Single Water Research Articles

How Microsolvation Affects the Balance of Atomic Level Mechanism in Substitution and Elimination Reactions: Insights into the Role of Solvent Molecules in Inducing Mechanistic Transitions

Solvents play a crucial role in ion–molecule reactions and have been used to control the outcome effectively. However, little is known about how solvent molecules affect atomic-level mechanisms. Therefore, we executed direct dynamics simulations of the HO−(H2Ow) + CH3CH2Br system to elucidate the dynamics behavior of chemical reactions in a microsolvated environment and compared them with previous gas-phase data. Our results show that the presence of a single water solvent molecule significantly suppresses the direct mechanism, reducing its ratio from 0.62 to 0.18, thereby promoting the indirect mechanism. Spatial effects and prolonged ion–molecule collisions combine to drive this mechanism shift. Among them, water molecules impede the reactive collisions of HO− and CH3CH2Br, while at the same time, the attractive interaction of hydrogen bonds between ions and molecules produces long-lived intermediates that favor the indirect mechanism. On the other hand, microsolvation also affects the reaction preference of the SN2 and E2 channels, which is more conducive to stabilizing the transition state of the SN2 channel due to the difference in solute–solvent interactions, thus increasing the competitiveness of this pathway. These results emphasize the profound influence of solvent molecules in regulating reaction selectivity and underlying microscopic mechanisms in more complex systems.

A Single Water Pipeline Design Considering Pressure-Dependent Consumptions: A New Perspective

A Single Water Pipeline Design Considering Pressure-Dependent Consumptions: A New Perspective

The artificial intelligence-based agricultural field irrigation warning system using GA-BP neural network under smart agriculture.

This work explores an intelligent field irrigation warning system based on the Enhanced Genetic Algorithm-Backpropagation Neural Network (EGA-BPNN) model in the context of smart agriculture. To achieve this, irrigation flow prediction in agricultural fields is chosen as the research topic. Firstly, the BPNN principles are studied, revealing issues such as sensitivity to initial values, susceptibility to local optima, and sample dependency. To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. Secondly, the EGA-BPNN model can overcome the local optimization and overfitting problems of traditional BPNN through the global search ability of GA. Moreover, it is suitable for the irrigation flow prediction task with complex environmental factors in smart agriculture. Finally, comparative experiments compare the prediction accuracy of BPNN and EGA-BPNN using single and dual water level flow prediction models respectively. The results reveal that as the number of nodes in the hidden layer increases, the model's Mean Squared Error (MSE) and Relative Error (RE) show a decreasing trend, indicating an improvement in model prediction accuracy. When the number of nodes in the hidden layer increases from 6 to 16, the MSE of the single and dual water level flow prediction models decreases from 4.53×10-4 to 3.68×10-4 and 2.38×10-4 to 1.66×10-4, respectively. Under a standalone BPNN, the absolute relative error in flow prediction is 1.09%. In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. Furthermore, compared to the BPNN, the EGA-BPNN model exhibits a 2.11 reduction in MSE, further emphasizing the positive impact of introducing the GA on model performance. The research outcomes contribute to more accurate water resource planning and management, providing a more reliable basis for decision-making.

Increased surface temperature at critical heat flux for single water droplet impact with alcohol additives

Increased surface temperature at critical heat flux for single water droplet impact with alcohol additives

IMPACT OF CARBON QUANTUM DOT NANOPARTICLES ON COMBUSTION, PERFORMANCE AND EMISSIONS IN DIESEL/MICROWAVE-ASSISTED CANOLA OIL BIODIESEL BLEND

