6 Materialchemie
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This paper reports the formation of zinc phosphate nanoparticles from the artificial digestion of zinc chloride. Initially, the formation of amorphous primary particles with a mean radius of 1.1 nm is observed, alongside the formation of larger, protein stabilized aggregates. These aggregates, with a radius of gyration of 37 nm, are observed after 5 minutes of exposure to artificial saliva and are shown to be colloidally stable for a minimum time of two weeks. The initially formed primary particles are thought to consist of amorphous zinc phosphate, which is then transformed into crystalline Zn3(PO4)2·4H2O over the course of two weeks. Our results demonstrate that the interaction of inorganic salts with bodily fluids can induce the formation of de novo nanoparticles, which in turn, provides insights into how zinc‐enriched foods may also facilitate the formation of nanoparticles upon contact with saliva. As such, this may be considered as an undesirable (bio)mineralization.
Compared to the clear, real-space images you can get from electron microscopy, X-ray scattering patterns are rather featureless. These patterns, however, contain structural information from all of the material structure illuminated by the X-ray beam. With this technique, you can measure nanoparticle dispersions, catalysts, composites, MOF powders, battery materials, light metal alloys and gels to reveal information on the structural features found within these materials. We have even measured many such materials for several research groups from the University of Birmingham, revealing structure features in the sub-nm to the micrometer range.
Measuring an X-ray scattering pattern is relatively easy, but measuring a high-quality, useful pattern 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) [1]. With the MOUSE, we have combined: a) a comprehensive and highly automated laboratory workflow with b) 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.
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
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).
X-ray scattering datasets for samples described in the 2022 publication "Side chain length dependent dynamics and conductivity in self assembled ion channels". This dataset includes both raw and processed X-ray scattering data for samples ILC8, ILC10, ILC12, ILC14 and ILC16 alongside background measurement files (BKG).
X-ray scattering datasets for samples described in the 2022 publication "Molecular Mobility of Polynorbornenes with Trimethylsiloxysilyl side groups: Influence of the Polymerization Mechanism". This dataset includes both raw and processed X-ray scattering data for samples APTCN and MPTCN, alongside background measurements files (BKG).
X-ray scattering datasets for samples described in the 2020 publication "Molecular Dynamics of Janus Polynorbornenes: Glass Transitions and Nanophase Separation". This dataset includes both raw and processed X-ray scattering data for samples PTCHSiO-Pr, Bu, Hx, Oc and De, alongside background measurements files (BKG). This data was collected using the MOUSE project (instrument and methodology).
This dataset contains the processed and analysed small-angle X-ray scattering data associated with all samples from the publications "Bio-SAXS of Single-Stranded DNA-Binding Proteins: Radiation Protection by the Compatible Solute Ectoine" (https://doi.org/10.1039/D2CP05053F).
Files associated with McSAS3 analyses are included, alongside the relevant SAXS data, with datasets labelled in accordance to the protein (G5P), its concentration (1, 2 or 4 mg/mL), and if Ectoine is present (Ect) or absent (Pure). PEPSIsaxs simulations of the GVP monomer (PDB structure: 1GV5 ) and dimer are also included.
TOPAS-bioSAXS-dosimetry extension for TOPAS-nBio based particle scattering simulations can be obtained from https://github.com/MarcBHahn/TOPAS-bioSAXS-dosimetry which is further described in https://doi.org/10.26272/opus4-55751.
This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under grant number 442240902 (HA 8528/2-1 and SE 2999/2-1). We acknowledge Diamond Light Source for time on Beamline B21 under Proposal SM29806. This work has been supported by iNEXT-Discovery, grant number 871037, funded by the Horizon 2020 program of the European Commission.
X-ray generation
(2020)
This talk introduces the expanded view that comes from wide-range X-ray scattering investigations.
Compared to X-ray diffraction studies alone, the additional angular range of this technique provides information on the larger structural dimensions present in your samples. This allows for the extraction of information on the size and size distribution of nanostructural components, such as nanoparticles, nanovoids, and any other structure exhibiting an electron density contrast.
