Crown ether-ammonium inclusion compounds have attracted great interest in the fields of supramolecular chemistry, crystal engineering, and molecular switches due to their tunable host-guest dynamics and stimuli-responsive phase transitions. However, most reported systems exhibit phase transitions only below room temperature, limiting practical applications, and their luminescence properties remain largely unexplored. Herein, we report a host-guest inclusion compound, [(2-fluorophenethylaminium)(18-crown-6)][PF6] (1) that undergoes a reversible phase transition at 404 K, approaching the highest values reported in crown ether-based systems. Single-crystal X-ray diffraction confirms that the ammonium cation is tightly anchored within the 18-crown-6 cavity through N-H⋯O hydrogen bonds. Remarkably, the regioisomeric 3-fluoro (2) and 4-fluoro (3) analogues show no detectable phase transition, yet all three isomers display intense blue emission under 365 nm UV irradiation. This contrast demonstrates that 2-fluorine substitution is essential for the high-temperature transition, while luminescence arises from supramolecular confinement and does not depend on the fluorine substitution position. Density functional theory calculations support an intermolecular charge-transfer mechanism: the HOMO is localized on the crown ether oxygen atoms, the LUMO on the aromatic ring of the cation, with a calculated HOMO-LUMO gap of 4.49 eV. Collectively, these results demonstrate decoupling of the two functions, where the phase transition is governed by fluorine regiochemistry and emission is controlled by confinement effects. This decoupling provides a design principle for independently tuning thermal and optical properties in multifunctional molecular crystals.

The principles of green chemistry have progressively expanded into green analytical chemistry (GAC) and green sample preparation (GSP), fostering the development of quantitative tools such as AGREE and AGREEprep to assess the environmental sustainability of analytical workflows. Although these tools are increasingly adopted, their application is often limited to numerical scoring, with scarce discussion of the underlying assumptions and decision-making processes. This study critically evaluates the applicability and effectiveness of AGREE and AGREEprep in the context of Microwave-induced Plasma Atomic Emission Spectroscopy (MP-AES) analyses, using a real analytical workflow adopted within the Italian PRIN2022 project SECURE-COATS focused on developing functionalized and sustainable coatings for the conservation of stone materials in cultural heritage. The case study involves the determination of Ag, Zn, Ca and P in aqueous solutions obtained from immersion tests in bacterial growth media and from artificial ageing tests, aimed at assessing, respectively, the release of potentially antibacterial metals and the durability of the new coatings. A systematic and transparent data collection was performed to populate both AGREE tools, and the rationale behind each input parameter is explicitly discussed. This approach allows a critical assessment of how methodological choices, instrumental features and sample preparation steps influence the final greenness scores. This work demonstrates their value as decision-support instruments for improving analytical processes also in the field of chemistry for cultural heritage, by reducing both environmental impact and operational costs. The provided data and proposed methodology could serve as a useful reference framework for future green assessments.

Dataset creation is a critical component of predictive machine learning technology. In the field of chemistry, large experimental datasets are scarce, especially for niche chemical properties and topics, and their creation is cumbersome and time-consuming when performed manually. Here, we present Librarian of Alexandria (LoA), an open-source and lightweight framework for testing large-language models (LLMs) on the task of generating large datasets via direct extraction from scientific literature. LoA is available on GitHub along with example inputs, outputs, Docker container, and a Colab-friendly Jupyter Notebook. LoA has the chosen LLM(s) check the relevance of a research paper and perform data extraction. Two separate or identical LLMs may be independently and modularly specified by the end-user for these separate tasks. LoA can be easily updated via simplified user incorporation of the latest available LLMs. We compare several LLMs for both relevance and extraction functions and automate the collection of research papers for several popular chemical journals providing open access. LoA provides a much-needed testing environment which can be used to develop LLMs capable of assembling enormous chemical datasets with minimal effort on the part of the scientist. The best models we were able to test achieved ∼95% accuracy, which is sufficient for the purposes of training predictive machine learning models.

Accurate NOE/ROE-based distance determination is a crucial tool in stereochemistry and conformational analysis of both protein and small molecule structure elucidation. Despite being widely used in countless fields of chemistry and biology, the factors determining the accuracy of the obtained distances are sometimes neglected. Herein, we present the systematic analysis of the performance of six commonly used NOESY and ROESY pulse programmes for quantitative NOE/ROE analysis, evaluating the quality of the data based on the number of quantifiable correlations and the accuracy of the corresponding NOE-derived interproton distances. The effect of two solvent suppression schemes on the NOE/ROE quantitativity is assessed. We found that the total number of quantifiable correlations and the errors of the derived distances depend on the pulse programme used, and the error increases drastically when two or more spectra are removed from the build-up curves for the generation of NOE/ROE build-up rates, using the initial-rate approximation. Solvent suppression using excitation sculpting results in the underestimation of the NOE-derived distances. EASY ROESY run without solvent suppression shows a bias towards overestimated NOE-derived distances. The obtained data suggest that the determination of quantitative interproton distances necessitates the careful selection of pulse programme.

