Moist/hydrated biofilms have been well-studied in the medical area, and their association with infections is widely recognized. In contrast, dry-surface biofilms (DSBs) on environmental surfaces in ...healthcare settings have received less attention. DSBs have been shown to be widespread on commonly used items in hospitals and to harbor bacterial pathogens that are known to cause healthcare-acquired infections (HAI). DSBs cannot be detected by routine surface swabbing or contact plates, and studies have shown DSBs to be less susceptible to cleaning/disinfection products. As DSBs are increasingly reported in the medical field, and there is a likelihood they also occur in food production and manufacturing areas, there is a growing demand for the rapid in situ detection of DSBs and the identification of pathogens within DSBs. Raman microspectroscopy allows users to obtain spatially resolved information about the chemical composition of biofilms, and to identify microbial species. In this study, we investigated Staphylococcus aureus mono-species DSB on polyvinylchloride blanks and stainless steel coupons, and dual-species (S. aureus/Bacillus licheniformis) DSB on steel coupons. We demonstrated that Raman microspectroscopy is not only suitable for identifying specific species, but it also enables the differentiation of vegetative cells from their sporulated form. Our findings provide the first step towards the rapid identification and characterization of the distribution and composition of DSBs on different surface areas.
An easy, inexpensive, and rapid method to identify microorganisms is in great demand in various areas such as medical diagnostics or in the food industry. In our study, we show the development of ...several predictive models based on Raman spectroscopy combined with support vector machines (SVM) for 21 species of microorganisms. The microorganisms, grown under standardized conditions, were placed on a silver mirror slide to record the data for model development. Additional data was obtained from microorganisms on a polished stainless-steel slide in order to validate the models in general and to assess possible negative influences of the material change on the predictions. The theoretical prediction accuracies for the most accurate models, based on a five-fold cross-validation, are 98.4%. For practical validation, new spectra (from stainless-steel surfaces) have been used, which were not included in the calibration data set. The overall prediction accuracy in practice was about 80% and the inaccurate predictions were only due to a few species. The development of a database provides the basis for further investigations such as the application and extension to single-cell analytics and for the characterization of biofilms.
One of the most prominent applications of terahertz time-domain spectroscopy is the spectral investigation of materials covered by visibly opaque objects. Therefore, terahertz waves are well suited ...to inspect the content of mail. We report on our work on mail inspection in this spectral range including machine design, optical layouts, data analysis, and implementations.
The Pilbara, located in Western Australia is one of the largest iron ore-mining regions in the world and will need to achieve significant emission reductions in the short term to conserve the limited ...carbon budget and abide by the Paris Agreement targets. Green hydrogen has been communicated as the desired solution, however, the high production cost limits the deployment of these systems. The thermo-catalytic methane decomposition (TCMD) process is an alternative solution, which could be implemented as a bridge technology to produce low-emission hydrogen at a potentially lower cost. This is especially attractive for iron ore mines due to the utilisation of iron ore as a process catalyst, which reduces the catalyst turnover costs and can increase the grade of spent iron ore catalyst. In this study, a preliminary techno-economic assessment was carried out in comparison with green hydrogen to determine the feasibility of the TCMD process for the decarbonisation of iron ore mine sites in the Pilbara. The results show that the TCMD process had a CO2 abatement cost between 25 and 40% less than green hydrogen, however, the magnitude of these costs was lowest for mining operations >60 Mt/yr at approximately $150 and $200 USD/t CO2 respectively. Since green hydrogen is expected to have significant cost reductions in the future, integrating renewables already into the mine could reduce emissions in the short term, which could then be extended for green hydrogen production once it becomes viable. The TCMD process, therefore, only has a narrow window of opportunity, although considering the uncertainty of the process and that green hydrogen is a proven technology with greater emission-reduction potential, green hydrogen may be the most suitable solution despite the model results presented in this work.
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•The TCMD process was studied for the decarbonization of Pilbara iron ore mines.•Techno-economic and GHG assessment of green hydrogen and the TCMD process.•Levelised cost of green and turquoise hydrogen was US $6.16/kg and US $1.45/kg.•Green and turquoise hydrogen CO2 abatement cost was US $200/t CO2 and US $150/t CO2.
Numerous publications showing that robust prediction models for microorganisms based on Raman micro-spectroscopy in combination with chemometric methods are feasible, often with very precise ...predictions. Advances in machine learning and easier accessibility to software make it increasingly easy for users to generate predictive models from complex data. However, the question regarding why those predictions are so accurate receives much less attention. In our work, we use Raman spectroscopic data of fungal spores and carotenoid-containing microorganisms to show that it is often not the position of the peaks or the subtle differences in the band ratios of the spectra, due to small differences in the chemical composition of the organisms, that allow accurate classification. Rather, it can be characteristic effects on the baselines of Raman spectra in biochemically similar microorganisms that can be enhanced by certain data pretreatment methods or even neutral-looking spectral regions can be of great importance for a convolutional neural network. Using a method called Gradient-weighted Class Activation Mapping, we attempt to peer into the black box of convolutional neural networks in microbiological applications and show which Raman spectral regions are responsible for accurate classification.
Absorption and reflection spectra have successfully been used for substance identification, which is also applicable to the THz spectral range. For optical spectroscopy, the Kramers–Kronig ...transformation (KKT) is a powerful tool to determine the complex refractive index n˜ (with k, n absorption and refractive indices, respectively) from either an absorption or reflection measurement. By terahertz time-domain spectroscopy (THz-TDS) materials are probed with short pulses of radiation. The detection is sensitive to the sample on both the amplitude and the phase of the electrical field. Thus, THz-TDS spectroscopy can provide more information than conventional Fourier-transform spectroscopy, by which a power spectrum is measured. In the case of transmission measurements, for instance, formulae exist by which the frequency-dependent complex refractive index is directly calculated from the time-dependent electrical field (waveform) without the necessity of a KKT. In the case of reflection experiments, a comparable computation is possible for the frequency-dependent phase angle; here a KKT can help to recover essential parameters. We present a combination of KKT and TDS methods for the calculation of optical constants in the THz regime.
