Model Reaction Research Articles

Near-infrared light-driven biomass conversion.

Current photocatalytic technologies mainly rely on the input of high-energy ultraviolet-visible (UV-vis) light to obtain the desired excited states with adequate energy to drive redox reactions, precluding the use of low-energy near-infrared (NIR) light that occupies ~50% of the solar spectrum. Here, we report the efficient utilization of NIR light by coupling the low-energy NIR photons with reactive biomass conversion. A unique mechanism of photothermally synergistic photocatalysis was revealed for the selective biomass conversion under NIR light. Using biomass-derived 5-hydroxymethylfurfural (HMF) conversion as a model reaction, it was found that NIR and UV-vis light featured markedly different reaction patterns. 5-Formyl-2-furancarboxylic acid (FFCA) was almost exclusively produced under NIR light, whereas UV-vis light favored the formation of 2,5-diformylfuran (DFF) as the major product. This work provides a paradigm for sustainable and selective chemical synthesis using the Earth's abundant resources, sunlight and biomass.

Enhanced catalytic reduction of 4-nitrophenol using bimetallic MOFs: a one-pot synthesis approach

ABSTRACT Several organic pollutants can harm the environment and human health. A typical environmentally toxic contaminant, 4-Nitrophenol (4-NP), may cause serious health issues. Therefore, catalytic reduction (hydrogenation) of 4-nitrophenol into less toxic 4-aminophenol (4-AP) is mostly preferred. A three-dimensional (3D) metal-organic framework of Ni-MOF-74 is mostly used which contains maximum unsaturated metal sites and the catalytic activity is enhanced due to partial exchange at the node position in MOF. In order to study the catalytic hydrogenation/reduction of organic dye, 4-nitrophenol as a model reaction, a bimetallic MOF, FeNi-MOF-74 was prepared by partially substituting Ni with Fe metal. The catalyst was synthesised using a one-pot solvothermal technique, and 4-nitrophenol was then reduced catalytically in aqueous media. For the reduction of nitrophenol, the FeNi-MOF-74 catalyst surpassed Ni-MOF (9.3 × 10−3 s−1) and Fe-MOF (5.4 × 10−3 s−1) with a lower reduction time and a higher rate constant; (1.6 × 10−2 s−1). The high conversion rate and economical induction time are attributed to the bimetallic synergistic effect.

Revealing the Size and Potential Dependent D2O Microkinetics on Pt Nanoparticles Using Grand Canonical Ensemble Modeling.

Revealing the potential and nanoparticle size effect is significant for understanding the electrochemical microkinetic behaviors under real reaction conditions. Herein, an efficient strategy of combining the robust fully converged constant potential (FCP) algorithm and the size dependent site distribution rule assumption was proposed. A simple reaction of isotopic D2O/H2O adsorption and dissociation on Pt nanoparticles was set as the model reaction. The results show that the cathodic negative potential and the anodic positive potential would result in the D2O orientation of the D-down/O-down physisorption configuration. Microkinetic simulations by this strategy obtained electrochemical widows for D2O/H2O dissociation, and the optimal Pt nanoparticle diameter was predicted to be 1.8 nm, which agrees well with the experimental observation of ∼2 nm threshold. The kinetic isotope effect (KIE) rate constant ratio at the optimal potential of -0.80 V vs SHE was calculated to be ∼1.83. This work provides a guideline in studying electrochemical electrode-electrolyte interactions on nanoparticles.

