Research Center Pharmaceutical Engineering (Austria)

Microplastics are of growing concern due to their ubiquity and potential risks to ecosystems and human health. Their small size, chemical diversity, and coexistence with natural colloids make comprehensive analysis difficult. Here, we evaluate two emerging single particle techniques, single particle inductively coupled plasma-mass spectrometry (SP ICP-MS) and optofluidic force induction coupled with Raman spectroscopy (OF2i-Raman), for their ability to provide complementary information at single microplastic resolution. SP ICP-MS determined carbon mass per particle and enabled detection of degradation-induced trends in size and abundance, while OF2i-Raman identified polymer type and molecular changes via optical trapping and inelastic light scattering. OF2i-Raman is a novel method in the field of microplastic research and was therefore first benchmarked by analysing mixed suspensions of polymethylmethacrylate (PMMA), polystyrene (PS), and polyamide-6 (PA-6), as well as PA-6 in a soil extract to assess selectivity under complex matrix conditions. Subsequently, both techniques were applied in parallel to study the UV-induced degradation of PA-6 and low-density polyethylene (LDPE) as relevant industrial polymers. SP ICP-MS detected longitudinal carbon loss and relative changes in particle sizes and numbers, while OF2i-Raman revealed polymer-specific structural alterations and detected spectral fingerprints even after extended irradiation. Together, SP ICP-MS and OF2i-Raman link elemental mass with molecular identity, providing complementary insights into microplastic degradation. While SP ICP-MS remains confined to controlled laboratory experiments due to its limited selectivity and size range, OF2i-Raman extends the analytical window to complex matrices and mixed polymer systems.

A benchtop NMR instrument in combination with spectral hard modeling enabled monitoring and subsequent kinetic fitting of a chlorination reaction. Different modes were investigated, an NMR tube, re-circulating batch and single pass continuous flow.

Automated electrochemical platforms are attracting attention for their potential in streamlining reaction preparation, electrolysis, and analysis to generate large datasets in a fast and efficient manner. Moreover, the recent implementation of on‐line analytics together with closed‐loop workflows has enabled the emergence of electrochemical self‐driving laboratories. In this review, the common guidelines for the development of these platforms are presented, covering the main modules to assemble these systems. Furthermore, a comprehensive survey of all the platforms applied in synthetic organic electrochemistry is reported, where each example is described in terms of elements and applications and classified by category. Finally, an outlook including a perspective on the topic is presented, proposing potential future directions of the field.

Phosphate plays a crucial role in various physiological and pathological processes; however, effective strategies for analyzing diverse phosphates and monitoring phosphate hydrolysis remain limited. Herein, we develop a metal–organic framework wrapped Cu nanoclusters-based (CuNCs@MOF) fluorescent sensor array for high-throughput discrimination of phosphates and real-time monitoring of their enzymatic hydrolysis. Leveraging the confinement effect of zinc-based MOFs, the encapsulated CuNCs exhibited reduced intramolecular vibration and rotation, resulting in enhanced luminescence performance. Due to the distinct affinities of various phosphates toward zinc ions, the sensor array generates differentiated fluorescence responses for seven phosphates, including adenosine triphosphate (ATP), cytidine triphosphate, uridine triphosphate, adenosine diphosphate, adenosine monophosphate, pyrophosphate (PPi), and inorganic phosphate. Subsequently, the fluorescence response signals are processed using the pattern recognition algorithm to generate the unique fingerprint spectra of each phosphate. We demonstrate that the sensor array can not only identify seven distinct phosphates at concentrations as low as 5 μM and effectively distinguish between their mixtures but also exhibit excellent anti-interference capability and enable dynamic monitoring of ATP and PPi hydrolysis. Notably, the sensor array achieved outstanding performance in complex real-world samples and cellular-level analyses, demonstrating 100% accuracy in blind sample identification. Overall, this work develops a strategy for high-throughput discrimination of phosphates and real-time monitoring of their enzymatic hydrolysis.

The widespread use of peptide-based drugs and the prevalence of amide-containing pharmaceuticals underscore the critical need for efficient, sustainable, and environmentally friendly amidation methods in the pharmaceutical industry. However, traditional approaches rely on harmful solvents, highlighting the urgent need for a paradigm shift toward greener alternatives. We leveraged continuous slurry flow technology to facilitate solid handling and develop scalable and sustainable protocols for amide bond formation in water as the reaction medium. To ensure optimal mass transfer through efficient active mixing, we utilized a spinning disc reactor and an agitated continuous stirred-tank reactor series, both of which are commercially available, including industrial-scale versions. As model reactions, we selected the synthesis of a key efaproxiral intermediate and a technically challenging amidation involving a protected tryptophan derivative. The best results were achieved using hydroxypropyl methylcellulose, a cost-effective, nontoxic, cellulose-derived surface-active agent in water. The optimized lab-scale protocols enabled rapid amidations with productivities of up to 2 kg per day. Notably, neither the synthesis nor the isolation processes required any organic solvents, resulting in minimal waste generation.