Conference Agenda

Ensuring safe drinking water requires effective disinfection, but the interaction of chemical disinfectants (e.g., chlorine) with organic matter leads to the formation of disinfection byproducts (DBPs), many of which pose environmental and health risks [1,2]. Monitoring these contaminants in real-time remains a major challenge due to the complexity of aqueous matrices and the need for highly sensitive innovative detection methods for on-site monitoring. To address these concerns, this study presents two portable mid-infrared (mid-IR) sensing systems, providing data for the simultaneous detection and quantification of DBPs, combining both experimental and computational approaches. The portable compact devices - each approximately the size of a shoebox - facilitate long-term, detailed monitoring campaigns at selected pilot sites.

The sensing systems use attenuated total reflection infrared (ATR-IR) spectroscopy, utilizing broadband light sources, providing an efficient method for in situ DBP detection This innovative sensor technology combines advanced photonic detection schemes with automated sampling enabling continuous on-site monitoring of contaminants at critical points such as water distribution systems, reservoirs, and water treatment plants. The active sensing interface is based on a fiberoptic waveguide coated with a polymeric molecular recognition membrane preconcentrating the analytes of interest from the water matrix [3, 4]. The evanescent field generated in an active optical transducer (silver halide fiber) penetrates a few micrometers into the sample, allowing real-time interaction and analysis without extensive sample preparation. This approach enables online monitoring of dissolved pollutants, eliminating the need for costly and time-consuming laboratory procedures. Linear calibration functions of simultaneously detected DBPs revealed limits of detection at low ppb concentration levels [5].

The developed mid-IR spectroscopic sensing systems were deployed in March 2025 at a pilot site in Coimbra, for real-time water quality monitoring. These systems allowed for the rapid on-site detection, differentiation, and quantification of 15 DBPs in water at regulatory levels including trihalomethanes, haloacetic acids, haloacetonitriles, oxyhalide compounds and haloketones [3].

To enhance spectral interpretation, as well as the accuracy and reliability of DBP detection, the experimental IR spectra were calibrated using computational methods of quantum chemistry, contributing to more effective water quality management strategies. The characteristic IR signatures of 28 critical DBPs [1] in polar solvent (water) and in hydrophobic solvent (toluene) were computed theoretically. Experimental spectra obtained from the IR sensing devices were validated against those from a benchtop spectrometer and compared with theoretical data in the full mid-IR range (4000-600 cm⁻¹). This allowed us to confirm the identities of several DBPs detected during field experiments in the mid-IR fingerprint range (1800-830 cm⁻¹). Selected results from this collection will be presented and discussed at the meeting.

Funding

This work is part of the project H2OforAll [3], funded by the European Union, Grant Agreement GA101081963, and is also supported by Portugal-Germany Bilateral Cooperation 2024, project No. 2024.07770.CBM. The Research Centre CERES (http://www.uc.pt/ceres/) is supported by the Portuguese Science Foundation, projects UIDB/EQU/00102/2020, DOI: 10.54499/UIDB/00102/2020 and UIDP/EQU/00102/2020, DOI: 10.54499/UIDP/00102/2020 (National Funds).

References

1. I. Kalita et al. ACS EST Water 2024, 4, 1564-1578. DOI: 10.1021/acsestwater.3c00664

2. M. I. Roque et al. Water 2023, 15, 1724. DOI: 10.3390/w15091724

3. H2OforAll: “Innovative Integrated Tools and Technologies to Protect and Treat Drinking Water from Disinfection Byproducts”. DOI: 10.3030/101081963.

4. R. Lu et al. Angew. Chem. Int. Ed. 2013, 52, 2265. DOI: 10.1002/anie.201209256

5. R. Lu et al. Sci. Rep. 2013, 3, 2525. DOI: 10.1038/srep02525

Due to their presence in everyday products and accumulation in the biosphere, microplastics have become an ever-growing concern for human health. To enable a comprehensive characterization of microplastics, which are formed as by- or degradation product of plastics, typically several different analytical methods are necessary to assess their particle size and distribution as well as their molecular/elemental composition. While a combination of Laser Ablation-ICP-MS (LA-ICP-MS) and Single Particle-ICP-MS is able to evaluate the majority of these properties1, 2, it typically requires knowledge about the polymer type beforehand to accurately determine the occurring trace element levels. Since the Inductively Coupled Plasma is a hard ionization source, molecular information is not available and thus a preceding analysis with techniques such as Fourier Transform-Infrared Spectroscopy or Raman Spectroscopy is required.

However, continued development of instrument technologies have led to significant improvements in the time resolution for LA-ICP-MS setups, enabling the investigation of the signal response of individual laser shots, the so-called Single Pulse Response (SPR). Investigations of the SPR of gelatine by van Helden et al.3, 4 showed that some elements (e.g., C, Zn, and Hg) exhibit a bimodal SPR profile, which they explained by separation of the ablated material into a particulate and a gaseous phase.

Considering that synthetic polymers (and therefore microplastics) can contain varying amounts of carbon (and oxygen, nitrogen, etc.), we assume that the ratio of particulate and gaseous phase is different for each polymer, which would allow for polymer classification based on the SPR of carbon. For this, we investigate the two-phase sample transport resulting from the ablation of polyimide (PI), poly(methyl methacrylate) (PMMA), polyvinylpyrrolidone (PVP), polysulfone (PSU), and polyvinyl chloride (PVC). We discuss the impact of laser ablation parameters (laser energy, spot size, ablation cell parameters) on the SPR profile and the classification accuracy and how the addition of heteroatoms, e.g., sulfur for PSU and chlorine for PVC, can influence the performance.

