CeO2−x nanoparticles in haloperoxidase- and peroxidaselike reactions scales with their active surface area, their surface charge, given by the ζ-potential, and their surface defects (via the Ce3+/Ce4+ ratio). Haloperoxidase-like reactions are controlled through the ζ-potential as they involve the adsorption of charged halide anions to the CeO2 surface, whereas peroxidase-like reactions without charged substrates are controlled through the specific surface area SBET. Mesoporous CeO2−x particles, with large surface areas, were prepared via template-free hydrothermal reactions and characterized by small-angle X-ray scattering. Surface area, ζ-potential and the Ce3+/Ce4+ ratio are controlled in a simple and predictable manner by the synthesis time of the hydrothermal reaction as demonstrated by X-ray photoelectron spectroscopy, sorption and ζ-potential measurements. The surface area increased with synthesis time, whilst the Ce3+/Ce4+ ratio scales inversely with decreasing ζ-potential. In this way the catalytic activity of mesoporous CeO2−x particles could be tailored selectively for haloperoxidase- and peroxidase-like reactions. The ease of tuning the surface properties of mesoporous CeO2x particles by varying the synthesis time makes the synthesis a powerful general tool for the preparation of nanocatalysts according to individual needs.
Mechanically stable structures with interconnected hierarchical porosity combine the benefits of both small
and large pores, such as high surface area, pore volume, and good mass transport capabilities. Hence, lightweight micro-/meso-/macroporous monoliths are prepared from ordered mesoporous silica COK-12 by means of spark plasma sintering (SPS, S-sintering) and compared to conventionally (C-) sintered monoliths. A multi-scale model is developed to fit the small angle X-ray scattering data and obtain information on the hexagonal lattice parameters, pore sizes from the macro to the micro range, as well as the dimensions of the silica population. For both sintering techniques, the overall mesoporosity, hexagonal pore ordering, and amorphous character are preserved. The monoliths' porosity (77–49%), mesopore size (6.2–5.2 nm), pore volume (0.50–0.22 g cm-3
), and specific surface area (451–180 m2 g-1) decrease with increasing processing temperature and pressure. While the difference in porosity is enhanced, the
structural parameters between the C-and S-sintered monoliths are largely converging at 900 C, except for the mesopore size and lattice parameter, whose dimensions are more extensively preserved in the
S-sintered monoliths, however, coming along with larger deviations from the theoretical lattice. Their higher mechanical properties (biaxial strength up to 49 MPa, 724 MPa HV 9.807 N) at comparable porosities and ability to withstand ultrasonic treatment and dead-end filtration up to 7 bar allow S-sintered monoliths to reach a high permeance (2634 L m-2 h-1 bar-1), permeability (1.25 x 10^-14 m2), and ability to reduce the chemical oxygen demand by 90% during filtration of a surfactant-stabilized oil in water emulsion, while indicating reasonable resistance towards fouling.
Polymers of intrinsic microporosity (PIMs) are promising candidates for the active layer in gas separation membranes due to their high permeability and reasonable permselectivity. These appealing properties originate from a microporous structure as a result of inefficient segment packing in the condensed state due to a combination of a ladder-like rigid backbone and sites of contortion. However, this class of polymers suffers from a significant decrease in the permeability with time due to physical aging, whereby typically, the permselectivity increases. The initial microporous structures approach a denser state via local rearrangements, leading to the reduction of the permeability. Hence, a detailed characterization of the molecular mobility in such materials can provide valuable information on physical aging. In this work, the dielectric behavior of PIM-1 films and their behavior upon heating (aging) were revisited by isothermal frequency scans during different heating/cooling cycles over a broad temperature range between 133 and 523 K (−140 to 250 °C). In addition, the obtained results were compared with data of samples that were annealed at ambient temperatures over different time scales. Multiple dielectric processes were observed: several relaxation processes due to local fluctuations and a Maxwell−Wagner−Sillars polarization effect related to the microporosity. The temperature dependence of the rates of all processes follows the Arrhenius law where the estimated activation energy depends on the nature of the process. The influence of the thermal history (aging) on the processes is discussed in detail.
Li-rich nanoparticles of Li1+xMn2–xO4 doped with Al, Co, or Ni are successfully synthesized using a facile, fast, and efficient microwave-assisted hydrothermal route. Synchrotron X-ray diffraction confirms the formation of the crystalline cubic spinel phase type. X-ray absorption spectroscopy analysis at the Co and Ni K- and L-edges verifies that the dopants are within the Li1+xMn2–xO4 spinel structure and are inactive during cycling in the bulk and at the surface. Moreover, we demonstrate that nanocrystallinity and cationic doping play an important role in improving the electrochemical performance with respect to LiMn2O4 microparticles. They significantly reduce the charge-transfer resistance, lower the first cycle irreversible capacity loss to 6%, and achieve a capacity retention between 85 and 90% after 380 cycles, with excellent Coulombic efficiency close to 99% without compromising the specific charge at a 5C cycling rate. Furthermore, the Mn K- and L-edges attest that after long cycling, the Mn oxidation state in the bulk differs from that at the surface caused by the Mn disproportion reaction; however, the cationic doping helps mitigate the Mn dissolution with respect to the undoped Li1+xMn2–xO4 nanoparticles, as indicated by inductively coupled plasma atomic emission spectrometry.