ABSTRACT This paper focuses on the relationships between scientists and software. We propose to view the field of computational chemistry as a particular ‘repertoire’ where software is central and where interactions among practitioners involve disputed visions of software openness. We argue that the multifaceted category of ‘users’ is key to understanding these visions of openness. Our aim is thus to discuss how the computational chemistry community evolves in its relationship to software packages. Throughout our paper, the notion of ‘users’ becomes more complex, all along the commodification of programs into packages and the increasing complexity of the packages themselves. We relate four different vignettes from the history of computational chemistry, spanning from 1962 to 2024, to illustrate how visions of openness and user agency evolve. These include a software-sharing initiative, controversies over licensing and user management, and debates about the AlphaFold AI tool. Ultimately, the paper explores how these dynamics contribute to inequity in how scientists engage with computational tools. A general trend of dispossession of agency of users in their relationship with a piece of software is finally put forward.

Ferroptosis is a specialized form of regulated cell death that is dependent on intracellular iron and is characterized by excessive lipid peroxidation, accumulation of lipid peroxides, and increased intracellular iron levels. This process is regulated through complex and tightly coordinated molecular mechanisms involving multiple signaling pathways and regulatory proteins, including key antioxidant defense components such as glutathione peroxide 4 (GPX4) and ferroptosis suppressor protein-1 (FSP-1). Increasing experimental evidences suggested that modulation of ferroptosis pathway might offer a potent target for breast cancer management, as ferroptosis dysregulation has been strongly associated with tumor invasion, progression, and drug resistance. Current cancer treatment strategies including surgery, chemotherapy, radiation therapy have detrimental effects on cancer patients. Therefore, it is highly needed to focus on safe and effective therapeutics like natural compounds for cancer therapy. These compounds have shown the significance of ferroptosis-mediated cell death, thereby providing drug candidate for developing ferroptosis-inducing agents. Current research studies suggested that numerous plant-based compounds have strong anticancer potential via ferroptosis induction in breast carcinoma. However, these results are dependent upon preclinical experimentation and lacking validation of long-term clinical research. Thus, this review is designed to provide a mechanistic overview of plant-derived natural compounds by targeting ferroptosis pathway specifically in breast cancer. This could help the researchers working in medicinal chemistry field and pharmacology to better understand the mechanism of action of these compounds against breast carcinoma and provide an alternative approach to treat breast cancer.

Biomolecular condensates, which are membraneless organelles formed through liquid-liquid phase separation, serve as fields that regulate chemical reactions and functions by linking functionally related molecules. Accumulated data from the field of phase separation chemistry suggests that biomolecular condensates form and grow via the widely involved mechanisms, including diffusion-limited growth, fusion, and Ostwald ripening. However, tracking individual emerging or growing condensates is required to differentiate and quantify these mechanisms. In this study, we developed a label-free condensate growth analysis platform based on ultra-widefield dark-field microscopy and image analysis. Our system enables long-term detection for at least 30 min, high-time-resolution imaging at 0.1 s, and an ultra-wide imaging area of 5.8 mm2. Using this platform, we characterized the growth processes of approximately 10,000 condensates in two model proteins, HP1α and FUS, by counting the occurrences of the three growth mechanisms. For these two proteins, condensates form through diffusion-limited growth and unexpectedly primarily grow via fusion rather than Ostwald ripening, either simultaneously or with a short lag time. Our results demonstrate that the platform can analyze the formation and growth of various biomolecular condensates in vitro without labeling the sample.

Allenes, as versatile intermediates with unique cumulative double bond systems, have been widely used in cycloaddition reactions for constructing various cyclic skeletons, yet the selective synthesis of cyclobutenes via double allenes [2+ 2] annulation still remains a long-standing challenge. Herein, we report a phosphine-catalyzed unsymmetric [2+ 2] annulation of allenyl phosphonates for the efficient construction of highly substituted cyclobutenes. The reaction exhibits broad substrate scope, delivering the target cyclobutenes in moderate to good yields with exceptional Z/E selectivities and diastereoselectivities. Mechanistic studies reveal that the reaction proceeds via phosphine-induced zwitterion formation and deprotonation of allene. The Lewis acid enables precise control of diastereoselectivity, while silane effectively suppresses allene isomerization to conjugated dienes and prevents catalyst deactivation, thus ensuring reaction efficiency. Furthermore, the synthesized cyclobutene derivatives demonstrate good structural modifiability through diverse transformations. This work enriches the field of phosphine-catalyzed allene chemistry, fills a gap in allene-based [2+ 2] cyclization modes, expands the methodological toolbox for cyclobutene synthesis, and provides a versatile platform for accessing complex cyclobutene-containing molecules.