The talk introduces the technique, the MOUSE instrument used for these investigations, and provides several real-world examples of its uses. The audience is invited to choose which examples captures their interest from a range of options, in the latter segment of the talk.
Zinc is an essential trace element and is ingested daily by humans, partly in dissolved form. The first contact is with saliva, in which many ions are dissolved whose solubility product with zinc can be low. This could result in compounds forming, possibly in nanoparticular form, which could have different effects on the organism than pure zinc ions.
In this study, we report on the saliva stage of the artificial digestion of zinc chloride as a model substance for zinc ions. To facilitate in situ measurements, the sample is continuously passed through a small-angle x-ray scattering (SAXS) system. This custom-made machine is capable of measuring over a wide q-range and thereby able to resolve structures from around 250 nm down to the crystal structure. It is thus an excellent tool for investigating both the particle size distribution and the atomic structure of the sample.
By curve fitting, we found that shortly after addition of zinc chloride to saliva, small particles with a mean radius of 1.9 ± 0.1 nm and a distribution width of 0.6 ± 0.1 nm formed. These particles are aggregated to compact mass fractals with a fractal aggregate size of 14.7 ± 0.1 nm and a fractal dimension of 2.96 ± 0.02. Approximately 7200 single particles form each mass fractal, whose radius of gyration was found to be 36 ± 1 nm. The growth of these structures continues over the course of several weeks. To determine the compound that was formed, infrared spectroscopy was used in addition to the SAXS measurements, and zinc phosphate was identified as the product.
An artificial digestion of silver nitrate is reported. It is shown that AgSCN nanoparticles emerge from ionic silver in saliva and remain present during the entire digestion process. The particles were characterized by infrared spectroscopy and small- and wide-angle X-ray scattering (SAXS/WAXS) regarding their composition and size distribution.
Uptake and molecular impact of aluminum-containing nanomaterials on human intestinal caco-2 cells
(2018)
Aluminum (Al) is one of the most common elements in the earth crust and increasingly used in food, consumer products and packaging. Its hazard potential for humans is still not completely understood. Besides the metallic form, Al also exists as mineral, including the insoluble oxide, and in soluble ionic forms. Representatives of these three species, namely a metallic and an oxidic species of Al-containing nanoparticles and soluble aluminum chloride, were applied to human intestinal cell lines as models for the intestinal barrier. We characterized physicochemical particle parameters, protein corona composition, ion release and cellular uptake. Different in vitro assays were performed to determine potential effects and molecular modes of Action related to the individual chemical species. For a deeper insight into signaling processes, microarray transcriptome analyses followed by bioinformatic data analysis were employed. The particulate Al species showed different solubility in biological media. Metallic Al nanoparticles released more ions than Al2O3 nanoparticles, while AlCl3 showed a mixture of dissolved and agglomerated particulate entities in biological media. The protein corona composition differed between both nanoparticle species. Cellular uptake, investigated in transwell experiments, occurred predominantly in particulate form, whereas ionic Al was not taken up by intestinal cell lines. Transcellular transport was not observed. None of the Al species showed cytotoxic effects up to 200 mg Al/mL. The transcriptome analysis indicated mainly effects on oxidative stress pathways, xenobiotic metabolism and metal homeostasis. We have shown for the first time that intestinal cellular uptake of Al occurs preferably in the particle form, while toxicological effects appear to be ion-related.
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.
Negatively charged flat gold nanotriangles, formed in a vesicular template phase and separated by an AOT-micelle-based depletion flocculation, were reloaded by adding a cationic polyelectrolyte, that is, a hyperbranched polyethylenimine (PEI). Heating the system to 100 °C in the presence of a gold chloride solution, the reduction process leads to the formation of gold nanoparticles inside the polymer shell surrounding the nanoplatelets. The gold nanoparticle formation is investigated by UV−vis spectroscopy, small-angle X-ray scattering, and dynamic light scattering measurements in combination with transmission electron microscopy. Spontaneously formed gold clusters in the hyperbranched PEI shell with an absorption maximum at 350 nm grow on the surface of the nanotriangles as hemispherical particles with diameters of ∼6 nm. High-resolution micrographs show that the hemispherical gold particles are crystallized onto the {111} facets on the bottom and top of the platelet as well as on the edges without a grain boundary. Undulated gold nanoplatelet superstructures with special properties become available, which show a significantly modified performance in SERS-detected photocatalysis regarding both reactivity and enhancement factor.
