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Most chemical processes happen at a local scale where only a subset of molecular orbitals is directly involved and only a subset of covalent bonds may be rearranged. To model such reactions, Density Functional Theory (DFT) is often inadequate, and the use of computationally more expensive correlated wavefunction (WF) methods is required for accurate results. Mixed-resolution approaches backed by quantum embedding theory have been used extensively to approach this imbalance. Based on the frozen density embedding freeze-and-thaw algorithm, we describe an approach to embed complete active space self-consistent field simulations run in the OpenMolcas code in a DFT environment calculated in CP2K without requiring any external tools. This makes it possible to study a local, active part of a chemical system in a larger and relatively static environment with a computational cost balanced between the accuracy of a WF method and the efficiency of DFT, which we test on environment–subsystem pairs. Finally, we apply the implementation to an oxygen molecule leaving an aluminum (111) surface and a ruthenium(IV) oxide (110) surface. [ABSTRACT FROM AUTHOR]

Chemical and physical processes on the surfaces of amorphous solids have been the focus of many studies over the past decades. These studies have established that dynamics in a thin layer near a glass surface are often dramatically faster than those in the glass bulk. Nevertheless, recent advances also emphasize the need for new experimental techniques capable of characterizing the structure and dynamics of the near-surface regions in glassy materials at the molecular length scale. Using a quasi-adiabatic fast scanning calorimetry (FSC) technique, we have investigated softening and vaporization of pure amorphous methylbenzene films of moderately heightened kinetic stability with thicknesses ranging from 1 to 20 nm. The analysis of the FSC thermograms reveals the existence of a high fictive temperature (liquid-like) layer on the surface of the solid glass with a thickness of 3.5 ± 0.5 nm or seven molecular diameters. Furthermore, the width of the boundary between liquid-like and solid layers in the films is less than 1 nm. These preliminary findings compliment and substantiate past determinations of the mobile surface layer thicknesses obtained by introduction of nanoparticles or spectroscopic molecular probes to near-surface regions of amorphous samples. The developed FSC methodology will advance the theoretical and computational research by providing calorimetric data on the enhanced interfacial dynamics phenomenon in a variety of low-molecular-weight amorphous materials. [ABSTRACT FROM AUTHOR]

Solid–water interfaces are crucial to many physical and chemical processes and are extensively studied using surface-specific sum-frequency generation (SFG) spectroscopy. To establish clear correlations between specific spectral signatures and distinct interfacial water structures, theoretical calculations using molecular dynamics (MD) simulations are required. These MD simulations typically need relatively long trajectories (a few nanoseconds) to achieve reliable SFG response function calculations via the dipole moment–polarizability time correlation function. However, the requirement for long trajectories limits the use of computationally expensive techniques, such as ab initio MD (AIMD) simulations, particularly for complex solid–water interfaces. In this work, we present a pathway for calculating vibrational spectra (IR, Raman, and SFG) of solid–water interfaces using machine learning (ML)-accelerated methods. We employ both the dipole moment–polarizability correlation function and the surface-specific velocity–velocity correlation function approaches to calculate SFG spectra. Our results demonstrate the successful acceleration of AIMD simulations and the calculation of SFG spectra using ML methods. This advancement provides an opportunity to calculate SFG spectra for complicated solid–water systems more rapidly and at a lower computational cost with the aid of ML. [ABSTRACT FROM AUTHOR]

Fast ion beams induce damage to deoxyribonucleic acid (DNA) by chemical products, including secondary electrons, produced from interaction with liquid water in living cells. However, the production process of these chemical products in the Bragg peak region used in particle therapy is not fully understood. To investigate this process, we conducted experiments to evaluate the radiolytic yields produced when a liquid water jet in vacuum is irradiated with MeV-energy carbon beams. We used secondary ion mass spectrometry to measure the products, such as hydronium cations (H3O+) and hydroxyl anions (OH−), produced along with ·OH radicals, which are significant inducers of DNA damage formation. In addition, we simulated the ionization process in liquid water by incident ions and secondary electrons using a Monte Carlo code for radiation transport. Our results showed that secondary electrons, rather than incident ions, are the primary cause of ionization in water. We found that the production yield of H3O+ or OH− was linked to the frequency of ionization by secondary electrons in water, with these electrons having energies between 10.9 and 550 eV. These electrons are responsible for ionizing the outer-shell electrons of water molecules. Finally, we present that the elementary processes contribute to advancing radiation biophysics and biochemistry, which study the formation mechanism of DNA damage. [ABSTRACT FROM AUTHOR]

Quantum dynamics simulation and computational spectroscopy serve as indispensable tools for the theoretical understanding of various fundamental physical and chemical processes, ranging from charge transfer to photochemical reactions. When simulating realistic systems, the primary challenge stems from the overwhelming number of degrees of freedom and the pronounced many-body correlations. Here, we present Kylin-V, an innovative quantum dynamics package designed for accurate and efficient simulations of dynamics and spectroscopic properties of vibronic Hamiltonians for molecular systems and their aggregates. Kylin-V supports various quantum dynamics and computational spectroscopy methods, such as time-dependent density matrix renormalization group and our recently proposed single-site and hierarchical mapping approaches, as well as vibrational heat-bath configuration interaction. In this paper, we introduce the methodologies implemented in Kylin-V and illustrate their performances through a diverse collection of numerical examples. [ABSTRACT FROM AUTHOR]

A hydrogen sensor is created on the basis of an acoustic topological material with a coiled structure. Compared to traditional hydrogen sensors, the sensor does not possess a sensitive layer and works with the shift of a topological interface state induced by hydrogen. The sensor is composed of two phononic crystals with distinct topological characteristics, and an interface state is achieved at the interface of both phononic crystals. When hydrogen is introduced into the sensor, the density and the sound velocity of the gas in the sensor change, which shifts the frequency of the interface state. Thus, the concentration of hydrogen can be obtained by measuring the frequency shift of the interface state. Due to the absence of a sensitive layer, the sensor operates without a chemical sorption process, and the performance of the sensor is marginally influenced by working conditions, temperature, and humidity. Theoretical analysis, numerical simulations, and experimental results show that in different background gases, synthetic air, nitrogen, and argon, the sensor exhibits relative sensitivities of 0.50, 0.50, and 0.37, which do not change with the working conditions. Additionally, the sensor possesses a rapid response, a good linearity and robustness, and a long lifespan. Furthermore, the sensor is designed based on a coiled structure, which considerably improves the space utilization and decreases the bulk. [ABSTRACT FROM AUTHOR]

Electron transfer reactions play an essential role in many chemical and biological processes. Fermi's golden rule (GR), which assumes that the coupling between electronic states is small, has formed the foundation of electron transfer rate theory; however, in short range electron/energy transfer reactions, this coupling can become very large, and, therefore, Fermi's GR fails to make even qualitatively accurate rate predictions. In this paper, I present a simple modified GR theory to describe electron transfer in the Marcus inverted regime at arbitrarily large electronic coupling strengths. This theory is based on an optimal global rotation of the diabatic states, which makes it compatible with existing methods for calculating GR rates that can account for nuclear quantum effects with anharmonic potentials. Furthermore, the optimal GR (OGR) theory can also be combined with analytic theories for non-adiabatic rates, such as Marcus theory and Marcus–Levich–Jortner theory, offering clear physical insights into strong electronic coupling effects in non-adiabatic processes. OGR theory is also tested on a large set of spin-boson models and an anharmonic model against exact quantum dynamics calculations, where it performs well, correctly predicting rate turnover at large coupling strengths. Finally, an example application to a boron-dipyrromethane–anthracene photosensitizer reveals that strong coupling effects inhibit excited state charge recombination in this system, reducing the rate of this process by a factor of 4. Overall, OGR theory offers a new approach to calculating electron transfer rates at strong couplings, offering new physical insights into a range of non-adiabatic processes. [ABSTRACT FROM AUTHOR]

