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The pivotal role of nuclear physics in nucleosynthesis processes is being investigated, in particular the intricate influence of photon strength functions (PSFs) and nuclear level densities (NLDs) on shaping the outcomes of the i-, r- and p-processes. Exploring diverse NLD and PSF model combinations uncovers large uncertainties for (p,[Formula: see text]), (n,[Formula: see text]) and ([Formula: see text],[Formula: see text]) rates across many regions of the nuclear chart. These lead to potentially significant abundance variations of the nucleosynthesis processes and highlight the importance of accurate experimental nuclear data. Theoretical insights and advanced experimental techniques lay the ground work for profound understanding that can be gained of nucleosynthesis mechanisms and the origin of the elements. Recent results further underscore the effect of PSF and NLD data and its contribution to understanding abundance distributions and refining knowledge of the intricate nucleosynthesis processes. This article is part of the theme issue 'The liminal position of Nuclear Physics: from hadrons to neutron stars'.

Large diurnal temperature changes (ΔT) (or the diurnal temperature range (DTR)) in surface soils, ranging from 5°C to often greater than 20°C, are generally acknowledged to occur yet largely disregarded in studies that seek to understand how temperature affects microbially-mediated carbon and nitrogen cycling processes. The soil DTR is globally significant at depths of 30 cm or less, occurring from spring through summer in temperate biomes, during summer periods in the arctic, and year-round in the tropics. Thus, although temperature has long been considered an important factor in controlling microbial processes, our understanding of its effects remains incomplete when considering natural soil temperature cycles. Here we show: (1) documented impacts of diurnal temperature changes on microbial respiration rates; (2) documented observations of surface soils with large DTR (>5°C) that affect soil microbial mineralization rates and redox potentials of important biogeochemical reactions; and (3) direct evidence that the constant temperature regime typically used in laboratory soil incubation studies may therefore lead to mischaracterization of in situ temperature controls on microbially influenced processes in the environment. The overall effect is that the DTR yields process rates that are often higher than what has been observed under experimental mean temperature incubation. We suggest that overlooked genetic mechanisms, such as the presence of a circadian clock or thermophilic activity during summer months, are likely contributing to the observed effects of the DTR. To improve our understanding of climate change effects on soil greenhouse gas emissions, nutrient cycling, and other biogeochemical soil processes, we propose a paradigm shift in approach to temperature-inclusive process modeling and laboratory incubation studies that accounts for the important role of natural diurnal temperature fluctuations. [ABSTRACT FROM AUTHOR]

A combustion air stream is introduced tangentially into the interior of a premix burner by means of a swirl producer, and is mixed with fuel. At the burner outlet, the vortex flow which arises bursts open at a sudden change of cross section, with the initiation of a back-flow zone which serves to stabilize a flame in the operation of the burner. Although premix burners make possible an operation with very low pollutant emissions, they often operate dangerously near to the extinction limit of the flame. Cavity structures have been designed for the purpose of improving flame stability. However, the precise mechanism by which the cavity method provides increased flame stability remains unclear. This study relates to the combustion characteristics and flame stability of a micro-structured cavity-stabilized burner. Computational fluid dynamics simulations are conducted to gain insights into burner performance such as reaction rates, species concentrations, temperatures, and flames. Factors affecting combustion characteristics and flame stability are determined. Design recommendations are provided. The results indicate that the thermal conductivity of the burner walls plays a vital role in flame stability. Improvements in flame stability are achievable by using walls with anisotropic thermal conductivity. Heat-insulating materials are favored to minimize external heat losses. Burner dimensions greatly affect flame stability. The inlet velocity of the mixture is a critical factor in assuring flame stability within the cavity-stabilized burner. There is a narrow range of inlet velocities that permit sustained combustion within the cavity-stabilized burner. There are issues of efficiency loss for fuel-rich cases. Burners with large dimensions lead to a delay in flame ignition and may cause blowout. The combustion is stabilized by recirculation of hot combustion products induced by the cavity structure.

A thorough understanding of nuclear reaction rates at low energies is essential for improving our understanding of energy generation in stars and primordial and stellar nucleosynthesis. At low energies, fusion reactions between charged particles are strongly suppressed by the presence of the Coulomb barrier, which classically inhibits the penetration of one nucleus into another. The barrier penetration causes the cross section to have a steep energy dependence at low energies, making cross section measurements very challenging. Furthermore, little is known about the impact of surrounding electrons in stellar plasmas that are currently beyond the reach of experiments. As a result, measuring the bare cross sections as accurately as possible is essential. Reaction rate measurements at very low energies have been made possible in recent years by the development of high-current low-energy accelerators as well as enhanced target and detection methods. Nevertheless, the presence of atomic electrons, which alter the Coulomb barrier by screening the nuclear charge and increase the cross section at low energies compared to the case of bare nuclei, complicates these observations. A review of the experimental and corresponding theoretical work on laboratory electron screening performed so far will be presented.