Ultimately, we intend to employ this classification approach on real-life samples containing different polymers in order to avoid using multiple instruments and techniques, therefore providing a complete solution for microplastics characterization when trying to quantify trace metals.

(1) Brunnbauer, L.; Kronlachner, L.; Foisner, E.; Limbeck, A. Novel calibration approach for particle size analysis of microplastics by laser ablation single particle-ICP-MS. Journal of Analytical Atomic Spectrometry 2025, 40 (3), 753-761, 10.1039/D4JA00351A. DOI: https://doi.org/10.1039/D4JA00351A.

(2) Van Acker, T.; Rua-Ibarz, A.; Vanhaecke, F.; Bolea-Fernandez, E. Laser Ablation for Nondestructive Sampling of Microplastics in Single-Particle ICP-Mass Spectrometry. Analytical Chemistry 2023, 95 (50), 18579-18586. DOI: https://doi.org/10.1021/acs.analchem.3c04473.

(3) Van Helden, T.; Mervič, K.; Nemet, I.; van Elteren, J. T.; Vanhaecke, F.; Rončević, S.; Šala, M.; Van Acker, T. Evaluation of two-phase sample transport upon ablation of gelatin as a proxy for soft biological matrices using nanosecond laser ablation – inductively coupled plasma – mass spectrometry. Analytica Chimica Acta 2024, 1287, 342089. DOI: https://doi.org/10.1016/j.aca.2023.342089.

(4) van Elteren, J. T.; Van Helden, T.; Metarapi, D.; Van Acker, T.; Mervič, K.; Šala, M.; Vanhaecke, F. Predicting image quality degradation as a result of two-phase sample transport in LA-ICP-TOFMS mapping of carbon-based materials. Journal of Analytical Atomic Spectrometry 2025, 40 (2), 520-528. DOI: https://doi.org/10.1039/D4JA00288A.

The contamination of aquatic environments by pharmaceuticals is a critical global concern, not only due to their persistence, bioaccumulation, and adverse effects on ecosystems and public health, but also because of their role in accelerating bacterial resistance affecting public health. Tackling this issue effectively requires a preventive approach based on continuous and reliable environmental monitoring. However, conventional detection and quantification methods often fall short in practical applications due to their complexity, high cost, and limited scalability.

A promising alternative is surface-enhanced infrared absorption spectroscopy (SEIRA), a technique capable of enhancing vibrational signals and enabling the detection of analytes at trace levels. Traditionally, SEIRA uses plasmonic nanoparticles of gold (Au) or silver (Ag) to amplify signals. However, silver-based semiconductor nanocrystals, such as silver chalcogenides, have recently shown great potential as alternative amplifiers due to their unique surface properties and interaction mechanisms.

In this study, silver selenide quantum dots (Ag₂Se QDs) were evaluated as SEIRA signal amplifiers for the detection of pharmaceuticals, namely the antidepressant venlafaxine. These nanomaterials have the potential to promote strong local field enhancements and interact with pharmaceutical molecules through electrostatic forces or surface adsorption interactions that can localize vibrational modes and lead to significant signal amplification.

Ag2Se QDs were prepared in aqueous medium, using glutathione (GSH) and ascorbic acid as the stabilizing and reducing agent, respectively. These QDs were purified to reduce the spectral interference from free stabilizer bonds, ensuring a clearer assessment of analyte – QD interactions. The SEIRA experimental strategy focused on optimizing sample preparation and deposition methods onto the FTIR crystal, comparing two approaches: i) deposition of the QDs and analytes mixture, where QDs and analytes were applied simultaneously; and ii) layered deposition, where QDs were first deposited and dried before analyte application. Preliminary results showed that specific IR signal regions of venlafaxine could be enhanced by up to 32 times compared to the pharmaceutical alone, enabling its detection at concentrations in the µg/mL range.

The proposed SEIRA-based analysis setup built on Ag-based QDs can be an accessible and practical experimental tool for the detection of pharmaceuticals. Thus, this work contributes to the development of efficient and environmentally responsible tools for monitoring organic microcontaminants in water.

The authors acknowledge financial support from UID Centro de Estudos do Ambiente e Mar (CESAM) – LA/P/0094/2020 and the project NanoSEIRA (COMPETE2030-FEDER-00866600); as well as the Erasmus+ program and the DAAD (German Academic Exchange Service) for enabling the research exchange.

Given the growing global demand for cannabis, both for recreational and medicinal purposes, it is critical to establish and adhere to strict regulatory standards, that include sustainable agricultural practices, continuous monitoring of contaminants, and the use of advanced testing techniques.

Cannabis plants have the ability to accumulate metals from atmospheric pollution, soil, or contaminated irrigation water. Toxic heavy metals such as Cd, Pb, and Hg can appear in cannabis products through plant bioaccumulation, cross-contamination during processing, or post-processing adulteration. Exposure to these metals via ingestion or inhalation poses long-term toxicological risks, making their monitoring a priority in quality control protocols.

Cannabis testing is governed by a complex regulatory framework, posing challenges for analytical laboratories that must develop methods compliant with varying regional and national regulatory limits.

Currently, for the analysis of heavy metals in cannabis flowers and derived products, international regulatory agencies recommend inductively coupled plasma optical emission spectrometry (ICP-OES) or inductively coupled plasma mass spectrometry (ICP-MS). These techniques are widely used due to their ability to analyse multiple elements with high sensitivity, speed, robustness, and broad dynamic range for both major and trace elements. One of their main disadvantages is the high cost, both in terms of initial investment and operation, which can limit accessibility, particularly for analytical laboratories in developing countries.

