Towards the direct detection of viral materials at the surface of protective face masks via infrared spectroscopy.

The ongoing COVID-19 pandemic represents a considerable risk for the general public and especially for health care workers. To avoid an overloading of the health care system and to control transmission chains, the development of rapid and cost-effective techniques allowing for the reliable diagnosis of individuals with acute respiratory infections are crucial. Uniquely, the present study focuses on the development of a direct face mask sampling approach, as worn (i.e., used) disposable face masks contain exogenous environmental constituents, as well as endogenously exhaled breath aerosols. Optical techniques-and specifically infrared (IR) molecular spectroscopic techniques-are promising tools for direct virus detection at the surface of such masks. In the present study, a rapid and non-destructive approach for monitoring exposure scenarios via medical face masks using attenuated total reflection infrared spectroscopy is presented. Complementarily, IR external reflection spectroscopy was evaluated in comparison for rapid mask analysis. The utility of a face mask-based sampling approach was demonstrated by differentiating water, proteins, and virus-like particles sampled onto the mask. Data analysis using multivariate statistical algorithms enabled unambiguously classifying spectral signatures of individual components and biospecies. This approach has the potential to be extended towards the rapid detection of SARS-CoV-2-as shown herein for the example of virus-like particles which are morphologically equivalent to authentic virus-without any additional sample preparation or elaborate testing equipment at laboratory facilities. Therefore, this strategy may be implemented as a routine large-scale monitoring routine, e.g., at health care institutions, nursing homes, etc. ensuring the health and safety of medical personnel.

Innovative Substrate-Integrated Hollow Waveguide Coupled Attenuated Total Reflection Sensors for Quantum Cascade Laser Based Infrared Spectroscopy in Harsh Environments.

An innovative mid-infrared spectroscopic sensor system based on quantum cascade lasers has been developed. The system combines the versatility of substrate-integrated hollow waveguides (IHWGs) with the robustness of attenuated total reflection (ATR) crystals employed as internal reflection waveguides for evanescent field sensing. IHWGs are highly reflective metal structures that propagate infrared (IR) radiation and were used as light pipes for coupling radiation into the ATR waveguide. The combined IHWG-ATR device has been designed such that the utmost stability and robustness of the optical alignment were ensured. This novel assembly enables evanescent field absorption measurements at yet unprecedently harsh conditions, that is, high pressure and temperature. Combining these advantages, this innovative sensor assembly is perfectly suited for taking ATR spectroscopy into the field where the robustness of the assembly and optical alignment is essential.

Simultaneous Infrared Spectroscopy, Raman Spectroscopy, and Luminescence Sensing: A Multispectroscopic Analytical Platform.

Scientific questions in fields such as catalysis, monitoring of biological processes, or environmental chemistry demand analytical technologies combining orthogonal spectroscopies. Combined spectroscopic concepts facilitate in situ online monitoring of dynamic processes providing a better understanding of the involved reaction pathways. In the present study, a low-liquid-volume multispectroscopic platform was developed based on infrared attenuated total reflection (IR-ATR) spectroscopy combined with Raman spectroscopy and luminescence sensing. To demonstrate the measurement capabilities, exemplary analyte systems including water/heavy water and aqueous solutions of ammonium sulfate were analyzed as proof-of-principle studies. It was successfully demonstrated that three optical techniques may be integrated into a single analytical platform without interference providing synchronized and complementary data sets by probing the same minute sample volume. In addition, the developed assembly provides a gastight lid sealing the headspace above the probed liquid for monitoring the concentration of molecular oxygen also in the gas phase via luminescence quenching. Hence, the entire assembly may be operated at inert conditions, as required, for example, during the analysis of photocatalytic processes.

Activation by oxidation and ligand exchange in a molecular manganese vanadium oxide water oxidation catalyst.

