Reaction Systems Research Articles

Phosphate-mediated degradation of organic pollutants in water with peroxymonosulfate revisited: Radical or non-radical oxidation?

Whilst it is generally recognized that phosphate enables to promote the removal of some organic pollutants with peroxymonosulfate (PMS) oxidation, however, there is an ongoing debate as to whether free radicals are involved. By integrating different methodologies, here we provide new insights into the reaction mechanism of the binary mixture of phosphates (i.e., NaH2PO4, Na2HPO3, and NaH2PO2) with peroxymonosulfate (PMS) or hydrogen peroxide (H2O2). Enhanced degradation of organic pollutants and observation of 5,5-dimethyl-1-pyrroline-N-oxide (DMPO) adducts (i.e. DMPOOH and 5,5-dimethyl-2-oxopyrroline-1-oxyl (DMPOX)) with electron paramagnetic resonance (EPR) in most phosphates/PMS system seemly support a radical-dominant mechanism. However, fluorescence probe experiments confirm that no significant amount of hydroxyl radicals (•OH) are produced in such reaction systems. PMS in the phosphate solutions (without any organics) remains relatively stable, but is only consumed while organic substrates are present, which is distinct from a typical radical-dominant Co2+/PMS system where PMS is continuously decomposed. Through density functional theory (DFT) calculation, the energy barriers of the phosphates/PMS reaction processes are greatly decreased when non-radical mechanism dominates. Complementary evidence suggests that the reactive intermediates of PMS-phosphate complex, rather than the free radicals, are capable of oxidizing electron-rich substrates such as DMPO and organic pollutants. Taking the case of phosphate/PMS system as an example, this study demonstrates the necessity of acquisition of lines of evidence for resolving paradoxes in identifying EPR adducts.

Formation of alkoxymethyl hydroperoxides and alkyl formates from simplest Criegee intermediate (CH2OO) + ROH (R=CH3, CH3CH2, and (CH3)2CH) reaction systems

Formation of alkoxymethyl hydroperoxides and alkyl formates from simplest Criegee intermediate (CH2OO) + ROH (R=CH3, CH3CH2, and (CH3)2CH) reaction systems

A numerical compass for experiment design in chemical kinetics and molecular property estimation

Kinetic process models are widely applied in science and engineering, including atmospheric, physiological and technical chemistry, reactor design, or process optimization. These models rely on numerous kinetic parameters such as reaction rate, diffusion or partitioning coefficients. Determining these properties by experiments can be challenging, especially for multiphase systems, and researchers often face the task of intuitively selecting experimental conditions to obtain insightful results. We developed a numerical compass (NC) method that integrates computational models, global optimization, ensemble methods, and machine learning to identify experimental conditions with the greatest potential to constrain model parameters. The approach is based on the quantification of model output variance in an ensemble of solutions that agree with experimental data. The utility of the NC method is demonstrated for the parameters of a multi-layer model describing the heterogeneous ozonolysis of oleic acid aerosols. We show how neural network surrogate models of the multiphase chemical reaction system can be used to accelerate the application of the NC for a comprehensive mapping and analysis of experimental conditions. The NC can also be applied for uncertainty quantification of quantitative structure–activity relationship (QSAR) models. We show that the uncertainty calculated for molecules that are used to extend training data correlates with the reduction of QSAR model error. The code is openly available as the Julia package KineticCompass.Graphical

Bi2O2S/CAU-17 bifunctional heterojunction for boosting CO2 photoreduction performance origin from the simultaneous photoxidation of tetracycline

