Reaction Time Scale Research Articles

Evaluation of chemical kinetic models for simulations of hydrogen detonations by comparison with experimental data

Two-dimensional numerical simulations of a weakly unstable detonation mixture 2H2+O2+3.76Ar at 20kPa and 295K were performed using our validated OpenFOAM solver based on reacting-PimpleCentralFoam. This study compared the detonation dynamics obtained with four chemical models, namely Hong 2011, Burke 2012, Mével 2014, and FFCM-2 with recently obtained experimental results. The experimental–numerical comparisons were performed in threefold: (i) quantitative comparisons of the cell sizes (λ) and their distributions (2σ/λ); (ii) qualitative comparisons of the detonation structure based on simultaneous planar laser-induced fluorescence of both nitric oxide (NO-PLIF) and OH radical (OH-PLIF); (iii) qualitative and quantitative comparisons of the detonation dynamics based on combined Rayleigh scattering and NO-PLIF measurements. The simulations conducted with Hong 2011’s, Burke 2012’s, and FFCM-2’s models satisfactorily reproduced the average cell size (within 10%), while it was 1.5 times smaller with Mével 2014’s model. The opposite trends were observed in cell size distributions (2σ/λ) with satisfactory predictions from Mével 2014’s model (within 25%) and almost no cell size variations (2σ/λ<0.1) for the other models. By comparing the simultaneous NO- and OH-PLIF imaging, the simulations conducted with FFCM-2’s and Mével 2014’s models qualitatively reproduced the reaction zone structure, while more discrepancies were obtained with Hong 2011’s and Burke 2012’s models. Quantitatively, simulations conducted with FFCM-2’s and Mével 2014’s models presented the lowest discrepancy (below two-fold) at reproducing the induction zone dynamics along the cellular cycle, while large discrepancies (approximately three-fold) were observed with Hong 2011’s and Burke 2012’s models. Chemical timescale analyses evidenced the relation between the faster reaction timescales of Mével 2014’s model and the ability to reproduce the experimental variability on both λ and Δi. These detailed comparisons emphasized the importance of the chemical model selection and the need for combined experimental measurements to both validate chemical models and achieve predictive detonation simulations.

Determining reaction rate parameters for an energetic material through inverse multi-scale analysis of shock-to-detonation transition

ABSTRACT In multi-scale predictive models of shock-to-detonation transition (SDT), microstructure-aware burn models are employed to connect meso-scale dynamics with macro-scale energy release. Meso-scale calculations of hotspot ignition and growth rely on chemical reaction rates expressed in Arrhenius forms. However, even for well-studied energetic materials such as HMX, the reaction time scales and pathways provided by available reaction kinetic schemes vary widely. Uncertainties in reaction rate parameters can amplify to produce large uncertainties in predicted initiation envelopes (James curves or Pop-plots). To better pin down reaction rate parameters for HMX, we perform an inverse analysis to extract the rate constants in an Arrhenius model (assuming a single reaction global kinetics model) that best predicts an experimentally obtained criticality envelope. Interestingly, the estimated global kinetic scheme is shown to conform to the well-known Henson 1-equation model. To establish the validity of the inverse analysis, we further carry out a forward analysis using the determined rate law and demonstrate good predictions of SDT for a different class of pressed HMX material. While the inverse analysis has been applied herein to HMX, the paper presents a general route to arrive at global kinetics models that can be applied to a wide class of EM species.

