Chemistry methods : new approaches to solving problems in chemistry最新文献

A red squirrel with a nut symbolizes the importance of sustainability—a core value of a continuous-flow solid-phase peptide synthesis (CF-SPPS) approach. In their Research Article (DOI: 10.1002/cmtd.202500010), I. M. Mádity and co-workers reveal how they used propylene carbonate (PC), a green solvent selected by using the GSK guide, to achieve high-yield synthesis of α- and β-peptides, including challenging sequences, even on >4 g scale. The image reflects low solvent use, reduced PMI, and the eco-friendly, scalable nature of this breakthrough CF-SPPS technology.

The Front Cover depicts copper nanoparticles with finely tuned wettability beneath a cut-away electrolyte layer, forming abundant three-phase interfaces where CO₂, protons, and electrons meet. This balance of hydrophilicity and hydrophobicity enriches local CO₂ concentration, boosting activity, selectivity, and stability. For details, see the Concept by T. W. B. Lo, J. Yin, Q. Lei, and co-workers (DOI: 10.1002/cmtd.202400080).

In this work, inverse gas chromatography at infinite dilution was used to associate the surface properties (London component, acid and basic constants, and enthalpy) of two tannic based adsorbent materials with the removal capacity against lead pollutant in contaminated water. Such materials have been prepared with same molar ratio TEOS/tannic (5/1) using p-toluene sulfonic (p-TSA) and nitric acids (NA) as catalyst. The dispersive component of the surface (London component, γ_S^D) is higher for the p-TSA material (64.7 mJ.m⁻²) than NA material (35.3 mJ.m⁻²). Identical behavior is found for enthalpy (81.2 mJ.m⁻² for p-TSA and 39.2 mJ.m⁻² for NA) and acid constant of the surface (0.25 and 0.15 for p-TSA and NA, respectively). The porous structure is not very important in the removal capacity for these materials due to the very low specific surface area and pore volume being very close for both samples. Kinetically, the adsorption of Pb(II) on p-TSA material follows a Freundlich isotherm model indicating that the surface is heterogeneous. The maximum adsorption capacity of the best TEOS/tannic sample for Pb (II) was 62 mg.g⁻¹. The results obtained in this work establishes that the surface energy also would play a very important role on the removal capacity of contaminants independent of the textural characteristics of the adsorbent.

Polyoxometalates (POM) are promising materials for electrochemical applications, such as supercapacitors. However, their stability in aqueous electrolytes is compromised due to POM cluster leaching. To mitigate this issue, POM can be combined with organic counter cations, which reduce their solubility in water and influence interactions with carbon support materials. Nevertheless, further research is needed to determine the optimal characteristics and electrode design for maximizing performance. In this work, a synergistic methodology to investigate POM compounds bearing cations with three core functionalities (ammonium, imidazolium, and pyridinium) and varying alkyl side chain lengths, is developed in order to elucidate and optimize the effects of hydrophobicity on the structure of organic–inorganic hybrid materials, electrode films, and their electrochemical performance. The results show that, although cations with long alkyl chains exhibit lower capacitance, they can be activated through molecular rearrangement in the solid state, facilitated by the flexibility of these chains within the structure. By combining thermal and electrochemical techniques, the electrode materials are optimized. These findings demonstrate that the careful selection of counter-cations with the appropriate molecular structures, followed by a thermal activation protocol, is key to developing more efficient and durable energy storage systems.

Accurate quantification of both crystalline and amorphous phases of active pharmaceutical ingredients is crucial for ensuring drug efficacy and stability. However, amorphous content quantification poses significant challenges using traditional analytical techniques. To overcome these limitations, this work introduces a novel method combining solid-state nuclear magnetic resonance (SSNMR) with multivariate curve resolution-alternating least squares(MCR-ALS). Tested on mebendazole and indomethacin as model compounds, this approach enables accurate and robust quantification of crystalline and amorphous phases by leveraging the full spectral deconvolution through advanced multivariate analysis, overcoming the intrinsic challenges of cross polarization magic angle spinning (CPMAS) quantification. The approach allows for accurate quantification by either using reference spectra of the pure forms as constraints or extracting the spectral contributions directly from mixture data, making it applicable even when pure components are not available. While demonstrated in pharmaceuticals, this fast, robust, and user-independent approach is broadly applicable for solid-state quantification across various fields.

