Ingenieurwissenschaften und zugeordnete Tätigkeiten
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Photoluminescence Quantum Yields of Luminescent Nanocrystals and Particles in the UV/vis/NIR/SWIR
(2023)
The rational design of functional luminescent materials such as semiconductor quantum dots and lanthanide-based upconversion nanoparticles, all photophysical and mechanistic studies, and the comparison of different emitters require accurate and quantitative photoluminescence measurements. Particularly the reliable determination of the key performance parameter photoluminescence quantum yield (f), the number of emitted per absorbed photons, and the brightness are of special importance for luminescence applications in the life and material sciences and nano(bio)photonics.[1] In this context, examples for absolute measurements of the photoluminescence quantum yields of UV/vis/NIR/SWIR emissive semiconductor quantum dots and rods, made from different materials, and spectrally shifting lanthanide upconversion nanocrystals with different surface chemistries in transparent matrices are presented including excitation wavelength and power density dependent studies utilizing integration sphere spectroscopy.[2,3] In addition, procedures for the absolute determination of the photoluminescence quantum yields of scattering dispersions of larger size quantum rods and differently sized inorganic particles have been developed as well as procedures for the characterization of solid luminescent nanomaterials such as different perovskites and YAG:Cer converter materials.[4] Thereby, challenges and pitfalls of f measurements in different wavelength regions including the SWIR and material-specific effects related to certain emitter classes are addressed, achievable uncertainties are quantified, and relative and absolute measurements of photoluminescence quantum yield measurements are compared to underline limitations of the former approach. Finally, a set of novel UV/vis/NIR quantum yield standards is presented including their certification with a complete uncertainty budget.[5]
In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators. Combined with automated data correction pipelines, and our analysis and simulation software, this led to more than 40 papers in the last 5 years with just over 2 full-time staff members.
This year, our new, modular synthesis platform has made more than 1000 additional samples for us to analyse and catalogue. By virtue of the automation, the synthesis of these samples is automatically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases.
This talk is intended to spark ideas and invite collaborations by providing an overview of: 1) the current improvements in our wide-range X-ray scattering laboratory methodology, and 2) introducing our open, modular robotic platform for systematic sample preparation.
McSAS3 is a refactored software package for fitting large batches of (X-ray or Neutron) scattering data. It uses a Monte-Carlo acceptance-rejection algorithm to optimize model parameters - ideal for analysis of size-disperse scatterers.
The refactored code can exploit multiprocessing, traceably stores (multiple) results in the output file, and allows for re-histogramming of previous optimizations. Besides analysis of large batches, it can also be integrated in automated data processing pipelines.
The live demonstration will show how to use the software, what its limitations are, and what outcomes can look like for batches of results.
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.
## Summary:
This notebook and associated datasets (including VASP details) accompany a manuscript available on the ArXiv (https://doi.org/10.48550/arXiv.2303.13435) and hopefully soon in a journal as short communication as well. Most of the details needed to understand this notebook are explained in that paper with the same title as above. For convenience, the abstract is repeated here:
## Paper abstract:
We demonstrate a strategy for simulating wide-range X-ray scattering patterns, which spans the small- and wide scattering angles as well as the scattering angles typically used for Pair Distribution Function (PDF) analysis. Such simulated patterns can be used to test holistic analysis models, and, since the diffraction intensity is presented coupled to the scattering intensity, may offer a novel pathway for determining the degree of crystallinity.
The ``Ultima Ratio'' strategy is demonstrated on a 64-nm Metal Organic Framework (MOF) particle, calculated from $Q<0.01$\,$\mathrm{nm}^{-1}$ up to $Q\approx150$\,$\mathrm{nm}^{-1}$, with a resolution of 0.16\,\AA. The computations exploit a modified 3D Fast Fourier Transform (3D-FFT), whose modifications enable the transformations of matrices at least up to $8000^3$ voxels in size. Multiple of these modified 3D-FFTs are combined to improve the low-$Q$ behaviour.
The resulting curve is compared to a wide-range scattering pattern measured on a polydisperse MOF powder.
While computationally intensive, the approach is expected to be useful for simulating scattering from a wide range of realistic, complex structures, from (poly-)crystalline particles to hierarchical, multicomponent structures such as viruses and catalysts.