Hydrated cation–π interactions at liquid–solid interfaces between hydrated cations and aromatic ring structures of carbon-based materials are pivotal in many material, biological, and chemical processes, and water serves as a crucial mediator in these interactions. However, a full understanding of the hydrated cation–π interactions between hydrated alkaline earth cations and aromatic ring structures, such as graphene remains elusive. Here, we present a molecular picture of hydrated cation–π interactions for Mg2+ and Ca2+ by using the density functional theory methods. Theoretical results show that the graphene sheet can distort the hydration shell of the hydrated Ca2+ to interact with Ca2+ directly, which is water–cation–π interactions. In contrast, the hydration shell of the hydrated Mg2+ is quite stable and the graphene sheet interacts with Mg2+ indirectly, mediated by water molecules, which is the cation–water–π interactions. These results lead to the anomalous order of adsorption energies for these alkaline earth cations, with hydrated Mg2+–π < hydrated Ca2+–π when the number of water molecules is large (n ≥ 6), contrary to the order observed for cation–π interactions in the absence of water molecules (n = 0). The behavior of hydrated alkaline earth cations adsorbed on a graphene surface is mainly attributed to the competition between the cation–π interactions and hydration effects. These findings provide valuable details of the structures and the adsorption energy of hydrated alkaline earth cations adsorbed onto the graphene surface. [ABSTRACT FROM AUTHOR]

Enhanced mixing in microfluidic systems is necessary in many applications such as chemical processing, biological assays, and diagnosis. We are developing a microfluidic system to efficiently mix minute reagents (down to several microliters) using vibration-induced flow (VIF), in which a net flow is generated around a micropillar by applying periodic vibration. In this study, we numerically investigate the enhancement in chaotic mixing using the VIF technique and periodic switching of vibrations. By extending our previous numerical simulation model, we investigate the flow field and trajectories of fluid particles in three-dimensional space. We demonstrate that chaotic advection characteristics can be observed by periodically switching the vibrational direction of a substrate using simple cylindrical pillars. In addition, using an appropriate interval for switching the vibration axes yields better mixing performance. The extent of chaotic advection is evaluated quantitatively using the Lyapunov exponent considering various vibration parameters, such as the vibration amplitude, separation distance between each pillar and pillar shape. The flow field induced by a large-amplitude and sharp-edged wall pillar provides excellent mixing results. Thus, VIF is successfully applied to obtain an efficient mixing strategy with the aid of the chaotic theory. [ABSTRACT FROM AUTHOR]

Solar fuels catalysis is a promising route to efficiently harvesting, storing, and utilizing abundant solar energy. To achieve this promise, however, molecular systems must be designed with sustainable components that can balance numerous photophysical and chemical processes. To that end, we report on the structural and photophysical characterization of a series of Cu(I)–anthraquinone-based electron donor–acceptor dyads. The dyads utilized a heteroleptic Cu(I) bis-diimine architecture with a copper(I) bis-phenanthroline chromophore donor and anthraquinone electron acceptor. We characterized the structures of the complexes using x-ray crystallography and density functional theory calculations and the photophysical properties via resonance Raman and optical transient absorption spectroscopy. The calculations and resonance Raman spectroscopy revealed that excitation of the Cu(I) metal-to-ligand charge-transfer (MLCT) transition transfers the electron to a delocalized ligand orbital. The optical transient absorption spectroscopy demonstrated that each dyad formed the oxidized copper–reduced anthraquinone charge-separated state. Unlike most Cu(I) bis-phenanthroline complexes where increasingly bulky substituents on the phenanthroline ligands lead to longer MLCT excited-state lifetimes, here, we observe a decrease in the long-lived charge-separated state lifetime with increasing steric bulk. The charge-separated state lifetimes were best explained in the context of electron-transfer theory rather than with the energy gap law, which is typical for MLCT excited states, despite the complete conjugation between the phenanthroline and anthraquinone moieties. [ABSTRACT FROM AUTHOR]

Chemical vapor deposition (CVD) is a crucial technique to prepare high-quality graphene because of its controllability. In the research, we perform a systematic computational fluid dynamics numerical investigation on the effect of gas-phase reaction dynamics on the graphene growth in a horizontal tube CVD reactor. The research results indicate that the gas-phase chemical reactions in the CVD reactor are in a nonequilibrium state, as evidenced by the comparison of species mole fraction distributions during the CVD process and under chemical equilibrium conditions. The effect of gas-phase reaction dynamics on the deposition rate of graphene under different conditions is studied, and our research shows that the main causes of change in graphene growth rates under different conditions are gas-phase reaction dynamics and active species transport. The results of numerical simulation agree well with the experimental phenomena. The research results also indicate that, for methane, the main limiting factor of graphene growth is the surface kinetic reaction rate. Conversely, for active species, the main limiting factor of graphene growth is species transport. Our research suggests that the growth rate of graphene can be regulated from the perspective of the gas reaction mechanism. This method has theoretical guiding significance and can be extended to the preparation of large-area graphene. [ABSTRACT FROM AUTHOR]

The technological landscape for industrial processes handling asphaltene is evolving at a rapid pace due to the increase in the extraction of heavy crude oil. The main underlying challenges in this regard are the flow assurance, the recovery of the spent solvent, and the sophisticated extractor setup required to develop the process to an industrial scale. The number of studies focused on the handling of the asphaltene at the atomic and molecular scales is growing enormously in order to identify new sustainable solvents for the effective extraction of asphaltene from heavy crude oil or oil-bearing sands. This Perspective focuses on the importance of density functional theory and molecular dynamics simulations to explore the broader range of asphaltene inhibitors, e.g., nanoparticles, ionic liquids, and deep eutectic solvents, to prevent asphaltene precipitation. We provide a concise overview of the major accomplishments, analyze the aspects that require attention, and highlight the path-breaking studies having a significant impact on the process of chemical enhanced oil recovery from heavy crude oil reservoirs primarily based on atomistic and molecular simulations. [ABSTRACT FROM AUTHOR]

Many important chemical processes involve reactivity and dynamics in complex solutions. Gaining a fundamental understanding of these reaction mechanisms is a challenging goal that requires advanced computational and experimental approaches. However, important techniques such as molecular simulation have limitations in terms of scales of time, length, and system complexity. Furthermore, among the currently available solvation models, there are very few designed to describe the interaction between the molecular scale and the mesoscale. To help address this challenge, here, we establish a novel hybrid approach that couples first-principles plane-wave density functional theory with classical density functional theory (cDFT). In this approach, a region of interest described by ab initio molecular dynamics (AIMD) interacts with the surrounding medium described using cDFT to arrive at a self-consistent ground state. cDFT is a robust but efficient mesoscopic approach to accurate thermodynamics of bulk electrolyte solutions over a wide concentration range (up to 2M concentrations). Benchmarking against commonly used continuum models of solvation, such as SMD, as well as experiments, demonstrates that our hybrid AIMD–cDFT method is able to produce reasonable solvation energies for a variety of molecules and ions. With this model, we also examined the solvent effects on a prototype SN2 reaction of the nucleophilic attack of a chloride ion on methyl chloride in the solution. The resulting reaction pathway profile and the solution phase barrier agree well with experiment, showing that our AIMD/cDFT hybrid approach can provide insight into the specific role of the solvent on the reaction coordinate. [ABSTRACT FROM AUTHOR]