To address the issues of energy scarcity and environmental pollution, a photocatalytic coupling system is employed to simultaneously harness electrons and holes in a single photocatalytic system. The current study presents a novel approach to construct a dual reaction pathway system for tetracycline hydrochloride (TC) oxidation and CO2 reduction. Herein, Bi2O2S/CAU-17 composite was designed and fabricated through a facile solvothermal method. The hybrid photocatalyst exhibited an excellent performance for simultaneous TC degradation and CO2 reduction. The CO-production rate can be reached 22.0 μmol g-1h−1 through the optimized 20% Bi2O2S/CAU-17 sample. Notably, the source of CO2 in the reaction system is solely derived from the photoxidation of TC. The theoretical calculations and experimental findings have shown that the existed Bi2O2S can enrich electron and separation of photo-generated electrons from CAU-17, thus, the holes in Bi2O2S and CAU-17 can be involved in the photodegradation of TC. Afterwards, the CO2 generated by TC oxidation moves to Bi2O2S via diffusion of molecules and could be efficiently reduced by electrons to produce CO. The development of this novel bifunctional Bi2O2S/CAU-17 hybrid photocatalytic system could provide valuable insights for the advancement of photocatalytic coupling reaction systems.

Tailoring Iridium Valence States on ZSM-5 for Enhanced Catalytic Performance in CO Selective Catalytic Reduction of NO under Oxygen-Enriched Environments.

Barium and iridium supported on Zeolite Socony Mobil-5 (ZSM-5) are efficient catalysts for the selective catalytic reduction of nitric oxide by carbon monoxide (CO-SCR), with enhanced cyclic stability. The introduction of Ba hindered the oxidation of metallic Ir active species and enabled Ir to maintain an active metallic state, thereby preventing a decrease in catalytic activity in the CO-SCR reaction. Moreover, the Ba modification increased the NO adsorption of the catalyst, further improving the catalytic activity. Owing to the better anti-oxidation ability of Ir0 in IrBa0.2/ZSM-5(27) than in Ir/ZSM-5(27), IrBa0.2/ZSM-5(27) showed better stability than Ir/ZSM-5(27). Considering that all samples in the present study were tested to simulate actual flue gases (such as sintering flue gas and coke oven flue gas), NH3 was introduced into the reaction system to serve as an extra reductant for NOx. The NOx conversion to N2 (77.1%) was substantially improved using the NH3-CO-SCR system. The proposed catalysts and reaction systems are promising alternatives for treating flue gas, which contains considerable amounts of NOx and CO in oxygen-enriched environments.

Modeling and Analyzing Reaction Systems in Maude

Reaction Systems (RSs) are a successful computational framework for modeling systems inspired by biochemistry. An RS defines a set of rules (reactions) over a finite set of entities (e.g., molecules, proteins, genes, etc.). A computation in this system is performed by rewriting a finite set of entities (a computation state) using all the enabled reactions in the RS, thereby producing a new set of entities (a new computation state). The number of entities in the reactions and in the computation states can be large, making the analysis of RS behavior difficult without a proper automated support. In this paper, we use the Maude language—a programming language based on rewriting logic—to define a formal executable semantics for RSs, which can be used to precisely simulate the system behavior as well as to perform reachability analysis over the system computation space. Then, by enriching the proposed semantics, we formalize a forward slicer algorithm for RSs that allows us to observe the evolution of the system on both the initial input and a fragment of it (the slicing criterion), thus facilitating the detection of forward causality and influence relations due to the absence/presence of some entities in the slicing criterion. The pursued approach is illustrated by a biological reaction system that models a gene regulation network for controlling the process of differentiation of T helper lymphocytes.

Design Strategy of Metal Nanoparticle Catalysis for C−H Bond Activation Reactions

AbstractC−H bond activation reactions facilitate highly efficient molecular transformations without requiring pre‐activating substrates. While the majority of reported reaction systems for C−H activation rely on metal complexes, certain reactions have demonstrated unique or superior catalysis of metal nanoparticles. This Concept article seeks to delineate recent reports that examine the novel catalysis and design strategy of supported metal nanoparticles for C−H bond activation reactions. These reactions include oxidative homocoupling of arenes, dehydrogenative alkylation of benzenes, selective H/D exchange reactions, and α,β‐dehydrogenation of ketones.

