Highly Efficient Low-loaded PdOx/AlSiOx Catalyst for Ethylene Dimerization.

Ethylene dimerization is an industrial process that is currently carried out using homogeneous catalysts. Here we present a highly active heterogeneous catalyst containing minute amounts of atomically dispersed Pd. It requires no co-catalyst(s) or activator(s) and significantly outperforms previously reported catalysts tested under similar reaction conditions. The selectivity to C4- and C6-hydrocarbons was about 80 % and 10 % at 42 % ethylene conversion at 200 °C using an industrially relevant feed containing 50 vol % ethylene, respectively. Our kinetic and catalyst characterization experiments complemented by density functional theory calculations provide molecular insights into the local environment of isolated Pd(II)Ox species and their role in achieving high activity in the target reaction. When the developed catalyst was rationally integrated with a Mo-containing olefin metathesis catalyst in the same reactor, the formed butenes reacted with ethylene to propylene with a selectivity of 98 % at about 24 % ethylene conversion.

A comparative study of the predictive performance of different descriptor calculation tools: Molecular-based elution order modeling and interpretation of retention mechanism for isomeric compounds from METLIN database.

In the pharmaceutical industry, the need for analytical standards is a bottleneck for comprehensive evaluation and quality control of intermediate and end products. These are complex mixtures containing structurally related molecules. In this regard, chromatographic peak annotation, especially for critical pairs of isomers and closest structural analogs, can be supported by using a Quantitative Structure Retention Relationship (QSRR) approach. In our study, we investigated the fundamental basis of the reversed-phase (RP) retention mechanism for 1141 isomeric compounds from the METLIN SMRT dataset. Nine different descriptor calculation tools combined with different feature selection methods (genetic algorithm (GA), stepwise, Boruta) and machine learning (ML) approaches (support vector machine (SVM), multiple linear regression (MLR), random forest (RF), XGBoost) were applied to provide a reliable molecular structure-based interpretation of RP retention behaviour of the isomeric compounds. Strict internal and external validation metrics were used to select models with the best predictive capabilities (rtest > 0.73, order of elution > 60 %). For the developed models, mean absolute errors were in the range of 60 to 110 s. Stepwise and GA showed the most suitable performance as descriptor selection methods, while SVM and XGBoost modeling gave satisfactory predictive characteristics in most cases. Validation performed on the published experimental data for structurally related pharmaceutical compounds confirmed the best accuracy of MLR modeling in combination with GA feature selection of general physico-chemical properties. The resulting models will be useful for the prediction of separation and identification of structurally related compounds in pharmaceutical analysis, providing a simultaneous understanding of the interaction mechanisms leading to their retention under RP conditions.

Room temperature epoxidation of ethylene over delafossite-based AgNiO2 nanoparticles.

A mixed oxide of silver and nickel AgNiO2 was obtained via co-precipitation in alkaline medium. This oxide demonstrates room temperature activity in the reaction of ethylene epoxidation with a high selectivity (up to 70%). Using the PDF method, it was found that the initial structure of AgNiO2 contains stacking faults and silver vacancies, which cause the nonstoichiometry of the oxide (Ag/Ni < 1). It has been established that on the initial surface of AgNiO2 oxide, silver state can be considered as an intermediate between Ag2O and Ag0 (i.e. Agδ+-like), while nickel is characterized by signs of a deeply oxidized state (Ni3+-like). The interaction of AgNiO2 with C2H4 at room temperature leads to the simultaneous removal of two oxygen species with Eb(O 1s) = 529.0 eV and 530.5 eV considered as nucleophilic and electrophilic oxygen states, respectively. Nucleophilic oxygen was attributed to the lattice oxygen (Ag-O-Ni), while the electrophilic species with epoxidation activity was associated with the weakly bound oxygen stabilized on the surface. According to the TPR-C2H4 data, a large number of weakly bound oxygen species were found on the pristine AgNiO2 surface. The removal of such species at room temperature didn't result in noticeable structural transformation of delafossite. As the temperature of ethylene oxidation over AgNiO2 increased, the appearance of Ag0 particles was first observed below 200 °C followed by the complete destruction of the delafossite structure at higher temperatures.

Unraveling the low-temperature activity of Rh-CeO2 catalysts in CO oxidation: probing the local structure and Red-Ox transformation of Rh3+ species.