Programmable C−N Bond Formation through Radical‐Mediated Chemistry in Plasma‐Microdroplet Fusion

AbstractNon‐thermal plasma discharge produced in the wake of charged microdroplets is found to facilitate catalyst‐free radical mediated hydrazine cross‐coupling reactions without the use of external light source, heat, precious metal complex, or trapping agents. A plasma‐microdroplet fusion platform is utilized for introduction of hydrazine reagent that undergoes homolytic cleavage forming radical intermediate species. The non‐thermal plasma discharge that causes the cleavage originates from a chemically etched silica capillary. The coupling of the radical intermediates gives various products. Plasma‐microdroplet fusion occurs online in a programmable reaction platform allowing direct process optimization and product validation via mass spectrometry. The platform is applied herein with a variety of hydrazine substrates, enabling i) self‐coupling to form secondary amines with identical N‐substitutions, ii) cross‐coupling to afford secondary amine with different N‐substituents, iii) cross‐coupling followed by in situ dehydrogenation to give the corresponding aryl‐aldimines with two unique N‐substitutions, and iv) cascade heterocyclic carbazole derivatives formation. These unique reactions were made possible in the charged microdroplet environment through our ability to program conditions such as reagent concentration (i. e., flow rate), microdroplet reactivity (i. e., presence or absence of plasma), and reaction timescale (i. e., operational mode of the source). The selected program is implemented in a co‐axial spray format, which is found to be advantageous over the conventional one‐pot single emitter electrospray‐based microdroplet reactions.

Programmable C-N Bond Formation through Radical-Mediated Chemistry in Plasma-Microdroplet Fusion.

Non-thermal plasma discharge produced in the wake of charged microdroplets is found to facilitate catalyst-free radical mediated hydrazine cross-coupling reactions without the use of external light source, heat, precious metal complex, or trapping agents. A plasma-microdroplet fusion platform is utilized for introduction of hydrazine reagent that undergoes homolytic cleavage forming radical intermediate species. The non-thermal plasma discharge that causes the cleavage originates from a chemically etched silica capillary. The coupling of the radical intermediates gives various products. Plasma-microdroplet fusion occurs online in a programmable reaction platform allowing direct process optimization and product validation via mass spectrometry. The platform is applied herein with a variety of hydrazine substrates, enabling i) self-coupling to form secondary amines with identical N-substitutions, ii) cross-coupling to afford secondary amine with different N-substituents, iii) cross-coupling followed by in situ dehydrogenation to give the corresponding aryl-aldimines with two unique N-substitutions, and iv) cascade heterocyclic carbazole derivatives formation. These unique reactions were made possible in the charged microdroplet environment through our ability to program conditions such as reagent concentration (i. e., flow rate), microdroplet reactivity (i. e., presence or absence of plasma), and reaction timescale (i. e., operational mode of the source). The selected program is implemented in a co-axial spray format, which is found to be advantageous over the conventional one-pot single emitter electrospray-based microdroplet reactions.

Toward a Universal Model of Hyporheic Exchange and Nutrient Cycling in Streams

AbstractIn this paper we demonstrate that several ubiquitous hyporheic exchange mechanisms can be represented simply as a one‐dimensional diffusion process, where the diffusivity decays exponentially with depth into the streambed. Based on a meta‐analysis of 106 previously published laboratory measurements of hyporheic exchange (capturing a range of bed morphologies, hydraulic conditions, streambed properties, and experimental approaches) we find that the reference diffusivity and mixing length‐scale are functions of the permeability Reynolds Number and Schmidt Number. These dimensionless numbers, in turn, can be estimated for a particular stream from the median grain size of the streambed and the stream's depth, slope, and temperature. Application of these results to a seminal study of nitrate removal in 72 headwater streams across the United States, reveals: (a) streams draining urban and agricultural landscapes have a diminished capacity for in‐stream and in‐bed mixing along with smaller subsurface storage zones compared to streams draining reference landscapes; (b) under steady‐state conditions nitrate uptake in the streambed is primarily biologically controlled; and (c) median reaction timescales for nitrate removal in the hyporheic zone are 0.5 and 20 hr for uptake by assimilation and denitrification, respectively. While further research is needed, the simplicity and extensibility of the framework described here should facilitate cross‐disciplinary discussions and inform reach‐scale studies of pollutant fate and transport and their scale‐up to watersheds and beyond.

