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SI Files for "Towards automation of the polyol process for the synthesis of silver nanoparticles"
(2022)
The graphml file: reaction_graph_AgNP.graphml is included. It contains topological information (Fig. 1 in the main text) about the reaction setup and metadata with reaction condtions. It used by the Python API used to control the Chemputer.
SAXS reports. The complete report sheets generated by McSAS are included. They contain extended information characterising the size distributions and the fitting parameters.
NP3_I: saxs_report_NP3_I.pdf
NP3_II: saxs_report_NP3_II.pdf
NP3_III: saxs_report_NP3_III.pdf
NP3_IV: saxs_report_NP3_IV.pdf
NP5_I: saxs_report_NP5_I.pdf
NP5_II: saxs_report_NP5_II.pdf
NP5_III: saxs_report_NP5_III.pdf
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).
he main objective of the nPSize project is to improve the measurement capabilities for nanoparticle size based on both measurement methods traceable to SI units and new reference materials. Two basic approaches have been used in order to develop measurement procedures resulting in traceable results of the nanoparticle size distribution: physical modelling for the methods used in the project (TSEM, SEM, AFM and SAXS) and machine learning.
Physical modelling: In this part, the physical models associated with different shape measurements for the techniques TSEM, SEM, AFM and SAXS have been collected and further developed with the aim to simulate the resulting signal as measured by the individual methods. Uncertainties and traceability associated with each model were investigated and evaluated. In the following, the progress on these physical models is reported for each individual method.
Machine Learning modelling: The aim of this part is to use machine learning to enable automatic measurement of nanoparticle shape from expert a-priori information only. No physical model will be used as a-priori information in this task.
The accuracy and traceability of the size results obtained by each technique will be analyzed and compared with the physical modelling. A machine learning database will then be used to create automatic detection algorithms.
We report dielectric and calorimetric studies on metathesis and addition-type polytricyclononenes, both based on the same monomer bearing three pendant OSiMe3 groups. For the addition-type polymer, dielectric spectroscopy reveals a β*-process related to the microporosity, whereas for its metathesis counterpart, the segmental dynamics manifests as an α-process related to a glass transition. Besides active dielectric processes, a significant conductivity contribution is detected for both samples which for the microporous additiontype polymer is three orders of magnitude greater than for the metathesis polymer. The broadband dielectric spectroscopy is complemented by detailed calorimetric investigations, comprising DSC, FSC, and TMDSC. The calorimetric methods detected the glass transition for the metathesis polymer in agreement with the observed dielectric α-process. Furthermore, the already reported gas transport properties for both polymers are compared, setting them in correlation with the observed molecular mobility and conductivity behavior. The discussed results reflect significant differences in molecular mobility of the two polymers affecting the appearance of microporosity which strongly determines the gas transport properties.
In recent years, we have come to appreciate the astounding intricacy of the formation process of minerals from ions in aqueous solutions. In this context, a number of studies have revealed that nucleation in the calcium sulfate system is non-classical, involving the aggregation and reorganization of nanosized prenucleation particles. In a recent work we have shown that this particle-mediated nucleation pathway is actually imprinted in the resultant single micron-sized CaSO4 crystals. This property of CaSO4 minerals provides us with an unique opportunity to search for evidence of non-classical nucleation pathways in geological environments. In particular, we focused on the quintessential single crystals of anhydrite extracted from the Naica mine in Mexico. We elucidated the growth history from this mineral sample by mapping growth defects at different length scales. Based on these data we argue that the nano-scale misalignment of the structural sub-units observed in the initial calcium sulfate crystal seed propagate through different length-scales both in morphological, as well as strictly crystallographic aspects, eventually causing the formation of large mesostructured single crystals of anhydrite. Hence, the nanoparticle mediated nucleation mechanism introduces a 'seed of imperfection', which leads to a macroscopic single crystal, in which its fragments do not fit together at different length-scales in a self-similar manner. Consequently, anisotropic voids of various sizes are formed with very well-defined walls/edges. But, at the same time the material retains its essential single crystal nature. These findings shed new light on the longstanding concept of crystal structure.
Porous materials are of a great interest due to their ability to interact with ions and molecules not only on their surface but throughout their bulk. Porous materials are conventionally used in applications; such as ion exchange, adsorption/separation and in catalysis, exploiting the huge internal surface area of highly ordered porous materials. [1, 2] The ability for these materials to succeed, in a particular field, is dependent greatly upon the uniformity of the shape and size of the pores within the material. However, despite how well we are able to understand the stability of 3-D frameworks in crystalline or polycrystalline zeolites and ZIFs, there still remains major limitations in fully understanding the synthetic mechanisms occurring prior to their formation. [3, 4] Though the syntheses of a wide variety of porous solids are already well established, their formation mechanisms continue to be of great interest to both academic and industrial communities, with the thought that with greater understanding of the formation of these solids can lead to their rational design. By obtaining a better knowledge of the underlying nucleation mechanisms, it can allow for increased predictability of new structures and in addition can reveal valuable information regarding the particle dimensions aiding in controlling particle morphology and size.
Small-angle and wide-angle X-ray scattering (SAXS/WAXS) are ideal techniques for determining morphological changes in-situ, where the shape, size and crystallinity can be followed at a high temporal resolution, and when these techniques are deployed alongside complimentary techniques, such as ex-situ microscopy, a great deal of information on the formation of materials can be obtained. The above-mentioned methodologies were utilised to study the formation of Silicalite-1 from multiple silica sources to obtain a detailed picture of the formation as a whole, including the formation of intermediate species (Image 1 show the in-situ SAXS data collected from the formation of Silicalite-1 from tetraethyl orthosilicate).
In-situ SAXS/WAXS studies were also utilized to observe the formation of ZIF-8 alongside in-situ X-ray absorption spectroscopy (XAS) experiments to probe both the morphological changes, as well as any changes occurring to the local structure during synthesis (Image 2 show the in-situ SAXS data collected from the formation of ZIF-8). These timeresolved in-situ studies have been utilised to follow changes in crystallinity and crystallite size, whilst also providing valuable information on the formation of intermediate species, the nucleation of crystalline ZIFs, and their subsequent growth.
References:
[1] M E Davis. Nature, 417(6891):813–21, 2002
[2] S T Meek, J A Greathouse, M D Allendorf, Advanced Materials, 23 (2): 249-267, 2011
[3] J Grand, H Awala, CrystEngComm,18 (5): 650–664, 2016
[4] M J V Vleet, T Weng, X Li, J R Schmidt. Chem.Rev.,118 (7): 3681–3721, 2018
X-ray scattering and sorption data associated with the publication "Antiaromatic Covalent Organic Frameworks Based on Dibenzopentalenes". X-ray scattering data is provided for COF and POP materials, including data from stability tests, as three-column ascii files with columns q (nm-1), I (m-1) and uncertainty on I, as well as being provided in 2θ.
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.
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)