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.
Trinamic TMCL IOC is a Python package designed for controlling stepper motors connected to a Trinamic board using the TMCL language (all boards supported by PyTrinamic should now work, has been tested on the TMCM 6110 and the TMCM 6214). Since it is implementing the TMCL protocol, it should be easy to adapt to other Trinamic motor controller boards. This package assumes the motor controller is connected over a machine network via a network-to-serial converter, but the underlying PyTrinamic package allows for other connections too.
This allows the control of attached motors via the EPICS Channel-Access virtual communications bus. If EPICS is not desired, plain Pythonic control via motion_control should also be possible. An example for this will be provided in the example.ipynb Jupyter notebook.
This package leverages Caproto for EPICS IOCs and a modified PyTrinamic library for the motor board control, and interfaces between the two via an internal set of dataclasses. Configuration for the motors and boards are loaded from YAML files (see tests/testdata/example_config.yaml).
The modifications to PyTrinamic involved extending their library with a socket interface. This was a minor modification that should eventually find its way into the official package (a pull request has been submitted).
tNegatively charged ultrathin gold nanotriangles (AuNTs) were synthesized in a vesicular dioctyl sodiumsulfosuccinate (AOT)/phospholipid-based template phase. These “naked” AuNTs with localized surfaceplasmon resonances in the NIR region at about 1300 nm and special photothermal properties are ofparticular interest for imaging and hyperthermia of cancerous tissues. For these kinds of applicationsthe toxicity and the cellular uptake of the AuNTs is of outstanding importance. Therefore, this studyfocuses on the toxicity of “naked” AOT-stabilized AuNTs compared to polymer-coated AuNTs. Poly-meric coating consisted of non-modified hyperbranched poly(ethyleneimine) (PEI), maltose-modifiedpoly(ethyleneimine) (PEI-Mal) and heparin. The toxicological experiments were carried out with twodifferent cell lines (embryonic kidney carcinoma cell line HEK293T and NK-cell leukemia cell line YTS).This study revealed that the heparin-coating of AuNTs improved biocompatibility by a factor of 50 whencompared to naked AuNTs. Of note, the highest nontoxic concentration of the AuNTs coated with PEI andPEI-Mal is drastically decreased. Overall, this is mainly triggered by the different surface charges of poly-meric coatings. Therefore, AuNTs coated with heparin were selected to carry out uptake studies. Theirpromising high biocompatibility and cellular uptake may open future studies in the field of biomedicalapplications.
Metal nanoparticles have a substantial impact across diferent felds of science, such as photochemistry, energy conversion, and medicine. Among the commonly used nanoparticles, silver nanoparticles are of special interest due to their antibacterial properties and applications in sensing and catalysis. However, many of the methods used to synthesize silver nanoparticles often do not result in well-defned products, the main obstacles being high polydispersity or a lack of particle size tunability. We describe an automated approach to on-demand synthesis of adjustable particles with mean radii of 3 and 5 nm using the polyol route. The polyol process is a promising route for silver nanoparticles e.g., to be used as reference materials. We characterised the as-synthesized nanoparticles using small-angle X-ray scattering, dynamic light scattering and further methods, showing that automated synthesis can yield colloids with reproducible and tuneable properties.
Simulates X-ray and Neutron scattering patterns from arbitrary shapes defined by STL files.
Features:
- Uses multithreading to compute a number of independent solutions, then uses the variance of the results to estimate an uncertainty on the output.
- Can be launched from the command line using an excel sheet to define settings, or from a jupyter notebook.
- Outputs scattering patterns in absolute units if the contrast is set.
- A Gaussian size distribution is available, where the relative scaling of objects for each repetion can be varied. Recommended to be used with limited width (max. 10%) to avoid artefacts.
- Writes results with settings to an archival HDF5 file.
