Publications

Cyclobutane-fused heterocycles are important motifs in biologically active molecules, yet their enantioselective synthesis remains a significant challenge. We report a broadly applicable and modular strategy for constructing these strained architectures through a visible-light-mediated, Lewis acid-catalyzed dearomative [2+2] photocycloaddition of indoles, benzofurans, and benzothiophenes with alkenes. The method employs a simple catalytic system based on commercially available rare-earth Lewis acids and chiral pyridine-2,6-bis(oxazoline) (PyBox) ligands. A wide array of heteroarenes and styrenes bearing diverse functional groups participate efficiently, delivering cyclobutane-fused products in up to 96% yield, >20:1 dr, and >99% ee. The synthetic utility is further demonstrated by gram-scale synthesis and facile removal of the directing group to access functionalized amino acid derivatives. Mechanistic investigations, including ultraviolet-visible (UV–vis) spectroscopy, nonlinear effect studies, kinetic isotope effects, and density functional theory (DFT) calculations, reveal that a triplet-state heteroarene engages in regio- and enantio-selective C─C bond formation under mild photochemical conditions. This study highlights the potential of excited-state Lewis acid catalysis in unlocking enantioselective dearomatization pathways for complex molecular architectures.

The accumulation of large datasets by the scientific community has surpassed the capacity of traditional processing methods, underscoring the critical need for innovative and efficient algorithms capable of navigating through extensive existing experimental data. Addressing this challenge, our study introduces a machine learning (ML)-powered search engine specifically tailored for analyzing tera-scale high-resolution mass spectrometry (HRMS) data. This engine harnesses a novel isotope-distribution-centric search algorithm augmented by two synergistic ML models, assisting with the discovery of hitherto unknown chemical reactions. This methodology enables the rigorous investigation of existing data, thus providing efficient support for chemical hypotheses while reducing the need for conducting additional experiments. Moreover, we extend this approach with baseline methods for automated reaction hypothesis generation. In its practical validation, our approach successfully identified several reactions, unveiling previously undescribed transformations. Among these, the heterocycle-vinyl coupling process within the Mizoroki-Heck reaction stands out, highlighting the capability of the engine to elucidate complex chemical phenomena.

Photocatalysis has emerged as a cornerstone of synthetic chemistry, enabling mild and selective transformations by using sustainable light sources. A common assumption persists that most photocatalysts are taken for granted to function as monomorphic species throughout the catalytic cycle. Our findings challenge this premise and discover a new mechanistic picture, demonstrating that the evolution of the catalyst under light is not a degradation artifact but a productive and exploitable transformation pathway. Using phenothiazine (PHT) as a model, we demonstrate that light triggers in situ formation of a diverse "cocktail" of catalytically active dimer, trimer, oligomers and their oxides with unique photophysical and redox properties. These reconfigured species expand the usable light spectrum, including red light, and exhibit better catalytic performance in oxidative coupling and sulfide oxidation reactions. The reconfigured catalysts unlock multiwave activation, driving oxidative coupling and sulfide oxidation reactions with remarkable efficiency (up to 99% yield) across UV to red light (λ = 650 nm), far beyond the capabilities of the parent PHT. We introduce the ReAct-Light concept (Reconfigurable Active species under Light) to capture this dynamic, wavelength-adaptive behavior. The work provides an example of key mechanistic insight into dynamic catalyst evolution, opening the way for the design of next-generation adaptive catalysts with enhanced efficiency.

Catalytic cross-coupling reactions, such as the Mizoroki–Heck reaction, play a crucial role in synthetic chemistry but pose significant environmental and health risks due to the toxicity of reaction components and their mixtures. In this study, we conducted a comprehensive cytotoxicity assessment of individual substances and complex reaction mixtures at different stages of the Mizoroki–Heck reaction. We demonstrate that the cytotoxicity of these mixtures often deviates from predictions on the basis of individual components due to synergistic and antagonistic interactions, with chlorobenzene-containing mixtures mostly exhibiting the lowest toxicity. Furthermore, our findings suggest that noncovalent interactions, including halogen bonding and π-stacking, significantly influence cytotoxicity. Notably, incomplete conversion of the reactants leads to an increase in mixture toxicity, emphasizing the importance of optimizing the reaction conditions. This study underscores the necessity of revising current chemical safety assessment strategies to account for complex molecular interactions in catalytic reactions.