A thorough understanding of nuclear reaction rates at low energies is essential for improving our understanding of energy generation in stars and primordial and stellar nucleosynthesis. At low energies, fusion reactions between charged particles are strongly suppressed by the presence of the Coulomb barrier, which classically inhibits the penetration of one nucleus into another. The barrier penetration causes the cross section to have a steep energy dependence at low energies, making cross section measurements very challenging. Furthermore, little is known about the impact of surrounding electrons in stellar plasmas that are currently beyond the reach of experiments. As a result, measuring the bare cross sections as accurately as possible is essential. Reaction rate measurements at very low energies have been made possible in recent years by the development of high-current low-energy accelerators as well as enhanced target and detection methods. Nevertheless, the presence of atomic electrons, which alter the Coulomb barrier by screening the nuclear charge and increase the cross section at low energies compared to the case of bare nuclei, complicates these observations. A review of the experimental and corresponding theoretical work on laboratory electron screening performed so far will be presented. [ABSTRACT FROM AUTHOR]

This paper explores the temperature-dependent kinetics of organic reactions in aqueous solutions, focusing on how temperature variations influence reaction rates, activation energies, and mechanisms. By analyzing various studies and experiments, this paper elucidates the fundamental principles governing temperature effects on reaction kinetics, discusses the Arrhenius equation's role, and provides insights into practical implications and applications in industrial and environmental contexts. [ABSTRACT FROM AUTHOR]

Large diurnal temperature changes (ΔT) (or the diurnal temperature range (DTR)) in surface soils, ranging from 5°C to often greater than 20°C, are generally acknowledged to occur yet largely disregarded in studies that seek to understand how temperature affects microbially-mediated carbon and nitrogen cycling processes. The soil DTR is globally significant at depths of 30 cm or less, occurring from spring through summer in temperate biomes, during summer periods in the arctic, and year-round in the tropics. Thus, although temperature has long been considered an important factor in controlling microbial processes, our understanding of its effects remains incomplete when considering natural soil temperature cycles. Here we show: (1) documented impacts of diurnal temperature changes on microbial respiration rates; (2) documented observations of surface soils with large DTR (>5°C) that affect soil microbial mineralization rates and redox potentials of important biogeochemical reactions; and (3) direct evidence that the constant temperature regime typically used in laboratory soil incubation studies may therefore lead to mischaracterization of in situ temperature controls on microbially influenced processes in the environment. The overall effect is that the DTR yields process rates that are often higher than what has been observed under experimental mean temperature incubation. We suggest that overlooked genetic mechanisms, such as the presence of a circadian clock or thermophilic activity during summer months, are likely contributing to the observed effects of the DTR. To improve our understanding of climate change effects on soil greenhouse gas emissions, nutrient cycling, and other biogeochemical soil processes, we propose a paradigm shift in approach to temperature-inclusive process modeling and laboratory incubation studies that accounts for the important role of natural diurnal temperature fluctuations.

In this study, machine learning (ML) algorithms were employed to predict the pseudo-1st-order reaction rate constants for the sonochemical degradation of aqueous organic pollutants under various conditions. A total of 618 sets of data, including ultrasonic, solution, and pollutant characteristics, were collected from 89 previous studies. Considering the difference between the electrical power (Pele) and calorimetric power (Pcal), the collected data were divided into two groups: data with Pele and data with Pcal. Eight input variables, including frequency, power density, pH, temperature, initial concentration, solubility, vapor pressure, and octanol–water partition coefficient (Kow), and one target variable of the degradation rate constant, were selected for ML. Statistical analysis was conducted, and outliers were determined separately for the two groups. ML models, including random forest (RF), extreme gradient boosting (XGB), and light gradient boosting machine (LGB), were used to predict the pseudo-1st-order reaction rate constants for the removal of aqueous pollutants. The prediction performance of the ML models was evaluated using different metrics, including the root mean squared error (RMSE), mean absolute error (MAE), and R squared (R2). A significantly higher prediction performance was obtained using data without outliers and augmented data. Consequently, all the applied ML models could be used to predict the sonochemical degradation of aqueous pollutants, and the XGB model showed the highest accuracy in predicting the rate constants. In addition, the power density and frequency were the most influential factors among the eight input variables in prediction with the Shapley additive explanation (SHAP) values method. The degradation rate constants of the two pollutants over a wide frequency range (20–1,000 kHz) were predicted using the trained ML model (XGB) and the prediction results were analyzed.

The social restrictions that were implemented due to the COVID-19 pandemic had a profound impact on the field of education. There was an adaptation of changes from conventional to distance learning processes. This study aimed to develop a Chemistry Electronic Module (e-Module) based on the POE (Predict, Observe, Explain) approach to the study material of Reaction Rates for 11th grade science students. This module used videos as a stimulus for the student's learning process in three learning stages: predict, observe, and explain. This Research and Development research inspired by Borg and Gall used descriptive methods for analysis. The instrument used for this study was a questionnaire. The results from the validation test by three material and language experts, as well as media experts, showed that this e-module was classified as well to be very good for a percentage range of 80-90%. The results of the e-module feasibility test for seven high school chemistry teachers, 18 high-school students of class XI IPA, and 40 undergraduate students of Chemistry Education at the State University of Jakarta on the aspects of the developed electronic module were obtained with scores ranging from well to excellent with a percentage range of 81-94%. It can be concluded that the developed electronic module is suitable for use as independent teaching material for students on the material of reaction rates. [ABSTRACT FROM AUTHOR]

The measurement of the 7Be(d,3He)6Li* transfer cross section at 5 MeV/u is carried out. The population of the 2.186 MeV excited state of 6Li in this reaction channel is observed for the first time. The experimental angular distributions have been analyzed in the finite range DWBA and coupled-channel frameworks. The effect of the 7Be(d,3He)6Li reaction on both the 6Li and 7Li abundances are investigated at the relevant big-bang nucleosynthesis energies. The excitation function is calculated by TALYS and normalized to the experimental data. The S factor of the (d,3He) channel from the present work is about 50% lower than existing data at nearby energies. At big-bang energies, the S factor is about three orders of magnitude smaller than that of the (d,p) channel. The (d,3He) reaction rate is found to have a less than 0.1% effect on the 6,7Li abundances.