Packed‐Bed Microreactor Under Taylor Flow for MOFs Catalyst Testing Demonstrated on Phenylacetylene Hydrogenation

AbstractMetal‐Organic Frameworks (MOFs) represent a highly promising class of materials with diverse applications, particularly as catalytic materials. However, their synthesis typically yields powders available only at laboratory‐scale quantities, usually in the gram range or less. This study addresses the challenge of testing limited amounts of MOF catalysts for demanding applications, such as multiphase gas‐liquid‐solid reactions in flow, utilizing a packed‐bed microreactor. Specifically, we investigate the performance of a nanoparticle (NP) ‐immobilized Pd@UiO‐66 MOF catalyst in the selective semi‐hydrogenation of phenylacetylene to styrene, serving as a model reaction. Maintaining the Taylor flow regime upstream of the catalyst bed was crucial to ensure reproducible and reliable experimental results. We conducted 88 experiments at varying liquid flow rates, temperatures ranging from 15 to 45 °C, and relative pressures spanning 0.28 to 8 bar. Styrene selectivity within the range of 80–92.3 % was achieved at phenylacetylene conversions below 20 %. Notably, the optimal condition for styrene selectivity (70 %) was attained at 98.9 % phenylacetylene conversion under the lowest H2 pressure and highest temperature, demonstrating the significance of low H2 concentration for achieving optimal styrene selectivity. Remarkably, the catalyst exhibited stable activity and selectivity over a 20 h testing period, indicating its robust performance under prolonged reaction conditions. This study demonstrates the potential of the proposed catalyst testing system as a rapid and efficient approach for early‐stage exploration studies, particularly when limited quantities of catalyst, typically in the gram scale or less, are available.

Catalytic Biomass Transformation to Hydrocarbons under Supercritical Conditions over Nickel Supported on Schungite

Liquid fuel production from biomass-derived molecules has received great attention due to the diminished fossil fuel reserves, growing energy demand, and the necessity of CO2 emission reduction. The deoxygenation of oils and fatty acids is a promising process to obtain “green” diesel. Herein, we report the results of the study of the deoxygenation of stearic acid to alkanes as a model reaction. Series of Ni-supported on schungite were obtained by precipitation in subcritical water (hydrothermal deposition) and for comparison via wetness impregnation followed, in both cases, by calcination at 500 °C and a reduction in H2 at 300 °C. The catalyst obtained via hydrothermal synthesis showed a three-fold higher specific surface area with a four-fold higher active phase dispersion compared to the catalysts synthesized via conventional impregnation. The catalysts were tested in stearic acid deoxygenation in supercritical n-hexane as the solvent. Under optimized process conditions (temperature of 280 °C, hydrogen partial pressure of 1.5 MPa, and 13.2 mol of stearic acid per mol of Ni), a close to 100% yield of C10–C18 alkanes, containing over 70 wt.% of targeted n-heptadecane, was obtained after 60 min of reaction.

Degradation of a Wholly Aromatic Main-Chain Thermotropic Liquid-Crystalline Polymer Mediated by Superbases.

Plastic circular economy needs to be established to solve environmental issues related to plastic waste. Superengineering plastics such as liquid-crystalline (LC) polymers exhibit excellent thermal and mechanical properties, resulting in poor degradability in natural environment. Herein, we report the degradation of a wholly aromatic thermotropic LC polyester, poly(4-hydroxybenzoic acid-co-6-hydroxy-2-naphthoic acid) (Vectra) mediated by superbases. Methanolysis and hydrolysis of Vectra yield its monomeric compounds, 4-hydroxybenzoic acid, 6-hydroxy-2-naphthoic acid, and their methyl esters. Among several transesterification catalysts explored, 1,5,7-triazabicylco[4.4.0]dec-5-ene (TBD) is the most suitable for the methanolysis of Vectra. The complete degradation of Vectra is achieved under reflux. The degradation proceeds heterogeneously via a surface erosion mechanism, preferentially starting from less chain-packed regions. Model reactions using aryl arylates reveal that monomeric compound-superbase complexes could mediate the cleavage of the ester bonds in both homogeneous and heterogeneous systems. The ester bonds of Vectra have inherent poor reactivity and are protected by oriented robust structures of the polymer. Nevertheless, the superbases enable the degradation of Vectra via the cleavage of the ester bonds by methanol. These outcomes open the way for recycling high-performance plastics as well as demonstrate the feasibility of recovering precious aromatic compounds from plastic waste as aromatic feedstock.