The transition to eco-friendly chemical processes is a pressing concern for modern chemistry; still, current methodologies for evaluating the environmental safety of chemical reactions often fall short in terms of speed and clarity. This study presents tox-Scapes, a novel approach for rapid assessment of toxicity profiles of chemical reactions, exemplified by the widely used Buchwald–Hartwig amination. By integrating the half-maximal cytotoxic concentrations (CC50) measured in human cell lines, tox-Scapes provide a visually intuitive and quantitative tool for identifying the reaction pathways with the lowest toxicological impact. Upon screening 864 reaction routes, issued practical recommendations concerning the choice of catalyst, solvent, and other reagents were issued. In particular, the catalysts that contributed significantly to the "overall toxicity" of the reaction were identified, whereas using tetrahydrofuran as a solvent minimized the "overall toxicity". Although the roles of the starting materials and bases were less crucial, their careful selection could further refine the environmental impact. Usage of tumor selectivity indices (tSIs) enhanced the selection of less harmful chemicals among the substances tested. The novelty of tox-Scapes lies in their ability to swiftly analyze large numbers of reaction pathways. This methodology connects fundamental chemistry and its practical implementation by enabling the rapid identification of the toxicity drivers in catalytic reactions.

Cytotoxicity measurements are widely used in chemical research to evaluate the biological effects of chemical compounds, particularly in the context of green chemistry. While these assays appear straightforward, experiments have shown that their outcomes strongly depend on the parameters engaged and the logic applied in data interpretation. In this study, using three common imidazolium ionic liquids tested in two cell lines as an example, we demonstrate how seemingly minor changes in the experimental setup can significantly influence the results, complicating data interpretation and limiting comparability across studies. This work stresses the importance of adopting a systematic approach to cytotoxicity studies, considering cellular responses as part of a complex network of interconnected processes rather than as isolated data points. We aim to raise awareness among chemists about these pitfalls and to provide guidance for more reliable experimental practices, ultimately improving data quality and contributing to safer chemical development in green chemistry.

Magnetic stirrers, the most widely used and ubiquitous devices for performing chemical reactions in laboratory settings, may cause reproducibility problems. Reproducibility in a range of chemical processes can be affected by various factors, ranging from minor to significant effects, including yield, composition, and glassware contamination. In this study, we illustrate the reproducibility issues that may arise from the use of a magnetic stirrer for three fundamental types of chemical reactions. Significant differences were found in the reaction rates and sizes of the nanoparticles obtained via parallel synthesis with the same magnetic stirrer. For catalyst preparation, differences were observed in the morphology of the metal nanoparticles and the process rate depending on the location of the reaction vessel on the magnetic stirrer. In the case of organic synthesis examples, the conversions of parallel catalytic cross-coupling reactions in vessels standing beside each other on the same magnetic stirrer can be significantly different. The results of these experiments revealed the influence of previously unaccounted-for factors, and here, we suggest a control experiment to improve reproducibility. Given the ubiquitous use of magnetic stirrers in chemistry, biology, life sciences, and material sciences, the revealed reproducibility-affecting factor is of broad concern.

Biofilms are critical for understanding environmental processes, developing biotechnology applications, and progressing in medical treatments of various infections. Nowadays, a key limiting factor for biofilm analysis is the difficulty in obtaining large datasets with fully annotated images. This study introduces a versatile approach for creating synthetic datasets of annotated biofilm images with employing deep generative modeling techniques, including VAEs, GANs, diffusion models, and CycleGAN. Synthetic datasets can significantly improve the training of computer vision models for automated biofilm analysis, as demonstrated with the application of Mask R-CNN detection model. The approach represents a key advance in the field of biofilm research, offering a scalable solution for generating high-quality training data and working with different strains of microorganisms at different stages of formation. Terabyte-scale datasets can be easily generated on personal computers. A web application is provided for the on-demand generation of biofilm images.

High-temperature organic chemistry represents a transformative approach for accessing reaction pathways previously considered unattainable under conventional conditions. This study focuses on a high-temperature synthesis as a powerful method for performing solution-phase organic reactions at temperatures up to 500 °C. Using the isomerization of N-substituted pyrazoles as a model reaction, we demonstrate the ability to overcome activation energy barriers of 50–70 kcal mol−1, achieving product yields up to 50% within reaction times as short as five minutes. The methodology is environmentally friendly, leveraging standard glass capillaries and p-xylene as a solvent. The significance of high-temperature synthesis lies in its simplicity, efficiency, and ability to address the limitations of traditional methods in solution chemistry. Kinetic studies and DFT calculations validate the experimental findings and provide insights into the reaction mechanism. The method holds broad appeal due to its potential to access diverse compounds relevant to pharmaceuticals, agrochemicals, and materials science. By expanding the scope of accessible reactions, this exploration of experimental possibilities opens a new frontier in synthetic chemistry, enabling the exploration of previously inaccessible transformations. This study establishes a new direction for further innovations in organic synthesis, fostering advancements in both fundamental research and practical applications.