Attempts to understand the molecular structure of water were first made well over a century ago. Looking back at the various attempts, it is illuminating to see how these were conditioned by the state of knowledge of chemistry and physics at the time and the experimental and theoretical tools then available. Progress in the intervening years has been facilitated by not only conceptual and theoretical advances in physics and chemistry but also the development of experimental techniques and instrumentation. Exploitation of powerful computational methods in interpreting what at first sight may seem impenetrable experimental data has led us to the consistent and detailed picture we have today of not only the structure of liquid water itself and how it changes with temperature and pressure but also its interactions with other molecules, in particular those relevant to water's role in important chemical and biological processes. Much remains to be done in the latter areas, but the experimental and computational techniques that now enable us to do what might reasonably be termed "liquid state crystallography" have opened the door to make possible further advances. Consequently, we now have the tools to explore further the role of water in those processes that underpin life itself—the very prospect that inspired Bernal to develop his ideas on the structure of liquids in general and of water in particular. [ABSTRACT FROM AUTHOR]

Computational modelling for microchannel reactor design was conducted in the attempt to fully understand autothermal reforming phenomena in continuous flow reactors. The effects of pressure and flow rate on the efficiency and performance were evaluated by performing computational fluid dynamics under different design conditions. The reactor efficiency and performance were assessed by means of the reactant conversion, product yield, reaction rate, hydrogen productivity, and output power. Recommendations for designing an autothermal reforming system were made and strategies for performing efficient operation were set forth. The results indicated that the pressure and flow rate set strict limits on operation, and there is a trade-off between high productivity and low conversion. The pressure and flow rate play competing roles in the reactor efficiency and performance. Lower pressures and flow rates can increase the conversion and yield, but higher pressures and flow rates can significantly improve the hydrogen productivity and output power, which is essential to the success of start-up and acceleration of the downstream equipment. There may exist an optimum pressure and flow rate in terms of both efficiency and performance. The calculated output power is of the order of thousands of kilowatts per cubic meter.

Time-resolved pump–probe and two-dimensional spectroscopy are widely used to study ultrafast chemical and biological processes in solutions. However, the corresponding signals at long times can be contaminated by molecular photothermal effects, which are caused by the nonradiative heat dissipation of photoexcited molecules to the surroundings. Additionally, molecular diffusion affects the transient spectroscopic signals because photoexcited molecules can diffuse away from the pump and probe beam focuses. Recently, a theoretical description of molecular photothermal effects on time-resolved IR spectroscopy was reported. In this work, I consider the molecular photothermal process, molecular diffusion, and sample flow to develop a generalized theoretical description of time-resolved spectroscopy. The present work can be used to interpret time-resolved spectroscopic signals of electronic or vibrational chromophores and understand the rate and mechanisms of the conversion of high-frequency molecular electronic and vibrational energy to solvent kinetic energy in condensed phases. [ABSTRACT FROM AUTHOR]

Metal hexafluorides hydrolyze at ambient temperature to deposit compounds having fluorine-to-oxygen ratios that depend upon the identity of the metal. Uranium-hexafluoride hydrolysis, for example, deposits uranyl fluoride (UO2F2), whereas molybdenum hexafluoride (MoF6) and tungsten hexafluoride deposit trioxides. Here, we pursue general strategies enabling the prediction of depositing compounds resulting from multi-step gas-phase reactions. To compare among the three metal-hexafluoride hydrolyses, we first investigate the mechanism of MoF6 hydrolysis using hybrid density functional theory (DFT). Intermediates are then validated by performing anharmonic vibrational simulations and comparing with infrared spectra [McNamara et al., Phys. Chem. Chem. Phys. 25, 2990 (2023)]. Conceptual DFT, which is leveraged here to quantitatively evaluate site-specific electrophilicity and nucleophilicity metrics, is found to reliably predict qualitative deposition propensities for each intermediate. In addition to the nucleophilic potential of the oxygen ligands, several other contributing characteristics are discussed, including amphoterism, polyvalency, fluxionality, steric hindrance, dipolar strength, and solubility. To investigate the structure and composition of pre-nucleation clusters, an automated workflow is presented for the simulation of particle growth. The workflow entails a conformer search at the density functional tight-binding level, structural refinement at the hybrid DFT level, and computation of a composite free-energy profile. Such profiles can be used to estimate particle nucleation kinetics. Droplet formation is also considered, which helps to rationalize the different UO2F2 particle morphologies observed under varying levels of humidity. Development of predictive methods for simulating physical and chemical deposition processes is important for the advancement of material manufacturing involving coatings and thin films. [ABSTRACT FROM AUTHOR]

Metal hexafluorides hydrolyze at ambient temperature to deposit compounds having fluorine-to-oxygen ratios that depend upon the identity of the metal. Uranium-hexafluoride hydrolysis, for example, deposits uranyl fluoride (UO2F2), whereas molybdenum hexafluoride (MoF6) and tungsten hexafluoride deposit trioxides. Here, we pursue general strategies enabling the prediction of depositing compounds resulting from multi-step gas-phase reactions. To compare among the three metal-hexafluoride hydrolyses, we first investigate the mechanism of MoF6 hydrolysis using hybrid density functional theory (DFT). Intermediates are then validated by performing anharmonic vibrational simulations and comparing with infrared spectra [McNamara et al., Phys. Chem. Chem. Phys. 25, 2990 (2023)]. Conceptual DFT, which is leveraged here to quantitatively evaluate site-specific electrophilicity and nucleophilicity metrics, is found to reliably predict qualitative deposition propensities for each intermediate. In addition to the nucleophilic potential of the oxygen ligands, several other contributing characteristics are discussed, including amphoterism, polyvalency, fluxionality, steric hindrance, dipolar strength, and solubility. To investigate the structure and composition of pre-nucleation clusters, an automated workflow is presented for the simulation of particle growth. The workflow entails a conformer search at the density functional tight-binding level, structural refinement at the hybrid DFT level, and computation of a composite free-energy profile. Such profiles can be used to estimate particle nucleation kinetics. Droplet formation is also considered, which helps to rationalize the different UO2F2 particle morphologies observed under varying levels of humidity. Development of predictive methods for simulating physical and chemical deposition processes is important for the advancement of material manufacturing involving coatings and thin films. [ABSTRACT FROM AUTHOR]

This study was focused on the design and development of a new heterogeneous catalyst based on polyester (PE) fabric modified with graphene oxide nanosheets decorated with silver metallic nanoparticles (PE-rGO/Ag0), using a simple, easy, and effective approach. PE fabrics were coated by sonication with graphene oxide (GO) nanosheets followed by in situ deposition and reduction of silver nanoparticles over the GO surface, covering the PE fabric and producing PE-rGO/Ag0. The crystalline structure, surface morphology and chemical characteristics of the synthesised materials were identified by X-ray diffraction spectroscopy, scanning and transmission electron microscopy analyses (SEM and TEM) and by Fourier-transform infrared spectroscopy (FTIR), respectively. The catalytic performance of the prepared PE-rGO/Ag0 was assessed during the hydrogenation of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) in the presence of sodium borohydride (NaBH4). Experimental results indicate that PE-rGO/Ag0 with a surface of 6 cm2 (3x2 cm) showed the highest catalytic activity with an apparent reaction rate constant (Kapp) of 0.65 min−1. In addition, PE-rGO/Ag0 activity resulted to be comparable and significantly higher than previously reported values of silver-based catalysts. Remarkable stability values were achieved during different operating cycles without significant degradation in the catalytic activity, suggesting that PE-rGO/Ag0 can be used as a strong candidate in long-lasting chemical catalytic processes. [ABSTRACT FROM AUTHOR]