Usage of biodiesel produced with conventional transesterification methods decreases the conversion of biodiesel from vegetable oil. Microwave-assisted production enables higher reaction efficiency, providing better conversion of vegetable oils. It also causes to obtain poorer characteristics of biodiesel, such as higher viscosity and density. It was aimed to improving the properties of biodiesel with microwave-assisted production and mixing it with nanoparticles to investigate the performance, combustion and emission characteristics. The influences of nanoparticle addition (carbon quantum dot) on engine performance, combustion and emissions have been analyzed in a direct injection CI engine. A single cylinder water cooled CI engine was used in the experiments. Experiments were performed at 4.12, 9.61, 15.10, 20.60 Nm and 2200 rpm. Canola biodiesel was obtained via the microwave-assisted transesterification method and mixed with diesel at the ratio of 20% (B20). 50, 100 and 150 ppm nanoparticle were added to the obtained B20 and tested in a CI engine. Specific fuel consumption (SFC) raised by 2.03%, 4.83%, 4.40% and 1.69% with B20, B20CQD 50 ppm, B20CQD 100 ppm and B20CQD 150 ppm respectively compared that diesel at 15.10 Nm. Remarkable reduction was found on CO, HC with B20CQD 50 ppm, B20CQD 100 ppm and B20CQD 150 ppm according to B20. In addition, an impressive reduction was realized on soot emissions with the usage of nanoprticle addition. But, NOx increased using fuel blends. As a result, the usage of quantum dot nanoparticle improved the poor properties of canola oil biodiesel and test fuels were used easily without modification in a diesel engine.

Tropospheric Fate of Methylhydroxycarbene and the Ability of a Single Water Molecule to Efficiently Promote Its Isomerization into Acetaldehyde.

The ultraviolet (UV) photodissociation of pyruvic acid through the absorption of solar actinic flux generates methylhydroxycarbene (MHC) in the atmosphere. It is recognized that isolated MHC can undergo unimolecular isomerization to form acetaldehyde and vinyl alcohol. However, the rates and mechanism for its possible bimolecular reactions with atmospheric constituents, which can occur in parallel with its unimolecular reaction, is not well understood. Here we investigate the energetics, kinetics, and mechanism of the reaction of MHC with three ubiquitous atmospheric molecules N2, O2, and H2O over the 160 K-380 K temperature range. Our study, at the CCSD(T)/6-311++G(3df,3pd)//M06-2X/6-311++G(3df,3pd) level, reveals that the MHC + N2 encounter is nonreactive, while the MHC + O2 reaction, which leads to CH3CO + HO2 formation, has a rate that is significantly different from previous estimates. For the MHC + H2O reaction, we find that a single H2O molecule is very effective in catalyzing the isomerization of MHC to form predominantly acetaldehyde. An analysis of the computed rate for this reaction indicates that it will be an important source of tropospheric acetaldehyde ̵ a major pollutant and precursor for atmospheric reactive intermediates. Our findings are in sharp contrast to current assessments in the literature that the MHC + H2O reaction is minor. Furthermore, in the MHC + H2O reaction system, we find that due to the presence of the OH group on MHC, the concerted insertion mechanism, which is typically dominant in reactions involving singlet carbenes, is suppressed relative to a hydrogen bond mediated double hydrogen atom transfer mechanism.

Brakes and leverages for reducing the environmental impact of laboratory animal facilities: A case study at the Institut Pasteur.

The Institut Pasteur has set the ambition to encourage all staff to get involved in sustainable development across all departments on campus. The animal facility staff joined the efforts of the sustainable development department to analyse current and future processes and identify potential solutions and related brakes and leverages for the reduction of the animal facilities' environmental impact. The first step was to collect the managers' experience on the local initiatives. Then, the managers attended a workshop to share information on networks and initiatives relevant to the topic and community, and to discuss the use of consumables, including personal protective equipment, single use plastics, bedding, feed, water, chemicals, and waste management. On the topics of interest, local initiatives were specifically detailed to assess their eventual implementation in all the institute's animal facilities, and tasks were set to pursue the managers' efforts in the longer term. A scenario was used to teach how to compare the carbon footprints of washing and disinfection equipment and process and to decide on the design of an animal facility. Finally, a summary is drawn of the brakes and leverages for the reduction of the environmental impact of the institute's animal facilities.

