Toward Ab Initio Reaction Discovery Using the Artificial Force Induced Reaction Method.

Predicting the whole process of a chemical reaction while solving kinetic equations presents an opportunity to realize an on-the-fly kinetic simulation that directly discovers chemical reactions with their product yields. Such a simulation avoids the combinatorial explosion of reaction patterns to be examined by narrowing the search space based on the kinetic analysis of the reaction path network, and would open a new paradigm beyond the conventional two-step approach, which requires a reaction path network prior to performing a kinetic simulation. The authors addressed this issue and developed a practical method by combining the artificial force induced reaction method with the rate constant matrix contraction method. Two algorithms are available for this purpose: a forward mode with reactants as the input and a backward mode with products as the input. This article first numerically verifies these modes for known reactions and then demonstrates their application to the actual reaction discovery. Finally, the challenges of this method and the prospects for ab initio reaction discovery are discussed.

Development of a Five-Chemical-Probe Method to Determine Multiple Radicals Simultaneously in Hydroxyl and Sulfate Radical-Mediated Advanced Oxidation Processes.

Advanced oxidation processes (AOPs), such as hydroxyl radical (HO•)- and sulfate radical (SO4•-)-mediated oxidation, are attractive technologies used in water and wastewater treatments. To evaluate the treatment efficiencies of AOPs, monitoring the primary radicals (HO• and SO4•-) as well as the secondary radicals generated from the reaction of HO•/SO4•- with water matrices is necessary. Therefore, we developed a novel chemical probe method to examine five key radicals simultaneously, including HO•, SO4•-, Cl•, Cl2•-, and CO3•-. Five probes, including nitrobenzene, para-chlorobenzoic acid, benzoic acid, 2,4,6-trimethylbenzoic acid, and 2,4,6-trimethylphenol, were selected in this study. Their bimolecular reaction rate constants with diverse radicals were first calibrated under the same conditions to minimize systematic errors. Three typical AOPs (UV/H2O2, UV/S2O82-, and UV/HSO5-) were tested to obtain the radical steady-state concentrations. The effects of dissolved organic matter, Br-, and the probe concentration were inspected. Our results suggest that the five-probe method can accurately measure radicals in the HO•- and SO4•--mediated AOPs when the concentration of Br- and DOM are less than 4.0 µM and 15 mgC L-1, respectively. Overall, the five-probe method is a practical and easily accessible method to determine multiple radicals simultaneously.

Defining quality assurance guidance for effective selection of technical grade zero-valent iron production batch for groundwater remediation using permeable reactive barrier.

Zero-valent iron (ZVI) applied to the remediation of contaminated groundwater (GW) in situ, especially using engineered permeable reactive barriers (PRBs), has been proven to be an effective reactive material. However, many of ZVI brands do not represent tailored reagents specifically regarding destroying pollutants in GW. Thus, their reactivity towards certain contaminants in GW may vary significantly in a wide range even with different production batches of the same ZVI brand. This issue has rarely been known and consequently not addressed to a higher extend so far. Therefore, this study implemented extensive, long-term column experiments followed by short-term batch experiments for chlorinated volatile organic compounds (cVOCs) degradation for developing a semi-empirical test methodology to thoroughly resolve this pivotal issue by achieving an improved quality assurance guidance regarding proper field-scale emplacement of different ZVI brands and their production batches. The results showed that during column experiments perchloroethylene (PCE) led to a significant degradation up to a certain period but sulfate-reducing microorganisms enhanced the dehalogenation and led approximately to 100 % PCE removal. However, the efficacy varied for different ZVI brands, i.e., Gotthart Maier (GM) and Sponge Iron (Responge®). Furthermore, it could be shown that it might even vary among different production batches of the same ZVI brand. It was also observed that evolution of sulfate-reducing microorganisms may improve the efficacy of PCE degradation vastly that occur at different intensities with different ZVI brands and their respective production batches over time. Further, comparing comprehensive long-term column (kobs = 0.0488 1/h) and short-term batch experiments (kobs = 0.07794 1/h) as well as refined kinetic analyses (kobs = 0.0424 1/h) clearly prove that an appropriate guidance protocol for successful full-scale in situ remediation is required for properly select the right ZVI brand and production batch before it is loaded to a PRB in the field.