Despite their technological importance for water splitting, the reaction mechanisms of most water oxidation catalysts (WOCs) are poorly understood. This paper combines theoretical and experimental methods to reveal mechanistic insights into the reactivity of the highly active molecular manganese vanadium oxide WOC [Mn4V4O17(OAc)3]3- in aqueous acetonitrile solutions. Using density functional theory together with electrochemistry and IR-spectroscopy, we propose a sequential three-step activation mechanism including a one-electron oxidation of the catalyst from [Mn2 3+Mn2 4+] to [Mn3+Mn3 4+], acetate-to-water ligand exchange, and a second one-electron oxidation from [Mn3+Mn3 4+] to [Mn4 4+]. Analysis of several plausible ligand exchange pathways shows that nucleophilic attack of water molecules along the Jahn-Teller axis of the Mn3+ centers leads to significantly lower activation barriers compared with attack at Mn4+ centers. Deprotonation of one water ligand by the leaving acetate group leads to the formation of the activated species [Mn4V4O17(OAc)2(H2O)(OH)]- featuring one H2O and one OH ligand. Redox potentials based on the computed intermediates are in excellent agreement with electrochemical measurements at various solvent compositions. This intricate interplay between redox chemistry and ligand exchange controls the formation of the catalytically active species. These results provide key reactivity information essential to further study bio-inspired molecular WOCs and solid-state manganese oxide catalysts.

Spectral Signatures of Oxidation States in a Manganese-Oxo Cubane Water Oxidation Catalyst.

We report IR and UV/Vis spectroscopic signatures that allow discriminating between the oxidation states of the manganese-based water oxidation catalyst [(Mn4 O4 )(V4 O13 )(OAc)3 ]3- . Simulated IR spectra show that V=O stretching vibrations in the 900-1000 cm-1 region shift consistently by about 20 cm-1 per oxidation equivalent. Multiple bands in the 1450-1550 cm-1 region also change systematically upon oxidation/reduction. The computed UV/Vis spectra predict that the spectral range above 350 nm is characteristic of the managanese-oxo cubane oxidation state, whereas transitions at higher energy are due to the vanadate ligand. The presence of absorption signals above 680 nm is indicative of the presence of MnIII atoms. Spectroelectrochemical measurements of the oxidation from [Mn 2 III Mn 2 IV ] to [Mn 4 IV ] showed that the change in oxidation state can indeed be tracked by both IR and UV/Vis spectroscopy.

Segregation of respirable dust for chemical and toxicological analyses.

Respirable dust can pass beyond ciliated airways of the respiratory tract and influence adverse health effects. Health effects can be studied using samples generated from bulk dust segregation. Because previous segregation methods diverge from size-selection criteria of the international convention for respirable particles (ICRP), a method was developed to approximate the ICRP. The method was compared to an ideal sampler by measuring the sample collection bias. The comparison shows that the uncertainty due to the bias was 0.10 based on European Standard EN13205:2014 criteria, which indicates that the segregator effectively follows the ICRP. Respirable particle size distributions were confirmed by an aerodynamic particle sizer and by computer-controlled scanning electron microscopy. Consequently, a systematic way to generate respirable powders for health effects studies and chemical analyses was developed.

A Novel Calibration Method for the Quantification of Respirable Particles in Mining Scenarios Using Fourier Transform Infrared Spectroscopy.

The exposure of mining workers to crystalline particles, e.g., alpha quartz in respirable dust, is a ubiquitous global problem in occupational safety and health at surface and underground operations. The challenge of rapid in-field monitoring for direct assessment and adoption of intervention has not been solved satisfactorily to date, as conventional analytical methods such as X-ray diffraction and infrared spectroscopy require laboratory environments, complex system handling, tedious sample preparation, and are limited by, e.g., addressable particle size. A novel monitoring approach was developed for potential in-field application enabling the quantification of crystalline particles in the respirable regime based on transmission infrared spectroscopy. This on-site approach analyzes samples of dust in ambient air collected onto PVC filters using respirable dust sampling devices. In the present study, we demonstrate that portable Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate data analysis provides a versatile tool for the identification and quantification of minerals in complex real-world matrices. Without further sample preparation, the loaded filters are immediately analyzed via transmission infrared spectroscopy, and the mineral amount is quantified in real-time using a partial least squares regression algorithm. Due to the inherent molecular selectivity for crystalline as well as organic matrix components, infrared spectroscopy uniquely allows to precisely determine the particle composition even in complex samples such as dust from coal mines or clay-rich environments. For establishing a robust partial least squares regression model, a method was developed for generating calibration samples representative in size and composition for respirable mine dust via aerodynamic size separation. Combined with experimental design strategies, this allows tailoring the calibration set to the demands of air quality management in underground mining scenarios, i.e., the respirable particle size regime and the matrix of the target analyte.

Direct infrared spectroscopy for the size-independent identification and quantification of respirable particles relative mass in mine dusts.