The reactivity of interstellar carbon atoms (C) on water-dominated ices is one of the possible ways to form interstellar complex organic molecules (iCOMs). In this work, we report a quantum chemical study of the coupling reaction of C (3P) with an icy water molecule, alongside possible subsequent reactions with the most abundant closed-shell frozen species (NH3, CO, CO2, and H2), atoms (H, N, and O), and molecular radicals (OH, NH2, and CH3). We found that C reacts spontaneously with the water molecule, resulting in the formation of 3C–OH2, a highly reactive species due to its triplet electronic state. While reactions with the closed-shell species do not show any reactivity, reactions with N and O form CN and CO, respectively, the latter ending up in methanol upon subsequent hydrogenation. The reactions with OH, CH3, and NH2 form methanediol, ethanol, and methanimine, respectively, upon subsequent hydrogenation. We also propose an explanation for methane formation observed in experiments through additions of H to C in the presence of ices. The astrochemical implications of this work are: (i) atomic C on water ice is locked into 3C–OH2, making difficult the reactivity of bare C atoms on icy surfaces, contrary to what is assumed in current astrochemical models; and (ii) the extraordinary reactivity of 3C–OH2 provides new routes toward the formation of iCOMs in a nonenergetic way, in particular ethanol, the mother of other iCOMs once it is in the gas phase. [ABSTRACT FROM AUTHOR]

Presolar grains are stardust particles that condensed in the ejecta or in the outflows of dying stars and can today be extracted from meteorites. They recorded the nucleosynthetic fingerprint of their parent stars and thus serve as valuable probes of these astrophysical sites. The most common types of presolar silicon carbide grains (called mainstream SiC grains) condensed in the outflows of asymptotic giant branch stars. Their measured silicon isotopic abundances are not significantly influenced by nucleosynthesis within the parent star but rather represent the pristine stellar composition. Silicon isotopes can thus be used as a proxy for galactic chemical evolution (GCE). However, the measured correlation of ^29 Si/ ^28 Si versus ^30 Si/ ^28 Si does not agree with any current chemical evolution model. Here, we use a Monte Carlo model to vary nuclear reaction rates within their theoretical or experimental uncertainties and process them through stellar nucleosynthesis and GCE models to study the variation of silicon isotope abundances based on these nuclear reaction rate uncertainties. We find that these uncertainties can indeed be responsible for the discrepancy between measurements and models and that the slope of the silicon isotope correlation line measured in mainstream SiC grains agrees with chemical evolution models within the nuclear reaction rate uncertainties. Our result highlights the importance of future precision reaction rate measurements for resolving the apparent data–model discrepancy.

Reactions between cyano radicals and aromatic hydrocarbons are believed to be important pathways for the formation of aromatic nitriles in the interstellar medium (ISM) including those identified in the Taurus molecular cloud (TMC-1). Aromatic nitriles might participate in the formation of polycyclic aromatic nitrogen-containing hydrocarbons (PANHs) in Titan's atmosphere. Here, ab initio kinetic simulations reveal a high efficiency of ∼10−10 cm3 s−1 and the competition of the different products of the CN + toluene reaction at 30–1800 K and 10−7–100 atm. In the star-forming region of the TMC-1 environment, the product yields of benzonitrile and tolunitriles for CN reacting with toluene are approximately 17% and 83%, respectively. Detections of the main products, tolunitriles, can serve as proxies for the undetected toluene in the ISM due to their much larger dipole moments. Competition between bimolecular and unimolecular products is extremely intense in the warmer and denser PANH-forming region of Titan's stratosphere. Computational results show that the fractions of tolunitriles, adducts, and benzonitrile are 19%–68%, 15%–64%, and 17%, respectively, at 150–200 K and 0.0001–0.001 atm (Titan's stratosphere). Then, benzonitrile and tolunitriles may contribute to the formation of PANHs by consecutive C2H additions. The kinetic information of aromatic nitriles for the CN + toluene reaction calculated here helps to explain the formation mechanism of polycyclic aromatic hydrocarbons or PANHs under different interstellar environments and constrains corresponding astrochemical models. [ABSTRACT FROM AUTHOR]

In this paper, a coupled model of coating modification placed on a substrate is proposed. The model takes into account the different channels of stress effect on the evolution of coating and transition zone composition. The coupled model of coated material modification by pulsed electron beam is formulated for the first time, with particular attention paid to the mutual influence of stresses arising from composition changes and diffusion transport. Examples of calculations for the Ta-TiN system are presented which demonstrate both qualitative and quantitative differences between coupled and uncoupled problems. [ABSTRACT FROM AUTHOR]