The nickel metal hydride (NiMH) battery technology has been designed for use in electric vehicles, solar-powered applications and power tools. These batteries contain the critical and strategic raw materials cobalt, nickel and several rare earth elements (REE). When designing a battery recycling process, there are several choices to be made regarding end-products and process chemicals. The aim of this study is to investigate and compare the environmental and economic sustainability of different recycling options for NiMH batteries by taking projected market developments into consideration and by applying life cycle assessment and life cycle costing methods. The comparative study is limited to recovery of the REEs. Two hydrometallurgical processes for recovery of the REEs from the anode material are compared with extraction of REEs from primary sources in China. The processes compared are a high-temperature sulfation roasting process and a process based on hydrochloric acid leaching followed by precipitation of REE oxalates. By comparing the different recycling approaches, the hydrochloric acid process performs best. However, the use of oxalic acid has a large impact on the overall sustainability footprint. For the sulfation roasting process, the energy, sodium hydroxide and sulphuric acid consumption contribute most to the total environmental footprint. This article is part of the discussion meeting issue 'Sustainable metals: science and systems'. [ABSTRACT FROM AUTHOR]

Every year, a huge amount of lethal compounds, such as synthetic dyes, pesticides, pharmaceuticals, hydrocarbons, etc. are mass produced worldwide, which negatively affect soil, air, and water quality. At present, pesticides are used very frequently to meet the requirements of modernized agriculture. The Food and Agriculture Organization of the United Nations (FAO) estimates that food production will increase by 80% by 2050 to keep up with the growing population, consequently pesticides will continue to play a role in agriculture. However, improper handling of these highly persistent chemicals leads to pollution of the environment and accumulation in food chain. These effects necessitate the development of technologies to eliminate or degrade these pollutants. Degradation of these compounds by physical and chemical processes is expensive and usually results in secondary compounds with higher toxicity. The biological strategies proposed for the degradation of these compounds are both cost-effective and eco-friendly. Microbes play an imperative role in the degradation of xenobiotic compounds that have toxic effects on the environment. This review on the fate of xenobiotic compounds in the environment presents cutting-edge insights and novel contributions in different fields. Microbial community dynamics in water bodies, genetic modification for enhanced pesticide degradation and the use of fungi for pharmaceutical removal, white-rot fungi's versatile ligninolytic enzymes and biodegradation potential are highlighted. Here we emphasize the factors influencing bioremediation, such as microbial interactions and carbon catabolism repression, along with a nuanced view of challenges and limitations. Overall, this review provides a comprehensive perspective on the bioremediation strategies. [ABSTRACT FROM AUTHOR]

Biogenic volatile organic compounds are emitted by plants and influence human and environmental health. They contribute to the formation of pollutants such as ozone and secondary organic aerosols, thereby influencing air quality and climate. Here we review biogenic volatile organic compounds with focus on biosynthesis, release to the atmosphere, distribution at various scales, tropospheric chemical processes, and secondary organic aerosols. Biogenic volatile organic compounds are emitted primarily through enzymatic pathways in response to environmental factors, varying across plant species and ecosystems. These emissions exhibit heterogeneity at multiple scales, influenced by meteorological conditions and plant structure. [ABSTRACT FROM AUTHOR]

This work intended to study differences in oil yield and co-extraction of antioxidant and antibacterial compounds of Nigella sativa L. seed oil as a function of two main extraction processes: mechanical pressing and solvent extraction, including hexane and chloroform. Next, we studied such oils' chemical composition and antioxidant and antibacterial activities. Notably, the chemical cartelization was conducted by use of HPLC. The antioxidant activity of the oils was assessed using DPPH, TAC, and FRAP assays. Antimicrobial activity was investigated against bacteria and fungi with clinical importanceT. HPLC-DAD analysis identified some bioactive compounds in the oils, including thymoquinone, carvacrol, and gallic acid. Results showed that oils extracted by different methods exhibit varying levels of antioxidant activity, with a higher concentration of antioxidant compounds in chloroform-extracted oils. Antimicrobial tests revealed significant inhibitory effects of the studied oils on the growth of bacteria and fungi. In conclusion, this research has made it possible to characterize the oils extracted from Nigella sativa L. Seeds by determining their chemical composition and biological properties, notably their antioxidant, antibacterial, and antifungal activity. These results contribute to a better understanding of the potential benefits of these oils for human health and open up exciting prospects for their use in various fields, notably as food additives and therapeutic agents. [ABSTRACT FROM AUTHOR]

Operators in modular process plants face new demands due to features like increasing automation and digitalization combined with an architecture allowing for reconfigurations in short time spans. However, operators must be able to master process control tasks at all times. For research purposes on topics like supporting operators in their performance in process control of modular process plants, this article aims at developing scenarios of such plants. Based on three conceptual levels describing the relation of chemical processes and their modularized realization and a neutralization process as use case, four scenarios were developed. Having the common task to increase the throughput, the scenarios differ in terms of complexity and constraints that need to be considered for process control. [ABSTRACT FROM AUTHOR]

System‐scale computational fluid dynamics (CFD) simulations in chemical and process engineering remain limited owing to the complexity of integrating the results obtained at different scales. The present study addresses this issue by correlating the flow behaviors calculated by CFD in porous media at the micro‐scale and the macro‐scale using deep neural network (DNN) technology. The DNN model is trained using a dataset constructed from the results obtained for a large number of particle‐scale CFD simulations that are coupled to macroscopic governing equations. Comparisons with experimental results obtained with a packed bed show that the proposed CFD‐DNN method provides predictions of pressure drop with an accuracy that is 28% greater than that of a method based on the Ergun equation. [ABSTRACT FROM AUTHOR]

Background: Learning analytics dashboards are increasingly being used to communicate feedback to learners. However, little is known about learner preferences for dashboard designs and how they differ depending on the self‐regulated learning (SRL) phases the dashboards are presented (i.e., forethought, performance, and self‐reflection phases) and SRL skills. Insight into design preferences for dashboards with different reference frames (i.e., progress, social, internal achievement and external achievement) is important because the effectiveness of feedback can depend upon how a learner perceives it. Objective: This study examines workplace learner preferences for four dashboard designs for each SRL phase and how SRL skills relate to these preferences. Methods: Seventy participants enrolled in a chemical process apprenticeship program took part in the study. Preferences were determined using a method of adaptive comparative judgement and SRL skills were measured using a questionnaire. Preferences were tested on four dashboard designs informed by social and temporal comparison theory and goal setting theory. Multinomial logistic regressions were used to examine the relationship between dashboard preferences and SRL. Results and Conclusions: Results show that the progress reference frame is more preferred before and after task performance, and the social reference frame is less preferred before and after task performance. It was found that the higher the SRL skill score the higher the probability a learner preferred the progress reference frame compared to having no preference before task performance. The results are consistent with other findings, which suggest caution when using social comparison in designing dashboards which provide feedback. Lay Description: What is already known about this topic?: Learning analytics dashboards use visualisations to provide feedback on learning tasks to optimise learning.Learners can better understand the meaning of their feedback if it is presented alongside a point of comparison, such as a prior level of performance, the performance level of their peers or how their performance level compares to an achievement goal.Learning analytics dashboards can support learning behaviours before, during, and after learners perform a task.Learners can acquire information to improve their learning via learning analytics dashboards, such as feedback on performance, which illustrates areas of a task learners are stronger and weaker at, which in turn can help inform future training efforts. What this paper adds?: Workplace learners typically prefer dashboards which offer visualisations comparing their current performance level with past levels of performance.Comparison with peers is typically the least preferred point of comparison when offered in learning analytics dashboards.No clear preference emerged between reference frames containing assigned or self‐set goals in dashboards presented before and after task performance. Implications for practice: Designers should take into account learner preferences when designing learning analytics dashboard visualisations.Designers should consider presenting learning analytics dashboards before, during, and after task performance.Designers should gain more insight into how learners process learning analytic dashboards and act upon it. [ABSTRACT FROM AUTHOR]