Due to the global need for energy and resources, many workers are involved in underground and surface mining operations where they can be exposed to potentially hazardous crystalline dust particles. Besides commonly known alpha quartz, a variety of other materials may be inhaled when a worker is exposed to airborne dust. To date, the challenge of rapid in-field monitoring, identification, differentiation, and quantification of those particles has not been solved satisfactorily, in part because conventional analytical techniques require laboratory environments, complex method handling, and tedious sample preparation procedures and are in part limited by the effects of particle size. Using a set of the three most abundant minerals in limestone mine dust (i.e., calcite, dolomite, and quartz) and real-world dust samples, we demonstrate that Fourier transform infrared (FTIR) spectroscopy in combination with appropriate multivariate data analysis strategies provides a versatile tool for the identification and quantification of the mineral composition in relative complex matrices. An innovative analytical method with the potential of in-field application for quantifying the relative mass of crystalline particles in mine dust has been developed using transmission and diffuse reflection infrared Fourier transform spectroscopy (DRIFTS) within a unified multivariate model. This proof-of-principle study shows how direct on-site quantification of crystalline particles in ambient air may be accomplished based on a direct-on-filter measurement, after mine dust particles are collected directly onto PVC filters by the worker using body-mounted devices. Without any further sample preparation, these loaded filters may be analyzed via transmission infrared (IR) spectroscopy and/or DRIFTS, and the mineral content is immediately quantified via a partial least squares regression (PLSR) algorithm that enables the combining of the spectral data of both methods into a single robust model. Furthermore, it was also demonstrated that the size regime of dust particles may be classified into groups of hazardous and less hazardous size regimes. Thus, this technique may provide additional essential information for controlling air quality in surface and underground mining operations. Graphical Abstract.

Gallium arsenide waveguides as a platform for direct mid-infrared vibrational spectroscopy.

During recent years, mid-infrared (MIR) spectroscopy has matured into a versatile and powerful sensing tool for a wide variety of analytical sensing tasks. Attenuated total reflection (ATR) techniques have gained increased interest due to their potential to perform non-destructive sensing tasks close to real time. In ATR, the essential component is the sampling interface, i.e., the ATR waveguide and its material properties interfacing the sample with the evanescent field ensuring efficient photon-molecule interaction. Gallium arsenide (GaAs) is a versatile alternative material vs. commonly used ATR waveguide materials including but not limited to silicon, zinc selenide, and diamond. GaAs-based internal reflection elements (IREs) are a new generation of semiconductor-based waveguides and are herein used for the first time in direct spectroscopic applications combined with conventional Fourier transform infrared (FT-IR) spectroscopy. Next to the characterization of the ATR waveguide, exemplary surface reactions were monitored, and trace-level analyte detection via signal amplification taking advantage of surface-enhanced infrared absorption (SEIRA) effects was demonstrated. As an example of real-world relevance, the mycotoxin aflatoxin B1 (AFB1) was used as a model analyte in food and feed safety analysis. Graphical abstract.

Quantitative Analysis of Gas Phase IR Spectra Based on Extreme Learning Machine Regression Model.

Advanced chemometric analysis is required for rapid and reliable determination of physical and/or chemical components in complex gas mixtures. Based on infrared (IR) spectroscopic/sensing techniques, we propose an advanced regression model based on the extreme learning machine (ELM) algorithm for quantitative chemometric analysis. The proposed model makes two contributions to the field of advanced chemometrics. First, an ELM-based autoencoder (AE) was developed for reducing the dimensionality of spectral signals and learning important features for regression. Second, the fast regression ability of ELM architecture was directly used for constructing the regression model. In this contribution, nitrogen oxide mixtures (i.e., N2O/NO2/NO) found in vehicle exhaust were selected as a relevant example of a real-world gas mixture. Both simulated data and experimental data acquired using Fourier transform infrared spectroscopy (FTIR) were analyzed by the proposed chemometrics model. By comparing the numerical results with those obtained using conventional principle components regression (PCR) and partial least square regression (PLSR) models, the proposed model was verified to offer superior robustness and performance in quantitative IR spectral analysis.

Hydrogel-Embedded Model Photocatalytic System Investigated by Raman and IR Spectroscopy Assisted by Density Functional Theory Calculations and Two-Dimensional Correlation Analysis.