Performance of zero-valent iron immobilized on activated carbon cloth for the removal of phenol from wastewater

BackgroundDischarge of large amounts of untreated industrial effluent into water bodies pose significant environmental challenges worldwide. This is due to the limitations of traditional wastewater treatment methods in the treatment of recalcitrant organic pollutants. Fenton processes involves the generation of hydroxyl radicals that are well suited to degrade organics in effluent water. This study focuses on reducing slag generation during Fenton processes and enhancing the reuse of nano-zero-valent iron (NZVI) through the immobilization of NZVI on activated carbon cloth (ACC) through a chitosan (CH) linker with phenol as a model pollutant.ResultsMicrostructural and spectroscopic techniques were employed to study the materials prepared and 37.5 wt% iron loading was achieved. Phenol degradation of 96.3% at 40 °C at pH of 3.0 with 50 mM H2O2 was achieved using ACC-CH-NZVI. Adsorption and degradation studies carried out using ACC-CH-NZVI catalyst revealed that phenol adsorption onto ACC-CH-NZVI fits the Langmuir isotherm model, following the pseudo-second-order kinetic model and first-order reaction kinetics. Thermodynamic studies indicate the non-spontaneous, endothermic and irreversible nature of the removal process. Comparing ACC-CH-NZVI with ACC and ACC-CH, phenol removal using ACC drops from 87.8 to 39%, while using ACC-CH, the removal efficiency drops from 73 to 20.9% and using ACC-CH-NZVI, phenol removal drops from 96.3 to about 70% and total organic carbon removal drops from 79 to about 60% with minimal iron leaching, highlighting the superior performance of ACC-CH-ZVI and the role of NZVI in enhancing phenol removal.ConclusionsThe catalyst demonstrated good stability for phenol degradation to about 70% phenol removal from simulated wastewater and 60% TOC removal from industrial wastewater after five treatment cycles with minimal Fe leaching.Graphical abstract

Glycyrrhetinic acid interaction with solvated and free electrons studied by the CIDNP and dissociative electron attachment techniques.

Electron transfer plays a crucial role in living systems, including the generation of reactive oxygen species (ROS). Oxygen acts as the terminal electron acceptor in the respiratory chains of aerobic organisms as well as in some photoinduced processes followed by the formation of ROS. This is why the participation of exogenous antioxidants in electron transfer processes in living systems is of particular interest. In the present study, using chemically induced dynamic nuclear polarization (CIDNP) and dissociative electron attachment (DEA) techniques, we have elucidated the affinity of solvated and free electrons to glycyrrhetinic acid (GA)-the aglicon of glycyrrhizin (the main active component of Licorice root). CIDNP is a powerful instrument to study the mechanisms of electron transfer reactions in solution, but the DEA technique shows its effectiveness in gas phase processes. For CIDNP experiments, the photoionization of the dianion of 5-sulfosalicylic acid (HSSA2-) was used as a model reaction of solvated electron generation. DEA experiments testify that GA molecules are even better electron acceptors than molecular oxygen, at least under gas-phase conditions. In addition, the effect of the solvent on the energetics of the reactants is discussed.

Reaction kinetics and mechanism of UVC-LED265–285nm and UVC-LED265–285nm/hydrogen peroxide toward foodborne pathogenic Listeria monocytogenes cells and its chromosomally encoded virulent hly genes