The local structure of the active sites is one of the key aspects of establishing the nature of the catalytic activity of the systems. In this work, a detailed structural investigation of the Rh-CeO2 catalysts prepared by the co-precipitation method was carried out. The application of a variety of physicochemical methods such as XRD, Raman spectroscopy, XPS, TEM, TPR-H2, and XAS revealed the presence of highly dispersed Rh3+ species in the catalysts: Rh3+ single ions and RhOx clusters. The substitution of Ce4+ ions by Rh3+ species, which provided a strong distortion of the CeO2 lattice, is shown. XAS data ensured the refinement of the Rh local structure. It was shown that single Rh3+ sites located next to each other can merge the formation of RhOx clusters with Rh local environment close to the one in Rh2O3 and CeRh2O5 oxides. The distortion of the CeO2 lattice around single and cluster rhodium species had a beneficial effect on the catalytic activity of the samples in low-temperature CO oxidation (LTO-CO). TEM, XAS, and in situ XRD data allowed establishing the structural transformations of the catalysts under Red-Ox treatments. The reduction treatment led to Rhn metallic cluster formation localized on defects of the reduced CeO2-δ. The reduced sample demonstrated efficient CO conversion at 0 °C. However, this system was not stable: its contact with air led to ceria reoxidation and partial reoxidation of Rh to highly dispersed Rh3+ species at room temperature, while heating in an oxidizing atmosphere resulted in the complete reoxidation of metallic rhodium species. The results of the work shed light on the structural aspects of the reversibility of the Rh-CeO2 catalysts based on the highly dispersed Rh3+ species under treatment in the reaction conditions.

Comparative Analysis of Catabolic and Anabolic Dehydroshikimate Dehydratases for 3,4-DHBA Production in Escherichia coli.

The production of 3,4-dihydroxybenzoic acid (3,4-DHBA or protocatechuate) is a relevant task owing to 3,4-DHBA's pharmaceutical properties and its use as a precursor for subsequent synthesis of high value-added chemicals. The microbial production of 3,4-DHBA using dehydroshikimate dehydratase (DSD) (EC: 4.2.1.118) has been demonstrated previously. DSDs from soil-dwelling organisms (where DSD is involved in quinate/shikimate degradation) and from Bacillus spp. (synthesizing the 3,4-DHBA-containing siderophore) were compared in terms of the kinetic properties and their ability to produce 3,4-DHBA. Catabolic DSDs from Corynebacterium glutamicum (QsuB) and Neurospora crassa (Qa-4) had higher Km (1 and 0.6 mM, respectively) and kcat (61 and 220 s-1, respectively) than biosynthetic AsbF from Bacillus thuringiensis (Km~0.04 mM, kcat~1 s-1). Product inhibition was found to be a crucial factor when choosing DSD for strain development. AsbF was more inhibited by 3,4-DHBA (IC50~0.08 mM), and Escherichia coli MG1655 ΔaroE PlacUV5-asbFattφ80 strain provided only 0.2 g/L 3,4-DHBA in test-tube fermentation. Isogenic strains MG1655 ΔaroE PlacUV5-qsuBattφ80 and MG1655 ΔaroE PlacUV5-qa-4attφ80 expressing QsuB and Qa-4 with IC50 ~0.35 mM and ~0.64 mM, respectively, accumulated 2.7 g/L 3,4-DHBA under the same conditions.

Deep learning for retention time prediction in reversed-phase liquid chromatography.

Retention time prediction in high-performance liquid chromatography (HPLC) is the subject of many studies since it can improve the identification of unknown molecules in untargeted profiling using HPLC coupled with high-resolution mass spectrometry. Lots of approaches were developed for retention time prediction in liquid chromatography for a different number of molecules considering various molecular properties and machine learning algorithms. The recently built large retention time data set of standard compounds from the Metabolite and Chemical Entity Database (METLIN) allows researchers to create a model that can be used for retention time prediction of small molecules with wide varieties of structures and physicochemical properties. The ability to predict retention times using the largest data set was studied for different architectures of deep learning models that were trained on molecular fingerprints, and SMILES (string representation of a molecule) represented as one-hot matrices. The best result was achieved with a one-dimensional convolutional neural network (1D CNN) that uses SMILES as an input. The proposed model reached the mean absolute error and the median absolute error equal to 34.7 and 18.7 s, respectively, which outperformed the results previously obtained for this data set. The pre-trained 1D CNN on the METLIN SMRT data set was transferred on five other data sets to evaluate the generalization ability.

Omics Untargeted Key Script: R-Based Software Toolbox for Untargeted Metabolomics with Bladder Cancer Biomarkers Discovery Case Study.

Large-scale untargeted LC-MS-based metabolomic profiling is a valuable source for systems biology and biomarker discovery. Data analysis and processing are major tasks due to the high complexity of generated signals and the presence of unwanted variations. In the present study, we introduce an R-based open-source collection of scripts called OUKS (Omics Untargeted Key Script), which provides comprehensive data processing. OUKS is developed by integrating various R packages and metabolomics software tools and can be easily set up and prepared to create a custom pipeline. Novel computational features are related to quality control samples-based signal processing and are implemented by gradient boosting, tree-based, and other nonlinear regression algorithms. Bladder cancer biomarkers discovery study which is based on untargeted LC-MS profiling of urine samples is performed to demonstrate exhaustive functionality of the developed software tool. Unique examination among dozens of metabolomics-specific data curation methods was carried out at each processing step. As a result, potential biomarkers were identified, statistically validated, and described by metabolism disorders. Our study demonstrates that OUKS helps to make untargeted LC-MS metabolomic profiling with the latest computational features readily accessible in a ready-to-use unified manner to a research community.