Investigation of Flame Structures of Double-Base Propellant and Modified Double-Base Propellant Containing Nitramine Using OH-PLIF and Kinetic Simulation.

The combustion behavior of various propellant samples, including double-base propellants, pressed nitramine powders, and modified double-base propellants containing nitramine, was examined using OH-PLIF technology. The combustion process took place within a combustion chamber, and images capturing the flame at the moment of stable combustion were selected for further analysis. The distribution and production rate of OH radicals in both the double-base propellant and the nitramine-modified double-base propellant were simulated using Chemkin-17.0 software. The outcomes from both the experimental and simulation studies revealed that the concentration of OH radicals increased with a higher content of NG in the double-base propellant. In the modified double-base propellant containing RDX, the OH radical concentration decreased as the RDX content increased, with these tendencies of change aligning closely with the simulation results.

Electron Signatures of Reconnection in a Global eVlasiator Simulation.

Geospace plasma simulations have progressed toward more realistic descriptions of the solar wind-magnetosphere interaction from magnetohydrodynamic to hybrid ion-kinetic, such as the state-of-the-art Vlasiator model. Despite computational advances, electron scales have been out of reach in a global setting. eVlasiator, a novel Vlasiator submodule, shows for the first time how electromagnetic fields driven by global hybrid-ion kinetics influence electrons, resulting in kinetic signatures. We analyze simulated electron distributions associated with reconnection sites and compare them with Magnetospheric Multiscale (MMS) spacecraft observations. Comparison with MMS shows that key electron features, such as reconnection inflows, heated outflows, flat-top distributions, and bidirectional streaming, are in remarkable agreement. Thus, we show that many reconnection-related features can be reproduced despite strongly truncated electron physics and an ion-scale spatial resolution. Ion-scale dynamics and ion-driven magnetic fields are shown to be significantly responsible for the environment that produces electron dynamics observed by spacecraft in near-Earth plasmas.

Identifying Phase-Dependent Electrochemical Stripping Performance of FeOOH Nanorod: Evidence from Kinetic Simulation and Analyte-Material Interactions.

Metal hydroxide nanomaterials are widely applied in the energy and environment fields. The electrochemical performance of such materials is strongly dependent on their crystal phases. However, as there are always multiple factors relating to the phase-dependent electrochemistry, it is still difficult to identify the determining one. The well-defined crystal phases of α- and ß-FeOOH nanorods are characterized through the transmission electron microscopy by a series of rotation toward one rod, where the cross-section shape and the growth direction along the [001] crystalline are first verified for 1D FeOOH nanostructures. The electrosensitivity of the two materials toward Pb(II) is tested, where α-FeOOH performs an outstanding sensitivity whilst it is only modest for ß-FeOOH. Experiments via Fourier transform infrared spectroscopy, X-ray absorption fine structure (XAFS), etc., show that α-FeOOH presents a larger Pb(II) adsorption capacity due to more surficial hydroxyl groups and weaker PbO bond strength. The reaction kinetics are simulated and the adsorption capacity is found to be the determining factor for the distinct Pb(II) sensitivities. Combining experiment with simulation, this work reveals the physical insights of the phase-dependent electrochemistry for FeOOH and provides guidelines for the functional application of metal hydroxide nanomaterials.

Optimizing biomethane production of mesophilic chicken manure and sheep manure digestion: Mono-digestion and co-digestion kinetic investigation, autofluorescence analysis and microbial community assessment.

Optimization of mesophilic methane production from Chicken manure (CM) and Sheep manure (SM) at total solid (TS) of 8% and 1.6% were obtained by sequence tests in mono-digestion. However, the positive synergy of co-digestion with an optimum CM/SM of 2.5 (310 mLCH4/gVSadded) resulted in a high hydrolytic capacity and methane production. The modified Gompertz model (R2 > 0.98) and modified Aiba model (R2 > 0.88) illustrated co-digestion significantly improved the methane generation rate with strong ammonia tolerance. Dissolved Organic Matter (DOM) variation in response to the metabolic rate of microbial community illustrated that the SMP-like and protein-like components half-split by EEM-PARAFAC were significantly negative corresponded to bio-methane production. Moreover, the canonical correlation analysis (CCA) resulted a significant difference between the substrate and DOM composition. Potential functional metabolic illustrated statistically significance difference between mono and co-digestion, however, Methanosaeta and Syntrophobacter predominated the syntrophic methanogenesis. The constructed complex metabolic cooperation caused the co-digestion stable and high efficiency.