• Novel cryogenic desublimation carbon capture system for LNG-powered ships is proposed. • Thermodynamic analyses are carried out for the proposed system. • Comparative analyses with the typical monoethanolamine absorption process are conducted. • The energy consumption per unit of carbon capture reaches as low as 1.19 MJ/kg. The traditional carbon capture technologies such as alcohol-amine decarburization, membrane separation, etc., are difficult to be used to cope with carbon emissions for ships, due to the power-hungry combustion exhaust pressurization consumption, poor economic benefits of carbon capture, etc. This paper presents a novel cryogenic desublimation CO 2 capture system (CDCC) coupled with LNG cold energy for LNG-powered ships. The proposed system not only significantly reduces the energy consumption of exhaust gas boosting but also utilizes waste cold energy from the LNG fuel gas supply system (FGSS). This enables the CO 2 gas to condense and separate at low temperatures. Through simulation and parameter optimization, the CO 2 capture rate and purity of CO 2 product can reach 92.87 % and 96.49 % respectively, with an energy consumption of 5.72 MJ/kg. To evaluate the CDCC performance, the typical monoethanolamine chemical absorption process (MEA) under the same flue gas inlet conditions and the consistent CO 2 product outlet temperature and pressure is also simulated. Comparative simulation with the MEA process shows similar CO 2 capture rates (87.13 % for MEA and 87.18 % for CDCC), but MEA achieves higher product purity by 2.58 %. However, MEA exhibits significantly higher energy consumption (33.28 MJ/kg) compared to CDCC (5.90 MJ/kg). Investigation into process parameters, engine powers, and CO 2 product parameters demonstrates CDCC's robustness in energy consumption, capture rate, and purity. The proposed CDCC system is well-suited for LNG-powered ships, which can be attributed to atmospheric exhaust gas treatment and self-contained utilization of cold energy. [ABSTRACT FROM AUTHOR]

Laser chemical machining (LCM) is a method for removing material by thermally induced chemical dissolution of self-passivating metals. However, the process window is limited by disrupted material removal due to gas bubble formation and metallic salts and oxides deposition at higher energy input. Since the temperature increases, and therefore gas bubble growth takes time, it is hypothesized that the temporal modulation of laser power can remove the metal homogeneously, i.e., without disrupted material removal, while achieving a higher removal rate. Based on this, the dynamic process behavior of material removal is investigated for the LCM of titanium in phosphoric acid, using a rectangular modulation of the laser power with varying irradiation durations. As a result, however, high-speed videos show that gas bubbles are consistently generated, regardless of the applied laser power and power modulation, although the quantity of bubbles varies with different parameters. Even with short power durations (10 ms), the material deposition occurs after multiple irradiations. When the duration is longer, the material deposition increases in height along the laser scan direction. For the studied process parameters, a Fourier analysis in the spatial domain further indicates the correlation between the material removal frequencies and the modulation frequencies. In conclusion, the laser power modulation cannot prevent the disturbed material removal at high laser powers. Nevertheless, the material deposition can be utilized to generate periodic surface structures with a depth below and above the initial surface. [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyze how thermal stratification affects fluid movement past an impulsively initiated infinite upright plate when first‐order chemical reactions are present. Laplace's transform method is applied to achieve a closed‐form solution for the nondimensional governing equations when Pr=1. The formula L{n(t)}=∫0∞e−stn(t)dt=n¯(s), where t is the time and s is a parameter, can be used to obtain the Laplace transform of an exponentially ordered piece‐wise continuous function n(t). The unstable flow past an infinite vertical plate, starting abruptly in the presence of heat stratification and chemical reactions, has never been studied before. The research focuses on the combined impact of thermal stratification and chemical processes on the flow of an incompressible viscous fluid over an indefinitely tall plate. In this study, the significant findings that resulted from heat stratification are compared to the condition in which heat stratification is absent. The impacts of a number of parameters, such as S,K,Gr, and Gc, are investigated and visually displayed with respect to the following variables: concentration, velocity, shear stress, rate of heat transfer, temperature, and rate of mass transfer. It is demonstrated that applying stratification increases the frequency of oscillation in shear stress and heat transfer rate. The results obtained can be useful in the design of heat exchangers and other engineering applications. [ABSTRACT FROM AUTHOR]

In this research, field studies, surface sediment samples, and laboratory studies were used to determine the textural and mineralogical characteristics of the sediments that originated from the salt domes of the northern coastal area of Hormuz Strait. In this way, were studied the texture and mineralogy of sediments. The main minerals of the sediments are quartz, calcite, feldspar, and clay. Pyroxene and Fe-bearing minerals are the main heavy minerals of studied sediments. The abundance of these minerals is determined by the mineralogy and creation of sediment of the source rocks. The presence of stable clay minerals indicates the re-entry into the sedimentary cycle, and unstable minerals indicate the initial diagenesis conditions of their mineralogical transformation in surface sediments. Thus, the presence of salt diapirs is the most important structural-tectonic phenomenon that has caused rock fractures and intensified the effect of weathering. On the other hand, dry weather has weakened the intensity and extent of chemical weathering processes, especially in clay minerals. However, the seasonal flooding hydrological system has caused dissolution and changes in soluble and unstable sediment components and introduced some minerals, such as illite, into the re-sedimentary cycle. In addition, the transport of sedimentary particles in waterways with the mechanism of seasonal flood waters has created a non-continuous transportation system. All these factors have caused the sediments originating from salt domes to be texturally bad sorted, platykurtic, and have to vary kurtosis affected by the presence and extent of source rock units. [ABSTRACT FROM AUTHOR]

Here we comprehensively review the available knowledge on effects of different pretreatment technologies on microbial population and microbial dynamics in anaerobic digestion (AD) fed with different substrates and different operational parameters. To identify peer-reviewed studies published in English-language journals, a comprehensive search was performed across multiple electronic databases. The eligible studies were analyzed to extract data and information pertaining to the configuration of anaerobic reactors, operational parameters, and various pretreatment processes such as chemical, biological, enzymatic, thermal, microaerobic, and ultrasonic. The findings derived from this current review demonstrated that different chemical, biological, and physical pretreatment technologies improve the biomethane potential (BMP) and potentially affect the dominant bacteria and archaea. Moreover, although hydrogenotrophic methanogenesis are more observed due to resistance to extreme conditions, methane production follows both aceticlastic and hydrogenotrophic pathways in AD assisted with different pretreatment process. Firmicutes and Bacteroidetes phyla of bacteria were the dominant hydrolytic bacteria due to synergetic effects of different pretreatment process on solubilization and bioavailability of recalcitrant substrates. In summary, a holistic understanding on bacteria and archaea communities, along with the mechanisms of the dominant microorganisms leads to enhanced stability and overall performance of anaerobic digestion (AD) processes. [ABSTRACT FROM AUTHOR]