Microwave plasma atomic emission spectrometry (MP-AES) emerges as a promising alternative due to its accurate results, ease of operation, and environmentally friendly design, as it uses air instead of argon, significantly reducing operational costs.

This study presents the development, optimization, and validation of alternative analytical methods for the determination of Cd, Pb, and Hg in cannabis flowers using MP-AES as the detection technique. For Hg determination, a cold vapor generation system was employed to produce elemental mercury, which was subsequently analyzed by MP-AES.

Samples were obtained from licensed recreational cannabis dispensaries. In the laboratory, the samples were dried, milled, and stored under controlled conditions until analysis. A 0.5 g aliquot was placed into a digestion vessel, followed by the addition of 10.0 mL of 4.7 mol L⁻¹ HNO₃. The vessels were then subjected to microwave-assisted acid digestion. The same procedures were applied to reagent blanks and certified reference materials.

Elemental analysis was performed using an Agilent 4210 MP-AES spectrometer equipped with a multimode spray chamber for vapor generation, a double-pass glass cyclonic spray chamber, and a standard torch.

A matrix effect resulting in signal suppression was observed for Cd and Pb. To mitigate this, the matrix was diluted prior to measurement without compromising analytes detectability.

Sodium tetrahydroborate (NaBH₄) was employed as a reducing agent for the in-line generation of mercury vapor via the cold vapor technique. No additional dilution was required, which was advantageous given the expected low concentrations of Hg in the samples.

Following optimization, the methods were validated by evaluating linearity, limits of detection (LOD) and quantification (LOQ), precision, and trueness.

The LOQ values obtained were 0.202 mg kg⁻¹ for Cd, 0.319 mg kg⁻¹ for Pb, and 0.015 mg kg⁻¹ for Hg, all below the maximum limits established by international regulations. Precision, expressed as relative standard deviation (%RSD), was evaluated using spiked samples and was below 10% for all elements. Trueness was assessed using two certified reference materials—spinach (NIST 1570a) and tomato leaves (NIST 1573a). A Student’s t-test comparison between experimental and certified values was conducted. All calculated t values were below the critical t value (0.05, 5) = 2.57, indicating no statistically significant differences at the 95% confidence level.

The obtained figures of merit confirm that the proposed method is suitable for monitoring purposes, enabling the determination of all three elements with a single sample preparation step.

Additionally, the developed methods offer several advantages over argon-plasma techniques, including lower initial investment, reduced operational costs, and decreased energy consumption, while minimizing the generation of hazardous waste. These features make MP-AES an efficient, sustainable, and practical alternative for implementation in laboratories conducting quality control of cannabis products.

Pancreatic exocrine insufficiency (PEI) is a prevalent yet frequently underdiagnosed condition associated with chronic pancreatitis, pancreatic cancer, and pancreatic resection. It results from insufficient secretion of digestive enzymes, leading to impaired nutrient absorption, weight loss, and micronutrient deficiencies. Conventional diagnostic methods, such as the coefficient of fat absorption (CFA) and fecal elastase testing, are hindered by technical complexity, limited patient adherence, and suboptimal diagnostic performance. These limitations underscore the pressing need for alternative diagnostic strategies based on reliable, non-invasive biomarkers.

In this context, urine represents a promising biological matrix for biomarker discovery, as it could be collected non-invasively and reflects systemic metabolic changes. This study presents the development and validation of a multielemental analytical method employing inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) for the accurate quantification of metals and metalloids in human urine. The ultimate objective was to evaluate its applicability in identifying elemental signatures associated with PEI and related metabolic dysfunctions.

The analytical protocol was optimized to address main challenges associated with urine analysis, particularly matrix effects and spectral interferences. Strategies included appropriate sample dilution, internal standardization, and the use of collision/reaction gases were employed to reduce spectral and non-spectral interferences and to enhance the accuracy. The optimal dilution factor was determined to be 1:2, representing a balance between matrix suppression and analytical sensitivity. Method validation was carried out using certified reference materials at various concentration levels, with evaluation of trueness, intra- and inter-day precision, and detection limits.

The method enabled simultaneous quantification of more than 20 elements, including essential (Zn, Cu, Fe, Se), toxic (As, Cd, Pb), and trace elements, at concentrations ranging from low parts-per-billion to parts-per-milion levels. This multielemental approach provided a comprehensive elemental profile that may reflect biochemical alterations associated with pancreatic dysfunction.

The proposed validated methodology offered a solid analytical methodology for future clinical studies aiming to establish urinary metallomic patterns as diagnostic or prognostic biomarkers of PEI.

The determination of arsenic in clinical samples is a key analytical task in biomedical research and public health, given the toxicological and carcinogenic nature of this metalloid. Chronic exposure to inorganic arsenic is strongly associated with skin, lung, bladder, and kidney cancers, as well as cardiovascular, neurological, and metabolic disorders. Accurate quantification of arsenic in biological fluids such as blood serum and urine enables both diagnosis and monitoring of acute or chronic poisoning and supports epidemiological surveillance and health policy design.

Inductively coupled plasma mass spectrometry (ICP-MS) offers high sensitivity for trace elemental analysis. However, its applicability to biological matrices is often limited by matrix effects and the ultra-trace concentration of the analyte. Conventional sample preparation methods like acid digestion or liquid–liquid extraction involve significant drawbacks, including analyte loss, matrix degradation, high solvent consumption, toxicity, and low potential for automation.