Application examples:
This software has been used in several studies to date. For example, it has been used here to simulate a model scattering pattern for a cuboid shape, which was then fed forward into the McSAS3 analysis program for analyzing scattering patterns of polydisperse cuboids. A second use is here, where it was used for the modeling of flattened helices. In this paper, scattering pattern features could be matched with particular morphological changes in the structure. Lastly, this paper has an example where it was used to validate the analytical analysis model, and explore the realistic limits of application of the analytical model.
The SPONGE
(2020)
In contrast to microplastics, little is known about nanoplastics (1 to 100 nm). In order to make the dectecability of nanoplasics more reliable, we started to develop nanoplastic reference materials. This project also aims to anser the question of how the single chain conformation of bio(polymers) changes in contact with nanoplastics. Small-angle X-ray and neutron scattering methods are suitable methods for studing this topic. Recently the soft and hard interactions between polystyrene nanoplasics and human serum albumin corona was investigated with small-angle neutron scattering. Here we concentrate on small-angle X-ray scattering as our favorite method to study how (bio)polymers change their conformation in contact with nanoplastics. The scattering of bovine serum albumin in its native state can be detected easily. The scattering pattern of this biopolymer changes dramatically when its globular stucture changes to a coil structure. Modeling of chain conformations and the calculation of the scattering pattern is relatively easy to perform. Numerous model calculations will be provided to predict the changes of conformation of single bio(polymer) chains when in conatact with nanoplastics. These predictions will be compared with recent experimenal results from in situ measurments of bio(polymers) in contact with nanoplastics. The impact of temperature, polymer concentration and salt on the single-chain conformation changes will be discussed.
The SAXS platform at BAM
(2021)
Iron oxides used as food colorants are listed in the European Union with the number E172. However, there are no specifications concerning the fraction of nanoparticles in these pigments.
Here, seven E172 products were thoroughly characterized. Samples of all colors were analyzed with a Broad spectrum of methods to assess their physico-chemical properties. Small-Angle X-ray Scattering (SAXS), Dynamic Light Scattering (DLS), Transmission Electron Microscopy (TEM), zeta-potential, Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), X-ray diffraction (XRD), Brunauer-Emmett-Teller analysis (BET), Asymmetric Flow Field-Flow Fractionation (AF4) and in vitro cell viability measurements were used.
Nanoparticles were detected in all E172 samples by TEM or SAXS measurements. Quantitative results from both methods were comparable. Five pigments were evaluated by TEM, of which four had a size median below 100 nm, while SAXS showed a size median below 100 nm for six evaluated pigments. Therefore, consumers May be exposed to iron oxide nanoparticles through the consumption of food pigments.
Herein, we provide a "systems architecture"-like overview and detailed discussions of the methodological and instrumental components that, together, comprise the "MOUSE" project (Methodology Optimization for UltrafineStructure Exploration). The MOUSE project provides scattering information on a wide variety of samples, with traceable dimensions for both the scattering vector (q) and the absolute scattering cross-section (I). The measurable scattering vector-range of 0.012≤ q (nm-1) ≤ 92, allows information across a hierarchy of structures with dimensions ranging from ca. 0.1 to 400 nm. In addition to details that comprise the MOUSE project, such as the organisation and traceable aspects, several representative examples are provided to demonstrate its flexibility. These include measurements on alumina membranes, the tobacco mosaic virus, and dual-source information that overcomes fluorescence limitations on ZIF-8 and iron-oxide-containing carbon catalyst materials.
The Meticulous Approach: Fully traceable X-ray scattering data via a comprehensive lab methodology
(2021)
To find out if experimental findings are real, you need to be able to repeat them. For a long time, however, papers and datasets could not necessarily include sufficient details to accurately repeat experiments, leading to a reproducibility crisis. It is here, that the MOUSE project (Methodology Optimization for Ultrafine Structure Exploration) tries to implement change – at least for small- and wide-angle X-ray scattering (SAXS/WAXS).
In the MOUSE project, we have combined: a) a comprehensive laboratory workflow with b) a heavily modified, highly automated Xenocs Xeuss 2.0 instrumental component. This combination allows us to collect fully traceable scattering data, with a well-documented data flow (akin to what is found at the more automated beamlines). With two full-time researchers, the 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.