Evolution of Nucleic-Acid-Based Constitutional Dynamic Networks Revealing Adaptive and Emergent Functions.

The evolution of networks is a fundamental unresolved issue in developing the area of systems chemistry. We introduce a versatile rewiring mechanism that leads to the emergence of nucleic-acid-based constitutional dynamic networks (CDNs). A two-component constituent AA' functionalized with a Mg2+ -ion-dependent DNAzyme activator unit forms a complex with an intact hairpin HBB' composed of B and B' sequences. Cleavage of HBB' leads to the two-component constituent BB', and its rewiring with AA' yields CDN X composed of the equilibrated constituents AA', AB', BA', and BB'. In analogy, subjecting AA' to an intact hairpin HCC' leads to the formation of CDN Y consisting of AA', AC', CA', and CC'. Subjecting AA' to the mixture of HBB' and HCC' evolves the [3×3] CDN Z, composed of nine constituents, thus demonstrating hierarchical adaptive properties. Furthermore, the DNAzyme units associated with the constituents are applied to tailor emerging catalytic functions from the different CDNs.

Full rate constant matrix contraction method for obtaining branching ratio of unimolecular decomposition.

The branching ratio of unimolecular decomposition can be evaluated by solving the rate equations. Recent advances in automated reaction path search methods have enabled efficient construction of the rate equations based on quantum chemical calculations. However, it is still difficult to solve the rate equations composed of hundreds or more elementary steps. This problem is especially serious when elementary steps that occur in highly different timescales coexist. In this article, we introduce an efficient approach to obtain the branching ratio from a given set of rate equations. It has been derived from a recently proposed rate constant matrix contraction (RCMC) method, and termed full-RCMC (f-RCMC). The f-RCMC gives the branching ratio without solving the rate equations. Its performance was tested numerically for unimolecular decomposition of C3 H5 and C4 H5 . Branching ratios obtained by the f-RCMC precisely reproduced the values obtained by numerically solving the rate equations. It took about 95 h to solve the rate equations of C4 H5 consisting of 234 elementary steps. In contrast, the f-RCMC gave the branching ratio in less than 1 s. The f-RCMC would thus be an efficient alternative of the conventional kinetic simulation approach. © 2016 Wiley Periodicals, Inc.

Bivalent kinetic binding model to surface plasmon resonance studies of antigen-antibody displacement reactions.

Molecular and functional analysis of small molecule binding to protein can provoke insights into cellular signaling and regulatory systems as well as facilitate pharmaceutical drug discovery. In label free small molecule detection the displacement assay format can be applied. This is beneficial because displacement of high molecular weight receptors is detected instead of low molecular weight ligand as in classical binding analysis. Thus, detection limit is potentially lowered. Using the influenza haemagglutinin (HA) peptide binding to mono or bivalent anti-haemagglutinin peptide antibody displacement assay formats could be established. The exact time resolved analysis of binding and dissolution of ligand HA and anti-Haemagglutinin peptide antibody was achieved with surface plasmon resonance (SPR) spectroscopy. Mathematical models could be developed from kinetic equations of ligand binding to mono or bivalent antibodies. With this, an accurate simulation of the SPR results was reached. The simulation plot had to be exactly adjusted to the SPR results to determine all kinetic rate constants defining ligand and receptor binding kinetics. Large variations in receptor concentration gave almost identical rate constants in binding. It became obvious that rebinding is in any case not necessary to understand the binding kinetics of our model system HA/anti-HA. Maximum decline of SPR response could be used to determine ligand concentrations in analyte.

Realistic kinetic loading of the jaw system during single chewing cycles: a finite element study.

