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Evaluating arbitrary strain configurations and doping in graphene with Raman spectroscopy
The properties of graphene depend sensitively on strain and doping affecting its behavior in devices and allowing an advanced tailoring of this material. A knowledge of the strain configuration, i.e. the relative magnitude of the components of the strain tensor, is particularly crucial, because it governs effects like band-gap opening, pseudo-magnetic fields, and induced superconductivity. It also enters critically in the analysis of the doping level. We propose a method for evaluating unknown strain configurations and simultaneous doping in graphene using Raman spectroscopy. In our analysis we first extract the bare peak shift of the G and 2D modes by eliminating their splitting due to shear strain. The shifts from hydrostatic strain and doping are separated by a correlation analysis of the 2D and G frequencies, where we find Delta omega(2D)/Delta omega(G) = 2.21 +/- 0.05 for pure hydrostatic strain. We obtain the local hydrostatic strain, shear strain and doping without any assumption on the strain configuration prior to the analysis, as we demonstrate for two model cases: Graphene under uniaxial stress and graphene suspended on nanostructures that induce strain. Raman scattering with circular corotating polarization is ideal for analyzing frequency shifts, especially for weak strain when the peak splitting by shear strain cannot be resolved.
Composition profiling of inhomogeneous SiGe nanostructures by Raman spectroscopy
In this work, we present an experimental procedure to measure the composition distribution within inhomogeneous SiGe nanostructures. The method is based on the Raman spectra of the nanostructures, quantitatively analyzed through the knowledge of the scattering efficiency of SiGe as a function of composition and excitation wavelength. The accuracy of the method and its limitations are evidenced through the analysis of a multilayer and of self-assembled islands.
Multimodal Molecular Imaging and Identification of Bacterial Toxins Causing Mushroom Soft Rot and Cavity Disease
Soft rot disease of edible mushrooms leads to rapid degeneration of fungal tissue and thus severely affects farming productivity worldwide. The bacterial mushroom pathogen Burkholderia gladioli pv. agaricicola has been identified as the cause. Yet, little is known about the molecular basis of the infection, the spatial distribution and the biological role of antifungal agents and toxins involved in this infectious disease. We combine genome mining, metabolic profiling, MALDI-Imaging and UV Raman spectroscopy, to detect, identify and visualize a complex of chemical mediators and toxins produced by the pathogen during the infection process, including toxoflavin, caryoynencin, and sinapigladioside. Furthermore, targeted gene knockouts and in vitro assays link antifungal agents to prevalent symptoms of soft rot, mushroom browning, and impaired mycelium growth. Comparisons of related pathogenic, mutualistic and environmental Burkholderia spp. indicate that the arsenal of antifungal agents may have paved the way for ancestral bacteria to colonize niches where frequent, antagonistic interactions with fungi occur. Our findings not only demonstrate the power of label-free, in vivo detection of polyyne virulence factors by Raman imaging, but may also inspire new approaches to disease control. © 2021 The Authors. ChemBioChem published by Wiley-VCH GmbH
Molecular dynamics investigated by temporally two-dimensional coherent Raman spectroscopy
A six-wave set-up is described to determine molecular dynamics in the condensed phase. Applying two independent time delays between excitation and probe pulses additional information on the dynamics should be obtainable. We show experimentally that such investigations can be carried out with noisy light having intensity fluctuations in the femtosecond region. As first result we found a fast relaxation time in neat nitrobenzene of 100 fs, becoming even faster in mixtures with low viscosity liquids. Switching on a Raman resonance yields a longer relaxation time, which could be explained by an additional contribution by that vibration.
Evolution of Low-Frequency Vibrational Modes in Ultrathin GeSbTe Films
GeSbTe (GST) phase-change alloys feature layered crystalline structures made of lamellae separated by van der Waals (vdW) gaps. This work sheds light on the dependence of interlamellae interactions at the vdW gap on film thickness of GST alloys as probed by vibrational spectroscopy. Molecular beam epitaxy is used for designing GST layers down to a single lamella. By combining density-functional theory and Raman spectroscopy, a direct and simple method is demonstrated to identify the thickness of the GST film. The shift of the vibrational modes is studied as a function of the layer size, and the low-frequency range opens up a new route to probe the number of lamellae for different GST compositions. Comparison between experimental and theoretical Raman spectra highlights the precision growth control obtained by the epitaxial technique.
Assessment of Subsampling Strategies in Microspectroscopy of Environmental Microplastic Samples
The analysis of environmental occurrence of microplastic (MP) particles has gained notable attention within the past decade. An effective risk assessment of MP litter requires elucidating sources of MP particles, their pathways of distribution and, ultimately, sinks. Therefore, sampling has to be done in high frequency, both spatially and temporally, resulting in a high number of samples to analyze. Microspectroscopy techniques, such as FTIR imaging or Raman particle measurements allow an accurate analysis of MP particles regarding their chemical classification and size. However, these methods are time-consuming, which gives motivation to establish subsampling protocols that require measuring less particles, while still obtaining reliable results. The challenge regarding the subsampling of environmental MP samples lies in the heterogeneity of MP types and the relatively low numbers of target particles. Herein, we present a comprehensive assessment of different proposed subsampling methods on a selection of real-world samples from different environmental compartments. The methods are analyzed and compared with respect to resulting MP count errors, which eventually allows giving recommendations for staying within acceptable error margins. Our results are based on measurements with Raman microspectroscopy, but are applicable to any other analysis technique. We show that the subsampling-errors are mainly due to statistical counting errors (i.e., extrapolation from low numbers) and only in edge cases additionally impacted by inhomogeneous distribution of particles on the filters. Keeping the subsampling-errors low can mainly be realized by increasing the fraction of MP particles in the samples.