To investigate the principle-based inactivation kinetics and mechanisms of the foodborne pathogen Listeria monocytogenes (Lm), along with its representative virulence gene (hly) encoded in both intracellular and extracellular genomic DNA, we applied disinfection treatments using UVC-LED265–285nm and UVC-LED265–285nm combined with hydrogen peroxide (10 mg/L). These treatments were conducted under controlled model reaction matrices (phosphate-buffered solutions at pH 6.2 and 7.9) and/or actual agricultural water, depending on filtration pre-treatment. Comprehensive analytical methods, such as plate count, flow cytometry, and quantitative real-time PCR, were adopted for the qualitative/quantitative determination of bacterial or gene inactivation parameters. According to the experimentally determined fluence-based first-order rate constants (kUVC-LED and kUVC-LED/H2O2), the k value of Lm viability and hly genes was 1.14–2.19 cm2/mJ and 2.18 × 10−2–2.42 × 10−1 cm2/mJ, respectively. Damage to the longer amplicon or the extracellular form of the hly gene was higher than that to the shorter amplicon or the intracellular form by a factor of 2∼10 fold. Increasing pH in reaction matrices were marginally affected to the rates of inactivation kinetics. Dose-dependent inactivation levels tested in agriculture water matrices were comparable with the kinetics from the PB solutions of both UVC-LED265–285nm and UVC-LED265–285nm/hydrogen peroxide owing to OH radical scavenging by the water matrix components. These results will be valuable for optimizing UVC-LED and UVC-LED-based advanced oxidation process disinfection systems, specifically tailored to the unique challenges of bacterial or gene inactivation in the (waste)water at food processing and agricultural sectors.

Overcoming the Pitfalls of Computing Reaction Selectivity from Ensembles of Transition States.

The prediction of reaction selectivity is a challenging task for computational chemistry, not only because many molecules adopt multiple conformations but also due to the exponential relationship between effective activation energies and rate constants. To account for molecular flexibility, an increasing number of methods exist that generate conformational ensembles of transition state (TS) structures. Typically, these TS ensembles are Boltzmann weighted and used to compute selectivity assuming Curtin-Hammett conditions. This strategy, however, can lead to erroneous predictions if the appropriate filtering of the conformer ensembles is not conducted. Here, we demonstrate how any possible selectivity can be obtained by processing the same sets of TS ensembles for a model reaction. To address the burdensome filtering task in a consistent and automated way, we introduce marc, a tool for the modular analysis of representative conformers that aids in avoiding human errors while minimizing the number of reoptimization computations needed to obtain correct reaction selectivity.

A green Heck reaction protocol towards trisubstituted alkenes, versatile pharmaceutical intermediates.

The Heck reaction is widely employed to build a variety of biologically relevant scaffolds and has been successfully implemented in the production of active pharmaceutical ingredients (APIs). Typically, the reaction with terminal alkenes gives high yields and stereoselectivity toward the trans-substituted alkenes product, and many green variants of the original protocol have been developed for such substrates. However, these methodologies may not be applied with the same efficiency to reactions with challenging substrates, such as internal olefins, providing trisubstituted alkenes. In the present work, we have implemented a Heck reaction protocol under green conditions to access trisubstituted alkenes as final products or key intermediates of pharmaceutical interest. A set of preliminary experiments performed on a model reaction led to selecting a simple and green setup based on a design of experiments (DoE) study. In such a way, the best experimental conditions (catalyst loading, equivalents of alkene, base and tetraalkylammonium salt, composition, and amount of solvent) have been identified. Then, a second set of experiments were performed, bringing the reaction to completion and considering additional factors. The protocol thus defined involves using EtOH as the solvent, microwave (mw) irradiation to achieve short reaction times, and the supported catalyst Pd EnCat®40, which affords an easier recovery and reuse. These conditions were tested on different aryl bromides and internal olefines to evaluate the substrate scope. Furthermore, with the aim to limit as much as possible the production of waste, a simple isomerization procedure was developed to convert the isomeric byproducts into the desired conjugated E alkene, which is also the thermodynamically favoured product. The approach herein disclosed represents a green, efficient, and easy-to-use handle towards different trisubstituted alkenes via the Heck reaction.

Encapsulation of Imidazole into Ce-Modified Mesoporous KIT-6 for High Anhydrous Proton Conductivity.