Thermonuclear reaction rates are calculated for three oxygen isotopes 14,15,16O in CNO cycles reactions occurring in red giant stars. These reactions are: F19 (p, α)16O, N 15 (p, γ)16O, N 14 (p, γ)15O, F 18 (p, α)15O, N 13 (p, γ)14O, O 15 (α, γ)19Ne and O 16 (p, γ)17F. Reaction rates have been calculated using MATLAB codes, and related comparisons were made with NACRE II and Reaclib libraries, and the ratios of production to the destruction of 15,16O isotopes were found. Present reaction rate results were close to most of the selected reactions, and in some cases larger with a factor of 1-3. 15,16O production to destruction ratios indicated a special tendency to saturate at temperatures higher than ~ 2 GK, and these ratios were in general larger than 1 indicating an excess of producing such isotopes in red giant stars. [ABSTRACT FROM AUTHOR]

In this work, a reliable kinetic reaction mechanism was revised to accurately reproduce the detailed reaction paths of steam reforming of methane over a Ni/Al 2 O 3 catalyst. A steady-state fixed-bed reactor experiment and a 1D reactor catalyst model were utilized for this task. The distinctive feature of this experiment is the possibility to measure the axially resolved temperature profile of the catalyst bed, which makes the reaction kinetics inside the reactor visible. This allows for understanding the actual influence of the reaction kinetics on the system; while pure gas concentration measurements at the catalytic reactor outlet show near-equilibrium conditions, the inhere presented temperature profile shows that it is insufficient to base a reaction mechanism development on close equilibrium data. The new experimental data allow for achieving much higher quality in the modeling efforts. Additionally, by carefully controlling the available active surface via dilution in the experiment, it was possible to slow down the catalyst conversion rate, which helped during the adjustment of the reaction kinetics. To assess the accuracy of the revised mechanism, a monolith experiment from the literature was simulated. The results show that the fitted reaction mechanism was able to accurately predict the experimental outcomes for various inlet mass flows, temperatures, and steam-to-carbon ratios. [ABSTRACT FROM AUTHOR]

We describe pynucastro 2.0, an open-source library for interactively creating and exploring astrophysical nuclear reaction networks. We demonstrate new methods for approximating rates and use detailed balance to create reverse rates, show how to build networks and determine whether they are appropriate for a particular science application, and discuss the changes made to the library over the past few years. Finally, we demonstrate the validity of the networks produced and share how we use pynucastro networks in simulation codes. [ABSTRACT FROM AUTHOR]

The present contribution deals with the simultaneous estimation of the reaction rates and input disturbances in a bioprocess. Online estimation of just the reaction rates is possible by sliding mode observer techniques or high-gain observers, in finite-time or with exponential convergence, respectively. However, these techniques are not robust against unpredictable input bioreactor disturbances and are not readily adaptable to treat external disturbances. Motivated by these facts, we propose a novel extended super-twisting algorithm for a class of nonlinear systems, such that the estimation of uncertain parameters, unknown internal dynamics, and external disturbances converge in a finite time or a neighborhood near its nominal values. The effectiveness of the developed algorithm is tested through simulations in an anaerobic digestion process using a batch and a continuous bioreactor. Simulation results show good robustness performance of the extended super-twisting algorithm. • An extended super-twisting observer-based estimator is proposed. • The stability of the proposed algorithm is proved within Lyapunov's formalism. • Bioprocess reaction rates and input disturbance can be estimated simultaneously. [ABSTRACT FROM AUTHOR]

In this paper, we test the ability of a recently proposed effective frequency theory, viz. the generalised Feynman–Kleinert effective frequency theory (GFK), for calculating the Wigner transform of the thermalised flux operator needed in reaction rate computations based on the classical Wigner model. We consider one-dimensional symmetric and asymmetric barriers at both high and low temperatures. The reaction rates obtained from the GFK theory are found to be close to the results obtained using the accurate Wigner function. The reaction rates obtained from the classical Wigner model are approximate since they are based on classical trajectories. We therefore also present a new version of the so-called effective quantum force method, that improves the classical Wigner rates. This new implementation utilises as input matrix elements of the thermalised flux operator obtained from the GFK theory. We find a significant improvement compared to the classical Wigner reaction rates. Possible extensions to multi-dimensional systems are discussed. [ABSTRACT FROM AUTHOR]

Until about a decade or so, till the fast-paced development and usage of computers, organic chemistry students often chose experimental projects during an internship. Presently, there are software packages that solve quantum chemical equations and present the possibility of a 'black-box' type of approach to getting exposed to computational organic chemistry. Encouraging as this may seem, Indian university students can find the entry to and an understanding of computational chemistry daunting due to a lack of exposure to research. This article attempts to bridge the gap for such students by providing a gentle introduction to the field of quantum chemistry. [ABSTRACT FROM AUTHOR]

In this work, we are presenting a new database of astrophysical interest, based on calculations performed with the nuclear reaction code TALYS. Four quantities are systematically calculated for over 8000 nuclides: cross sections, reaction rates, Maxwellian Averaged Cross Sections (or MACS) at 30 keV and partition functions. For cross sections and reaction rates, nine reactions are considered, induced by neutron, proton or alpha. The main complement of this database compared to existing ones is that the impact of reaction models (e.g. level density, gamma strength function, and optical model) is estimated by varying 9 different models, and by proposing calculated values for each of them, together with averages, standard deviations and other statistical quantities. This new database, called TENDL-astro, version 2023, is available online (https://tendl.web.psi.ch/tendl%5f2023/astro/astro.html) and linked to the well-known TENDL database, used in a variety of applications. [ABSTRACT FROM AUTHOR]