Comparison of Measurements for Enhanced Diffusion Problem in Chemical Reaction Systems

Comprehensive SummaryThe problem of molecular diffusion in the soup of chemical reactions attracts mounting interest across fields ranging from chemistry to biophysics to material science. Chemical reactions involve bond breakup and formation, whose time scale is typically on the orders of fs to ps, while molecular diffusion occurs at time scales of μs to ms. The two processes are often considered orthogonal, given the vastly different scales. The serial results show that the enzyme's diffusion is enhanced in a substrate‐dependent manner, which was further extended to small molecule reaction systems, challenging this classical paradigm. However, the results from different groups using different techniques do not quantitatively agree, and a general mechanism is yet to be understood. We summarize experimental studies on diffusion problems and seek to reconcile the interpretation with understanding the limits of measurement tools and the chemical nature of reaction systems. Understanding molecular diffusion in chemical reactions will provide fresh thoughts in designing chemical systems such as molecular machines that harvest work at the nanoscale in a controllable manner.

An ONIOM-Based High-Level Thermochemistry Study on Hydrogen Abstraction Reactions of Large Straight-Chain Alkanes by Hydrogen, Hydroxyl, and Hydroperoxyl Radicals

Accurate thermochemical data are of great importance in developing quantitatively predictive reaction mechanisms for transportation fuels, such as diesel and jet fuels, which are primarily composed of large hydrocarbon molecules, especially large straight-chain alkanes containing more than 10 carbon atoms. This paper presents an ONIOM[QCISD(T)/CBS:DFT]-based theoretical thermochemistry study on the hydrogen abstraction reactions of straight-chain alkanes, n-CnH2n+2, (n = 1–16) by hydrogen (H), hydroxyl (OH), and hydroperoxyl (HO2) radicals. These reactions, with n ≥ 10, pose significant computational challenges for prevalent high-level ab initio methods. However, they are effectively addressed using the ONIOM-based method. One notable aspect of this study is the consideration of the high symmetry of straight-chain alkanes. This symmetry allows us to study half of the reactions, employing a generalized approach. Therefore, a total of 216 reactions are systematically studied for the three reaction systems. Our results align very well with those from the widely accepted high-level QCISD(T)/CBS method, with discrepancies between the two generally less than 0.10 kcal/mol. Furthermore, we compared large straight-chain alkanes (n-C16H34 and n-C18H38) with large methyl ester molecules (C15H31COOCH3 and C17H33COOCH3) to elucidate the impact of functional groups (ester group and C=C double bond) on the reactivity of the long-chain structure. These findings underscore the accuracy and efficiency of the ONIOM-based method in computational thermochemistry, particularly for large straight-chain hydrocarbons in transportation fuels.

Increasing temperature and sulfate enhances the efficiency of methane abatement in an anaerobic oxidation of methane bioreactor (AOMB) system

Controlling methane emission sources is important for the sustainable application of energy from the deep sea to alleviate methane-induced global warming. The anaerobic oxidation of methane (AOM) process coupled with sulfate reduction (SR) plays a key role in seafloor methane biofiltration. However, the mechanisms for the enhancement of the methane abatement efficiency in an AOM reaction system and the responses of temperature and sulfate concentration remain known. To cover the knowledge gap, this study investigated the enhancement of methane abatement in a self-manufactured AOMB system for 230 days via increasing temperatures and sulfate concentrations. The primary conclusions are as follows: (a) AOM and SR rates were significantly elevated at the conditions of temperature increase (8 to 15 °C) and sulfate addition (+15 mM). (b) Sulfate and temperature were key factors influencing the diversity of archaea and bacterial communities. (c) ANME-2c, ANME-1b, SEEP-SRB1, and Halodesulfovibrio were dominant genera of methane‑sulfur cycling in the system. (d) Functional gene prediction revealed that the coupling of methane oxidation and dissimilatory sulfate reduction was responsible for the methane abatement. Our findings provide new insights into the enhancement of methane abatement efficiency in the deep sea and the application of AOM reaction systems.