Imidazole molecules entrapped in porous materials can exhibit high and stable proton conductivity suitable for elevated temperature (>373 K) fuel cell applications. In this study, new anhydrous proton conductors based on imidazole and mesoporous KIT-6 were prepared. To explore the impact of the acidic nature of the porous matrix on proton conduction, a series of KIT-6 materials with varying Si/Al ratios and pure silica materials were synthesized. These materials were additionally modified with cerium atoms to enhance their Brønsted acidity. TPD-NH3 and esterification model reaction confirmed that incorporating aluminum into the silica framework and subsequent modification with cerium atoms generated additional acidic sites. UV-Vis and XPS identified the presence of Ce3+ and Ce4+ in the KIT-6 materials, indicating that high-temperature treatment after cerium introduction may lead to partial cerium incorporation into the framework. EIS studies demonstrated that dispersing imidazole within the KIT-6 matrices resulted in composites showing high proton conductivity over a wide temperature range (300-393 K). The presence of weak acidic centers, particularly Brønsted sites, was found to be beneficial for achieving high conductivity. Cerium-modified composites exhibited conductivity surpassing that of molten imidazole, with the highest conductivity (1.13 × 10-3 S/cm at 393 K) recorded under anhydrous conditions for Ce-KIT-6. Furthermore, all tested composites maintained high stability over multiple heating and cooling cycles.

Dark scattering: accelerated constraints from KiDS-1000 with ReACT and CosmoPower

ABSTRACT We present constraints on the dark scattering model through cosmic shear measurements from the Kilo Degree Survey (KiDS-1000), using an accelerated pipeline with novel emulators produced with CosmoPower. Our main emulator, for the dark scattering non-linear matter power spectrum, is trained on predictions from the halo model reaction framework, previously validated against simulations. Additionally, we include the effects of baryonic feedback from HMCode2016, whose contribution is also emulated. We analyse the complete set of statistics of KiDS-1000, namely band powers, COSEBIs, and correlation functions, for dark scattering in two distinct cases. In the first case, taking into account only KiDS cosmic shear data, we constrain the amplitude of the dark energy–dark matter interaction to be $\vert A_{\rm ds} \vert \lesssim 20$$\rm b\,GeV^{-1}$ at 68 per cent C.L. Furthermore, we add information from the cosmic microwave background (CMB) from Planck, along with baryon acoustic oscillations (BAO) from 6dFGS, SDSS, and BOSS, approximating a combined weak lensing+CMB+BAO analysis. From this combination, we constrain $A_{\rm ds} = 10.6^{+4.5}_{-7.3}$$\rm b\,GeV^{-1}$ at 68 per cent C.L. We confirm that with this estimated value of $A_{\rm ds}$ the interacting model considered in this work offers a promising alternative to solve the $S_8$ tension.

A comparative analysis of NADPH supply strategies in Saccharomyces cerevisiae: Production of d-xylitol from d-xylose as a case study

Enhancing the supply of the redox cofactor NADPH in metabolically engineered cells is a critical target for optimizing the synthesis of many product classes, such as fatty acids or terpenoids. In S. cerevisiae, several successful approaches have been developed in different experimental contexts. However, their systematic comparison has not been reported. Here, we established the reduction of xylose to xylitol by an NADPH-dependent xylose reductase as a model reaction to compare the efficacy of different NADPH supply strategies in the course of a batch fermentation, in which glucose and ethanol are sequentially used as carbon sources and redox donors. We show that strains overexpressing the glucose-6-phosphate dehydrogenase Zwf1 perform best, producing up to 16.9 g L−1 xylitol from 20 g L−1 xylose in stirred tank bioreactors. The beneficial effect of increased Zwf1 activity is especially pronounced during the ethanol consumption phase. The same notion applies to the deletion of the aldehyde dehydrogenase ALD6 gene, albeit at a quantitatively lower level. Reduced expression of the phosphoglucose isomerase Pgi1 and heterologous expression of the NADP+-dependent glyceraldehyde-3-phosphate dehydrogenase Gdp1 from Kluyveromyces lactis acted synergistically with ZWF1 overexpression in the presence of glucose, but had a detrimental effect after the diauxic shift. Expression of the mitochondrial NADH kinase Pos5 in the cytosol likewise improved the production of xylitol only on glucose, but not in combination with enhanced Zwf1 activity. To demonstrate the generalizability of our observations, we show that the most promising strategies – ZWF1 overexpression and deletion of ALD6 - also improve the production of l-galactonate from d-galacturonic acid. Therefore, we expect that these findings will provide valuable guidelines for engineering not only the production of xylitol but also of diverse other pathways that require NADPH.