While these numbers do not light a candle to those achieved by our hardworking compatriots at the synchrotron beamlines, the laboratory approach does allow us to continually modify and fine-tune the integral methodology. So for the last three years, we have incorporated e.g. FAIR principles, traceability, automated processing, data curation strategies, as well as a host of good scattering practices into the MOUSE system. We have concomitantly expanded our purview as specialists to include an increased responsibility for the entire scattering aspect of the resultant publications, to ensure full exploitation of the data quality, whilst avoiding common pitfalls.
This talk will discuss the MOUSE project1 as implemented to date, and will introduce foreseeable upgrades and changes. These upgrades include better pre-experiment sample scattering predictions to filter projects on the basis of their suitability, exploitation of the measurement database for detecting long-term changes and automated flagging of datasets, and enhancing MC fitting with sample scattering simulations for better matching of odd-shaped scatterers.
The hexapeptide hIAPP22–27 (NFGAIL) is known as a crucial amyloid core sequence of the human islet amyloid polypeptide (hIAPP) whose aggregates can be used to better understand the wild‐type hIAPP′s toxicity to β‐cell death. In amyloid research, the role of hydrophobic and aromatic‐aromatic interactions as potential driving forces during the aggregation process is controversially discussed not only in case of NFGAIL, but also for amyloidogenic peptides in general. We have used halogenation of the aromatic residue as a strategy to modulate hydrophobic and aromatic‐aromatic interactions and prepared a library of NFGAIL variants containing fluorinated and iodinated phenylalanine analogues. We used thioflavin T staining, transmission electron microscopy (TEM) and small‐angle X‐ray scattering (SAXS) to study the impact of side‐chain halogenation on NFGAIL amyloid formation kinetics. Our data revealed a synergy between aggregation behavior and hydrophobicity of the phenylalanine residue. This study introduces systematic fluorination as a toolbox to further investigate the nature of the amyloid self‐assembly process.
A Round Robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions, and two from powders.
Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5 % and half of the population width entries within 40 %, respectively. Due to the added complexity of the structure factor, much fewer people submitted answers on the powder datasets.
For those that did, half of the entries for the means and widths were within 44 % and 86 % respectively. This Round Robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
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.
This is a remote presentation I gave at the 2022 Small-angle Scattering conference in Campinas, Brazil. The video has been obtained from the conference organisers with their explicit permission for use on YouTube. I've tried to spruce up the audio from the remote recording the best I could.
The conference abstract for this talk was:
"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 samples[1]. 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.ph....
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."
This paper reports a systematic study into the effect of different biomass-derived precursors on the structure and porosity of carbons prepared via catalytic graphitization. Glucose, starch and cellulose are combined with iron nitrate and heated under a nitrogen atmosphere to produce Fe3C nanoparticles, which catalyze the conversion of amorphous carbon to graphitic nanostructures. The choice of organic precursor provides a means of controlling the catalyst particle size, which has a direct effect on the porosity of the material. Cellulose and glucose produce mesoporous carbons, while starch produces a mixture of micro- and mesopores under the same conditions and proceeds via a much slower graphitization step, generating a mixture of graphitic nanostructures and turbostratic carbon. Porous carbons are critical to energy applications such as batteries and electrocatalytic processes. For These applications, a simple and sustainable route to those carbons is essential. Therefore, the ability to control the precise structure of a biomass-derived carbon simply through the choice of precursor will enable the production of a new generation of energy materials.
This paper reports a systematic study into the effect of nitrogen on iron-catalyzed graphitization of biomass. Chitin, chitosan, N-acetylglucosamine, gelatin and glycine were selected to represent nitrogen-rich saccharides and amino-acid/polypeptide biomass precursors. The materials were pyrolyzed with an iron catalyst to produce carbons with a wide range of chemical and structural features such as mesoporosity and nitrogen-doping. Many authors have reported the synthesis of nitrogen-doped carbons by pyrolysis and these have diverse applications. However, this is the first systematic study of how nitrogen affects pyrolysis of biomass and importantly the catalytic graphitization step. Our data demonstrates that nitrogen inhibits graphitization but that some nitrogen survives the catalytic graphitization process to become incorporated into various chemical environments in the carbon product.