Dynamics of supramolecular complexes serve to rationalize the constant motion inherent to the formation of non-covalent adducts. Here, the C60S8 adduct is evaluated through the combined molecular dynamics energy decomposition analysis approach (MD + EDA), unraveling the constant orbit-like motion of S8 around the C60 fullerene globe, showing comparable supramolecular interaction energies for the entire dynamic process, arising from a balance between stabilizing (electrostatic, London dispersion, orbital) and destabilizing (Pauli repulsion) forces. Thus, molecular dynamics simulations reveal the dynamic flexibility, with the S8 ring freely reorienting in relation to the C60 surface, remaining at a similar distance with similar interaction energy. The charge transfer analysis indicates negligible net electron transfer, but interestingly, the calculated electronic coupling and charge hopping rates suggest efficient charge transport. These findings highlight the delicate interplay of weak non-covalent interactions governing the formation of the C60-S8 system and its potential for supramolecular charge transport applications, combining dynamic adaptability with specific binding properties for applications in supramolecular chemistry and related fields.

Open Access Journals in the Field of Chemistry: An Analytical Study of the DOAJ

Dual atom catalysts (DACs) have attracted extensive attention due to their synergistic effects in enhancing various catalytic reactions, opening up new research directions in the fields of chemistry and material science. Strategically, constructing bimetallic pairs with asymmetric active sites is a key strategy for further improving DACs performances. However, achieving the universal synthesis of a structurally controllable library for DACs supported on inorganic materials remains a significant challenge. In this work, we propose a general strategy for synthesizing asymmetric DACs (A-DACs) through molecular explosion, which can transiently generate extreme conditions in a confined space, offering capabilities that are difficult to realize by conventional approaches. Using this technology, we successfully prepared and systematically characterized 15 kinds of A-DACs containing different metal combinations (Cu-Fe, Cu-Co, Fe-Pt, Ni-Cu, Pt-Pd etc.) and loaded them onto different inorganic carriers (Ti3C2Tx, TiN, TiO2, CeO2, MoS2, etc.). Moreover, Cu1Fe1/Ti3C2Tx and Pt1Pd1/MoS2 are selected as model catalysts to investigate their worthwhile applications in diverse electrochemical reactions. This study provides an ingenious method for the rational design of atomic dispersed catalysts, which is of great significance in the fields of energy conversion and environmental governance scenarios.

Sulfur(VI) fluorides based on sulfur(VI) fluoride exchange (SuFEx) chemistry have demonstrated their unique versatility and high efficiency in the field of medicinal chemistry. Acting as both covalent and hydrogen bond donors, the novel N-CF2H sulfamoyl fluoride will enhance the binding strength between drugs and receptors in organism, thereby injecting new vitality into the research of targeted drugs. Herein, we report the two-step synthesis of N-CF2H sulfamoyl fluorides from primary amines via successive fluorosulfonylation and insertion of difluorocarbene. This method shows broad scope, provides a platform for rapidly generating N-CF2H sulfamoyl fluorides by virtue of the diversity and availability of amines. The stability of N-CF2H sulfamoyl fluorides was tested in aqueous environment at different pH, showing that most compounds remained >95% intact for 72 h. As a novel SuFEx building block, N-CF2H sulfamoyl fluoride shows chemoselectivity toward phenol and does not react with amines and alcohols. Besides, N-CF2H sulfamoyl fluorides were subjected to debenzylation and amide-bond-formation reactions to generate peptides, Sitagliptin derivative and bioactive alkylamine. Finally, N-CF2H sulfamoyl fluoride underwent successful F-18 labeling. With the reported syntheses, we believe that N-CF2H sulfamoyl fluoride will soon be practically applied in drugs, covalent targeted radioligand, F-18 PET tracers, electrolyte in general.