Mixed‐alkali effect in the thermal collapse and melting kinetics of Zeolite X

AbstractThe thermal stability of zeolites underlies their many applications. Structural collapse usually occurs through a series of reactions, involving an initial low‐density amorphous state (LDA), a high‐density melt (HDA), and, eventually, a dense recrystallization product. The LDA–HDA transition resembles a glass melting process; the HDA phase can sometimes be quenched into a glass. Using isothermal as well as nonisothermal in situ observation methodology on the faujasitic zeolite X and its potassium‐for‐sodium ion‐exchanged derivatives, we find a pronounced mixed‐alkali effect in the characteristic nonisothermal transition temperatures as well as in the isothermal reaction timescale of the LDA–HDA transition. The latter is taken as being directly related to the viscosity of the liquid into which the zeolite framework is melting; the apparent viscosity associated with this melting process was found to reach as high as 1015 Pa.s at 740°C. The observed mixed‐alkali effect is similar to the one observed in the dynamics of common oxide glasses and their corresponding melts.

Probing Asymmetric Interactions with Time-Separated Mutual Information: A Case Study Using Golden Shiners.

Leader-follower modalities and other asymmetric interactions that drive the collective motion of organisms are often quantified using information theory metrics like transfer or causation entropy. These metrics are difficult to accurately evaluate without a much larger number of data than is typically available from a time series of animal trajectories collected in the field or from experiments. In this paper, we use a generalized leader-follower model to argue that the time-separated mutual information between two organism positions can serve as an alternative metric for capturing asymmetric correlations that is much less data intensive and more accurately estimated by popular k-nearest neighbor algorithms than transfer entropy. Our model predicts a local maximum of this mutual information at a time separation value corresponding to the fundamental reaction timescale of the follower organism. We confirm this prediction by analyzing time series trajectories recorded for a pair of golden shiner fish circling an annular tank.

Electrofiltration-Enabled Nitrate Reduction Reactivity of Carbon Nanotube Electrified Membrane for Drinking Water Treatment

Electrocatalytic nitrate reduction could enable nitrate removal in drinking water without generating concentrated waste streams. However, current processes heavily rely upon metal catalysts with high activity to achieve sufficient nitrate removal, which increases treatment costs and can inevitably lead to leaching of metals into treated water. In this study, we elucidate how electrified filtration enables sufficient nitrate conversion to meet drinking water standards in metal-free defective CNTs by tunable matching of mass transport and reaction timescales. The metal-free carbon nanotube (CNT)-based electrified membrane (EM) was employed as a porous flow-through cathode to decrease the diffusion boundary layer. Computational fluid dynamics simulations revealed that the flow-through mode mitigates diffusion limitations to enhance overall reaction activity, as compared to the conventional flow-by mode at the same flow rate. Additionally, the nitrate reduction rate could be tuned by controlling the nitrate advection rate using permeate flux (0 to 60 L h-1 m-2). A maximum removal efficiency of 86.9% was reached when the mass transport rate matched the reaction rate across a range of applied potentials. Furthermore, defects in CNTs were identified as the catalytic active sites. We employed density functional theory and molecular dynamics simulations to gain insight into CNT defect-catalyzed nitrate reduction under electrofiltration. Finally, the long-term stability, tolerance of environmental interferences, and sufficient nitrate removal and N2 selectivity to meet drinking water standards were demonstrated in synthetic surface water, suggesting that the CNT-EM and flow-through reactor may provide a promising solution for decentralized nitrate destruction in drinking water.