In this context, this work presents an innovative solid-phase microextraction strategy that employs a novel class of sorbent materials referred to as Guefoams (guest-containing foams). These materials consist of a porous metallic matrix - specifically aluminum - within which freely mobile particulate entities, designated as guest phases (in this case, activated carbon), are physically entrapped in the internal cavities of the host structure. The structural features of Guefoams confer a high specific surface area, mechanical robustness, and tailored porosity, allowing complete exposure of the functional guest surfaces for selective adsorption.

The sorptive performance of Guefoams for arsenic was investigated. Optimization of adsorption and desorption conditions was carried out using a Box-Behnken experimental design. The best desorption efficiency was achieved with 5% HNO₃, reaching a preconcentration factor of 2. Limits of detection were in the order of ng kg-1, making the method suitable for trace-level analysis in clinical matrices. Adsorption efficiency showed no significant differences among arsenic species, indicating good versatility. Moreover, method accuracy was validated through the analysis of certified reference materials, including two urine and two blood serum samples, with recoveries close to 100%.

These results demonstrated that Guefoams represent a promising alternative for the preconcentration and determination of arsenic in complex biological samples, offering operational simplicity, cost-effectiveness, low environmental impact, and compatibility with ICP-MS detection.

Accurate determination of arsenic in tire pyrolysis oils (TPOs) is essential due to its environmental toxicity, impact on fuel stability, and deactivation of catalysts in refining processes. Although inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) is renowned for its sensitivity and low detection limits, its application to organic matrices such as TPOs is hindered by plasma instability, spectral interferences, and soot deposition. Interfering ions such as 40Ar35Cl+, 38Ar37Cl+, 59Co16O+, 40Ca35Cl+, Sm2+ and 150Nd2+ overlap with 75As+ peaks, thereby complicating the quantification. Moreover, the complexity of the matrix could affect all stages of the analytical process, from nebulization to ionization, leading matrix effects and varying arsenic chemical forms, which could degrade the accuracy of determination.

To address these analytical challenges, in this work, we present a robust method that combined a high-temperature torch integrated sample introduction system (hTISIS), operated at 400 °C, with ICP-MS/MS, applied to TPOs previously diluted 1:10 in xylene. The hTISIS enabled efficient aerosol evaporation and enhanced analyte transport, resulting in signal intensities up to 20 times greater than those observed with a conventional sample introduction system. The use of oxygen as a reaction gas allowed effective mitigation of chloride-based polyatomic interferences, even in samples with chlorine levels exceeding 750 mg kg⁻¹.This configuration yielded arsenic detection limits as low as 2 ng kg⁻¹ and procedural quantification limits (pLOQ) of 60 ng kg⁻¹, an order of magnitude better than conventional systems. Furthermore, the combination of hTISIS and ICP-MS/MS successfully mitigated both matrix-induced effects and the influence of arsenic speciation.

Thirteen TPO samples, originating from diverse tire types and production processes, were analyzed, revealing arsenic concentrations ranging from 41 ± 4 to 924 ± 80 µg kg⁻¹. Results were validated via comparison with a reference method based on microwave-assisted acid digestion and conventional ICP-MS. Statistical analysis showed no significant differences for most samples at the 95% confidence level. Overall, the hTISIS–ICP-MS/MS configuration provided a sensitive, accurate, and operationally simple solution for the routine determination of arsenic in complex organic matrices.

Catalytic carbon dioxide hydrogenation distinguishes as a potential technology due to the possibility of producing high-added value products such as methanol, formic acid and others, including gasoline. Furthermore, it is estimated that on long term, CO2 conversion is about 40 times more efficient in solving the climate change issue than its sole capture and storage CO2 [1]. The most investigated and widely used catalytic system is the Cu/ZnO/Al2O3, where copper is the main actor, ZnO is seen as co-catalyst and alumina is a kind of stabilizer for both. However, the mechanism and role of each component is still under debate. Typical routes to prepare metal oxide-based catalysts consist in precipitation methods followed by calcination. For example, Zinc-Copper mixed oxides were made by co-precipitating zinc/copper basic carbonates and then by thermally treating them [2]. It can be seen that the choice of Cu/Zn nitrates molar ratios and the precipitation approach can lead to different mixed products (basic carbonates or nitrates) Here we report on the comparison between a batch precipitation [2] and a titrimetric method [3] to synthesize catalyst precursors. Fourier Transform Infrared spectroscopy operated in attenuated total reflectance mode allowed the identification of the as-produced compounds. Moreover, TEM analysis provided information about morphology. Results indicate that the titration approach allows a fine tuning of the final product. Calcination above 350°C was also performed at different temperatures to prepare oxides. Data on their catalytic role in CO2 hydrogenation are also provided.

References:

[1]. J.L. Neto, O.T. Barros, B.S. Archanjo, O. Kuznetsov, J.B. dos Santos, C.A. Franchini, E.J. Corat, A.M. Silva, Catalysis Today 442 (2024) 114957.

[2] R.G. Herman, K. Klier, G.W. Simmons, B.P. Finn, J.B. Bulko, J. Catal., 56 (1979) 407

[3] M. Behrens, D. Brennecke, F. Girgsdies, S. Kißner, A. Trunschke, N. Nasrudin, S. Zakaria, N.F. Idris, S.B. Abd Hamid, B. Kniep, R. Fischer, W. Busser, M. Muhler, R. Schlogl, Applied Catalysis A: General 392 (2011) 93–102

Research funded by European Union - Next Generation EU, Mission 4 Component 1 CUP F93C24000420006 – “MACACO” project.