In chromatographic technology, the stationary phase is of paramount importance, with its properties intrinsically linked to both the separation performance and the mode of chromatography employed. The study of stationary phase modifiers has attracted considerable attention in the field of analytical chemistry due to their critical role in the separation process. Of late, hydrogels, characterized by a three-dimensional structure and multiple interaction sites, have been harnessed to augment the development of stationary phases for liquid chromatography. Hydrogel-modified silica stationary phases have demonstrated superior separation performance across various chromatographic modes, including hydrophilic interaction, reverse-phase, and ion exchange liquid chromatography. The evolution of these functionalized silica stationary phases holds significant importance in the fields of analytical chemistry and separation science. However, to date, there has been a lack of comprehensive reviews discussing the use of hydrogel-modified silica stationary phases in liquid chromatography. This review provides a succinct overview of the performance and recent advancements of hydrogel-modified silica stationary phases in high-performance liquid chromatography (HPLC). It also provides an in-depth discussion on the use of hydrogel-modified silica stationary phase composites for the separation of analytes in various chromatographic modes. Efficient separation and analysis of analytes crucial to life sciences and medicine, such as nucleoside bases, steroid hormones, antibiotics, pesticides, and environmental pollutants, can be achieved using various hydrogel-modified silica stationary phases. Finally, it outlines the challenges and prospects associated with the application of hydrogel-modified silica in separation science.

A novel discoid insertthat can be positioned into astandardNMR tube using an associated plunger tool has been developed. By attachingany type of semipermeable barrier to the bottom of the insert, thedetection volume of the tube can be divided into two or more chambers,separated by a barrier of choice. Slice-selective experiments arethen utilized to study a plethora of transport phenomena in real timeby NMR spectroscopy. The technological device is presented togetherwith a proof of concept for three different applications: permeabilitystudies, diffusion-controlled pH titrations, and diffusion-controlledprotein titrations. The developed approach unlocks new tools for scientistsworking in the fields of drug discovery, organic chemistry, biochemistry,chemical biology, microbiology, or electrochemistry that will enablenew types of experiments to be performed by NMR spectroscopy.

The genus Ocotea is a significant source of bioactive agents within the Lauraceae, yet it remains underexplored. Despite its ethnomedicinal relevance and chemical diversity, Ocotea species remain taxonomically challenging as they belong to the multifaceted "Ocotea complex", a phylogenetically unresolved group. Moving beyond previous literature Ocotea surveys, this review provides the first curated, genus-specific data set of both volatile and nonvolatile specialized metabolites. Covering research articles from 1830 to 2025, this review provides the most comprehensive synthesis to date, documenting 984 unique chemical compounds across 115 species. This effort culminated in the construction of the Ocotea Chemical Database (OcoteaDB), a novel digital resource created to streamline the genus's chemical diversity for the global scientific community. Furthermore, it presents current knowledge of biosynthetic routes leading to key bioactive scaffolds, including aporphinoid and benzylisoquinoline alkaloids, lignoids, glycosylated flavonoids, and a diverse array of terpenoids, while addressing the stereochemical and structural intricacies unique to the genus. This review lays a robust foundation to drive future Ocotea-focused bioprospecting studies and guides research in the fields of natural products, chemophenetics, metabolomics, and medicinal chemistry regarding the Ocotea species, its chemical scaffolds, and specialized metabolites.

In the field of functional small-molecule chemistry, fluorinated small molecules are frequently employed. Difluoromethylthiolated compounds are of particular interest due to their distinctive physiochemical characteristics. We present here the synthesis and application of sodium S-(difluoromethyl) sulfurothioate (NaSO3SCF2H) as a potent and adaptable difluoromethylthiolating reagent, which is readily synthesized in a simple step from BnSCF2H and sodium metabisulfite. Based on experimental and theoretical findings, we demonstrate the utility of NaSO3SCF2H in electrophilic, nucleophilic, and radical difluoromethylthiolation reactions, thereby showcasing its unprecedented versatility. Furthermore, the methodology has been expanded to various deuteriodifluoromethylthiolation reactions using NaSO3SCF2D.