Although knowledge of short-range kinetic interactions between antagonistic teeth during mastication is of essential importance for ensuring interference-free fixed dental reconstructions, little information is available. In this study, the forces on and displacements of the teeth during kinetic molar biting simulating the power stroke of a chewing cycle were investigated by use of a finite-element model that included all the essential components of the human masticatory system, including an elastic food bolus. We hypothesised that the model can approximate the loading characteristics of the dentition found in previous experimental studies. The simulation was a transient analysis, that is, it considered the dynamic behaviour of the jaw. In particular, the reaction forces on the teeth and joints arose from contact, rather than nodal forces or constraints. To compute displacements of the teeth, the periodontal ligament (PDL) was modelled by use of an Ogden material model calibrated on the basis of results obtained in previous experiments. During the initial holding phase of the power stroke, bite forces were aligned with the roots of the molars until substantial deformation of the bolus occurred. The forces tilted the molars in the bucco-lingual and mesio-distal directions, but as the intrusive force increased the teeth returned to their initial configuration. The Ogden material model used for the PDL enabled accurate prediction of the displacements observed in experimental tests. In conclusion, the comprehensive kinetic finite element model reproduced the kinematic and loading characteristics of previous experimental investigations.

Introduction of a new platform for parameter estimation of kinetically complex environmental systems.

A modeling framework (ReKinSim - Reaction Kinetics Simulator) is introduced, within which biogeochemical reactions in environmental systems can be described and inversely fitted to experimental data. Three key features of this simulation environment are: (1) a generic mathematical tool for solving sets of unlimited, arbitrary, non-linear ordinary differential equations; (2) no limitation to the number or type of reactions or other influential dynamics (e.g., isotope fractionation or small-scale mass-transfer limitations); (3) an easy to use and flexible module for nonlinear data-fitting. It allows users to easily define any kinetic model by a set of biogeochemical reactions relevant to the experimental application and to obtain the values of the kinetic parameters by fitting of the model to data. By allowing users to include the environmentally related processes and solving them along with the chemical kinetics, ReKinSim helps the user to elucidate the extent that these processes are controlled by factors other than kinetics. The novelty of the presented program primary lays in its unique combination of flexibility, computational efficiency and user-friendliness. ReKinSim's usability is showcased by four case studies of varying complexity, and compared against a set of currently available modeling tools.

Acetyl Radical Generation in Cigarette Smoke: Quantification and Simulations.

Free radicals are present in cigarette smoke and can have a negative effect on human health. However, little is known about their formation mechanisms. Acetyl radicals were quantified in tobacco smoke and mechanisms for their generation were investigated by computer simulations. Acetyl radicals were trapped from the gas phase using 3-amino-2, 2, 5, 5-tetramethyl-proxyl (3AP) on solid support to form stable 3AP adducts for later analysis by high performance liquid chromatography (HPLC), mass spectrometry/tandem mass spectrometry (MS-MS/MS) and liquid chromatography-mass spectrometry (LC-MS). Simulations were performed using the Master Chemical Mechanism (MCM). A range of 10-150 nmol/cigarette of acetyl radical was measured from gas phase tobacco smoke of both commerial and research cigarettes under several different smoking conditions. More radicals were detected from the puff smoking method compared to continuous flow sampling. Approximately twice as many acetyl radicals were trapped when a glass filber particle filter (GF/F specifications) was placed before the trapping zone. Simulations showed that NO/NO2 reacts with isoprene, initiating chain reactions to produce hydroxyl radical, which abstracts hydrogen from acealdehyde to generate acetyl radical. These mechanisms can account for the full amount of acetyl radical detected experimentally from cigarette smoke. Similar mechanisms may generate radicals in second hand smoke.

A machine learning-guided modeling approach to the kinetics of α-tocopherol and myricetin synergism in bulk oil oxidation.