Harnessing Electro-Descriptors for Mechanistic and Machine Learning Analysis of Photocatalytic Organic Reactions.

Photocatalysis has emerged as an effective tool for addressing the contemporary challenges in organic synthesis. However, the trial-and-error-based screening of feasible substrates and optimal reaction conditions remains time-consuming and potentially expensive in industrial practice. Here, we demonstrate an electrochemical-based data-acquisition approach that derives a simple set of redox-relevant electro-descriptors for effective mechanistic analysis and performance evaluation through machine learning (ML) in photocatalytic synthesis. These electro-descriptors correlate to the quantification of shifted charge transfer processes in response to the photoirradiation and enabled construction of reactivity diagram where high-yield reactive "hot zones" can reflect subtle changes of the reaction system. For the model reaction of photocatalytic deoxygenation reaction, the influence of varying carboxylic acids (substrate A, oxidation-intended) and alkenes (substrate B, reduction-intended) and varying reaction conditions on the reaction yield can be visualized, while mathematical analysis of the electro-descriptor patterns further revealed distinct mechanistic/kinetic impacts from different substrates and conditions. Additionally, in the application of ML algorithms, the experimentally derived electro-descriptors reflect an overall redox kinetic outcome contributed from vast reaction parameters, serving as a capable means to reduce the dimensionality in the case of complex multiparameter chemical space. As a result, utilization of electro-descriptors enabled efficient and robust quantitative evaluation of chemical reactivity, demonstrating promising potential of introducing operando-relevant experimental insights in the data-driven chemistry.

Uncovering Factors Controlling Reactivity of Metal-TEMPO Reaction Systems in the Solid State and Solution.

Nitroxides find application in various areas of chemistry, and a more in-depth understanding of factors controlling their reactivity with metal complexes is warranted to promote further developments. Here, we report on the effect of the metal centre Lewis acidity on both the distribution of the O- and N-centered spin density in 2,2,6,6-tetramethylpiperidine-N-oxyl (TEMPO) and turning TEMPO from the O- to N-radical mode scavenger in metal-TEMPO systems. We use Et(Cl)Zn/TEMPO model reaction system with tuneable reactivity in the solid state and solution. Among various products, a unique Lewis acid-base adduct of Cl2Zn with the N-ethylated TEMPO was isolated and structurally characterised, and the so-called solid-state 'slow chemistry' reaction led to a higher yield of the N-alkylated product. The revealed structure-activity/selectivity correlations are exceptional yet are entirely rationalised by the mechanistic underpinning supported by theoretical calculations of studied model systems. This work lays a foundation and mechanistic blueprint for future metal/nitroxide systems exploration.

The influence of branched polyethyleneimine concentration on the spectroscopic and morphology of BPEI/AuNPs for photocatalytic reduction of 4-nitrophenol

In this work, gold nanoparticles (AuNPs) were synthesized and stabilized by branched polyethyleneimine (BPEI) due to their amine groups as a low-cost alternative method. The concentration of BPEI as a critical factor can be used to optimize stable AuNPs with varying sizes. To evaluate BPEI concentrations on surface plasmonic resonance (SPR), size distribution, chemical coordination, and photocatalytic activity of BPEI-AuNPs products, UV–visible, transmission electron microscope, and Fourier transform infrared spectroscopy were used. The SPR bands appeared at 524, 520, and 517 nm as the BPEI concentration increased (10–30 µL), and the band remained stable as BPEI increased. TEM images show a wide range of sizes (polydisperse) for BPEI/AuNPs were formed. According to TEM images, gold nanoparticle sizes were calculated at (18, 12, and 5 nm) for BPEI concentrations 10, 20, and 30 µL. Fourier transform infrared spectroscopy (FTIR) revealed that amine groups from BPEI play an important role in stabilizing AuNPs. For accessing the photocatalytic activity of BPEI-AuNPs, the reduction of 4-nitrophenol (4-NP) by borohydride is a widely used model reaction. As the AuNPs sizes decreased from 18 to 5 nm, the reduction rate was accelerated and the reaction time of 4-NP to 4-AP conversion decreased from 270 to 150 s.