The gas|liquid interface eclipses the liquid|liquid interface for glucose oxidase rate acceleration in microdroplets

The curious chemistry observed in microdroplets has captivated chemists in recent years and has led to an investigation into their ability to drive seemingly impossible chemistries. One particularly interesting capability of these microdroplets is their ability to accelerate reactions by several orders of magnitude. While there have been many investigations into which reactions can be accelerated by confinement within microdroplets, no study has directly compared reaction acceleration at the liquid|liquid and gas|liquid interfaces. Here, we confine glucose oxidase, one of life's most important enzymes, to microdroplets and monitor the turnover rate of glucose by the electroactive cofactor, hexacyanoferrate (III). We use stochastic electrochemistry to monitor the collision of single femtoliter water droplets on an ultramicroelectrode. We also develop a measurement modality to robustly quantify reaction rates for femtoliter liquid aerosol droplets, where the majority of the interface is gas|liquid. We demonstrate that the gas|liquid interface accelerates enzyme turnover by over an order of magnitude over the liquid|liquid interface. This is the first apples-to-apples comparison of reaction acceleration at two distinct interfaces that indicates that the gas|liquid interface plays a central role in driving curious chemistry.

DFT and TST Study of the Calcium Cyanamide Process for Synthesizing Cyanamide and Dicyandiamide

Exploring the microscopic reaction mechanism of dicyandiamide (DCD) synthesis using calcium cyanamide (CaCN2) is highly desirable because of the low conversion of reactants and selectivity of DCD products. DCD synthesis consists of a two-step sequential hydrolysis of CaCN2, followed by dimerization of cyanamide to DCD in an alkaline environment. Density functional theory (DFT) results revealed that the rate-limiting step (RLS) was the formation of a C-N bond between the cyanamide and cyanamide anion in the dimerization of the DCD reaction. Secondary reactions of cyanamide with water, hydrogen sulfide, and DCD were also analyzed. The effects of solvation on the principal and secondary reactions were systematically explored. A single explicit water molecule can significantly lower the free energy barrier of the RLS. Water molecules facilitate the C-N bonding of the reactants in DCD reactions, resulting in a reduction in the free energy barrier of the RLS. The facilitation of double explicit water for the reaction is weaker than that of single explicit water and even yields negative catalysis. The effect of the [OH(H2O)3]− cluster lowering the reaction barrier with the hydrogen-bonding network is the most remarkable, which can alter the reaction path by the direct and indirect involvement of OH− ions. Furthermore, the reaction rate constants were computed by canonical variational theory with the Eckart tunneling correction (CVT/Eckart) and fitted to the Arrhenius expression. The reaction mechanism and kinetics revealed at the microscopic level provide efficient and clean production of DCD with certain theoretical guidance.

Effect of a single water molecule on the conformational preferences of a capped Pro–Gly dipeptide in the gas phase

Herein, we have investigated the effect of microhydration on the secondary structure of a capped dipeptide Boc-DPro-Gly-NHBn-OMe (Boc = tert-butyloxycarbonyl, Bn = Benzyl), i.e., Pro–Gly (PG) with a single H2O molecule using gas-phase laser spectroscopy combined with quantum chemistry calculations. Observation of a single conformer of the monohydrated peptide has been confirmed from IR-UV hole-burning spectroscopy. Both gas-phase experimental and theoretical IR spectroscopy results confirm that the H2O molecule is inserted selectively into the relatively weak C7 hydrogen bond (γ-turn) between the Pro C=O and NHBn N–H groups of the peptide, while the other C7 hydrogen bond (γ-turn) between the Gly N–H and Boc C=O groups remains unaffected. Hence, the single H2O molecule in the PG⋯(H2O)1 complex significantly distorts the peptide backbone without appreciable modification of the overall secondary structural motif (γ–γ) of the isolated PG monomer. The nature and strength of the intra- and inter-molecular hydrogen bonds present in the assigned conformer of the PG⋯(H2O)1 complex has also been examined by natural bond orbital and non-covalent interaction analyses. The present investigation on the monohydrated peptide demonstrates that several H2O molecules may be required for switching the secondary structure of PG from the double γ-turn to a β-turn that is favorable in the condensed phase.