Digitization of molecular complexity is of key importance in chemistry and life sciences to develop structure–activity relationships in chemical behavior and biological activity. The complexity of a given molecule compared to others is largely based on intuitive perception and lacks a standardized numerical measure. Quantifying molecular complexity remains a fundamental challenge, with key implications currently remaining controversial. In this study, we introduce a novel machine learning-based framework employing a Learning to Rank (LTR) approach to quantify molecular complexity on the basis of labeled data. As a result, we developed a ranking model utilizing the dataset that comprizes approximately 300 000 data points across diverse chemical structures, leveraging human expertise to capture complex decision rules that researchers intuitively use. Applications of our model in mapping the current organic chemistry landscape, analyzing FDA-approved drugs, guiding lead optimization processes, and interpreting total synthesis approaches reveal key trends in increasing molecular complexity and synthetic strategy evolution. Our study advances the methodologies available for quantifying molecular complexity, changing it from an elusive property to a numerical characteristic. With machine learning, we managed to digitize human perception of molecular complexity. Moreover, a corresponding large labeled dataset was produced for future research in this area.

Humins, a by-product of biomass-to-furanics processing, are sustainable and underutilized carbonaceous feedstock. This study introduces liquid humins as precursors for synthesizing innovative carbon materials tailored for Pd/C catalysts. These materials mitigate the "dead" metal issue, where inaccessible Pd particles hinder catalytic efficiency. By exploring methods to convert liquid humins into carbon materials with optimized porous structures and nitrogen doping, we developed Pd/C catalysts with significantly enhanced performance. A novel carbon support derived from a composite of thermally cured humins and melamine exhibited low microporosity and high nitrogen content, thereby minimizing Pd encapsulation. Catalytic applications of these Pd/C materials in Suzuki-Miyaura, Mizoroki-Heck, and nitroarene hydrogenation reactions demonstrated superior activity, surpassing many existing biomass-derived Pd/C catalysts. The work highlights humins as a renewable resource for high-performance catalyst development, addressing critical sustainability and efficiency challenges in catalysis. This approach opens new avenues in green chemistry and valorization of industrial by-products, paving the way for cost-effective and scalable applications in organic synthesis.

A novel series of bio-based cationic surfactants, synthesized from the platform chemical 5-(hydroxymethyl)furfural (5-HMF), fatty acids, and bio-based amines, has been developed, offering a sustainable alternative to conventional surfactants. These compounds, referred to as surface-active ionic liquids (SAILs), have critical micelle concentration (CMC) values lower compared to conventional quaternary ammonium cationic surfactants, indicating enhanced surface activity. The surface properties of the SAILs are predominantly influenced by the type of substitution in the cationic head group, with morpholinium-based surfactants having significantly lower CMC values than diethyl ammonium ones. The length of the alkyl chain also plays a significant role in determining the physicochemical and biological characteristics of these surfactants, which vary depending on the chain length. Surfactants with longer alkyl substituents demonstrate enhanced thermal stability and surface activity. The newly synthesized amphiphiles exhibit antimicrobial activity comparable to known quaternary ammonium cationic agents but with lower cytotoxicity. Importantly, these surfactants show controlled degradation under temperature-driven hydrolysis and basic conditions while maintaining stability in acidic environments. These findings highlight the potential of developed bio-based surfactants to deliver high performance with reduced environmental impact, positioning them as potential candidates for antimicrobial applications and industrial uses focusing on sustainability goal.

The transition toward renewable resources is pivotal for the sustainability of the chemical industry, making the exploration of biobased furanic platform chemicals derived from plant biomass of paramount importance. These compounds, promising alternatives to petroleum-derived aromatics, face challenges in terms of stability under synthetic conditions, limiting their practical application in the fuel, chemical, and pharmaceutical sectors. Our study presents a comprehensive evaluation of the stability of furan derivatives in various solvents and under different conditions, addressing the significant challenge of their instability. Through systematic experiments involving GC‒MS, NMR, FT‒IR and SEM analyses, we identified key degradation pathways and conditions that either promote stability or lead to undesirable degradation products. These findings demonstrate the strong stabilizing effect of polar aprotic solvents, especially DMF, and reveal the dependence of furan stability on solvent and additive type. This research opens new avenues in the utilization of renewable furans by providing critical insights into their behavior under synthetic conditions, significantly impacting the development of sustainable materials and processes. The broad appeal of this study lies in its potential to guide the selection of conditions for the efficient and sustainable synthesis of furan-based chemicals, marking a significant advance in green chemistry and materials science.