The presented study reports the synthesis and the vibrational spectroscopic characterization of different matrix-embedded model photocatalysts. The goal of the study is to investigate the interaction of a polymer matrix with photosensitizing dyes and metal complexes for potential future photocatalytic applications. The synthesis focuses on a new rhodamine B derivate and a Pt(II) terpyridine complex, which both contain a polymerizable methacrylate moiety and an acid labile acylhydrazone group. The methacrylate moieties are afterward utilized to synthesize functional model hydrogels mainly consisting of poly(ethylene glycol) methacrylate units. The pH-dependent and temperature-dependent behavior of the hydrogels is investigated by means of Raman and IR spectroscopy assisted by density functional theory calculations and two-dimensional correlation spectroscopy. The spectroscopic results reveal that the Pt(II) terpyridine complex can be released from the polymer matrix by cleaving the C═N bond in an acid environment. The same behavior could not be observed in the case of the rhodamine B dye although it features a comparable C═N bond. The temperature-dependent study shows that the water evaporation has a significant influence neither on the molecular structure of the hydrogel nor on the model photocatalytic moieties.

polyHWG: 3D Printed Substrate-Integrated Hollow Waveguides for Mid-Infrared Gas Sensing.

Gas analysis via mid-infrared (MIR) spectroscopic techniques has gained significance due to its inherent molecular selectivity and sensitivity probing pronounced vibrational, rotational, and roto-vibrational modes. In addition, MIR gas sensors are suitable for real-time monitoring in a wide variety of sensing scenarios. Our research team has recently introduced so-called substrate-integrated hollow waveguides (iHWGs) fabricated by precision milling, which have been demonstrated to be useful in online process monitoring, environmental sensing, and exhaled breath analysis especially if low sample volumes (i.e., few hundreds of microliters) are probed with rapid signal transients. A logical next step is to establish ultralightweight, potentially disposable, and low-cost substrate-integrated hollow waveguides, which may be readily customized and tailored to specific applications using 3D printing techniques. 3D printing provides access to an unprecedented variety of thermoplastic materials including biocompatible polylactides, readily etchable styrene copolymers, and magnetic or conductive materials. Thus, the properties of the waveguide may be adapted to suit its designated application, e.g., drone-mounted ultralightweight waveguides for environmental monitoring or biocompatible disposable sensor interfaces in medical/clinical applications.

Cation solvation with quantum chemical effects modeled by a size-consistent multi-partitioning quantum mechanics/molecular mechanics method.

In the condensed phase, quantum chemical properties such as many-body effects and intermolecular charge fluctuations are critical determinants of the solvation structure and dynamics. Thus, a quantum mechanical (QM) molecular description is required for both solute and solvent to incorporate these properties. However, it is challenging to conduct molecular dynamics (MD) simulations for condensed systems of sufficient scale when adapting QM potentials. To overcome this problem, we recently developed the size-consistent multi-partitioning (SCMP) quantum mechanics/molecular mechanics (QM/MM) method and realized stable and accurate MD simulations, using the QM potential to a benchmark system. In the present study, as the first application of the SCMP method, we have investigated the structures and dynamics of Na+, K+, and Ca2+ solutions based on nanosecond-scale sampling, a sampling 100-times longer than that of conventional QM-based samplings. Furthermore, we have evaluated two dynamic properties, the diffusion coefficient and difference spectra, with high statistical certainty. Furthermore the calculation of these properties has not previously been possible within the conventional QM/MM framework. Based on our analysis, we have quantitatively evaluated the quantum chemical solvation effects, which show distinct differences between the cations.

Mid-Infrared Spectroscopic Method for the Identification and Quantification of Dissolved Oil Components in Marine Environments.

The use of mid-infrared sensors based on conventional spectroscopic equipment for oil spill monitoring and fingerprinting in aqueous systems has to date been mainly confined to laboratory environments. This paper presents a portable-based mid-infrared attenuated total reflectance (MIR-ATR) sensor system that was used to quantify a number of environmentally relevant hydrocarbon contaminants in marine water. The sensor comprises a polymer-coated diamond waveguide in combination with a room-temperature operated pyroelectric detector, and the analytical performance was optimized by evaluating the influence of polymer composition, polymer film thickness, and solution flow rate on the sensor response. Uncertainties regarding the analytical performance and instrument specifications for dissolved oil detection were investigated using real-world seawater matrices. The reliability of the sensor was tested by exposition to known volumes of different oils; crude oil and diesel samples were equilibrated with seawater and then analyzed using the developed MIR-ATR sensor system. For validation, gas chromatographic measurements were performed revealing that the MIR-ATR sensor is a promising on-site monitoring tool for determining the concentration of a range of dissolved oil components in seawater at ppb to ppm levels.