Characterization Of Smart Materials: A Vibrational Spectroscopy Approach

Michael Freduah Agyemang (a,b), Stefan Zechel (c,d), Martin D. Hager (c,d,e), Michael Schmitt (a), Juergen Popp (a,b)

(a) Institute of Physical Chemistry (IPC), Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Helmholzweg 4, 07743 Jena, Germany;

(b)Leibniz Institute of Photonic Technology, e.V Jena, Albert-Einstein-Str. 9, 07745 Jena, Germany;

(c)Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena, Humboldstr. 10, 07743 Jena, Germany;

(d)Jena Center of Soft Matter (JCSM), Friedrich Schiller University Jena, Philosophenweg 7, 07743 Jena, Germany

(e)HIPOLE Jena, Philosphenweg 7a, 07743 Jena, Germany

Smart materials are materials engineered to respond predictably to external stimuli such as temperature, change in pH value or light, often enabled by reversible mechanisms in their molecular structure. Their functionality is controlled by active centers or moieties, which are embedded within a complex matrix, e.g., polymer network. Gaining insights into the behavior of these active centers within their complex environment is crucial for understanding the molecular dynamics processes. This calls for the use of non-invasive analytical techniques such as vibrational spectroscopy, which can be combined with advanced evaluation and computational algorithms like two-dimensional (2D) correlation analysis and Density Functional Theory (DFT).

Here, we are currently investigating smart polymers with self-healing functionality. Our focus is on intrinsic self-healing polymers, which are based on the reversible interactions (e.g., reversible covalent bonds, supramolecular interactions) within the polymer matrix. The dynamic bonds can be metal-ligand interactions, Diels-Alder reactions, disulfide bonds, acylhydrazone bonds, just to mention a few.

We employ vibrational techniques like Raman and IR spectroscopy to unravel the complex molecular mechanisms underlying their self-healing processes. These methods are non-destructive, highly specific, and powerful tools for probing chemical structures, monitoring reaction pathways, and capturing dynamic processes in real time. In addition to these techniques, analytical techniques like 2D correlation analysis will be utilized to untangle the intricate correlations between different spectral features and DFT calculation to provide theoretical foundation for experimental interpretations. Together, these techniques offer complementary perspective that help understand the intricate molecular dynamics at play in these self-healing materials.

Acknowledgements: The authors would like to thank Deutsche Forschungsgemeinschaft (DFG) for their support and funding under project number 455748945.

References

1. T. Baetz, M. Agyemang, J. Meurer, J. Hniopek, S. Zechel, M. Schmitt, J. Popp, M. D. Hager and U. S. Schubert, Dual orthogonal metal-complexes and their utilization for the versatile fabrication of smart interpenetrating polymer networks, Polymer Chemistry, 2024, DOI: 10.1039/D4PY01079E.

2. https://doi.org/10.1080/17452759.2025.2499470 (yet to be published online).

Microplastics (MPs) are emerging pollutants of increasing environmental and health concern, primarily due to their persistence, ubiquity across ecosystems, and capacity to interact with toxic substances. These small synthetic particles could originate either from the degradation of larger plastic debris or from their direct manufacture for specific applications. Once in the environment, MPs could adsorb and transport hazardous trace elements such as heavy metals and metalloids in the so-called Trojan-horse effect. Evaluating the fraction of these elements that becomes bioaccessible during digestion is key to understanding potential health risks.

This study aimed to quantify the gastrointestinal bioaccessibility of eight trace elements (As, Br, Cd, Cr, Pb, Sb, Sn, and Zn) leached from low-density polyethylene MPs (ERM®-EC680m) under simulated human digestive conditions. Two validated static in vitro digestion protocols were applied: the Unified BARGE Method (UBM), mimicking fasting conditions, and the Versantvoort model, simulating digestion after food intake. Both procedures included sequential exposure of the MPs to artificial saliva, gastric fluid, duodenal juice, and bile at 37 °C, under dark conditions. Quantification of released analytes was carried out using inductively coupled plasma tandem mass spectrometry (ICP-MS/MS), employing helium as a collision gas to reduce polyatomic interferences.

The Versantvoort model resulted in markedly higher bioaccessibility values compared to UBM, particularly for As (108 ± 6%), Br (92.3 ± 1.7%), and Zn (48 ± 5%). Conversely, Pb, Cd, Cr, Sn, and Sb exhibited lower bioaccessibility, ranging from 0.5 ± 0.1% (Cd) to 10.8 ± 1.6% (Cr). The influence of MP mass and particle size was also examined under fed-state conditions. An inverse relationship was found between MP quantity and bioaccessibility for Sb, Sn, and Zn: Sb decreased from 5.8 ± 1.8% to 1.0 ± 0.4%, Sn from 0.6 ± 0.2% to 0.08 ± 0.02%, and Zn from 9 ± 3% to 1.19 ± 0.06%, as MP mass increased from 0.2 g to 2.0 g. In contrast, particle size had no significant impact on bioaccessibility. MPs were categorized into three size fractions (>0.84 mm, 0.84–0.5 mm, and 0.5–0.25 mm), with Pb and Cr bioaccessibility showing minor variation across sizes (e.g., Pb: 39.4 ± 1.6% in the largest fraction vs. 35 ± 2% in the smallest; Cr: 2.79 ± 0.12% vs. 3.1 ± 0.7%).

As a proof of concept, the method was applied to real MPs recovered from recycled rubber turf pellets used in outside surfaces and playgrounds. This demonstrated the applicability of the approach for assessing potential human exposure to inorganic contaminants associated with environmental MPs under realistic ingestion scenarios.