Light-Induced Redox Dynamics in Plasmonic Nanostructures and Photosensitizer Transition Metal Compounds

Solar energy harvesting is a nuanced scientific field that involves precise control across energy, time, and nanometer length scales. The understanding of how to harness sunlight to promote chemical reactions is vital for the advancement of renewable energy applications and a sustainable future. Limited knowledge of the precise chemical mechanisms underlying solar energy harvesting restricts widespread technological use and the development of photovoltaic devices that utilize light-harvesting biodegradable materials. My research focuses on developing a fundamental understanding of visible light-activated excited state chemistry that is of great importance in elucidating the mechanisms, structures, and design features for catalysis. In this talk, we will examine excited-state chemical structure dynamics in nanomaterials that use light-matter interactions to drive interfacial or intramolecular charge transfer. Steady-state and time-resolved optical/X-ray spectroscopy allow for the observation of these dynamics across an expansive timescale—from the seconds timescale of oxygen-evolving reactions to the ultrafast timescales of electronic and vibrational motion. Novel light-matter interactions in plasmonic nanostructures, biomimetic metal oxides, and molecular transition metal complexes will be discussed. The talk will conclude with future opportunities for expanding the scope of nanoscale photocatalysis and for designing enhanced localized control over excited-state chemistry.[1] E. A. Sprague-Klein*, X. He, M. W. Mara, B. J. Reinhart, S. Lee, L. M. Utschig, K. L. Mulfort, L. X. Chen*, D. M. Tiede*. “Photo-Electrochemical Effect in the Water Oxidation Catalyst Cobalt-Phosphate (CoPi),” ACS Energy Letters, 2022, 7, 9, 3129–3138. [2] N. L. Warren, U. Yunusa, A. B. Singhal, E. A. Sprague-Klein*. "Facilitating Excited-State Plasmonics and Photochemical Reaction Dynamics," Chemical Physics Reviews, (Accepted December 2023).[3] U. Yunusa, N. Warren, D. Schauer, P. Srivastava, E. Sprague-Klein*. "Plasmon resonance dynamics and enhancement effects in Tris(bipyridine)ruthenium(II) gold nanosphere oligomers," Nanoscale, (Under Review).

Unveiling the environmental significance of acetylperoxyl radical: Reactivity quantification and kinetic modeling.

Acetylperoxyl radical (CH3C(O)OO•) is among highly reactive organic radicals which are known to play crucial roles in atmospheric chemistry, aqueous chemistry and, most recently, peracetic acid (PAA)-based advanced oxidation processes. However, fundamental knowledge for its reactivity is scarce and severely hampers the understanding of relevant environmental processes. Herein, three independent experimental approaches were exploited for revelation and quantification of the reaction rates of acetylperoxyl radical. First, we developed and verified laser flash photolysis of biacetyl, ultraviolet (UV) photolysis of biacetyl, and pulse radiolysis of acetaldehyde, each as a clean source of CH3C(O)OO•. Then, using competition kinetics and selection of suitable probe and competitor compounds, the rate constants between CH3C(O)OO• and compounds of diverse structures were determined. The three experimental approaches complemented in reaction time scale and ease of operation, and provided cross-validation of the rate constants. Moreover, the formation of CH3C(O)OO• was verified by spin-trapped electron paramagnetic resonance, and potential influence of other reactive species in the systems was assessed. Overall, CH3C(O)OO• displays distinctively high reactivity and selectivity, reacting especially favorably with naphthyl and diene compounds (k ∼ 107-108 M-1 s-1) but sluggishly with N- and S-containing groups. Significantly, we demonstrated that incorporating acetylperoxyl radical-oxidation reactions significantly improved the accuracy in modeling the degradation of environmental micropollutants by UV/PAA treatment. This study is among the most comprehensive investigation for peroxyl radical reactivity to date, and establishes a robust methodology for investigating organic radical chemistry. The determined rate constants strengthen kinetic databases and improve modeling accuracy for natural and engineered systems.