In this study, machine learning (ML) algorithms were employed to predict the pseudo-1st-order reaction rate constants for the sonochemical degradation of aqueous organic pollutants under various conditions. A total of 618 sets of data, including ultrasonic, solution, and pollutant characteristics, were collected from 89 previous studies. Considering the difference between the electrical power (P ele) and calorimetric power (P cal), the collected data were divided into two groups: data with P ele and data with P cal. Eight input variables, including frequency, power density, pH, temperature, initial concentration, solubility, vapor pressure, and octanol–water partition coefficient (K ow), and one target variable of the degradation rate constant, were selected for ML. Statistical analysis was conducted, and outliers were determined separately for the two groups. ML models, including random forest (RF), extreme gradient boosting (XGB), and light gradient boosting machine (LGB), were used to predict the pseudo-1st-order reaction rate constants for the removal of aqueous pollutants. The prediction performance of the ML models was evaluated using different metrics, including the root mean squared error (RMSE), mean absolute error (MAE), and R squared (R2). A significantly higher prediction performance was obtained using data without outliers and augmented data. Consequently, all the applied ML models could be used to predict the sonochemical degradation of aqueous pollutants, and the XGB model showed the highest accuracy in predicting the rate constants. In addition, the power density and frequency were the most influential factors among the eight input variables in prediction with the Shapley additive explanation (SHAP) values method. The degradation rate constants of the two pollutants over a wide frequency range (20–1,000 kHz) were predicted using the trained ML model (XGB) and the prediction results were analyzed. [ABSTRACT FROM AUTHOR]

We build on the simplified spectral deferred corrections (SDC) coupling of hydrodynamics and reactions to handle the case of nuclear statistical equilibrium (NSE) and electron/positron captures/decays in the cores of massive stars. Our approach blends a traditional reaction network on the grid with a tabulated NSE state from a very large, ${ \mathcal O }(100)$ nuclei network. We demonstrate how to achieve second-order accuracy in the simplified-SDC framework when coupling NSE to hydrodynamics, with the ability to evolve the star on the hydrodynamics time step. We discuss the application of this method to convection in massive stars leading up to core collapse. We also show how to initialize the initial convective state from a 1D model in a self-consistent fashion. All of these developments are done in the publicly available Castro simulation code and the entire simulation methodology is fully GPU-accelerated.

The ^18 O( p , α ) ^15 N reaction is of particular importance for influencing the abundances of key isotopes such as ^19 F, ^18 O, and ^15 N. Peculiar abundances for these nuclei are observed from spectra or meteorite grains originating in asymptotic giant branch stars. The ^18 O( p , α ) ^15 N could provide a way to explain the discrepancy between the observations and model predictions. A comprehensive R -matrix analysis has been performed for the ^18 O( p , α ) ^15 N reaction by including additional constraints from other reaction channels; in particular, the ^15 N+ α scattering data were involved in the analysis for the first time. All available data were compiled and used in the R -matrix analysis. The fitted resonance parameters are compared with previous works. A revised determination of reaction rate has been extracted, relying on the present fitting parameters. The uncertainties on the corresponding reaction rates were then obtained by a Monte Carlo analysis.

Measurements of concentrations of neutral and ion species in the upper atmosphere of Mars by the Neutral Gas and Ion Mass Spectrometer (NGIMS) on board the Mars Atmosphere and Volatile EvolutioN mission have served as model input and/or for comparison with model output in numerous earlier studies of the Martian dayside ionosphere. While many models reproduce the altitudinal density profiles of key ion species within a factor of a few, it has proven challenging to achieve a level of agreement within tens of percent for multiple ion species over a wide range of altitudes. We explore means to overcome this issue while keeping with a reduced chemical model and utilizing the assumptions of photochemical equilibrium and that the NGIMS data are devoid of any measurement errors. We entertain, for instance, the idea that the rate coefficient for the charge-transfer reaction between ${{\rm{CO}}}_{2}^{+}$ and O may vary with altitude as a result of a pressure-controlled internal energy distribution of the ${{\rm{CO}}}_{2}^{+}$ population.

The gas-phase reactions of methanimine (CH _2 NH) with small radicals, such as CN, CP, CCH, and OH, have been extensively studied theoretically in the literature, and the presence of a common, general reaction mechanism has been postulated. Since methanimine is considered the main precursor of complex imines in the interstellar medium (ISM), the present study extends the investigation of its reaction with other small radicals that have already been detected in the ISM. These are SiN, SH, NO, NS, HCO, HCS, and C _3 N. The corresponding products are easily formulated on the basis of the aforementioned general mechanism, and to understand whether they can be formed in the ISM, a preliminary thermochemical study has been carried out. The only exothermic addition reaction is that occurring between CH _2 NH and the C _3 N radical. This reaction has been further investigated in order to accurately characterize its reactive potential energy surface, which has then been employed in ab initio transition state theory calculations to derive global rate coefficients. The products of the CH _2 NH + C _3 N reaction are new potential interstellar species, namely, the Z and E isomers of HNCHCCCN and CH _2 NCCCN. For the first time, their structural characterization has been reported. In addition, this work investigates the possibility of H-abstraction processes for each radical species considered, and re-examines the CH _2 NH + CP reaction to derive the corresponding rate constants, that were still missing in the literature.