Oligomeric proanthocyanidins (OPCs) are bioactive polyphenols known for their versatile and health-promoting properties. In particular, OPCs with a degree of polymerization (DP) between two and four are considered bioavailable, rendering them highly relevant for research and industry, especially as active ingredients in dietary supplements.[1, 2] However, the selective isolation and identification of these bioactive compounds from complex natural sources such as grape seeds – a sustainable, cost-effective by-product of the wine industry – remain a significant analytical challenge due to their structural diversity, low concentration, and susceptibility to degradation, highlighting the demand for robust analysis strategies.[3]

To address these isolation challenges, 3D-printed molecularly imprinted polymer (3DMIP) cartridge inserts present a promising, selective, and cost-efficient alternative to conventional purification techniques. These tailor-made materials are designed to recognize specific structural features and thus efficiently bind and enrich the targeted OPCs.

Herein, a solution for classification and characterization of OPCs in grape seed extracts using infrared attenuated total reflection (IR-ATR) spectroscopy in combination with multivariate data analysis is demonstrated. A spectral database was established using reference compounds and purified fractions. Principal component analysis (PCA) was then applied to correlate spectral variations with the composition and DP of OPCs. The focus was specially on distinguishing between monomers, bioavailable and bioactive OPCs and higher polymerized forms.

The developed spectroscopic method provides a rapid, solvent-free, and non-destructive alternative to conventional chromatographic techniques. Combined with selective enrichment via 3DMIPs, this approach enables efficient targeted purification and quality control of OPC-containing products for industrial and research applications.

References

1. Rauf, A. et al. Proanthocyanidins: A comprehensive review. Biomed. Pharmacother. 116, (2019).

2. Ou, K. & Gu, L. Absorption and metabolism of proanthocyanidins. J. Funct. Foods 7, 43–53 (2014).

3. Kuhnert, S., Lehmann, L. & Winterhalter, P. Rapid characterisation of grape seed extracts by a novel HPLC method on a diol stationary phase. J. Funct. Foods 15, 225–232 (2015).

Microscopy is one of the standard analytical methods for characterizing biological samples. It is routinely used in many fields to investigate the structure of samples and identify patterns or anomalies by visually assessing an image. However, typical light microscopy is limited to visible light, which gives little information on the chemical composition of a sample. To obtain additional – ideally molecular - information, hyperspectral imaging presents a powerful technique, combining the advantages of spectroscopy and imaging. With this method, a two dimensional, spatially resolved image is recorded, with each pixel location representing a spectrum [1]. This additional third dimension allows for the analysis of a sample not only visually but also through its diverse spectral signatures in a single measurement. Thus, insight into the sample composition is provided by extracting spectral information using multivariate data analysis routines. Furthermore, classification strategies can be useful for recognizing patterns and for differentiating between two or more cases (e.g. healthy vs. diseased).

The versatility of molecular imaging techniques facilitates applications in a wide range of scenarios. An interesting spectral regime in hyperspectral imaging is the mid-infrared (MIR) region since IR spectroscopy is a common analytical method to characterize various samples. This method offers many advantages, such as obtaining molecular specific information quickly in a non-destructive process, allowing for the label free extraction of chemical information that is both qualitatively and quantitatively possible. The emergence and recent integration of quantum cascade lasers (QCLs) into IR microscopy provides a significant advancement, revolutionizing its application in the clinical field. The SPERO microscope, developed by Daylight Solutions, exemplifies this innovation [2]. In comparison to conventional IR microscopy using broadband thermal light sources usually requiring a Fourier transformation (FT) for achieving spectrally resolved data, tunable QCL light sources scan a range of wavelengths with a high energy density. Albeit covering a narrower spectral window, significantly shorter analysis times are resulting while preserving comparable spatial and spectral resolution. This advancement fulfills the clinical need for fast and reliable diagnostic analysis.

The current state of research demonstrates the capability of such a QCL IR microscope in addressing various research questions, with the objective of quickly characterizing samples with detailed spectral information at a microscopic level. The potential scope of research ranges from the analysis of polymers to biological materials. To establish a basic understanding of how the SPERO microscope operates and how to handle and evaluate the resulting hyperspectral data, the objective of this work was to carry out fundamental measurements as proof of principle studies and generate a workflow for sample analysis. After using principal components analysis (PCA) as an exploratory unsupervised data evaluation method to identify patterns and trends within the obtained MIR hyperspectral images, classification by partial least squares – discriminant analysis (PLS-DA) was carried out. The obtained results show a successful differentiation between different polymer materials in the case of analyzing blank sample slides, a visual identification of crystallized caffeine in coffee and black tea by assessing images of class prediction probability and a discrimination between fungal contaminated and non-contaminated wheat kernels. In the future, the identification of tumor tissue to diagnose and characterize different cancer types by applying classification models using hyperspectral images obtained by QCL-IR microscopy is a central and promising field of research [3].

[1] Schultz, R. A. , Nielsen, T. , Zavaleta, J. R. , Ruch, R. , Wyatt, R. , and Garner, H. R. Hyperspectral Imaging: A Novel Approach for Microscopic Analysis. Cytometry 2001, 43, 239–247.

[2] Spero® Chemical Imaging Microscope: Real-time QCL-IR Spectroscopy. https://www.daylightsolutions.com/products/spero/ (accessed May 23, 2025).

[3] Kuepper, C. , Kallenbach-Thieltges, A. , Juette, H. , Tannapfel, A. , Großerueschkamp, F. , and Gerwert, K. Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections. Scientific Reports 2018, 8

Helium is one of the most important, if not the most important refrigerant in cryogenics. Generating temperatures as low as the normal boiling point of helium (4.2 K) are easily achievable using helium. Using other helium-based technologies such as evaporation cooling or 3He-4He dilution refrigeration, even lower temperatures down to ~10 mK can be achieved. The purity of the helium is crucial here. Even minute traces of hydrogen, ranging from 10⁻⁹ to 10⁻⁷, are enough to cause laboratory flow cryostats to fail due to blocking. Adequate analysis methods are therefore essential in cryogenics.