This presentation highlights ongoing scientific misconduct as found in academic literature. This includes data- and image manipulation, and paper mills. Starting with an expose of examples, it delves deeper into the causes and metrics driving this phenomenon. Finally a range of possible tools is presented, that the young researcher can use to prevent themselves from sliding into the dark scientific methods.
An introductory lecture on the Dark Side of Science; what it is, why it exists, and what can be done to fight it. This lecture illuminates the increasing prevalence of fraudulent scientific work (e.g. faked data, manipulated images, paper mills) with plenty of examples and sources. The second section expands on the driving forces that caused this phenomenon to emerge, largely driven by pressures from management, peers and the researcher themselves. The third section expands on methods and tools that can be used to educate and arm oneself against this phenomenon. The 2023 edition includes new examples of larger fraudulent bodies of work emerging, and the problems posed by the arrival of LLMs.
The Dark side of Science
(2021)
We all may have started out as bright-eyed students trying to do science to the best of our abilities, but over time, some of us have gradually drifted to the dark side. The dark side of science has an impressive publication rate in high-ranking journals, good success with funding agencies, and rocks the world with stellar findings. Unfortunately, these findings aren't real, either by accident or on purpose. As the presenter and his colleagues found, trying to correct or even dispute any of these findings in literature is a supremely complex and time-consuming effort.
With no recent reduction in the frequency of such false findings, it is up to us to try to stem the flow. Besides looking at examples, we need to understand the underlying driving forces behind this dark scientific movement. By combining this understanding with a refresher of the core scientific principles, we can then develop the necessary argumentative tools and mechanisms that may prevent our own slide down the slippery slope.
This talk will therefore start out with several entertaining examples of probably accidental, as well as definitely deliberate, false scientific findings in literature (and in particular in the field of materials research). We will then take a brief look at the possible causes for these developments, after which some tools will be presented that can help both the fresh as well as the well-seasoned scientist to rise up against the dark side.
The dark side of science
(2020)
The Dark Side of Science
(2019)
The Joint Summer School of the two Marie Skłodowska-Curie Innovative Training Networks (ITN) “BioCapture” and “GlycoImaging”, funded by the EU within the Horizon 2020 framework programme, which are both devoted to the development of new methods for cancer biomarker and cancer cell detection, will take place at the Adlershof Campus of BAM. 19 Early stage researchers of both projects will convene, discuss their own science and plan future collaborative research. Training in scientific writing (instructor: Luita Spangler, Free University of Berlin), an employability workshop (Antti Kapanen, University of Applied Sciences Berlin) and first contacts with the “dark side of science” (Brian R. Pauw, BAM) will complement the programme of the summer school.
The Dark Side of Science
(2020)
Contrast-variation small-angle neutron scattering (CV-SANS), small-angle X-ray scattering (SAXS), nuclear magnetic resonance (NMR) measurements of diffusion and isothermal titration calorimetry (ITC) are used to gain insight into the aggregation of an alkyl–C60 derivative, molecule 1, in n-hexane, n-decane and toluene as a function of concentration and temperature. Results point to an associative mechanism of aggregation similar to other commonly associating molecules, including non-ionic surfactants or asphaltenes in non-aqueous solvents. Little aggregation is detected in toluene, but small micelle-like structures form in n-alkane solvents, which have a C60-rich core and alkyl-rich shell. The greatest aggregation extent is found in n-hexane, and at 0.1 M the micelles of 1 comprise around 6 molecules at 25 °C. These micelles become smaller when the concentration is lowered, or if the solvent is changed to n-decane. The solution structure is also affected by temperature, with a slightly larger aggregation extent at 10 °C than at 25 °C. At higher concentrations, for example in solutions of 1 above 0.3 M in n-decane, a bicontinuous network becomes apparent. Overall, these findings aid our understanding of the factors driving the assembly of alkyl–π-conjugated hydrophobic amphiphiles such as 1 in solution and thereby represent a step towards the ultimate goal of exploiting this phenomenon to form materials with well-defined order.