Water Vapor Adsorption on CAU-10-X: Effect of Functional Groups on Adsorption Equilibrium and Mechanisms.

Metal-organic frameworks (MOFs) possess unique flexibility of structure and properties, which drives them toward applications as water adsorbents in many emerging technologies, such as adsorptive heat transformation, water harvesting from the air, dehumidification, and desalination. A deep understanding of the surface phenomena is a prerequisite for the target-oriented design of MOFs with the required adsorption properties. In this work, we comprehensively study the effect of functional groups on water adsorption on a series CAU-10-X substituted with both hydrophilic (X = NH2) and hydrophobic (X = NO2) groups in the linker. The adsorption equilibrium is measured at P = 7.6-42 mbar and T = 5-100 °C. The study of water adsorption by a set of mutually complementary physicochemical methods (TG, XRD in situ, FTIR, and 1H NMR relaxometry) elucidates the nature of primary adsorption sites and water adsorption mechanisms.

Mixed silver-nickel oxide AgNiO2: Probing by CO during XPS study.

In this work, the reaction properties of mixed silver-nickel oxide AgNiO2 were investigated in the reaction of CO oxidation ranging from room temperature up to 350 °C. X-ray photoelectron spectroscopy revealed the presence of a single oxidized silver state and the combination of Ni2+ and Ni3+ species on the surface of the as-prepared mixed oxide. It was established that AgNiO2 was able to interact with CO at room temperature. It was accompanied by the simultaneous titration of the lattice (O2--like) and weakly charged (O--like) oxygen species. The interaction with CO below 100 °C resulted in the accumulation of carbonate-like species on the AgNiO2 surface. Above 150 °C, the surface structure of mixed oxide was found to be disrupted, resulting in the formation of individual particles of metallic silver and oxidized nickel.

A novel crystal form of metacetamol: the first example of a hydrated form.

We report the crystal structure and crystallization conditions of a first hydrated form of metacetamol (a hemihydrate), C8H9NO2·0.5H2O. It crystallizes from metacetamol-saturated 1:1 (v/v) water-ethanol solutions in a monoclinic structure (space group P21/n) and contains eight metacetamol and four water molecules per unit cell. The conformations of the molecules are the same as in polymorph II of metacetamol, which ensures the formation of hydrogen-bonded dimers and R22(16) ring motifs in its crystal structure similar to those in polymorph II. Unlike in form II, however, these dimers in the hemihydrate are connected through water molecules into infinite hydrogen-bonded molecular chains. Different chains are linked to each other by metacetamol-water and metacetamol-metacetamol hydrogen bonds, the latter type being also present in polymorph I. The overall noncovalent network of the hemihydrate is well developed and several types of hydrogen bonds are responsible for its formation.

Adsorption of water and n-hexane on pristine and oxidized carbon nanotube supports of cobalt-based Fischer-Tropsch catalysts.

Adsorption of model polar (water) and non-polar (n-hexane) compounds on the surface of oxidized and non-oxidized carbon nanotube (CNT) supports at different stages of Co/CNT catalyst preparation has been studied to reveal the influence of the surface functionalization of the CNT support on the catalyst selectivity in Fischer-Tropsch synthesis (FTS). Dynamic vapor sorption experiments showed that defunctionalization of the surface of the CNT support during catalyst annealing and reduction led to its hydrophobization and, as a result, no noticeable difference was observed between the adsorption properties of the oxidized and non-oxidized supports towards water and hydrocarbons. Therefore, oxidation of the CNT support does not significantly affect the adsorption properties of the supported catalyst and it is not a crucial factor for the catalyst selectivity in FTS.

LC-MS determination of steroidal glycosides from Dioscorea deltoidea Wall cell suspension culture: Optimization of pre-LC-MS procedure parameters by Latin Square design.

In this paper, the ultrasound assisted extraction method for isolation of steroidal glycosides from D. deltoidea plant cell suspension culture with a subsequent HPLC-MS determination was developed. After the organic solvent was selected via a two-factor experiment the optimization via Latin Square 4 × 4 experimental design was carried out for the following parameters: extraction time, organic solvent concentration in extraction solution and the ratio of solvent to sample. It was also shown that the ultrasound assisted extraction method is not suitable for isolation of steroidal glycosides from the D. deltoidea plant material. The results were double-checked using the multiple successive extraction method and refluxing extraction. Optimal conditions for the extraction of steroidal glycosides by the ultrasound assisted extraction method were: extraction time, 60 min; acetonitrile (water) concentration in extraction solution, 50%; the ratio of solvent to sample, 400 mL/g. Also, the developed method was tested on D. deltoidea cell suspension cultures of different terms and conditions of cultivation. The completeness of the extraction was confirmed using the multiple successive extraction method.