Reverse paintings on glass are a group of specific artworks created in a reverse order with respect to conventional paintings. Their material research is particularly demanding because in many cases their dismantling is scarcely possible, limiting sampling and employing more sophisticated methods. Herein, different techniques ranging from noninvasive to destructive are employed in the investigation of two types, folk reverse paintings and reverse paintings with a metallic background. The potential of photography and digital microscopy observation is tested with the aim to help curators and restorers obtain as much information as possible without the need for expensive and hardly accessible analytical techniques. The acquired results were supported and, in some cases, clarified by scanning electron microscopy with energy-dispersive spectrometer analysis of the inorganic components, while organic components are studied by infrared (IR) spectroscopy and liquid chromatography–electrospray ionization–quadrupole time-of-flight mass spectrometry. The assessment of the different IR arrangements is also performed, suggesting the microattenuated total reflection Fourier transform infrared spectroscopy technique the most suitable for the analysis of reverse paintings on glass. The need for the utilization of complementary techniques is also demonstrated on the example of protein binder classification.

Combinatorial microfluidic systems (CMFs), including droplet-based platforms, concentration gradient generators, and valve-based architectures, enable systematic and high-throughput exploration of complex experimental spaces. These platforms generate large, multidimensional datasets at speeds and scales beyond the capacity of conventional methods. Machine learning (ML) represents a powerful way of analyzing these datasets, uncovering hidden patterns, and guiding experiments through real-time, adaptive control. This review explores the synergistic interaction between CMFs and ML, driving the development of intelligent platforms for chemical synthesis and reaction optimization, biological assays, and microfluidic device design. Emphasis is placed on closed-loop platforms where ML actively informs experimental decisions, improving speed, precision, and reproducibility. We discuss key challenges to broader adoption, including the limited scalability of microfluidic hardware, the need for standardized, high-quality datasets, and the interpretability of complex ML models. Finally, the importance of interdisciplinary collaboration among engineers, biologists, chemists, and data scientists is highlighted, alongside the development of modular design tools, curated data resources, and explainable artificial intelligence (AI). Together, these efforts are essential to realizing autonomous, ML-driven CMF platforms capable of transforming healthcare, chemical research, and industrial innovation.

Herein, the development and application of a customized nonthermal plasma diffuse reflectance infrared Fourier transform spectroscopy cell based on the Harrick reaction chamber is presented, which integrates a miniaturized dielectric barrier discharge (DBD), implemented in a Bruker Invenio S Fourier transform infrared spectroscopy (FTIR) spectrometer. The one-sided closed electrode-tube arrangement, mounted in a PEEK cylindrical holder, is inserted through the observation window. The stable operation of AC-driven (10.6 kHz) dielectric barrier discharges in binary gas mixtures of argon and CO₂ is monitored by electrical measurements, which also allows the determination of the discharge power. The gas outlet is connected to a mass spectrometer for online quantitative product gas analysis, enabling operando FTIR spectroscopic studies of plasma-assisted heterogeneous catalyzed reactions. The impact of applied discharge voltage under the variation of the gas composition, gas flow, catalyst pretreatment procedure, and the distance between electrode and catalyst bed has been studied for the CO₂ splitting employing CeO₂ as a catalyst. The operando FTIR spectroscopic study of the plasma-assisted CO₂ dissociation suggests both an active CO₂ dissociation on the ceria surface and a plasma-induced reorganization of the catalyst surface structure. The results in terms of calculated specific energy input and CO₂ conversion correspond with the trends reported for this transformation in coaxial DBD reactors.

Rapid and accurate characterization of carbohydrate ring conformers in oligosaccharides, glycoproteins, foldamers, and other sugar-containing molecules remains a challenge. Here, a state-of-the-art, fine-tuned cyclic ion mobility mass spectrometry (cIM-MS) method is presented to examine and separate ring conformers of sugar moieties at the μg-ng scale without purification. We compared ring structures obtained from X-ray crystallography (solid phase), nuclear magnetic resonance spectroscopy (NMR) (solution phase), and cIM-MS (gas phase) to assign conformational motifs. We performed detailed gas-phase conformational calculations, along with experimental and theoretical collisional cross-section (CCS) measurements using various software tools, to identify the most accurate prediction method for carbohydrates. Our analysis revealed that the current CCS calculation tools require further refinement for reliable application to sugars. Thus, the combination of experimental and theoretical methods holds strong potential for confident sugar conformation assignment in the future.