We present how mesoporosity can be engineered in transition metal phosphate (TMPs) materials in a template-free manner. The method involves a transformation of a precursor metal phosphate phase, called M-struvite (NH4MPO4·6H2O, M = Mg2+, Ni2+, Co2+, NixCo1-x2+). It relies on the thermal decomposition of crystalline M-struvite precursors to an amorphous and simultaneously mesoporous phase, which forms while degassing of NH3 and H2O. The temporal evolution of mesoporous frameworks and the response of the metal coordination environment were followed with in-situ and ex-situ scattering and diffraction, as well as X -ray spectroscopy. Despite sharing the same precursor struvite structure, different amorphous and mesoporous structures were obtained depending on the involved transition metal. We highlight the systematic differences in absolute surface area, pore shape, pore size, and phase transitions depending on a metal cation present in the analogous M-struvites. The amorphous structures of thermally decomposed Mg-, Ni- and NixCo1-x-struvites exhibit high surface areas and pore volumes (240 m²g-1 and 0.32 cm-3 g-1 for Mg and 90 m²g-1 and 0.13 cm-3 g-1 for Ni). We propose that the low-cost, environmentally friendly M-struvites could be obtained as recycling products from industrial and agricultural wastewaters. These waste products could be then upcycled into mesoporous TMPs through a simple thermal treatment for further applications, for instance, in (electro)catalysis.
OpenSCAD, STL and technical drawings for the solid sample rack designed primarily for use with The MOUSE instruments.
This solid sample rack can be used in conjunction with:
- Laser-cut sample holder (10.5281/zenodo.7499437)
- Modular sample holder (10.5281/zenodo.7499416)
- Capillary flow-cell for liquid samples (10.5281/zenodo.7499421)
PDF file for the laser-cut sample holder designed primarily for use with The MOUSE instruments.
This sample holder can be used in conjunction with:
- Solid sample rack/plate (10.5281/zenodo.7499424)
- Modular sample holder (10.5281/zenodo.7499416)
- Capillary flow-cell for liquid samples (10.5281/zenodo.7499421)
OpenSCAD, STL and technical drawings for the capillary flow-through cell designed primarily for use with The MOUSE instruments.
This flow-through cell can be used in conjunction with:
- Modular sample holder (10.5281/zenodo.7499416)
- Solid sample rack/plate (10.5281/zenodo.7499424)
- Laser-cut sample holder (10.5281/zenodo.7499437)
OpenSCAD, STL and technical drawings for the Modular sample holder designed primarily for use with The MOUSE instruments.
This modular sample holder can be used in conjunction with the following:
- Capillary flow-cell for liquid samples (10.5281/zenodo.7499421)
- Solid sample rack/plate (10.5281/zenodo.7499424)
- Laser-cut sample holder (10.5281/zenodo.7499437)
While the synthesis of Metal-Organic Framework (MOF) particles can be as easy as adding two solutions together, reproducibly obtaining the same particles, time and time again, is a lot harder. As laboratory-independent reproducibility is a cornerstone of the scientific method, we must put effort into finding and controlling all necessary parameters to achieve this.
An open-source Python/EPICS-controlled robotic platform (see picture) was adapted to systematically explore this for a 20 ml MOF synthesis of the Zeolitic Imidazole Framework-8 (ZIF-8) chemistry in methanol. Parameters that were explored included: 1) addition sequence, 2) addition speeds, 3) reaction times, 4) source chemicals, 5) stirring speeds, 6) stirring bar choice, 7) starting concentrations, and 8) workup methodologies. It was found that, by controlling these parameters, highly reproducible syntheses are obtained. Secondly, the variation of these parameters alone led to a dramatic difference in volume-weighted particle size means, which exceeds an order of magnitude as investigated by our in-house X-ray scattering instrument [1].
The syntheses are thoroughly documented in an automated fashion, and the synthesis libraries as well as analyses libraries will become available in batches soon. With this library, it will be possible to extract previously unknown correlations, and other laboratories can produce specific particles by following the exact procedures of the particles of their choice.