Tick salivary proteome and lipidome with low glycan content correlate with allergic type reactions in the zebrafish model

Ticks, as hematophagous ectoparasites, can manipulate host immune and metabolic processes, causing tick-borne allergies such as α-Gal syndrome (AGS). Glycolipids with bound galactose-alpha-1–3-galactose (α-Gal) are potential allergenic molecules associated with AGS. Nevertheless, proteins and lipids lacking α-Gal modifications may contribute to tick salivary allergies and be linked to AGS. In this study, we characterized the effect of deglycosylated tick salivary proteins without lipids on treated zebrafish fed with dog food formulated with mammalian (beef, lamb, pork) meat by quantitative proteomics analysis of intestinal samples. The characterization and functional annotations of tick salivary lipids with low representation of glycolipids was conducted using a lipidomics approach. Results showed a significant effect of treatment with saliva and saliva deglycosylated protein fraction on zebrafish abnormal or no feeding (p < 0.005). Treatment with this fraction affected multiple metabolic pathways, defense responses to pathogens and protein metabolism, which correlated with abnormal or no feeding. Lipidomics analysis identified 23 lipid classes with low representation of glycolipids (0.70% of identified lipids). The lipid class with highest representation was phosphatidylcholine (PC; 26.66%) and for glycolipids it corresponded to diacylglycerol (DG; 0.48%). Qualitative analysis of PC antibodies revealed that individuals bitten by ticks were more likely to produce PC-IgG antibodies (p < 0.001). DG levels were significantly higher in tick salivary glands (p < 0.05) compared with tick saliva and salivary fractions. The α-Gal content was higher in tick saliva than in deglycosylated saliva and lipid fractions. These results support a possible role for tick salivary proteins and lipids without α-Gal modifications in AGS.

Plasma Catalysis Modeling: How Ideal Is Atomic Hydrogen for Eley-Rideal?

Plasma catalysis is an emerging technology, but a lot of questions about the underlying surface mechanisms remain unanswered. One of these questions is how important Eley-Rideal (ER) reactions are, next to Langmuir-Hinshelwood reactions. Most plasma catalysis kinetic models predict ER reactions to be important and sometimes even vital for the surface chemistry. In this work, we take a critical look at how ER reactions involving H radicals are incorporated in kinetic models describing CO2 hydrogenation and NH3 synthesis. To this end, we construct potential energy surface (PES) intersections, similar to elbow plots constructed for dissociative chemisorption. The results of the PES intersections are in agreement with ab initio molecular dynamics (AIMD) findings in literature while being computationally much cheaper. We find that, for the reactions studied here, adsorption is more probable than a reaction via the hot atom (HA) mechanism, which in turn is more probable than a reaction via the ER mechanism. We also conclude that kinetic models of plasma-catalytic systems tend to overestimate the importance of ER reactions. Furthermore, as opposed to what is often assumed in kinetic models, the choice of catalyst will influence the ER reaction probability. Overall, the description of ER reactions is too much "ideal" in models. Based on our findings, we make a number of recommendations on how to incorporate ER reactions in kinetic models to avoid overestimation of their importance.

Celecoxib Catalyzed the Coupling Reaction of Epoxide and CO2

Abstract: In this study, high yields of various cyclic carbonates are obtained by employing the drug celecoxib to promote the coupling reaction of CO2 and epoxide using tetrabutylammonium bromide. This strategy enables the synthesis of benzoic acid, phenylpropiolic acid, and 2, 4- quinazolinedione. In addition, the model reaction mechanism is proposed.