Estimation of volume fraction percentage of the multiple phases flowing in pipes with limited access is a challenge in oil, gas, chemical processes, and petrochemical industries. In this research, the gamma backscattered spectra together with the machine learning model were used to predict precise volume fraction percentages in water-gasoil-air three-phase flows and solve the aforementioned challenge. The detection system includes a single energy 137Cs source and a NaI(Tl) detector to measure the backscattered rays. The MCNPX code was used to simulate the setup and produce the required data for the artificial neural network. The volume fraction was calculated with mean relative error percentage 13.60% and the root mean square error 2.68, respectively. Then, the results were compared with the acquired results of transmitted gamma-ray spectra. The proposed design is a suitable, safe, and low-cost choice for industries. [ABSTRACT FROM AUTHOR]

This study investigates the performance of serpentine and wavy serpentine millireactors. Millireactors, with their microscale features, offer advantages such as heightened surface-to-volume ratio, improved heat transfer coefficients, and reduced mass transfer pathways. The serpentine and wavy serpentine millireactors, characterized by their channel structures, demonstrate superior energy efficiency, reaction speed, and scalability compared to conventional reactors. The focus of this research is on understanding the mass transfer rates and residence time distribution (RTD) in these millireactors, crucial for optimizing their design and operation. The residence time distribution studies providing insights into the mixing characteristics and overall flow behavior. The (RTD) data was fitted to different models. Mass transfer studies examine the movement of acetic acid between aqueous and organic phases, with the volumetric mass transfer coefficient (KLa) as a key parameter. Results from the serpentine millireactor indicate a partially mixed flow behavior with a dispersion number of 0.611, while the wavy serpentine millireactor exhibits a dispersion number of 0.130, indicating improved mixing efficiency. The mass transfer studies yield KLa values in the range of 0.31–1.42 min−1 and 0.49–2.71 min−1 for serpentine and wavy serpentine millireactors, respectively. Efficiency assessments reveal 72.31% and 83.21% for serpentine and wavy serpentine millireactors, respectively. The study concludes that the use of serpentine and wavy serpentine millireactors represents an effective method for process intensification, offering valuable insights for chemical engineering and process optimization applications. The results contribute to advancing the millireactor technology and its potential in continuous flow chemical manufacturing. [ABSTRACT FROM AUTHOR]

[Display omitted] • Cellulose derived carbon/reduced graphene oxide composite aerogels were prepared. • The composite aerogels had unique lightweight characteristics and porous structure. • Microwave absorption capacity was regulated by the concentration of graphene oxide. • Maximum effective absorption bandwidth was 7.28 GHz, covering the whole Ku-band. • The RCS contribution of composite aerogels in the far-field is simulated by CST. The development of cellulose derived carbon-based composite aerogels with light weight, broad bandwidth and strong absorption remains a challenging task. In this work, the cellulose derived carbon/reduced graphene oxide composite aerogels were prepared by a two-stage process of chemical crosslinking and high-temperature carbonization. The results revealed that the as-fabricated binary composite aerogels had a unique lightweight characteristic and three-dimensional porous network structure, which was chemically crosslinked by epichlorohydrin. Furthermore, the weight concentration of graphene oxide (GO) had a notable influence on the electromagnetic parameters and microwave absorption properties of the composite aerogels. The obtained binary composite aerogel possessed the optimal microwave dissipation capability when the concentration of GO was 1.5 mg/mL. Remarkably, the minimum reflection loss reached −50.42 dB at a thickness of 2.47 mm and a filling ratio of 17.5 wt%. Concurrently, the composite aerogel with a comparable thickness of 2.73 mm showed a wide effective absorption bandwidth of 7.28 GHz, spanning the total Ku-band and extending into a portion of the X-band. The radar cross section contribution of binary composite aerogels in the far-field was also simulated by computer simulation technique. In addition, the potential microwave attenuation mechanism was proposed. It was believed that the results of this paper would offer a reference for the preparation of cellulose derived carbon-based composite aerogels as efficient and broadband microwave absorbers. [ABSTRACT FROM AUTHOR]

Biological process to extract chitin from crustacean wastes may be an interesting and safe alternative than chemical process. The inoculation of lactic acid bacteria is an environmentally-friendly strategy to extract chitin especially if low-cost raw materials are utilized as fermentation substrates. The deacetylation of chitin by chemical or biological processes results in an important and multifaceted biopolymer, the chitosan, with a range of applications in diverse areas. A two-step process consisting of lactic fermentation (by Lactiplantibacillus plantarum) of shrimp wastes and chemical deacetylation of chitin to obtain chitosan was here proposed focusing on the replacement of the semi-synthetic medium MRS (de Man–Rogosa–Sharpe) by sugarcane molasses, on the variation in the concentration and drying of shrimp wastes in the fermentation step, and increased deacetylation times of chitin. Chitosan was characterized and assayed for antimicrobial activity, microsphere and film-forming properties. Diluted molasses containing 150 g/L of total reducing sugars and supplemented with 12 g/L yeast extract is a viable and cost-effective alternative to MRS to recover chitin from oven-dried shrimp wastes at a concentration of 5% w/v. A low molecular weight chitosan (95.3 kDa) was obtained after a 2-h chemical deacetylation (79.6% deacetylation degree). Molasses chitosan exhibited antibacterial and antifungal activities. Chitosan rough microspheres capable of loading antibiotic (monensin), and transparent and homogenous films were also obtained. The complete flow of operations until obtaining chitosan with considerable yields is here presented, also demonstrating the intrinsic properties of this polymer. The molasses chitosan, utilized without purification, has potential application in industry and agriculture as a biomaterial. [ABSTRACT FROM AUTHOR]

The Algerian endemic plant Ammoides atlantica (Coss. et Durieu) H. Wolff was studied for the chemical profiling and biological activities of its essential oil (EO) and ethanolic extract (EE). The chemical analysis by GC/MS and HPLC/DAD/UV revealed, respectively, the major compounds thymol (39.46%), γ- terpinene (31.74%), and p-cymene (19.01%) in the EO, and apigenin (33.58%), luteolin 7-O-glucoside (20.09%), and luteolin (14.39%) in the EE. The EO exhibited strong antioxidant activity, with a significant ABTS•+ scavenging capacity (IC50 = 2.79 µg/mL) compared to EE, Trolox, and BHT. The EE showed comparable effects to BHT in DPPH scavenging and reducing power tests. Moreover, the EO demonstrated noteworthy antibacterial activity against S. aureus, E. coli, and P. aeruginosa, with inhibition zone diameters ranging from 32.1 to 70 mm and MICs below 0.3 to 5 mg/mL. Furthermore, the EE exhibited strong antiinflammatory activity by inhibiting hemolysis of red blood cells >70% at a concentration of 20 µg/mL. [ABSTRACT FROM AUTHOR]

Amides are an important type of synthetic intermediate used in the chemical, agrochemical, pharmaceutical, and nutraceutical industries. The traditional chemical process of converting nitriles into the corresponding amides is feasible but is restricted because of the harsh conditions required. In recent decades, nitrile hydratase (NHase, EC 4.2.1.84) has attracted considerable attention because of its application in nitrile transformation as a prominent biocatalyst. In this review, we provide a comprehensive survey of recent advances in NHase research in terms of natural distribution, enzyme screening, and molecular modification on the basis of its characteristics and catalytic mechanism. Additionally, industrial applications and recent significant biotechnology advances in NHase bioengineering and immobilization techniques are systematically summarized. Moreover, the current challenges and future perspectives for its further development in industrial applications for green chemistry were also discussed. This study contributes to the current state-of-the-art, providing important technical information for new NHase applications in manufacturing industries. [ABSTRACT FROM AUTHOR]