We present a data-driven point of view for rare events, which represent conformational transitions in biochemical reactions modeled by overdamped Langevin dynamics on manifolds in high dimensions. We first reinterpret the transition state theory and the transition path theory from the optimal control viewpoint. Given a point cloud probing the manifold, we construct a discrete Markov chain with a Q-matrix computed from an approximated Voronoi tesselation via the point cloud. We use this Q-matrix to compute a discrete committor function whose level set automatically orders the point cloud. Then based on the committor function, an optimally controlled random walk on point clouds is constructed and utilized to efficiently sample transition paths, which become an almost sure event in O(1) time instead of a rare event in the original reaction dynamics. To compute the mean transition path efficiently, a local averaging algorithm based on the optimally controlled random walk is developed, which adapts the finite temperature string method to the controlled Monte Carlo samples. Numerical examples on sphere/torus including a conformational transition for the alanine dipeptide in vacuum are conducted to illustrate the data-driven solver for the transition path theory on point clouds. The mean transition path obtained via the controlled Monte Carlo simulations highly coincides with the computed dominant transition path in the transition path theory. [ABSTRACT FROM AUTHOR]

Differential mobility spectrometry (DMS) uses high-frequency oscillating electrical fields to harness the differential mobility of ions for separating complex sample mixtures prior to detection. To increase the resolving power, a dynamic microsolvation environment is often created by introducing solvent vapors. Here, relatively large clusters are formed at low-field conditions which then evaporate to form smaller clusters at high-field conditions. The kinetics of these processes as the electrical field strength oscillates are not well studied. Here, we develop a computational framework to investigate how the different reactions (cluster association, cluster dissociation, and fast conformational changes) behave at different field strengths. We aim to better understand these processes, their effect on experimental outcomes, and whether DMS model accuracy is improved via incorporating their description. We find that cluster association and dissociation reactions for typical ion–solvent pairs are fast compared to the time scale of the varying separation fields usually used. However, low solvent concentration, small dipole moments, and strong ion–solvent binding can result in reaction rates small enough that a lag is observed in the ion's DMS response. This can yield differences of several volts in the compensation voltages required to correct ion trajectories for optimal transmission. We also find that the proposed kinetic approach yields generally better agreement with experiment than using a modified Boltzmann weighting scheme. Thus, this work provides insights into the chemical dynamics occurring within the DMS cell while also increasing the accuracy of dispersion plot predictions. [ABSTRACT FROM AUTHOR]

Large diurnal temperature changes (ΔT) (or the diurnal temperature range (DTR)) in surface soils, ranging from 5°C to often greater than 20°C, are generally acknowledged to occur yet largely disregarded in studies that seek to understand how temperature affects microbially-mediated carbon and nitrogen cycling processes. The soil DTR is globally significant at depths of 30 cm or less, occurring from spring through summer in temperate biomes, during summer periods in the arctic, and year-round in the tropics. Thus, although temperature has long been considered an important factor in controlling microbial processes, our understanding of its effects remains incomplete when considering natural soil temperature cycles. Here we show: (1) documented impacts of diurnal temperature changes on microbial respiration rates; (2) documented observations of surface soils with large DTR (>5°C) that affect soil microbial mineralization rates and redox potentials of important biogeochemical reactions; and (3) direct evidence that the constant temperature regime typically used in laboratory soil incubation studies may therefore lead to mischaracterization of in situ temperature controls on microbially influenced processes in the environment. The overall effect is that the DTR yields process rates that are often higher than what has been observed under experimental mean temperature incubation. We suggest that overlooked genetic mechanisms, such as the presence of a circadian clock or thermophilic activity during summer months, are likely contributing to the observed effects of the DTR. To improve our understanding of climate change effects on soil greenhouse gas emissions, nutrient cycling, and other biogeochemical soil processes, we propose a paradigm shift in approach to temperature-inclusive process modeling and laboratory incubation studies that accounts for the important role of natural diurnal temperature fluctuations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Sanford, Chee-Sanford and Yang.)

Observations of OH ^+ are used to infer the interstellar cosmic ray ionization rate in diffuse atomic clouds, thereby constraining the propagation of cosmic rays through and the shielding by interstellar clouds, as well as the low energy cosmic ray spectrum. In regions where the H _2 -to-H number density ratio is low, dissociative recombination (DR) is the dominant destruction process for OH ^+ and the DR rate coefficient is important for predicting the OH ^+ abundance and inferring the cosmic ray ionization rate. We have experimentally studied DR of electronically and vibrationally relaxed OH ^+ in its lowest rotational levels, using an electron–ion merged-beams setup at the Cryogenic Storage Ring. From these measurements, we have derived a kinetic temperature rate coefficient applicable to diffuse cloud chemical models, i.e., for OH ^+ in its electronic, vibrational, and rotational ground level. At typical diffuse cloud temperatures, our kinetic temperature rate coefficient is a factor of ∼5 times larger than the previous experimentally derived value and a factor of ∼33 times larger than the value calculated by theory. Our combined experimental and modeling results point to a significant increase for the cosmic ray ionization rate inferred from observations of OH ^+ and H _2 O ^+ , corresponding to a geometric mean of (6.6 ± 1.0) × 10 ^−16 s ^−1 , which is more than a factor of 2 larger than the previously inferred values of the cosmic ray ionization rate in diffuse atomic clouds. Combined with observations of diffuse and dense molecular clouds, these findings indicate a greater degree of cosmic ray shielding in interstellar clouds than has been previously inferred.

