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Non-stochiometric copper selenide nanocrystals are p-type semiconductors, which present localized surface plasmon resonances (LSPRs) in the near-infrared region, which are proportional to the Cu(I) vacancies. Here, an easy, low-cost, and environmentally friendly methodology for the one-pot aqueous colloidal synthesis of non-stoichiometric copper selenide nanocrystals (NCs) is described. The developed methodology consists in the use of CuCl and Na2O3Se as precursors of copper and selenium, respectively, stabilized by mercaptosuccinic acid (MSA). The best conditions for the non-stoichiometric NCs regarding Cu/stabilizer and Cu/Se molar ratios, and the initial pH, that provided the prominent plasmonic, were those with a Cu/Se molar ratio of 1 : 2 and pH 5.0, and both molar ratios of Cu/MSA used (1 : 6 and 1 : 9) with stirring for 60 min, at 90 °C, and under N2 flux. On the other hand, the nominal stoichiometric condition (Cu2−XSe, X = 0) presented a very weak LSPR behavior, suggesting lower copper vacancy defects, as expected. The obtained plasmonic NCs were characterized optically by electron absorption spectroscopy and structurally by X-ray diffractometry, transmission electron microscopy (TEM), Raman, and infrared spectroscopy (FTIR). For the best synthetic condition, the NCs produced presented a maximum absorption band at 1124 nm. TEM images for non-stoichiometric copper selenide systems showed highly crystalline and mostly spheroid particles, and a rather large size dispersion ranging from 2 to 13 nm, with a mean size of d = 8.6 ± 2.0 nm. The crystalline structure determined by the X-ray diffractometry profile for these as-prepared non-stoichiometric nanoparticles matches those observed for the Klockmannite hexagonal structure for CuSe (X = 1) structures. Furthermore, the use of the synthesized Cu2−XSe-MSA NCs in surface-enhanced infrared absorption (SEIRA) spectroscopy promoted an effective enhancement of infrared signatures of molecules in a very low concentration, as shown in our preliminary results with standard dye molecules.

Quantum dots (QDs) are semiconductor nanocrystals extensively applied as optoelectronic devices, sensors and fluorescent probes for (bio)molecular species. Silver chalcogenides (i.e., sulfide, selenide and telluride) are examples of I–VI-based QDs, which have low toxicity and excellent colloidal stability and hold great promise for applications including photovoltaics, lighting and displays as well as biomedical imaging. In this study, we investigated the potential SEIRA effect of silver selenide QDs stabilized via mercaptosuccinic acid (Ag2Se–MSA QDs) in aqueous suspension for amplifying the IR signature of a variety of dye molecules. For this purpose, time-resolved attenuated total reflection (ATR) spectra were recorded after the deposition of aqueous dye vs. dye/QD solutions until total evaporation of the liquid at an Si ATR waveguide surface. As main results, experimental enhancement factors (EF) of up to 10.9 were obtained, which indicates that Ag2Se–MSA QDs are able to enhance IR signatures effectively. In addition, an approach based on principal component analysis (PCA) and Euclidian distances was introduced to determine a novel parameter termed the ‘multivariate enhancement factor’ (MEF), which may be more suitable for multivariate studies performed using design of experiments (DoE) to optimize the experimental conditions for SEIRA studies. These PCA studies also evidenced how the enhancement effect by Ag2Se–MSA QDs may indeed occur, and corroborate that chemometrics tools not only aid in data analysis, but may also improve the understanding and knowledge on SEIRA systems.

The mineralogical complexity of mine dust complicates exposure monitoring methods for occupational, respirable hazards. Improved understanding of the variability in respirable dust characteristics, e.g., mineral phase occurrence and composition, is required to advance on-site monitoring techniques that can be applied across diverse mining sectors. Principal components analysis (PCA) models were applied separately to XRD and FTIR datasets collected on 130 respirable dust samples from seven mining commodities to explore similarities and differences among the samples. Findings from both PCA models classified limestone, iron, and granite mine samples via their analytical responses. However, the results also cautioned that respirable samples from these commodities may not always fit patterns observed within the model. For example, one unique sample collected in a limestone mine contained no carbonate minerals. Future predictive quantification models should account for unique samples. Differences between gold and copper mine dust samples were difficult to observe. Further investigation suggested that the key to their differentiation by FTIR may lie in the characterization of clays. The results presented in this study provide foundational information for guiding the development of quantification models for respirable mineral hazards in the mining industry., publishedVersion

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., publishedVersion

The nature of crystallisation processes is of major interest, as they are among the most frequently occurring reactions associated with a variety of relevant processes in chemistry, biochemistry, and geochemistry. In this study, an innovative approach towards fundamentally understanding crystallisation pathways in a seemingly simple system – gypsum – has been developed via infrared spectroscopic techniques. Specifically, infrared attenuated total reflection spectroscopy (IR-ATR) was instrumental in revealing detailed information on inter- and intramolecular interactions during gypsum crystallization via subtle changes in the vibrational spectra of the involved reactants. When applying D2O as an isotope marker, it was shown that isotopically labelled water may serve as a viable spectroscopic probe during mid-infrared (3–15 μm) studies providing unique insight into the crystallization process at molecular-level detail. In addition, it was revealed that H2O and D2O give rise to distinctly different reaction kinetics during the crystallization process.

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.