The demand for low-emission hydrogen is set to grow as the world transitions to a future hydrogen economy. Unlike current methods of hydrogen production, which largely derive from fossil fuels with ...unabated emissions, the thermo-catalytic methane decomposition (TCMD) process is a promising intermediate solution that generates no direct carbon dioxide emissions and can bridge the transition to green hydrogen whilst utilising existing gas infrastructure. This process is yet to see widespread adoption, however, due to the high catalyst turnover costs resulting from the inevitable deactivation of the catalyst, which plays a decisive role in the feasibility of the process. In this study, a feasible TCMD process was identified and a simplified mathematical model was developed, which provides a dynamic estimation for the hydrogen production rate and catalyst turnover costs over various process conditions. The work consisted of a parametric study as well as an investigation into the different process modes. Based on the numerous simulation results it was possible to find the optimal process parameters that maximise the hydrogen production rate and minimise the catalyst turnover costs, therefore increasing the economic potential of the process and hence its commercial viability.
•A viable thermo-catalytic methane decomposition process was identified.•A mathematical model estimating the dynamic catalyst turnover costs was developed.•A parametric study of the process through model-based optimisation was conducted.•The process conditions that maximise the economic potential could be determined.
Und der Haifisch, der hat Zähne …[1] Hetjens, Bernd; Platte, Frank; Scholz, Peter
Chemie in unserer Zeit,
June 2021, Letnik:
55, Številka:
3
Journal Article
Recenzirano
Zusammenfassung
Physikalisch‐chemische Analysetechniken, insbesondere die Röntgenfluoreszenzanalyse (RFA) sowie numerische Simulationen können herangezogen werden, um die Fossilierung von Haizähnen ...zu beschreiben. Ein Modell für die zeitliche Entwicklung der dabei vermuteten Diffusions‐ und Umkristallisationsvorgänge wird formuliert und könnte vice versa, gegebenenfalls kombiniert mit Elementsignaturen (fingerprints), Grundlage sein, um Datierungen von Funden vorzunehmen und/oder Objekte einer Fundstätte zuzuordnen.
Summary
Physiochemical analysis – first and foremost x‐ray fluorescence analysis – as well as numerical simulations may be used to describe fossilisation processes of shark teeth. Based on the spectroscopic data of samples from different places of discovery we provide a simple model for the description of diffusion and recrystallisation in the process of fossilization of these teeth over the course of time.
Ob während des Strandspaziergangs zufällig gefunden oder planvoll im Steinbruch zu Tage gefördert: Versteinerte Haizähne faszinieren den Phantasiebegabten, der sich Tier und Lebensumstände vorzustellen vermag. Die chemische Analytik von Fundstücken gibt Einblicke in das, was sich zwischen seinerzeitigem Leben und Fund des Fossils zugetragen haben mag.
•With renewed interest in the THz region, library search algorithms were tested.•Spectra from the publicly viewable online RIKEN THz database were used.•Spectral pre-processing was required for ...artefact removal prior to data comparison.•Successful removal of atmospheric water vapour rotational lines is demonstrated.•Fourier filtering for removal of channel spectra leads to efficient library search.
Over recent years terahertz spectroscopy has become a new tool for the characterization of solid materials, in particular for investigating polymorphism and crystallinity in pharmaceutics. Search strategies have been tested for THz spectra of various organic compounds with their spectra taken from the Riken database (http://www.riken.jp), using the GRAMS spectroscopy software. A subset of the entire database was used, which had been processed by removal of atmospheric water vapour lines and smoothing applied based on Savitzky-Golay convolution or time domain filtering. The spectral range available for all library substances was restricted to an interval from 0.9 to 4.5 THz (30–150cm−1). The number of vibrational bands within this spectral range is much reduced compared with mid-infrared or Raman spectra. The appropriateness of spectral pre-treatment is demonstrated with regard to reliability and robustness of the search methods. In particular, time-domain filters for smoothing and pre-treatment by the removal of water lines and etalon effects have been successfully tested in combination with least squares and correlation methods. With these insights, applications for substance identification, especially for the pharmaceutical industry, may be enlarged.
Previous research on the identification of fungi by means of their Raman spectra (i.e. spectra based on the inelastic scattering of light) of their spores indicates that this approach could be a ...fast, cheap and reliable method to distinguish fungi. Entomopathogenic fungi are used in commercially available insecticides (mycoinsecticides), in particular species of the genera Beauveria and Metarhizium. The identification of fungi in infected organisms is necessary for efficacy studies as well as in environmental impact assessments. This study aims at developing a method to differentiate isolates of these fungi, more precisely isolates of Metarhizium brunneum (Ca8II, Cb15III, Cb16III), Metarhizium pemphigi (X1c) and Beauveria bassiana (DSM 62075) as a non-related reference. To this end, fungi were grown on different culture media (both artificial and natural); samples were taken at different ages of the culture to assess possible impacts of nutrition and age on conidial pigmentation. It was possible to obtain spectra from the conidia of these fungi. The final predictive model was capable of determining isolated conidia grown on model insects with an overall goodness of prediction of 98.8% without any further sample preparation. In conclusion, Raman microspectroscopy proves to be a reliable and fast approach to distinguish entomopathogenic fungi.
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