Physics‐informed learning of chemical reactor systems using decoupling–coupling training framework

AbstractIt is known that physics‐informed learning become a new learning philosophy that has been applied in many scientific domains. However, this approach often struggles to achieve optimal performance in addressing the issue of multiphysics coupling. Here, for the first time, we extend this approach to modeling chemical reactor systems. We design a new decoupling–coupling training framework, which consists of decoupling pre‐training and multiphysics coupling training steps. With decoupling pre‐training, the complex physical domain is decomposed into subdomains of fluid flow, heat transfer, and mass transfer combined with reaction kinetics. Each subdomain is represented by a specialized neural network that can provide a coarse but reasonable distribution of network parameters for initializing the sub‐networks for the subsequent multiphysics coupling training. The capabilities of this approach, in comparison with the traditional CFD simulation, are demonstrated through an example of a plate reactor system with a heating cylinder.

Fixed points and attractors of additive reaction systems

Reaction systems are discrete dynamical systems that simulate biological processes within living cells through finite sets of reactants, inhibitors, and products. In this paper, we study the computational complexity of deciding on the existence of fixed points and attractors in the restricted class of additive reaction systems, in which each reaction involves at most one reactant and no inhibitors. We prove that all the considered problems, that are known to be hard for other classes of reaction systems, are polynomially solvable in additive systems. To arrive at these results, we provide several non-trivial reductions to problems on a polynomially computable graph representation of reaction systems that might prove useful for addressing other related problems in the future.

Abiotic Methane Production Driven by Ubiquitous Non‐Fenton‐Type Reactive Oxygen Species

Abiotic CH4 production driven by Fenton‐type reactive oxygen species (ROS) has been confirmed to be an indispensable component of the atmospheric CH4 budget. While the chemical reactions independent of Fenton chemistry to ROS are ubiquitous in nature, it remains unknown whether the produced ROS can drive abiotic CH4 production. Here, we first demonstrated the abiotic CH4 production at the soil‒water interface under illumination. Leveraging this finding, polymeric carbon nitrides (CNx) as a typical analogue of natural geobattery material and dimethyl sulfoxide (DMSO) as a natural methyl donor were used to unravel the underlying mechanisms. We revealed that the ROS, photocatalytically produced by CNx, can oxidize DMSO into CH4 with a high selectivity of 91.5%. Such an abiotic CH4 production process was further expanded to various non‐Fenton‐type reaction systems, such as electrocatalysis, pyrocatalysis and sonocatalysis. This work provides insights into the geochemical cycle of abiotic CH4, and offers a new route to CH4 production via integrated energy development.

Mechanistic Study of the Influence of Reactant Type and Addition Sequence on the Microscopic Morphology of α-Al2O3

To perform an in-depth study of the crystal growth habits and phase changes of alumina and its precursors in reaction systems, this paper studied the effects of reactant type and addition order on the morphology of alumina using hydrothermal methods with different precipitants and aluminum sources as reactants. Research has shown that sodium bicarbonate and ammonium bicarbonate can be used as precipitants to prepare adhered spherical alumina and irregular short rod alumina, while potassium bicarbonate can be used as a precipitant to prepare hexagonal flake alumina. Using aluminum sulfate octahydrate, aluminum chloride hexahydrate, and aluminum nitrate, nine hydrates were prepared as aluminum sources, and agglomerated alumina, irregular short rod-shaped alumina, and fused alumina were obtained. The order of reactant addition affects the precursor phase of alumina, thereby affecting the microstructure of alumina after calcination, resulting in flake alumina with pores and short rod alumina. The results of this paper will provide theoretical guidance for the preparation of alumina with different micromorphologies.