Do not forget the electrons: Extending moderately-sized nuclear networks for multidimensional hydrodynamic codes

Nuclear networks are widely used coupled with hydrodynamical simulations of explosive scenarios to account for the change of nuclear species and energy generation rate due to nuclear reactions. In this way, there is a feedback mechanism between the hydrodynamical state and the nuclear processes. Unfortunately, the timescale of nuclear reactions is orders of magnitude smaller than the dynamical timescale that drives hydrodynamical simulations. Therefore, these nuclear networks are usually very small, reduced in most cases to a dozen elements, especially when simulations are carried out in more than one dimension. We present here an extended nuclear network, with 90 species, designed for being coupled with hydrodynamic simulations, which includes neutrons, protons, electrons, positrons, and the corresponding neutrino and anti-neutrino emission. This network is also coupled with temperature, making it extremely robust and, together with its size, unique of its kind. The inclusion of electron captures on free protons makes the network very appropriate for multidimensional studies of Type Ia supernova explosions, especially when the exploding object is a massive white dwarf. We perform several tests that are relevant to simulate explosive scenarios, such as Type Ia supernovae and core-collapse supernovae. We compare the results of the 90 nuclei network with a standard alpha -chain network with 14 elements to evaluate the differences in the energy generation rate. We also evaluate the relevance of including the electrons in the network in terms of generated yields and how it affects the pressure of a degenerate fluid such as that of white dwarfs. The results obtained with the 90-nuclei network have been verified with a much larger 2000-nuclei network built from REACLIB (WinNet), in terms of nuclear energy generation rate, pressure, and produced yields. The results obtained with the proposed medium-sized network compare fairly well, to a few percent, with those computed with in scenarios reproducing the gross physical conditions of current Type Ia supernova explosion models. In those cases where the carbon and oxygen fuel ignites at high density, the high-temperature plateau typical of the nuclear statistical equilibrium regime is well defined and stable, allowing large integration time steps. We show that the inclusion of electron captures on free protons substantially improves the estimation of the electron fraction of the mixture. Therefore, the pressure is better determined than in networks where electron captures are excluded, which will ultimately lead to more reliable hydrodynamic models. Explosive combustion of helium at low density, occurring near the surface layer of a white dwarf, is also better described with the proposed network, which gives nuclear energy generation rates much closer to than typical reduced alpha networks. A nuclear network with N=90 species, including electrons, aimed at multidimensional calculations of supernova explosions is described and verified. The proposed network is suitable for the study of Type Ia supernova explosions because it provides better values of pressure and electron abundance than other existing networks with smaller or even a similar size but without including electron capture processes.

NOx Formation Mechanism and Emission Prediction in Turbulent Combustion: A Review

The field of nitric oxide (NOx) production combined with turbulent flow is a complex issue of combustion, especially for the different time scales of reactions and flow in numerical simulations. Around this, a series of approach methods, including the empirical formula approach, the computational fluid dynamics (CFD) approach coupling with an infinite rate chemical reaction, the chemical reaction networks (CRNs), and the CFD approach coupling with CRNs, were classified, and we discussed its advantages and applicability. The empirical-formula approach can provide an average range of NOx concentration, and this method can be involved only in special scenarios. However, its simplicity and feasibility still promote practical use, and it is still widely applied in engineering. Moreover, with the help of artificial intelligence, this method was improved in regard to its accuracy. The CFD approach could describe the flow field comprehensively. In compliance with considering NOx formation as finite-rate chemical reactions, the NOx concentration distribution via simulation cannot match well with experimental results due to the restriction caused by the simplification of the combustion reaction. Considering NOx formation as a finite-rate chemical reaction, the CRNs approach was involved in CFD simulation, and the CRNs approach could forecast the NOx concentration distribution in the flow field. This article mainly focuses on the simulation method of nitric oxide (NOx) production in different combustion conditions. This review could help readers understand the details of the NOx formation mechanism and NOx formation prediction approach.

Contrast and Complexity in the Low-Temperature Kinetics of CN(v = 1) with O2 and NO: Simultaneous Kinetics and Ringdown in a Uniform Supersonic Flow.

