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Raman spectroscopy is a well established tool for the analysis of vibration spectra, which then allow for the determination of individual substances in a chemical sample, or for their phase transitions. In the time-resolved-Raman-sprectroscopy the vibration spectra of a chemical sample are recorded sequentially over a time interval, such that conclusions for intermediate products (transients) can be drawn within a chemical process. The observed data-matrix M from a Raman spectroscopy can be regarded as a matrix product of two unknown matrices W and H, where the first is representing the contribution of the spectra and the latter represents the chemical spectra. One approach for obtaining W and H is the non-negative matrix factorization. We propose a novel approach, which does not need the commonly used separability assumption. The performance of this approach is shown on a real world chemical example.
This work addresses the problem of determining the number of components from sequential spectroscopic data analyzed by non-negative matrix factorization without separability assumption (SepFree NMF). These data are stored in a matrix M of dimension “measured times” versus “measured wavenumbers” and can be decomposed to obtain the spectral fingerprints of the states and their evolution over time. SepFree NMF assumes a memoryless (Markovian) process to underline the dynamics and decomposes M so that M = WH, with W representing the components’ fingerprints and H their kinetics. However, the rank of this decomposition (i.e., the number of physical states in the process) has to be guessed from pre-existing knowledge on the observed process. We propose a measure for determining the number of components with the computation of the minimal memory effect resulting from the decomposition; by quantifying how much the obtained factorization is deviating from the Markovian property, we are able to score factorizations of a different number of components. In this way, we estimate the number of different entities which contribute to the observed system, and we can extract kinetic information without knowing the characteristic spectra of the single components. This manuscript provides the mathematical background as well as an analysis of computer generated and experimental sequentially measured Raman spectra.
Performance Assessment for a Guided Wave-Based SHM System Applied to a Stiffened Composite Structure
(2022)
To assess the ability of structural health monitoring (SHM) systems, a variety of prerequisites and contributing factors have to be taken into account. Within this publication, this variety is analyzed for actively introduced guided wave-based SHM systems. For these systems, it is not possible to analyze their performance without taking into account their structure and their applied system parameters. Therefore, interdependencies of performance assessment are displayed in an SHM pyramid based on the structure and its monitoring requirements. Factors influencing the quality, capability and reliability of the monitoring system are given and put into relation with state-of-the-art performance analysis in a non-destructive evaluation. While some aspects are similar and can be treated in similar ways, others, such as location, environmental condition and structural dependency, demand novel solutions. Using an open-access data set from the Open Guided Waves platform, a detailed method description and analysis of path-based performance assessment is presented.The adopted approach clearly begs the question about the decision framework, as the threshold affects the reliability of the system. In addition, the findings show the effect of the propagation path according to the damage position. Indeed, the distance of damage directly affects the system performance. Otherwise, the propagation direction does not alter the potentiality of the detection approach despite the anisotropy of composites. Nonetheless, the finite waveguide makes it necessary to look at the whole paths, as singular phenomena associated with the reflections may appear. Numerical investigation helps to clarify the centrality of wave mechanics and the necessity to take sensor position into account as an influencing factor. Starting from the findings achieved, all the issues are discussed, and potential future steps are outlined.
The mechanism of mixed-ligand metal–organic framework (MOF) formation, and the possible role of intermediate single-ligand metal complexes during mechanosynthesis, have not been explored yet. For the first time, we report here in situ real-time monitoring of the mechanochemical formation mechanism of mixed-ligand MOFs. Our results show that binary phases can act as intermediates or competing products in one-pot and stepwise synthesis.
One of the challenges of high-temperature polymer electrolyte membrane fuel cells is the poisoning of the Pt catalyst with H3PO4. H3PO4 is imbibed into the routinely used polybenzimidazole-based membranes, which facilitate proton conductivity in the temperature range of 120−200 °C. However, when leached out of the membrane by water produced during operation, H3PO4 adsorbs on the Pt catalyst surface, blocking the active sites and hindering the oxygen reduction reaction (ORR).