This paper presents a simple spectrometric setup and the figures of merit achieved with it. The flowing sample gas is precisely conditioned to an absolute pressure of a few millibar inside a glass tube. This tube is located within a 3/4 lambda Broida cavity. A plasma is ignited by a spark generator and continuously excited using a microwave generator. Finally, the plasma is analysed by optical emission spectrometry. The hydrogen, neon and oxygen lines are of particular interest here, as are the nitrogen bands. A range of factors was investigated, including the impact of the detector exposure time, the effect of the microwave power coupled into the cavity, the role of the plasma pressure, and the significance of the flow velocity. After optimising these parameters, the setup has been calibrated for hydrogen. Based on the analysis of the H-alpha spectral line, the detection and quantification limits for hydrogen were found to be in the range of 10⁻⁶.

Infrared and Raman spectroscopy hold great promise for clinical applications. However, the inherent complexity of the associated spectral data necessitates the use of advanced machine learning techniques which, while powerful in extracting biological information, often operate as black-box models. Combined with the absence of standardized datasets, this hinders model optimization, interpretability, and the systematic benchmarking of the growing number of newly developed machine learning methods. To address this, we propose a simulation-based framework for generating fully synthetic spectral datasets using Monte Carlo approaches for benchmarking. The artificial datasets mimic a wide range of realistic scenarios, including overlapping spectral markers and non-discriminant features and can be adjusted to simulate the effect of different parameters, such as instrumental noise, number of interferences, and sample size. These spectra are simulated through the generation of Lorentzian bands across the mid-infrared range, without specific reference to experimental data or chemical structures. We used the proposed methodology to compare different spectral marker identification protocols in a partial least squares discriminant analysis (PLS-DA), showing that the orthogonal PLS-DA (OPLS-DA) approach, when combined with marker selection based on VIP scores or the regression vector, yielded higher sensitivity, specificity, and interpretability than standard PLS-DA using the same selection criteria. This framework was further used to benchmark the classification capabilities of commonly employed machine learning algorithms, incorporating both linear and non-linear markers reflective of compositional variations across the target classes. Key findings were validated using real infrared spectra from human blood serum and saliva collected in the frame of a clinical study. Overall, the proposed approach provides a versatile sandbox environment for the systematic evaluation of data analysis strategies in vibrational spectroscopy, that can help experimentalists to better interpret spectral markers or data analysts focused on benchmarking and validating new algorithms.

Liquid crystal (LC) devices with improved electro-optical properties are currently in active development. One of the promising areas is ferroelectric liquid crystals. The propagation of intense light beams in such media can be accompanied by their interaction, and such interaction can be controlled or switched by optical means. However, the structural characteristics of such molecules also play an important role. Recently, a new optically active molecule [1] containing a quaternary ammonium group, promising for liquid crystal systems, was synthesized (N-[4-((2R)-octan-2-yloxy)benzyl]-N,N-dimethylhexadecyl-1-ammonium tosylate; 1).

As was shown in [2–4], vibrational circular dichroism (VCD) spectra give full information about the absolute configuration of molecules. In this work, we analysed the sensitivity of the VCD and IR spectra of 1 to the mutual spatial orientations of the functional groups and estimated the probabilities of the second harmonic generation (SHG) by this molecule for a number of wavelengths in optical region. The equilibrium configuration, VCD and IR spectra of 1 were calculated at the B3LYP/6-311G level of theory. Then the mutual orientations of two functional groups containing the oxygen and the nitrogen atom, respectively, were changed by rotation around single bonds, and for such configurations the VCD and IR spectra were calculated anew. Comparison of the calculated VCD and IR spectra has shown that they are both very sensitive to the mutual orientation of the functional groups and can serve as a basis for assignment of such experimental spectra. For the monomer and some associates of 1, the calculation of the components of the first cubic and second quaternary hyperpolarizability tensor of the type β(-2ω,ω,ω) and γ(-2ω,ω,ω,0), which determine the efficiency of the second harmonic generation (including that induced by an external electric field γ(-2ω,ω,ω,0)), was carried out at the B3LYP/6-311G level of theory for the following wavelengths: 759.4, 569.5 and 455.6 nm. Analysis of the calculated data shows that the SHG efficiency increases nonlinearly with decreasing wavelength of the incident light. The greatest effect is achieved when the light flux is directed perpendicular to the direction of the dipole moment of the LC molecule (along the X axis), which is directed along the Y axis. Switching on an external electric field does not change the trends described above, but significantly increases the efficiency of the SHG process.

Keywords: VCD, IR spectra; LC molecules, SHG, configurations

Acknowledgements

This study was supported by the Belarusian State Program of Scientific Investigations 2021–2025 “GPNI Chemical processes, reagents and technologies, bioregulators and bioorgchemistry” (2.1.01.04). The work of A.A.K. was funded by the Ministry of Science and Higher Education of the Russian Federation as a state assignment for the Saratov Federal Scientific Centre of the Russian Academy of Sciences (research topic no. 124020100147-6).

References

[1] G. Pitsevich, I. Doroshenko et al., J. Mol. Cryst. Liq. Cryst., 748 (2022) 73–81.

[2] M.A.J. Koenis, C.S. Chibueze et al., Chem. Sci., 11 (2020) 8469–8475.

[3] S.R. Bhattacharya, T. Bűrgi, Nanoscale, 11 (2019) 23226.

[4] L.A. Nafie, J. Phys. Chem. A, 108 (2004) 7222–7231.