Searching for the global-minimum (GM) structure of clusters is a fundamental challenge in computational chemistry, as the potential energy surface (PES) of clusters exhibits a vast number of local minima that increase exponentially with cluster size. This work presents GMMLP (Global-Minimum Search of Clusters Accelerated by Machine Learning Potentials), an efficient software package developed for identifying the GM structures of clusters. GMMLP integrates the atom-in-molecules neural network potential (AIMNet2) with an improved genetic algorithm (GA), leveraging the high accuracy of AIMNet2 trained at the ωB97M-D3/def2-TZVPP level of theory and the global search capability of the optimized GA. To validate GMMLP, benchmark tests were performed on nine types of clusters, including (CH2O)n, (CH3NH2)n, (CH3OH)n, (CH4)n, (H2O)n, (H2SO4)n, (HNO3)n, (NH3)n, and [CO(NH2)2]n (n = 1-10). Computational results show that GMMLP efficiently explores the PES, searching a total of 9869 isomers across all benchmarked clusters with a total wall time of 39,055.14 s (~10.8 h). The average computational time per isomer ranges from 0.22 s for (CH4)n to 10.01 s for (H2SO4)n, demonstrating remarkable efficiency. Additionally, the evolution of relative energy and optimized structures of low-lying isomers are analyzed to illustrate the reliability of the search process. GMMLP provides a powerful tool for cluster research, enabling fast and accurate GM structure identification for a wide range of clusters, which is crucial for understanding cluster properties and their applications in chemistry, materials science, and related fields.

Coordination chemistry is one of the most diverse fields in chemistry. Starting from the unlimited combinations of metals and ligands, a large variety of structures with different coordination modes and geometries can be formed, giving rise to distinct electronic properties that can be harnessed for numerous applications. In particular, noncovalent interactions play a critical role in driving the formation of self-assemblies and supramolecular structures. This account chronicles the author's scientific journey guided by the exploration of noncovalent interactions, moving from the structural and photophysical studies of transition metal complexes to their self-assemblies and, more recently, supramolecular frameworks and organic crystals. These efforts in molecular design and engineering may provide new insights into the future development of functional materials for energy and environmental applications, thereby contributing to key challenges in global sustainability.

Magnetic nanoparticles show promise for applications including targeted drug delivery, contrast-enhanced imaging, and theranostics, but their efficacy is hindered by limited understanding of nanoparticle–tissue interactions that influence transport through biological tissue under magnetic field gradients. Here, we assess the particle size, surface chemistry, and magnetic field gradient dependence of magnetophoretic transport of magnetic nanoparticles (MNPs) through tissue models of increasing complexity/biological relevance. In all cases linear particle transits were observed through the gels, with progressively increasing velocity for higher gradients. The effect of particle size on velocity is negligible at low and intermediate gradient, but at higher gradient the larger MNPs have higher velocity (p-value 0.002). Scaled velocities, vexp × dhyd, were found to correct for hydrodynamic size-induced differences in drag, enabling identification of MNP–matrix interactions that arise from the particle surface functionalisation used; arginine- (Arg-; positive), citrate- (Cit-; negative) and polyethylene glycol (PEG-; neutral). In agarose vexp × dhyd is higher for Arg- and lower for Cit-, as compared to PEG-MNPs, due to increased and reduced flux, respectively, at negatively charged pore restrictions. This effect is eliminated at very high gradient (pore deformation), or on increasing the ionic strength (reduced electrostatic interactions). In contrast in agarose–collagen hydrogels for Cit-MNPs and particularly Arg-MNPs net attraction to the matrix, due to residual electrostatic interactions with the collagenous component, is evident even at high ionic strength. In ECM relatively slow scaled velocity is observed, despite the open pore structure. Cit-MNPs are particularly hindered, suggesting the residual electrostatic interactions are stronger in this case. The findings contribute to understanding of matrix–particle interactions in models of biological tissue, informing material design for effective MNP transport in targeted nanomaterial-based diagnostics and treatment applications.

The conversion of lignocellulosic biomass to platform chemicals and fuels is largely driven by the advancements in heterogeneous catalysis. The one-pot synthesis of the platform chemical, 2,5-furandicarboxylic acid (FDCA), provides a significant advantage in process efficiency, cost effectiveness and sustainability by combining multiple reactions in a single process. This study compares the effectiveness of various combinations of transition metal oxides supported on zeolite-5A for the biomass conversion to FDCA. The metal oxides such as Cr2O3, Fe2O3, MnO2, and Co2O3 were selected in binary combinations (CrMn, FeMn, CrCo, and FeCo) and prepared by simple wetness impregnation methods. The catalytic performance was evaluated through one-pot biomass conversion with sugarcane bagasse as the feedstock to an FDCA yield of 41.12%, 64.58%, 61.75%, and 20.91% for CrMn, FeMn, CrCo, and FeCo, respectively. The catalytic efficiency is correlated to metal dispersion, pore accessibility, and redox synergy between the metal oxides arising from varying oxidation states to facilitate cascade reactions, including dehydration and oxidation steps. This work emphasizes the crucial role of metal oxide combinations and their interaction with the zeolite-5A support in improving catalytic activity for effective biomass valorization. The findings contribute to the field of green chemistry by offering a pathway for catalyst design aimed at sustainable one-pot production of FDCA from renewable feedstock.