The shelf-life and quality of food products depend heavily on antioxidants, which protect lipids from free radical degradation. α-Tocopherol and myricetin, two potent antioxidants, synergistically enhance the prevention of oxidative rancidity in bulk oil systems. Understanding their degradation kinetics is essential for deepening our knowledge of their mechanisms and developing strategies to predict shelf-life before expiration. This paper introduces a generalized mathematical model to describe the degradation kinetics of α-tocopherol in the presence of myricetin. Using direct differential methods guided by a machine learning approach based on neural differential equations, we uncover two distinct phases of α-tocopherol degradation when coexisting with myricetin at varying concentration ratios. These findings inform the development of a mixed Weibull model that accurately captures the degradation process. Our study enhances the understanding of antioxidant interactions and provides a reliable method for predicting food system stability, offering valuable insights for optimizing natural antioxidants in food preservation.

The mammalian peroxisomal membrane is permeable to both GSH and GSSG - Implications for intraperoxisomal redox homeostasis.

Despite the large amounts of H2O2 generated in mammalian peroxisomes, cysteine residues of intraperoxisomal proteins are maintained in a reduced state. The biochemistry behind this phenomenon remains unexplored, and simple questions such as "is the peroxisomal membrane permeable to glutathione?" or "is there a thiol-disulfide oxidoreductase in the organelle matrix?" still have no answer. We used a cell-free in vitro system to equip rat liver peroxisomes with a glutathione redox sensor. The organelles were then incubated with glutathione solutions of different redox potentials and the oxidation/reduction kinetics of the redox sensor was monitored. The data suggest that the mammalian peroxisomal membrane is promptly permeable to both reduced and oxidized glutathione. No evidence for the presence of a robust thiol-disulfide oxidoreductase in the peroxisomal matrix could be found. Also, prolonged incubation of organelle suspensions with glutaredoxin 1 did not result in the internalization of the enzyme. To explore a potential role of glutathione in intraperoxisomal redox homeostasis we performed kinetic simulations. The results suggest that even in the absence of a glutaredoxin, glutathione is more important in protecting cysteine residues of matrix proteins from oxidation by H2O2 than peroxisomal catalase itself.

Dynamic Transcription Machineries Guide the Synthesis of Temporally Operating DNAzymes, Gated and Cascaded DNAzyme Catalysis.

Transient transcription machineries play important roles in the dynamic modulation of gene expression and the sequestered regulation of cellular networks. The present study emulates such processes by designing artificial reaction modules consisting of transcription machineries that guide the transient synthesis of catalytic DNAzymes, the transient operation of gated DNAzymes, and the temporal activation of an intercommunicated DNAzyme cascade. The reaction modules rely on functional constituents that lead to the triggered activation of transcription machineries in the presence of the nucleoside triphosphates oligonucleotide fuel, yielding the transient formation and dissipative depletion of the intermediate DNAzyme(s) products. The kinetics of the transient DNAzyme networks are computationally simulated, allowing to predict and experimentally validate the performance of the systems under different auxiliary conditions. The study advances the field of systems chemistry by introducing transcription machinery-based networks for the dynamic control over transient catalysis─a primary step toward life-like cellular assemblies.

Rationally Reconstructed Metal-Organic Frameworks as Robust Oxygen Evolution Electrocatalysts.

Reconstructing metal-organic framework (MOFs) toward a designed framework structure provides breakthrough opportunities to achieve unprecedented oxygen evolution reaction (OER) electrocatalytic performance, but has rarely, if ever, been proposed and investigated yet. Here, the first successful fabrication of a robust OER electrocatalyst by precision reconstruction of an MOF structure is reported, viz., from MOF-74-Fe to MIL-53(Fe)-2OH with different coordination environments at the active sites. Due to the radically reduced eg -t2g crystal-field splitting in Fe-3d and the much suppressed electron-hopping barriers through the synergistic effects of the O species the efficient OER of in MIL-53(Fe)-2OH is guaranteed. Benefiting from this desired electronic structure, the designed MIL-53(Fe)-2OH catalyst exhibits high intrinsic OER activity, including a low overpotential of 215 mV at 10 mA cm-2 , low Tafel slope of 45.4 mV dec-1 and high turnover frequency (TOF) of 1.44 s-1 at 300 mV overpotential, over 80 times that of the commercial IrO2 catalyst (0.0177 s-1 ).Consistent with the density functional theory (DFT) calculations, the real-time kinetic simulation reveals that the conversion from O* to OOH* is the rate-determining step on the active sites of MIL-53(Fe)-2OH.