Bimolecular rate coefficients were determined for the reaction CN(v = 1) + NO and O2 using continuous wave cavity ringdown spectroscopy in a uniform supersonic flow (UF-CRDS). The well-matched time scales for ringdown and reaction under pseudo-first-order conditions allow for the use of the SKaR method (simultaneous kinetics and ringdown) in which the full kinetic trace is obtained on each ringdown. The reactions offer an interesting contrast in that the CN(v = 1) + NO system is nonreactive and proceeds by complex-mediated vibrational relaxation, while the CN(v = 1) + O2 reaction is primarily reactive. The measured rate coefficients at 70 K are (2.49 ± 0.08) × 10-11 and (10.49 ± 0.22) × 10-11 cm3 molecule-1 s-1 for the reaction with O2 and NO, respectively. The rate for reaction with O2 is a factor 2 lower than previously reported for v = 0 in the same temperature range, a surprising result, while that for NO is consistent with extrapolation of previous high-temperature measurements to 70 K. The latter is also discussed in light of theoretical calculations and measurements of the rate constants for the association reaction in the high-pressure limit. The measurements are complicated by the presence of a metastable population of high-J CN formed by photolysis of the precursor BrCN, and a kinetic model is developed to treat the competing relaxation and reaction. It is particularly problematic for reactions at low temperatures where the rotational relaxation and reaction have similar rates, precluding a reliable determination of the rate coefficients at 30 K. Also presented are important modifications to the data acquisition and control for the instrument that have yielded considerably enhanced stability and throughput.

Numerical Investigation of the Operating Characteristics of the Passive and Active Prechamber Jet Ignition in a Natural Gas Engine.

Prechamber jet ignition is a promising technology that enables stable ignition and fast combustion by combining thermal effects, chemical kinetics, and turbulent disturbance. The development and application of the prechamber ignition require a comprehensive and in-depth understanding of the operating characteristics of the prechamber ignition in the real engine working cycle. Therefore, numerical simulations are conducted to explore the operating performance of the prechamber ignition applied to a large-bore natural gas engine in this study. The differences between the passive prechamber (PPRE) and active prechamber (APRE) near the lean burn limit are compared. The results show that the jet ignition performance of the PPRE is hampered by the high residual gas coefficient and lean mixture in the prechamber under lean burn conditions. The ignition mode of the PPRE is similar to torch ignition, and the combustion process in the main chamber is mainly turbulent flame propagation. The ignition mechanism of the APRE is flame jet ignition. The main chamber combustion process presents a two-stage heat release characteristic, which can be subdivided into three phases: the initial flame development phase, the rapid combustion phase, and the late combustion phase. The heat release rate during the initial flame development phase depends on the physical and chemical properties of the prechamber jet and the mixture conditions in the main chamber. During the rapid combustion phase, the flame propagation along the radial direction of the jet largely depends on the time scale of the chemical reaction. The heat release rate depends on the coverage area of the jet, the jet residual momentum, and the turbulent flame speed. During the late combustion phase, the flame propagation is mainly affected by the turbulent flame speed. These results provide theoretical guidance for the subsequent application of prechamber ignition systems in various powertrains.

Limitations to extracellular concentration sensing through signaling cascades

Signaling cascades refer to sequential biochemical reactions that occur in the cytoplasm of living cells in response to the binding of a ligand to a cell surface receptor, triggering a cellular response. Living cells need to sense extracellular concentrations with high precision. In this paper, we study the limitations of extracellular concentration measurement in linear signaling cascades. We find that as long as the cascade is linear and measurement times are much larger or much smaller than the timescales of the cytoplasmic reactions, the error in concentration measurement is independent of cascade length, the nature of the reactions and their rates. Our results can also be extended to generic non-linear signal cascades when the measurement time is much smaller than the timescales of cytoplasmic reactions. We illustrate this by considering the specific example of the accuracy of concentration detection in E. coli.

Good Rates From Bad Coordinates: The Exponential Average Time-dependent Rate Approach.