Wood is a sustainable, porous material with a diverse range of applications. However, the low permeability of liquids within wood poses significant challenges for the widespread application of advanced wood-based materials such as oil–water separation, as well as traditional chemical modification processes of wood. Surfactants exhibit potential to improve permeability of liquids within wood by effectively enhancing liquid wettability on solid surfaces. In this study, the effects of didecyl dimethyl ammonium chloride (DDAC) on liquid absorption of water and copper ethanolamine (CE) by wood were explored under atmospheric temperature and pressure. With an increase in concentration of DDAC, its promotion effect on liquid absorption of wood became more pronounced. The most notable enhancement was observed in wicking test where 0.10% DDAC increased liquid absorption of wood to water by 156.7% and to CE by 65.5%. The enhancement of liquid wettability on wood surface cannot be solely attributed to reduction of liquid surface tension, the adsorption of DDAC onto wood surface also plays a crucial role in this process. This study investigated the intrinsic mechanisms by which DDAC enhanced the permeability of liquids within wood, contributing to increased productivity and reduced energy consumption. [ABSTRACT FROM AUTHOR]

Groundwater contains high levels of dissolved ions, which pose health risks when consumed. This study proposes biochar production for fluoride (F-) removal from aqueous solutions using sustainable materials and functionalization processes. Biochar derived from coffee grounds carbonization at 500 ℃ was functionalized with hydrogen peroxide (H2O2). Structural morphology analysis utilized SEM+EDS, BET, and BJH techniques, while XRD and FTIR analyses assessed surface chemistry. Effects of pH, dosage, and initial F- concentration on adsorption were evaluated, along with kinetics and thermodynamics.H2O2 increased acid functional groups on the surface without significantly altering surface area or pore volume. The highest adsorption capacity (0.179 mg g-1) and removal efficiency (25.5%) were at pH = 4. Kinetic studies highlighted the influence of initial F- concentration on adsorption equilibrium time and capacity. Experimental data fitting to pseudo-second-order and Elovich models suggested chemical mechanisms predominance, with intraparticle diffusion as the rate-limiting step. Adsorption isotherm fitting to Langmuir and Freundlich models indicated physical and chemical processes combination. The highest adsorption capacity was recorded at 1.46 mg g-1 at 55 ℃. Thermodynamic analysis revealed endothermic and nonspontaneous nature, potentially affecting F- affinity towards the adsorbent. [ABSTRACT FROM AUTHOR]

Biochar has been widely used to solve the wastewater pollution of polycyclic aromatic hydrocarbons (PAHs). However, the competition of PAHs with different benzene ring numbers (e.g., phenanthrene [Phe], pyrene [Pyr], and benzo[a]pyrene [BaP]) for adsorption sites on biochar has received little attention. In this study, biochar was produced by co-pyrolysis of sludge and phosphorus tailing at different temperatures (300, 500, or 800 °C) to adsorb PAHs. The results show that phosphorus tailing increased the adsorption of PAH by increasing the biochar's BET surface area (SBET), micropore volume, hydrophobicity (at low temperatures) and aromaticity (at high temperatures). The maximum adsorption capacities were 29.90 µmol/g for Phe, 25.58 µmol/g for Pyr and 20.45 µmol/g for BaP, respectively. Importantly, the types and functions of groups involved in the adsorption of various PAHs were discussed. Adsorption of Phe and Pyr on the biochar mainly involved C=O and C–O–C functional groups, and there was a certain degree of competition between these PAHs for those sites. In contrast, BaP mainly adsorbed at C–OH and C=C moieties, without competing with Phe or Pyr at C–OH sites. The competitive edge of BaP was also stronger than that of Phe and Pyr on C=C functional groups. The adsorption mechanisms involving pore filling, hydrophobic interactions, and π–π interactions governed the adsorption of the evaluated PAHs. Overall, the adsorption of PAHs on biochar followed a heterogeneous chemical adsorption process. [ABSTRACT FROM AUTHOR]

The utilization of existing Skin-on-a-Chip (SoC) is constrained by the complex structures, the multiplicity of auxiliary devices, and the inability to evaluate exogenous chemicals that are hepatotoxic after percutaneous metabolism. In this study, a gravity-driven SoC without any auxiliary devices was constructed for the hepatocytotoxicity study of exogenous chemicals. The SoC possesses 3 layers of culture chambers, from top to bottom, for human skin equivalent (HSE), Human Umbilical Vein Endothelial Cells (HUVEC) and hepatocytes (HepG2), and the maintenance and expression capacity of the corresponding cells on the SoC were verified by specificity parameters. The reactivity of the SoC to exogenous chemicals was verified by 2-aminofluorene (2-AF). The SoC can realistically simulate the in vivo exposure process of exogenous chemicals that are percutaneously exposed and metabolized into the bloodstream and then to the liver to produce toxicity, and it can achieve the same effects on transcriptome as those of animal tests at lower exposure levels while examining multiple toxicological targets of the skin, vascular endothelial cells, and hepatocytes. Both in terms of species similarity, the principles of reduction, replacement and refinement (3R), or the level of exposure suggest that the present SoC has a degree of replacement for animal models in assessing exogenous chemicals, especially those that are hepatotoxic after percutaneous metabolism. [ABSTRACT FROM AUTHOR]

Fault detection has great significance for chemical process safety with the development of science and technology. The conventional echo state network‐based fault detection method does not highlight key fault features, and cannot forecast future fault trend after the occurrence of faults. For the above problems, a chemical process fault detection and trend analysis strategy based on key feature enhanced echo state network (KESN) is proposed. First, dynamic features are extracted by a detecting echo state network. Then, a weighting strategy is designed to enhance key features and increase fault detection rates. After detecting a fault, independent component analysis is utilized to extract independent key features. Future fault trend is forecasted based on the forecasting multi‐KESN. Simulation results on the Tennessee Eastman process demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Whilst synthetic polymers have changed the world in many important ways, the negative impacts associated with these materials are becoming apparent in waste accumulation and microplastic pollution due to lack of biodegradability. Society has become aware of the need to replace or substitute environmentally persistent synthetic polymers, and cellulose has received a large amount of attention in this respect. The mechanical properties of cellulose, its renewable nature and biodegradability are advantageous properties. Drawbacks exist for the use of plant cellulose (PC), including the water footprint of cotton, deforestation associated with wood/dissolving pulp, and the extensive processing required to refine plants and wood into pure cellulose. Bacterial cellulose (BC), also known as microbial cellulose, is gaining momentum in both academic and industry settings as a potential solution to the many drawbacks of plant-based cellulose. Compared to PC, BC has high purity, crystallinity and degree of polymerisation, and can be manufactured from waste in a way that yields more cellulose per hectare, per annum, and requires less intense chemical processing. Native bacterial cellulose can be formed and shaped to an extent and is found in a variety of commercial products. However, dissolving and regenerating bacterial cellulose is a potential avenue to broaden the applications available to this material. The aim of this study is to review the applications which utilize regenerated bacterial cellulose, with a focus on the dissolution/regeneration methods used and discussing the associated limitations and future outlook. [ABSTRACT FROM AUTHOR]

The prebiotic formation of RNA building blocks is well‐supported experimentally, yet the emergence of sequence‐ and structure‐specific RNA oligomers is generally attributed to biological selection via Darwinian evolution rather than prebiotic chemical selectivity. In this study, we used deep sequencing to investigate the partitioning of randomized RNA overhangs into ligated products by either splinted ligation or loop‐closing ligation. Comprehensive sequence‐reactivity profiles revealed that loop‐closing ligation preferentially yields hairpin structures with loop sequences UNNG, CNNG, and GNNA (where N represents A, C, G, or U) under competing conditions. In contrast, splinted ligation products tended to be GC rich. Notably, the overhang sequences that preferentially partition to loop‐closing ligation significantly overlap with the most common biological tetraloops, whereas the overhangs favoring splinted ligation exhibit an inverse correlation with biological tetraloops. Applying these sequence rules enables the high‐efficiency assembly of functional ribozymes from short RNAs without template inhibition. Our findings suggest that the RNA tetraloop structures that are common in biology may have been predisposed and prevalent in the prebiotic pool of RNAs, prior to the advent of Darwinian evolution. We suggest that the one‐step prebiotic chemical process of loop‐closing ligation could have favored the emergence of the first RNA functions. [ABSTRACT FROM AUTHOR]