The reduction of H3PO4 to H3PO3, which occurs at the anode due to a combination of a low potential and the presence of gaseous H2, has been investigated as an additional important contributing factor to the observed poisoning effect. H3PO3 has an affinity toward adsorption on Pt surfaces even greater than that of H2PO4 −. In this work, we investigated the poisoning effect of both H3PO3 and H3PO4 using a half-cell setup with a gas diffusion electrode under ambient conditions. By means of in situ X-ray absorption spectroscopy, it was possible to follow the signature of different species adsorbed on the Pt nanoparticle catalyst (H, O, H2PO4 −, and H3PO3) at different potentials under ORR conditions in various electrolytes (HClO4, H3PO4, and H3PO3). It was found that H3PO3 adsorbs in a pyramidal configuration P(OH)3 through a Pt−P bond. The competition between H3PO4 and H3PO3 adsorption was studied, which should allow for a better understanding of the catalyst poisoning mechanism and thus assist in the development of strategies to mitigate this phenomenon in the future by minimizing H3PO3 generation by, for example, improved catalyst design or adapted operation conditions or changes in the electrolyte composition.
The Boltzmann plot is one of the most widely used methods for determining the temperature in different types of laboratory plasmas. It operates on the logarithm as a function of the dimensional argument, which assumes that the correct physical units are used. In many works using the Boltzmann method, there is no analysis of the dimension of this argument, which may be the cause of a potential error. This technical note offers a brief description of the method and shows how to correctly use physical units when using transcendental functions like the logarithm.
The performance of the Monte Carlo (MC) algorithm for calibration-free LIBS was studied on the example of a simulated spectrum that mimics a metallurgical slag sample. The underlying model is that of a uniform, isothermal, and stationary plasma in local thermodynamical equilibrium.
Based on the model, the algorithm generates from hundreds of thousands to several millions of simultaneous configurations of plasma parameters and the corresponding number of spectra. The parameters are temperature, plasma size, and concentrations of species. They are iterated until a cost function, which indicates a difference between synthetic and simulated slag spectra, reaches its minimum. After finding the minimum, the concentrations of species are read from the model and compared to the certified values. The algorithm is parallelized on a graphical processing unit (GPU) to reduce computational time. The minimization of the cost function takes several minutes on the GPU NVIDIA Tesla K40 card and depends on the number of elements to be iterated. The intrinsic accuracy of the MC calibration-free method is found to be around 1% for the eight elements tested. For a real experimental spectrum, however, the efficiency may turn out to be worse due to the idealistic nature of the model, as well as incorrectly chosen experimental conditions. Factors influencing the performance of the method are discussed.
Shape memory alloy structures for actuator and vibration damper applications may be manufactured using wire arc additive manufacturing (W AAM), which is one of the additive manufacturing technologies. Multilayer deposition causes heat accumulation during W AAM, which rises the preheat temperature of the previously created layer. This leads to process instabilities, which result in deviations from the desired dimensions and mechanical properties changes. During W AAM deposition of the wall structure, a systematic research is carried out by adjusting the interlayer delay from 10 to 30 s. When the delay period is increased from 10 to 30 s, the breadth decreases by 45% and the height increases by 33%. Grain refinement occurs when the interlayer delay duration is increased, resulting in better hardness, phase transformation temperature, compressive strength, and shape recovery behavior. This study shows how the interlayer delay affects the behavior of W AAM-built nickel-titanium alloy (NiTi) structures in a variety of applications.
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.
This study will present a new approach to distinguishing writing inks that have the same elemental compositions and visual appearances. The approach is based on displaying the intensity of elemental distributions as heat maps that represent data recorded with a scanning μX-ray fluorescence spectrometer. The heat maps present the data so as to facilitate digitally identifying and distinguishing between inks used to produce, correct, and reink two medieval Torah scrolls. As ritual objects, Torah scrolls had to be written in accordance with exacting standards that evolved over time. This requirement led to successive stages of modifications, sometimes over centuries. Both vitriolic and non-vitriolic inks used to modify Torah scrolls can be visually identical to each other. Furthermore, different non-vitriolic inks usually have an identical elemental composition. The solid material analysis evidence and its presentation as heat maps made it possible to discriminate between original and altered portions of text that in some cases would have been impossible. Our interdisciplinary work brought together conservation, material science, paleog-raphy, and philology to enable the identification of complex stratigraphy in multiple stages of production, correction, and reinking. ©2 0 2 2 Published by Elsevier Masson SAS.