Metagenomic sequencing reveals mechanisms of adaptation and biodegradation of dechlorinating bacteria to trichloroethylene

Bioremediation is a sustainable, cost-effective, and eco-friendly way to remediate pollutants. However, the effectiveness of bioremediation is constrained by the underground environmental conditions, resulting in poor natural attenuation of organic pollution and degradation by functional microorganisms. In this study, a dechlorinating bacteria (DB) was enriched from contaminated soil and used to degrade trichloroethylene (TCE) in wastewater. The adaptation and degradation mechanisms of DB to TCE were investigated by degradation product analysis and metagenomic sequencing. The degradation of TCE by DB is pH and additional carbon source dependent. The highest TCE removal amount (1.86 × 10−7 mmol/CFU) was achieved at pH=8, 1% DB inoculum volume, and 400 mg/L sodium acetate concentration. Moreover, DB has a high acid resistance and a removal capacity of 1.18×10−7 mmol/CFU for TCE at pH =2. None of the co-occurring pollutants Cr (VI) and toluene had a significant effect on the ability of DB to degrade TCE in wastewater (maintained at 1.13–1.22×10−7 mmol/CFU). DB dechlorinated TCE mainly through the action of extracellular enzymes (contributed 91% of the total removal ability). DB playing a major role in degradation is Paraclostridium. Significant differences in alpha diversity indices were revealed in the reaction systems after 15 days of exposure to TCE (p < 0.01). The degradation of TCE by DB is mainly accomplished through the defense system, energy synthesis, electron supply and biodegradation. Metagenomic sequencing demonstrated that DB achieved adaptation and degradation of TCE through gene-regulated biological processes such as xenobiotic biodegradation and metabolism, carbohydrate metabolism, biosynthesis of other secondary metabolites, amino acid metabolism, membrane transport, and signal transduction. This study reveals for the first time the biodegradation efficiency and biotransformation process of DB under TCE stress.

Aqueous-phase chemistry of glyoxal with multifunctional reduced nitrogen compounds: a potential missing route for secondary brown carbon

Abstract. The aqueous-phase chemistry of glyoxal (GL) with reduced nitrogen compounds (RNCs) is a significant source for secondary brown carbon (SBrC), which is one of the largest uncertainties in climate predictions. However, a few studies have revealed that SBrC formation is affected by multifunctional RNCs, which have a non-negligible atmospheric abundance. Hence, we assessed theoretical and experimental approaches to investigate the reaction mechanisms and kinetics of the mixtures for ammonium sulfate (AS), multifunctional amine monoethanolamine (MEA), and GL. Our experiments indicate that light absorption and growth rate are enhanced more efficiently in the MEA–GL mixture relative to AS–GL and MEA–AS–GL mixtures and MEA reactions of the chromophores than in the analogous AS reactions. Quantum chemical calculations show that the formation and propagation of oligomers proceed via four-step nucleophilic addition reactions in three reaction systems. The presence of MEA provides the two extra branched chains that affect the natural charges and steric hindrance of intermediates, facilitating the formation of chromophores. Molecule dynamics simulations reveal that the interfacial and interior attraction on the aqueous aerosols with MEA is more pronounced for small α-dicarbonyls to facilitate further engagement in the aqueous-phase reactions. Our results show a possible missing source for SBrC formation on urban, regional, and global scales.

A simple chemical equilibrium algorithm applied for single and multiple reaction systems

AbstractThermodynamics is a branch of physics of high importance for engineering applications but is usually considered by most students as a rather obscure field, full of abstract concepts. Therefore, simple algorithms, which can exemplify the use of thermodynamic principles for practical situations, should be viewed as valuable teaching tools with large applications in engineering undergraduate courses. This point served as motivation for the present work, which proposes an alternative and simple computational approach for solving chemical equilibrium problems via successive reaction quotient calculations, both for single and multireactional systems. The code was written using MATLAB software; its fundamental theory was explained through a step‐by‐step approach and applied to both Shift and Boudouard reactions. Comparisons with ASPEN HYSYS and HSC Chemistry simulations corroborate its versatility and thermodynamic consistency. The full script is available in its entirety at the as supporting information together with the necessary text (.txt) files. Also, a user guide was provided to help students to replicate the results presented in the article.

Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning

The recently proposed Chemical Reaction Neural Network (CRNN) discovers chemical reaction pathways from time resolved species concentration data in a deterministic manner. Since the weights and biases of a CRNN are physically interpretable, the CRNN acts as a digital twin of a classical chemical reaction network. In this study, we employ a Bayesian inference analysis coupled with neural ordinary differential equations (ODEs) on this digital twin to discover chemical reaction pathways in a probabilistic manner. This allows for estimation of the uncertainty surrounding the learned reaction network. To achieve this, we propose an algorithm which combines neural ODEs with a preconditioned stochastic gradient langevin descent (pSGLD) Bayesian framework, and ultimately performs posterior sampling on the neural network weights. We demonstrate the successful implementation of this algorithm on several reaction systems by not only recovering the chemical reaction pathways but also estimating the uncertainty in our predictions. We compare the results of the pSGLD with that of the standard SGLD and show that this optimizer more efficiently and accurately estimates the posterior of the reaction network parameters. Additionally, we demonstrate how the embedding of scientific knowledge improves extrapolation accuracy by comparing results to purely data-driven machine learning methods. Together, this provides a new framework for robust, autonomous Bayesian inference on unknown or complex chemical and biological reaction systems.

HEAT STRESS IN CITRUS: A MOLECULAR FUNCTIONAL AND BIOCHEMICAL PERCEPTION

Misfortunes caused by high temperatures compel us to more readily comprehend the physiological, hormonal, and sub-atomic systems of reactions, particularly in humid and subhumid yields such as citrus organic products that are accustomed to specific conditions. Heat stress is accustomed to drought and many other environmental factors affecting Citriculture. We observe the role of Rubisco, antioxidant enzymes, HSPs, physiological changes in plasma membranes, and the role of ABA and SA under heat stress in citrus. Not-with-standing essential exploration, developing and utilizing new and well-developed citrus rootstocks is an essential element for the regulation, according to ecological circumstances. Rootstocks are essential in controlling how plants react to changing environmental factors, such as heat stress. They transfer beneficial features and increase stress tolerance, which helps citrus plants be more resilient overall. The duration of growth, yield, fruit quality, and tolerance to biotic and abiotic challenges are only a few of the characteristics of citrus horticulture that can be significantly improved using the right rootstocks. Enhancing citrus fruits' resistance to unfavorable environmental circumstances is urgently needed due to climate change. We can learn more about how different rootstocks affect the scion's capacity to withstand abiotic pressures by examining the metabolic responses caused by those rootstocks. Because of its increased antioxidant capacity, improved stomatal control, and storage of protective proteins, Carrizo citrange, for instance, demonstrates superior resilience to heat stress when compared to Cleopatra mandarin. The combined impacts of heat and drought on citrus vegetation differ from the effects of each stress alone. Specific metabolic changes are occur, which agree with findings from other plant research looking at the combined impacts of stress on physiology, transcriptome, proteome, and metabolome. When using rootstocks like Sunki Maravilha mandarin under drought stress, important metabolites such as galactinol, raffinose, and SA can be enhanced in scions through grafting. On the other hand, the Cleopatra rootstock alters the metabolism of the scion, resulting in lower quantities of the amino acids galactinol, raffinose, proline, phenylalanine, and tryptophan, which could lead to undesired characteristics. These results highlight the value of continued research to solve the problems brought on by climate change and provide light on the role of rootstocks in citriculture.

Unraveling the Prominent Existence of Trace Metals in Photocatalysis: Exploring Iron Impurity Effects.

Metal impurities can complicate the identification of active catalyst species in transition metal catalysis and electrocatalysis, potentially leading to misleading findings. This study investigates the influence of metal impurities on photocatalysis. Specifically, the photocatalytic reaction of inert alkanes using chlorides without the use of an external photocatalyst was studied, achieving successful C(sp3)-H functionalization. The observations reveal that Fe and Cu impurities are challenging to avoid in a typical laboratory environment and are prominently present in normal reaction systems, and iron impurities play a dominant role in the aforementioned apparent 'metal-free' reaction. Additionally, iron exhibits significantly higher catalytic activity compared to Cu, Ce, and Ni at low metal concentrations in the photocatalytic C(sp3)-H functionalization using chlorides. Considering the widespread presence of Fe and Cu impurities in typical laboratory environments, this study serves as a reminder of their involvement in reaction processes.