Optical biosensors provide a platform for qualitatively and quantitatively analyzing various biomolecular interactions. In addition to advantages such as label-free and high-throughput detection, these devices are also capable of measuring real-time binding curves in response to changes in optical properties of biomolecules. These kinetic data may be fitted to models to extract binding affinities such as association rates, dissociation rates, and equilibrium dissociation constants. In these biosensors, one of the binding pair is usually immobilized on a solid substrate for capturing the other. Due to the nature of these surface-based methods, mass transport effects and immobilization heterogenetity may cause problems when fitting the kinetic curves with the simple one-to-one Langmuir model. Here real-time binding curves of various antibody-antigen reactions were obtained by using an ellipsometry-based biosensor, and the results were fitted to the simple one-to-one model as well as a more sophisticated approach. The results show that the one-to-two model fitted much better to the curves than the one-to-one model. The two-site model may be explained by assuming two immobilization configurations on the surface. In summary, in fitting real-time curves obtained from optical biosensors, more sophisticated models are usually required to take surface-related issues, such as immobilization heterogenetity and mass transport effects within targets, into account.

A mathematical model of the process of composite synthesis from a mixture of powders is formulated. It is assumed that the synthesis is performed on a substrate and is controlled by a scanning laser beam. The stress-strain state is described in quasi-static approximation. The model takes into account two phenomena that are neglected in traditional surface treatment and 3D models: the mutual influence of the heat transfer process and deformation and the heat sources and sinks that result from chemical reactions. The formation of the composition is described by a total reaction scheme that includes a strengthening particle formation stage and a matrix formation stage. The nonlinear model is reduced to a dimensionless form and investigated numerically using an implicit difference scheme for the thermal conductivity equation, the semi-implicit Euler method for the kinetic equations, and the iteration procedure for the mechanical equilibrium problem. As a result of the calculations, we have the fields of temperature, concentrations, stresses, and strains at an arbitrary moment of time, as well as the final composition of the composite. It is shown that the coupling of processes of different physical nature is important both for determining the composition of the composite and for estimating the residual stresses and strains. [ABSTRACT FROM AUTHOR]

Formaldehyde has been widely observed in the icy mantle of interstellar grains. H2CO may be formed from successive hydrogenations of CO and may further contribute to the chemical complexity of the Interstellar medium (ISM) participating to heterogeneous reactions with colliding gas phase atoms. Within this context, Eley-Rideal and Langmuir-Hinshelwood rate constants of H2 formation on a formaldehyde doped amorphous water ice grain model of the ISM, were computed over a wide temperature range [15–2000 K]. We used classical molecular dynamics (MD) simulations to build the model of the H2CO doped ice surface. Then we studied theoretically by means of hybrid QM/MM ab initio and molecular mechanics methodology (ONIOM) H atoms abstraction from formaldehyde molecules and the H2 formation. Specifically, we investigate the reactivity of the gas phase H atom toward one formaldehyde molecule lying at one of the slab surfaces. The reaction path and the energetics are predicted, the mechanism is found to be exothermic by 14.89 kcal/mol and the barrier is 6.75 kcal/mol at the QM level CBS/DLPNO-CCSD(T)//ONIOM/aug-cc-pVTZ. We employ two approaches that take into account tunnelling and non-classical reflection effects by means of the Zero Curvature Tunnelling (ZCT), and the Small Curvature Tunnelling (SCT) which all provided comparable results to predict the kinetics of the reaction path. The rate constants show important quantum tunnelling effects at low temperatures when compared to rates obtained from the purely classical transition-state theory (TST) and from the canonical variational transition state theory (CVT). Corner cutting effects are highlighted in the SCT calculations by 4 to 5 orders of magnitude with respect to ZCT rate constants at low temperatures.

The investigation of reaction mechanisms in the interstellar medium requires the evaluation of reaction rates and branching ratios, which can be effectively obtained in the framework of the ab-initio transition state/master equation formalism. However, the reliability of this approach relies on the computation of accurate reaction enthalpies and activation energies for all the paths characterizing the potential energy surface under investigation. Two effective yet reliable parameter-free model chemistries are introduced to obtain accurate energies of all stationary points, with structural determination performed using double-hybrid density functionals. After their validation, these model chemistries have been employed to analyze the competition between hydrogen abstraction and addition/elimination in the reaction between the CN radical and ethylene or methanimine. The energetics has then been complemented by a kinetic study. The results provide new information about important reactive channels operative in different regions of the interstellar medium and in the atmospheres of exoplanets. These further extend the recent general addition/elimination mechanism for the formation of “complex imines” from the reaction of methanimine with a small radical species.