Increasing industrialization, intensive agricultural activities and climate change have significantly decreased the quality of water available for consumption, putting global health at risk. To minimize the occurrence of harmful pathogens like viruses, bacteria and protozoa, drinking water is subjected to a treatment process that includes disinfection, promoting the oxidative destruction of these microorganisms and preventing many waterborne diseases. However, the presence of natural organic matter (NOM) in the raw water supplied to this process can react with disinfection agents, usually free chlorine, and lead to the formation of unwanted disinfection byproducts (DBPs). Exposure to high concentrations of these DBPs may lead to asthma, cancer, or experience teratogenic, mutagenic or reproductive problems. Silica-based aerogels are an attractive alternative to remove these DBPs from water, due to their simple synthesis process and wide availability of silanes that can confer a variety of targeted properties to the final material.

We developed two silica-based aerogels based on hydrolyzed methyltrimethoxysilane (MTMS) and 3-aminopropyltriethoxysilane (APTES), with distinct surface charge using the sol-gel method. We studied their potential to remove DBPs from water, namely bromodichloromethane (BDCM) and monochloroacetic acid (MCAA), two representatives of the most predominant DBP families found in drinking water - trihalomethanes and haloacetic acids. These tests revealed a good capacity of the aerogels to rapidly remove this type of pollutants when at ppb level. To better understand how these aerogels work on a molecular level, we also conducted quantum chemistry calculations to survey how these two pollutants are adsorbed by hydrolyzed MTMS or APTES building blocks. In the future, we will validate these theoretical results using rotational spectroscopy, a powerful technique that can unambiguously distinguish different molecular species based on their structural properties. In this contribution, we will discuss how looking at the physics and chemistry of DBP adsorption using rotational spectroscopy can be a helpful tool to understand and guide the synthesis of new materials for water treatment.

Acknowledgments: Funded by the European Union, under the Grant Agreement GA101081963 attributed to the project H2OforAll - Innovative Integrated Tools and Technologies to Protect and Treat Drinking Water from Disinfection Byproducts (DBPs). This research was co-funded by the European Regional Development Fund (ERDF). This work was also supported by national funds from FCT - Fundação para a Ciência e a Tecnologia, I.P., within the projects 10.54499/UIDB/00102/2020, 10.54499/UIDP/00102/2020, 10.54499/UIDB/04564/2020, 10.54499/UIDP/04564/2020.

The authors acknowledge FCT for the advanced computing grants with references 2023.10981.CPCA.A2, 2024.07904.CPCA.A3 as well as the computational resources provided by the Laboratory for Advanced Computing at University of Coimbra, Minho Advanced Computing Center (MACC), and by Fundação para a Computação Científica Nacional (FCCN).

M.I.R. and N.M.C. acknowledge the PhD scholarships from FCT with references 2024.03908.BDANA and 2023.00840.BD, funded by national funds.

This work was funded by the European Union (ERC, 101040850 - MiCRoARTiS).

Background: Timely and accurate detection of blood contamination in cerebrospinal fluid (CSF) is critical in neurosurgical practice. While UV-Vis spectrophotometry remains the clinical gold standard for detecting xanthochromia in cerebrospinal fluid (CSF)—specifically targeting oxyhemoglobin (~413–415 nm) and bilirubin (~450–460 nm)—these methods are optimized for electron transitions and not for broader molecular profiling. Fourier transform infrared spectroscopy (FTIR), which probes vibrational modes rather than electronic transitions, is not routinely applied in this context. However, FTIR offers an orthogonal strategy for characterizing bulk biochemical changes associated with blood contamination, independent of pigment-specific absorption. Crucially, FTIR operates at room temperature, requires no reagents, and enables rapid detection of shifts in metabolic patterns of biological fluids—making it potentially attractive for bedside use in neurosurgical settings.

Methods: We applied full-range FTIR spectroscopy (4000–400 cm⁻¹, 4 cm⁻¹ resolution, Bruker Alpha II) to 50 clinical CSF samples (clinically validated: 29 uncontaminated, 21 blood-contaminated). A robust preprocessing pipeline was implemented: Savitzky–Golay baseline correction (window = 51, polyorder = 3, 3 iterations), multiplicative scatter correction (2nd-degree polynomial), standard normal variate (SNV), and z-score standardization. A mean difference spectrum (CSF_bloody – CSF) was computed, and statistical significance across wavenumbers was assessed using unpaired t-tests with Benjamini–Hochberg FDR correction (α = 0.05).

Results: Significant differences were observed in vibrational regions consistent with blood-borne macromolecular components. Specifically, the amide I (~1650 cm⁻¹) and amide II (~1545 cm⁻¹) bands showed elevated absorbance in contaminated samples, reflecting increased protein content (e.g., hemoglobin). Additional differences were detected in the CH-stretching region (2850–2950 cm⁻¹), likely due to lipid-rich plasma fractions, and in the C=O and N-H stretching bands (~1700–1750 cm⁻¹ and 3300–3500 cm⁻¹), consistent with bilirubin-like compounds. Although FTIR lacks sensitivity for chromophore-specific electronic transitions, these vibrational markers provide a reproducible and statistically robust molecular fingerprint of contamination.

Conclusion: This work demonstrates that FTIR spectroscopy—despite not targeting chromophores directly—can effectively discriminate blood-contaminated CSF through robust vibrational profiles. The method's simplicity and lack of sample preparation offer significant potential for clinical translation. FTIR could enable a preparation free bedside assessment of CSF for blood contamination using a single drop—facilitating monitoring and surveillance of patients after surgery for brain and spine lesions with early detection of re-bleeding.