Our ability to calculate rate constants of biochemical processes using molecular dynamics simulations is severely limited by the fact that the time scales for reactions, or changes in conformational state, scale exponentially with the relevant free-energy barrier heights. In this work, we improve upon a recently proposed rate estimator that allows us to predict transition times with molecular dynamics simulations biased to rapidly explore one or several collective variables (CVs). This approach relies on the idea that not all bias goes into promoting transitions, and along with the rate, it estimates a concomitant scale factor for the bias termed the "CV biasing efficiency" γ. First, we demonstrate mathematically that our new formulation allows us to derive the commonly used Infrequent Metadynamics (iMetaD) estimator when using a perfect CV, where γ = 1. After testing it on a model potential, we then study the unfolding behavior of a previously well characterized coarse-grained protein, which is sufficiently complex that we can choose many different CVs to bias, but which is sufficiently simple that we are able to compute the unbiased rate directly. For this system, we demonstrate that predictions from our new Exponential Average Time-Dependent Rate (EATR) estimator converge to the true rate constant more rapidly as a function of bias deposition time than does the previous iMetaD approach, even for bias deposition times that are short. We also show that the γ parameter can serve as a good metric for assessing the quality of the biasing coordinate. We demonstrate that these results hold when applying the methods to an atomistic protein folding example. Finally, we demonstrate that our approach works when combining multiple less-than-optimal bias coordinates, and adapt our method to the related "OPES flooding" approach. Overall, our time-dependent rate approach offers a powerful framework for predicting rate constants from biased simulations.

Diffusive Leakage of scCO2 in Shaly Caprocks: Effect of Geochemical Reactivity and Anisotropy

Summary Supercritical carbon dioxide (scCO2) trapping mechanisms within carbon geostorage (CGS) primarily hinge on the upper caprock system, with shales being favored for their fine-grained nature and geological abundance. Experimental assessments of CO2 reactivity in brine-saturated shales reveal microstructural changes, raising concerns about long-term CO2 leakage risks. Existing models of scCO2 transport through caprocks lack consideration for shale anisotropy. This study addresses these gaps by investigating the diffusive properties and propagation of geochemical reactivity in shaly caprocks, accounting for anisotropy. Horizontal and vertical core samples from three shale formations with varying petrophysical characteristics underwent mineralogical, total organic carbon (TOC), porosity, and velocity measurements. scCO2 treatment for up to 3 weeks at 150°F and 3,000 psi was conducted. The propagation of geochemical reactivity was monitored by multiple surface X-ray fluorescence (XRF) measurements and fine polishing. A nuclear magnetic resonance (NMR)-based H2O-D2O fluid exchange protocol was used to quantify effective diffusivities and tortuosities parallel and perpendicular to bedding. Results indicate preferential surface reactivity toward carbonate minerals; however, the apparent reaction diffusivity of the shaly caprock is notably slow (~10−15 m2/s). This aligns with previous experimental and reactive transport modeling studies, emphasizing long timescales for carbonate dissolution reactions to influence shale caprock properties. Shale-effective diffusivities display anisotropy increasing with clay content, where diffusivities parallel to bedding exceed those perpendicular by at least three times. Faster horizontal diffusion in shaly confining zones should be considered when estimating diffusive leakage along faults penetrating these zones, a significant risk in CGS. Post-scCO2 treatment, diffusivity changes vary among samples, increasing within the same order of magnitude in the clay-rich sample. Nonsteady-state modeling of scCO2 diffusion suggests limited caprock penetration over 100 years, with a minimal increase from 5 m to 7 m post-scCO2 treatment for the clay-rich sample. This study extends existing literature observations on the slow molecular diffusion of scCO2 within shaly caprocks, integrating the roles of geochemical reactions and shale anisotropy under the examined conditions.