Transition-metal-catalyzed C-H alkylation of heteroaromatics with alkenes represents an atom-economical and cost-effective strategy for accessing industrially and pharmaceutically relevant compounds. However, the selective C5-H alkylation of biomass-derived furfural and its isosteric analog, thiophene-2-carboxaldehyde, highly challenging yet industrially vital substrates, has remained elusive. Herein, we disclose a Ni/NHC-catalyzed strategy for the C5-H alkylation of furan- and thiophene-2-carboxaldehydes with styrenes and norbornene, enabled by a readily installable and recyclable N-PMP (p-methoxyphenyl) imine protecting group. This method also achieves selective C5-H alkenylation with internal alkynes. Mechanistic studies suggest that C-H alkylation proceeds via a ligand-to-ligand hydrogen transfer (LLHT) pathway. The N-PMP imine group effectively suppresses undesirable benzoin condensation of these reactive aldehydes and prevents NHC trapping in Breslow intermediates, a major catalyst deactivation pathway. The protecting group is efficiently cleaved under acid hydrolysis, yielding C5-functionalized aldehydes, while the liberated anisidine can be recycled for imine substrate preparation. This work also highlights the largely unexplored potential of the N-aryl imine group as the protecting group for distal C(sp²)-H functionalization of heteroaromatic aldehydes under Ni catalysis.

Isophthalonitrile derivatives (IPNs) have emerged as promising organic photocatalysts due to their efficiency and accessibility; however, their inherent lability under light-induced conditions poses significant challenges in monitoring their transformation pathways. Understanding these pathways is crucial for optimizing photocatalytic processes and enhancing reaction efficiency. In this study, we present a novel approach utilizing electrospray ionization mass spectrometry (ESI-MS) to visualize cyanoarene photocatalysts by taking advantage of their specific supramolecular interaction with bromide anions. Our findings reveal that bromide ions facilitate the detection of IPNs and their transformation products with high sensitivity and selectivity, even in complex reaction environments. The interaction predominantly occurs in the gas phase, minimizing interference in solution-based transformations. The developed anion-enhanced detection (AED-ESI-MS) not only provides real-time insights into photocatalyst behavior but also opens new possibilities for the detailed mechanistic investigation of light-driven reactions. The proposed AED-ESI-MS approach using other anions may offer broad applicability and may be worth studying further across various photocatalytic systems.

Adapting biological systems for nanoparticle synthesis opens an orthogonal Green direction in nanoscience by reducing the reliance on harsh chemicals and energy-intensive procedures. This study addresses the challenge of efficient catalyst preparation for organic synthesis, focusing on the rapid formation of palladium (Pd) nanoparticles using bacterial cells as a renewable and eco-friendly support. The preparation of catalytically active nanoparticles on the bacterium Paracoccus yeei represents a more suitable approach to increase the reaction efficiency due to its resistance to metal salts. We introduce an efficient method that significantly reduces the preparation time of Pd nanoparticles on Paracoccus yeei VKM B-3302 bacteria to only 7 min, greatly accelerating the process compared with traditional methods. Our findings reveal the major role of live bacterial cells in the formation and stabilization of Pd nanoparticles, which exhibit high catalytic activity in the Mizoroki–Heck reaction. This method not only ensures high yields of the desired product but also offers a greener and more sustainable alternative to conventional catalytic processes. The rapid preparation and high efficiency of this biohybrid catalyst opens new perspectives for the application of biosupported nanoparticles in organic synthesis and a transformative sustainable pathway for chemical production processes.

Ionic liquids (ILs) show promise for antimicrobial applications but raise concerns about their cytotoxicity. This study systematically evaluates 25 commercially available ILs, assessing their antimicrobial activity against clinically relevant pathogens and their cytotoxicity in nontumorous human embryonic kidney (HEK293T) cells. According to our findings, longer alkyl chains enhanced the antimicrobial potency but increased the cytotoxicity, highlighting a key trade-off. Notably, 1-hexadecyl-3-methylimidazolium chloride (C16MIm Cl) demonstrated high selectivity against Staphylococcus aureus and Candida albicans, while ammonium and phosphonium ILs exhibited high cytotoxicity. By using the selectivity index, we addressed the balance between the efficacy and safety of ILs. In addition, we tentatively assessed the mechanism of cytotoxic effects of ILs and considered possible correlations between the observed cytotoxic and antimicrobial activities and IL lipophilicity. This study provides practical considerations for designing safer antimicrobials on the basis of ILs and calls for a shift toward selectivity-driven IL research.