Aquatic photochemistry of Cu(II) in the presence of As(III): Mechanistic insights from Cu(III) production and As(III) oxidation under neutral pH conditions.

Surface complexation between arsenite (As(III)) and colloidal metal hydroxides plays an important role not only in the immobilization and oxidation of As(III) but also in the cycle of the metal and the fate of their ligands. However, the photochemical processes between Cu(II) and As(III) are not sufficiently understood. In this work, the photooxidation of As(III) in the presence of Cu(II) under neutral pH conditions was investigated in water containing 200 µM Cu(II) and 5 µM As(III) under simulated solar irradiation consisting of UVB light. The results confirmed the complexation between As(III) and Cu(II) hydroxides, and the photooxidation of As(III) is attributed to the ligand-to-metal charge transfer (LMCT) process and Cu(III) oxidation. The light-induced LMCT process results in simultaneous As(III) oxidation and Cu(II) reduction, then produced Cu(I) undergoes autooxidation with O2 to produce O2•⁻ and H2O2, and further the Cu(I)-Fenton reaction produces Cu(III) that can oxidize As(III) efficiently (kCu(III)+As(III) = 1.02 × 109 M-1 s-1). The contributions from each pathway (ρrCu(II)-As(III)+hv = 0.62, ρrCu(III)+As(III) = 0.38) were obtained using kinetic analysis and simulation. Sunlight experiments showed that the pH range of As(III) oxidation could be extended to weak acidic conditions in downstream water from acid mine drainage (AMD). This work helps to understand the environmental chemistry of Cu(II) and As(III) regarding their interaction and photo-induced redox reactions.

Evolution of Molar Mass Distributions Using a Method of Partial Moments: Initiation of RAFT Polymerization.

We describe a method of partial moments devised for accurate simulation of the time/conversion evolution of polymer composition and molar mass. Expressions were derived that enable rigorous evaluation of the complete molar mass and composition distribution for shorter chain lengths (e.g., degree of polymerization, Xn = N < 200 units) while longer chains (Xn ≥ 200 units) are not neglected, rather they are explicitly considered in terms of partial moments of the molar mass distribution, µxN(P)=∑n=N+1∞nx[Pn] (where P is a polymeric species and n is its' chain length). The methodology provides the exact molar mass distribution for chains Xn < N, allows accurate calculation of the overall molar mass averages, the molar mass dispersity and standard deviations of the distributions, provides closure to what would otherwise be an infinite series of differential equations, and reduces the stiffness of the system. The method also allows for the inclusion of the chain length dependence of the rate coefficients associated with the various reaction steps (in particular, termination and propagation) and the various side reactions that may complicate initiation or initialization. The method is particularly suited for the detailed analysis of the low molar mass portion of molar mass distributions of polymers formed by radical polymerization with reversible addition-fragmentation chain transfer (RAFT) and is relevant to designing the RAFT-synthesis of sequence-defined polymers. In this paper, we successfully apply the method to compare the behavior of thermally initiated (with an added dialkyldiazene initiator) and photo-initiated (with a RAFT agent as a direct photo-iniferter) RAFT-single-unit monomer insertion (RAFT-SUMI) and oligomerization of N,N-dimethylacrylamide (DMAm).

Cotranscriptional Kinetic Folding of RNA Secondary Structures Including Pseudoknots.

Computational prediction of ribonucleic acid (RNA) structures is an important problem in computational structural biology. Studies of RNA structure formation often assume that the process starts from a fully synthesized sequence. Experimental evidence, however, has shown that RNA folds concurrently with its elongation. We investigate RNA secondary structure formation, including pseudoknots, that takes into account the cotranscriptional effects. We propose a single-nucleotide resolution kinetic model of the folding process of RNA molecules, where the polymerase-driven elongation of an RNA strand by a new nucleotide is included as a primitive operation, together with a stochastic simulation method that implements this folding concurrently with the transcriptional synthesis. Numerical case studies show that our cotranscriptional RNA folding model can predict the formation of conformations that are favored in actual biological systems. Our new computational tool can thus provide quantitative predictions and offer useful insights into the kinetics of RNA folding.