The utilization of titanium dioxide (TiO2) photocatalysis for water and air purification is a frequently used method due to TiO2 having properties making it chemically inert, highly cost-effective, abundant, non-toxic, and environmentally-friendly. In an effort to increase the efficiency of the degradation process, an in-depth understanding of the effects of the structure and number of thin film coatings is needed. Transparent, anatase-form titanium dioxide thin films were prepared via the sol-gel method and deposited onto microscopic glass slides using a novel spraying technique, with coatings ranging from 1 to 10. Characterization of the TiO2 thin film coated slides was performed using X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The contribution shows that the coating technique is efficient in covering important areas of the surface and that it is suitable for a multiple coating layers thin film. The SEM imagines show that the surface of the slides increase coverage as the number of layers increases. This is potentially suitable for a mechanized spraying approach to upscaling the production of thin films for advanced oxidation applications. [ABSTRACT FROM AUTHOR]

Among the large family of emergent pharmaceutical contaminants, we find acetaminophen (ACE) that critically needs to be removed from wastewater. Advanced Oxidation Process (AOP) have proven effective in the degradation of large molecular contaminants from water. To the best of our knowledge this is the first study reported on the degradation of ACE based on immobilized TiO2 thin films. In an effort to increase the understanding of the efficiency of the degradation process, an in-depth investigation of the effects of the structure, i.e., coating layers and the amount of surface, i.e., number of coated slides used, is needed. Transparent, anatase-form TiO2 thin films were prepared via the sol-gel method (Rawal, S., S. Buer, J. R. Sanders, and P. E. Arce. 2021. "Photocatalytic Degradation of Acetaminophen from Water Solutions Via Thin Films. Part I: Synthesis and Characterization of TiO2 Thin Films." International Journal of Reactor Engineering [Accepted]) and deposited onto glass microscope slides using a novel spraying technique, with coatings ranging from one to 10 layers. This contribution summarizes the effect of several key factors including initial concentration of the ACE, the number of coating layers (6, 8, and 10) on the glass slides and the number (4 and 6) of slides on the degradation levels for three selected media, e.g., acid, neutral and base. Comparisons studies, supported by statistical analysis between two different sets (4 and 6) of slides with discussion of potential physical-chemical reasons behind the behaviors are reported. Finally, global, first order kinetic rate constants are also reported for the different conditions used in the investigation. Although further research would be needed, in general the results are promising for the potential degradation of ACE in continuous flow systems by using immobilized TiO2 on surfaces as thin films. [ABSTRACT FROM AUTHOR]

The name of Menshutkin is most frequently associated with his eponymous reaction (the quaternization of tertiary amines with alkyl halides). However, he made encyclopedic contributions to the field of reaction kinetics, where he carried out extensive studies of the effects of reactant structure on the rates of esterification of monohydric, dihydric and trihydric alcohols with monocarboxylic acids, and monobasic and dibasic carboxylic acids and anhydrides with monohydric alcohols. In these studies, he deduced an order of reactivity of alcohols in esterification on the basis of their reactions with acetic acid, and the effects of acid structure on the rates of esterification based on the reaction of the carboxylic acid with isobutyl alcohol. When his attention later turned to the substitution chemistry of amines, he defined the parameters that affected their reactions: anilines were less reactive than alkylamines, secondary more reactive than primary amines, and the reaction was accelerated by replacing benzene as a solvent with alcohols. The wide‐ranging work of Menshutkin, the physical organic chemist, is discussed. [ABSTRACT FROM AUTHOR]

The prediction of the initial reaction rate in the tungsten-catalyzed epoxidation of alkenes by using a machine learning approach is demonstrated. The ensemble learning framework used in this study consists of random sampling with replacement from the training dataset, the construction of several predictive models (weak learners), and the combination of their outputs. This approach enables us to obtain a reasonable prediction model that avoids the problem of overfitting, even when analyzing a small dataset. [ABSTRACT FROM AUTHOR]

Abstract The distribution of rheologically strong cratons, and their weakening by metamorphic hydration reactions, is of fundamental importance for understanding first‐order strength contrasts within the crust and the resulting controls on the tectonic evolution of the continents. In this study, the Douglas Harbor structural window within the Paleoproterozoic Trans‐Hudson orogen of Canada is used to study the hydration of the footwall Archean Superior craton basement by water released from the overlying Paleoproterozoic Cape Smith thrust‐fold belt. Phase equilibria modeling is applied to quantify the Archean and Paleoproterozoic metamorphic conditions, and to determine the effect of hydration on basement mineralogy. The amount of structurally bound water within the basement is calculated and shown to decrease as a function of distance below the basal décollement of the thrust‐fold belt. Applying a reactive fluid transport model to these results, the rate coefficient for fluid‐rock reaction is constrained to be 10−19 mol−1m3s−1, and the diffusivity of water through the grain boundary network to be 10−9 m2s−1 at the ambient metamorphic conditions of 570°C and 7.5 kbar. This newly documented rate of water diffusion is three orders of magnitude slower than thermal diffusion, implying that hydration by diffusion may be the rate‐limiting factor in the weakening of cratons, and therefore plays an important role in their geological persistence. This conclusion is consistent with field observations that Paleoproterozoic strain in the Douglas Harbor structural window is restricted to hydrated portions of the Archean Superior craton basement.