Nonthermal plasma removal of CH4-NOx under LNG engine exhaust environment: experiment, mechanism and kinetic analysis

To explore the mechanism underlying the removal of CH4 and NOx, which are typical emissions from LNG engines, through the nonthermal plasma method, a plasma chemistry model of CH4-NOx under the LNG engine exhaust environment was established in this study. Sixty key reactions affecting the conversion of CH4, CO, and NOx were determined through sensitivity analysis, and their pre-exponential factors were optimized using a genetic algorithm. The proposed model shows good performance in predicting the concentrations of CH4, CO, and NOx under the exhaust conditions of LNG engine. Then, reaction path analyses for evolution of CH4, CO, NO, and NO2 were performed under specific conditions. The results showed that CH4 mainly decomposed into CH2 that is subsequently converted into CO and CO2. CH2 is the main source for CO production. The concentration of NOx is determined by the oxidation reactions of N with O2, OH, and HO2. The specific concentration distributions of NO and NO2 were influenced by the oxidation–reduction reactions between them. Analyses of the time scales for the conversion processes of CH4, CO, and NOx were also conducted, and it was found that the reaction time scales of CH4 and CO were approximately 1 × 10−10−1 × 10−5 s, and that was approximately 1 × 10−9−1 × 10−4 s for NOx. Furthermore, during the overlapping period for the conversion of CH4, CO, and NOx, the NOx was dominant in the competition for O. This study provides a basis for the construction of a plasma catalytic chemistry model of CH4-NOx under LNG engine exhaust conditions.

Ecological regulation of chemical weathering recorded in rivers

We provide a new generalized framework accounting for the effects of water and nutrient uptake by roots in the weathering zone on broad patterns of solute concentration - discharge relationships in rivers. As plants withdraw water from the subsurface, they decrease the area-normalized fluid drainage rate. This results in a discharge flux to springs and streams which is a function of water use by plants, leading to ecosystem regulation of the characteristic timescales of chemical weathering reactions and fluid flow rate. Our predictive framework quantifies the pore water and river solute chemistry generated from water-rock interactions, regulated by the effects of vegetation on water flow rates. To this we add the capacity for vegetation to enrich, passively admit, or discriminate against a given dissolved solute based on ecophysiological needs, thus further modifying the local concentration of a given chemical species in solution across a weathering profile. This uptake flux is not lost to the atmosphere in the same manner as water is removed from the subsurface via evapotranspiration. Rather, these extracted chemical species become incorporated into the topsoil as litter which may be partially or fully resolubilized, creating an upper boundary condition which depends on the uptake and recycling characteristics of the ecosystem. These processes are united through a new solution to the advection-reaction equation which allows vegetation to regulate broad patterns of stream concentration - discharge relationships. We show that ecosystems are capable of both accelerating and impeding water-rock reaction rates across the weathering profile, ultimately leading to both thermodynamic and ecological controls on the baseflow concentration of rock-derived solutes in rivers.

An encompassed representation of timescale hierarchies in first-order reaction network

Complex networks are pervasive in various fields such as chemistry, biology, and sociology. In chemistry, first-order reaction networks are represented by a set of first-order differential equations, which can be constructed from the underlying energy landscape. However, as the number of nodes increases, it becomes more challenging to understand complex kinetics across different timescales. Hence, how to construct an interpretable, coarse-graining scheme that preserves the underlying timescales of overall reactions is of crucial importance. Here, we develop a scheme to capture the underlying hierarchical subsets of nodes, and a series of coarse-grained (reduced-dimensional) rate equations between the subsets as a function of time resolution from the original reaction network. Each of the coarse-grained representations guarantees to preserve the underlying slow characteristic timescales in the original network. The crux is the construction of a lumping scheme incorporating a similarity measure in deciphering the underlying timescale hierarchy, which does not rely on the assumption of equilibrium. As an illustrative example, we apply the scheme to four-state Markovian models and Claisen rearrangement of allyl vinyl ether (AVE), and demonstrate that the reduced-dimensional representation accurately reproduces not only the slowest but also the faster timescales of overall reactions although other reduction schemes based on equilibrium assumption well reproduce the slowest timescale but fail to reproduce the second-to-fourth slowest timescales with the same accuracy. Our scheme can be applied not only to the reaction networks but also to networks in other fields, which helps us encompass their hierarchical structures of the complex kinetics over timescales.