Electron spin plays a critical role in chemical processes, particularly in reactions involving metal complexes with unpaired electrons. However, more definitive state‐to‐state experiments are needed to better elucidate the role of electronic spin. Herein, we chose nickel (II) 5,10,15,20‐tetrakis(pentafluorophenyl) porphyrin 1 as a catalyst, which allows switching from a low spin to a high spin state of Ni (II) center through an axial pyridine coordination, for electrocatalytic hydrogen evolution reaction (HER). When pyridine is present, we observed β‐hydrogenation of porphyrin through electron transfer followed by proton transfer. In contrast, hydrogen evolution mainly occurs via the concerted proton‐coupling electron transfer without pyridine coordination. Similar distinct spin‐dependent selectivity was also observed in chemical reduction of 1 by CoCp2 with subsequent addition of pyridinium p‐toluenesulfonate. Computational calculations using density functional theory demonstrated that the transition from low spin to high spin state enriches the ligand's electron density after one‐electron reduction, leading to preferential protonation of β‐periphery rather than meso‐position or metal center. [ABSTRACT FROM AUTHOR]

Natural glauconite, as a mixed-layered clay mineral, was subjected to exfoliation processes, producing silicate monolayers or individual sheets that were further modified with methanol into methoxy exfoliated glauconite (Mth/EXG). The structure was assessed as an enhanced adsorbent for three types of common water contaminants, including phosphate (PO43-), safranin-O dye (SFR), and cadmium metal ions (Cd2+). The Mth/EXG structure achieved promising adsorption capacities at the saturation points equal to 269.9 mg/g for PO43-, 312 mg/g for SFR, and 234.5 mg/g for Cd2+ which are significantly better than the reported values for several studied adsorbents of higher costs and complex production procedures. The adsorption processes and the predicted regulated mechanisms in terms of the adsorbate/adsorbent interface were illustrated based on the steric and energetic findings that correspond to the applied monolayer equilibrium model of one energy site. The structure displays active site densities of 82.5 mg/g (PO43-), 136.3 mg/g (SFR), and 83.4 mg/g (Cd2+), which illustrate the high uptake performance of SFR. Also, the steric parameters reflected the suitability of each existing site to be filled with 4 ions of PO43-, SFR, and Cd2+. The adsorption energy (less than 40 kJ/mol) in conjunction with free adsorption energy from D-R model (8–16 kJ/mol) and steric parameters validate the dominant impact of the multi-ionic physical mechanisms (hydrogen bonding and van der Waals forces), in addition to the assistant impact of some weak chemical processes that might be assigned to the formed inner-sphere complex. Also, these reactions all occurred spontaneously with exothermic behaviors according to the thermodynamic functions. Additionally, the structure exhibit significant affinity for the studied pollutants even in the existing of completive chemical including anions, cations and organic molecules. [ABSTRACT FROM AUTHOR]

Chemical transport models (CTM) have wide and profound applications in air quality simulations and managements. However, its applications are often constrained by high computational burdens. In this study, we developed a neural network based CTM model (FastCTM) to efficiently simulate ten air pollutant composition variables, including major PM2.5 species of SO42-, NO3-, NH4+, organic matters and other inorganic components, coarse part of PM10, SO2, NO2, CO and O3. The FastCTM has a principle-informed structure by explicitly encoding atmospheric physical and chemical processes in a basic simulator. Specifically, in the simulator, five neural network modules are proposed to respectively represent five major atmospheric processes of primary emissions, transport, diffusion, chemical reactions and depositions. Given 1-hour initial condition data, the FastCTM is able to simulate future 24-hour concentrations of the ten air pollutants with corresponding meteorology fields and emissions as input. The FastCTM is trained with operational forecast data from a numerical CTM model named Community Multiscale Air Quality (CMAQ) in 2018–2022. The well-trained FastCTM is evaluated comparing to the long-term CMAQ forecast in an independent year 2023, and achieves high agreements with mean RMSE values of 9.1, 11.9, 4.4, 4.0, 48.9 and 10.9 μg/m3 and R2 values of 0.8, 0.81, 0.8, 0.83, 0.9 and 0.7 for PM2.5, PM10, SO2, NO2, CO, and O3. Besides, assessed against hourly site observations of six criteria pollutants, the RMSE values of FastCTM have small relative differences of 4.3 %, 4.2 %, -2.8 %, -1.7 %, -0.3 % and -3.2 % compared to that of CMAQ. The FastCTM model also exhibited reasonable responses of air quality to meteorological variables of air temperature, wind speed and planetary boundary layer height, as well as to input pollutant emissions. Furthermore, due to the principles-oriented structure, internal process analysis could be performed by FastCTM to quantify the specific contribution from each of the five processes for hourly air pollutant concentration changes. In a nutshell, FastCTM has multi-functional advantages in air pollutant concentration simulations, sensitivity analysis and internal process analysis with high computation efficiencies on GPU and accuracy. [ABSTRACT FROM AUTHOR]

A Non-Destructive technique (NDT) based on Active Thermography (AT) is proposed to correlate mechanical properties, process parameters and thermal response for High-Entropy Alloys (HEA) coatings. More in detail, the Pulsed technique is utilised to investigate thermal responses generated by different High-Entropy Alloys (HEA) coatings. In particular, specimens tested in this work are made of several chemical compositions (AlxCoCrCuFeNi and MnCoCrCuFeNi) and are realised by using different Cold Spray temperatures (650°C, 750°C and 850°C), generating coatings with various mechanical properties. This way, results in terms of thermal responses obtained with a Non-Destructive technique are correlated, by means of ANOVA, with the corresponding chemical compositions and process parameters of each specimen. The impact of both roughness and emissivity on the process characterisation was also investigated. [ABSTRACT FROM AUTHOR]

Ever-increasing consumption of plastic products and poor waste management infrastructure have resulted in a massive accumulation of plastic waste in environments, causing adverse effects on climate and living organisms. Although contributing ∼10% towards the total plastic waste management infrastructure, the chemical recycling of plastic waste is considered a viable option to valorize plastic waste into platform chemicals and liquid fuels. Among the various chemical upcycling processes, catalytic hydroprocessing has attracted interest due to its potential to offer higher selectivity than other thermal-based approaches. Heterogeneous catalytic hydroprocessing reactions offer routes for converting plastic waste into essential industrially important molecules. However, the functional group similarities in the plastic polymers frequently constrain reaction selectivity. Therefore, a fundamental understanding of metal selection for targeted bond activation and plastic interaction on solid surfaces is essential for catalyst design and reaction engineering. In this review, we critically assess the structure–activity relationship of catalysts used in the hydroprocessing of plastic waste for the selective production of liquid hydrocarbons. We discuss the significance of C–C/C–O bond activation in plastic waste through active site modulation and surface modification to elucidate reaction networks and pathways for achieving selective bond activation and cleavage. Finally, we highlight current challenges and future opportunities in catalyst design to upcycle real-life plastic waste and produce selective liquid hydrocarbons. [ABSTRACT FROM AUTHOR]