In this study, we explore extended design of metal–NHC complexes that relies on dual strategies for tuning ligand properties: (i) electronic modulation through π-extended frameworks such as bis(imino)acenaphthene (BIAN), and (ii) systematic aryl substitution to influence σ-donor strength and steric environment. We report the first integrated exploration of these two strategies on a unified ligand platform. A series of Au(I)/BIAN–NHCX complexes were synthesized by introducing electron-withdrawing substituents (X = F, Cl, Br, CF₃) at the ortho-, meta-, and para-positions of the N-aryl groups. This hybrid tuning approach allowed us to probe the synergistic and antagonistic effects arising from π–σ interplay across multiple dimensions. Each complex was thoroughly characterized with respect to synthetic yield, structural features (including X-ray structure and dynamics in solution), photophysical properties (UV-Vis and luminescence), catalytic performance in hydroamination of phenylacetylene, and cytotoxicity in HEK293T cells. Structure–property correlations revealed distinct cooperative and counteractive regimes depending on the substituent type and position. These findings demonstrate that combining orthogonal electronic control elements enables a more predictive and fine-grained design of NHC-based metal complexes, with future implications for catalysis, materials science, and biomedical applications.

Palladium catalysts form a cornerstone of modern chemistry with upmost scientific and industrial impact. Bulk palladium metal itself is chemically inert, and a sequence of chemical transformations has to be utilized to convert the metal into Pd pre-catalyst covered by ligands. However, the "cocktail" of catalysis concept discovered recently has shown that Pd systems can efficiently operate in catalysis without the necessity of a complicated and expensive pre-installed ligand environment. Here, we point out on a green and sustainable process for Pd active species generation without the need of waste-abundant pre-catalyst-related chemistry. In this work, an electric current was used to generate an active Pd catalyst from a bulk metal in an ionic liquid medium for the efficient cross-coupling of aryl iodides/bromides and boronic acids. Synthetically important Suzuki cross-coupling was utilized as a representative test reaction to confirm the idea. It should be emphasized that electric current is used only at the Pd dissolution stage. Afterwards, the electrodes are removed from the reaction mixture and a standard reaction procedure can be followed. The reported catalyst preparation process via electrochemical dissolution is potentially compatible with a number of already existing catalytic methods.

Working with liquid/gas-phase systems in chemical laboratories is a fundamentally important but difficult operation, mainly due to the explosion risk associated with conventional laboratory equipment. Such systems, in the case of improper operation or destruction, may pose a significant threat to researchers. To address this challenge, our work explores the potential of additive technologies, particularly fused filament fabrication (FFF), for improving laboratory safety. We have successfully utilized FFF to produce compact safety modules, including integrated bursting discs, which can be easily made on demand and adapted to various types of reaction setups. Compared with traditional glassware, these modules, when integrated with laboratory reactors, significantly enhance operational safety. Our research highlights that in the event of excessive internal pressure, 3D-printed reactor parts undergo delamination and cracking of the wall, a mechanism that notably avoids the creation of hazardous fragments from the whole reaction vessel. This study demonstrated the efficiency and safety of additively manufactured reactors in organic synthesis using a variety of gases, including acetylene, carbon dioxide, and hydrogen. We systematically tested these reactors in vinylation and azide–alkyne cycloaddition reactions. Our findings confirm that 3D-printed reactors not only provide increased safety during pressurized operations but also maintain operational efficiency. The discussed approach offers a transformative solution for safer and more effective handling of gaseous reagents in laboratory settings, marking a significant advancement in flexible reactor design and chemical laboratory safety practices.

The goal of this study is to estimate the amount of lost data in electron microscopy and to analyze the extent to which experimentally acquired images are utilized in peer-reviewed scientific publications. Analysis of the number of images taken on electron microscopes at a core user facility and the number of images subsequently included in peer-reviewed scientific journals revealed low efficiency of data utilization. Up to around 90% of electron microscopy data generated during routine instrument operation can remain unused. Of the more than 150,000 electron microscopy images evaluated in this study, only approximately 3500 (just over 2%) were made available in publications. For the analyzed dataset, the amount of lost data in electron microscopy can be estimated as >90% (in terms of data being recorded but not being published in peer-reviewed literature). On the one hand, these results highlight a shortcoming in the optimal use of microscopy images; on the other hand, they indicate the existence of a large pool of electron microscopy data that can facilitate research in data science and the development of AI-based projects. The considerations important to unlock the potential of lost data are discussed in the present article.