Numerical study of breakdown voltage calculation and discharge characteristics of millimeter-level short air gap with a single water droplet

Abstract Water droplets in the short air gap significantly affect the breakdown voltage. Currently, there is a lack of computational studies on the breakdown voltage and discharge process of short air gaps containing water droplets. In this paper, we establish a plasma dynamics-based model for the discharge in a millimeter-scale short air gap containing a single water droplet under ambient pressure and propose a breakdown voltage calculation method. We discuss typical discharge processes, calculate breakdown voltages for different gap lengths, validate the model through discharge phenomena and breakdown voltage, and analyze the impact of droplet parameters on discharge characteristics. The results show that negative streamer discharge in the cathode-side gap and positive streamer discharge in the anode-side gap occur sequentially, consistent with reported experimental results, with the positive streamer discharge being the primary process leading to gap breakdown. The average error rate between the calculated breakdown voltages for 4–8 mm gaps and reported experimental results is 4.85%, indicating good agreement. The observed streamer branching phenomenon may explain the difference between calculated and experimental breakdown voltages for the 10 mm gap. Under the influence of surface charges, low-conductivity droplets cause the discharge channel to propagate along the droplet surface. In contrast, high-conductivity droplets confine the discharge channel within the two gap sections. Increasing droplet diameter reduces breakdown voltage, with a critical value where the reduction becomes significant. Increased droplet deformation degree raises the breakdown voltage. This effect is related to the deviation of the positive streamer from the axial development and the reverse streamer generated on the droplet’s surface in different cases. The closer the droplet is to the electrode, the higher the breakdown voltage. The discharge is facilitated by the streamers generated on the droplet’s lower surface when it is close to the anode.

Using environmental DNA to assess the response of steelhead/Rainbow Trout and Coastrange Sculpin populations to postfire debris flows in coastal streams of Big Sur, California

Abstract Objective Debris flows are among the most extreme disturbances to streams and are predicted to become more frequent under climate change. We assessed the response of steelhead/Rainbow Trout Oncorhynchus mykiss (hereafter, collectively referred to as O. mykiss) and Coastrange Sculpin Cottus aleuticus populations to major postfire debris flows in two small coastal basins of California using noninvasive environmental DNA (eDNA) sampling. Methods We analyzed water samples from disturbed reaches for eDNA in the first two summers after debris flows. In Big Creek, all Coastrange Sculpin habitat was disturbed by debris flows, but a major tributary occupied by O. mykiss was not affected. In Mill Creek, all available habitat for both species was disturbed. We also sampled two unburned basins as undisturbed reference streams. Result In Big Creek, O. mykiss eDNA was detected in all water samples during both years, and concentrations in some samples approached the lowest concentrations in the reference streams. Coastrange Sculpin eDNA was detected only in a single water sample in the first year and was not detected in the second year. In Mill Creek, neither species was detected in the first year, but during the second year, O. mykiss eDNA was detected at very low concentrations in 40% of samples and Coastrange Sculpin eDNA was detected in a single sample. Conclusion Our results indicate that O. mykiss and Coastrange Sculpin either survived in or quickly reoccupied the disturbed reaches from within the basins. However, the detection rates for cases in which all habitat for a species in a basin was affected by debris flows indicate that abundances were very low, suggesting that persistence may be uncertain unless there is successful reproduction or immigration. Finally, eDNA appears to be effective for monitoring sensitive fish populations after a major disturbance; however, detection rates in individual samples may be low and require appropriate sampling designs to achieve the desired detection probability. Abstract Impact statement Monitoring of fish populations after disturbances is critical, yet traditional methods could have negative effects. Analysis of environmental DNA in water samples was able to detect the presence of Coastrange Sculpin and threatened steelhead/Rainbow Trout within 2 years after major debris flows in two small basins of California.

Boosting Hydrogen Production: Non-Noble Metal Catalysts Optimize Electrodes in Anion Exchange Membrane Water Electrolysis

As the world transitions to renewable energy sources, efficient energy storage is crucial for managing power fluctuations and decarbonize crucial high temperature processes. Achieving grid balance and optimizing renewable energy capacity requires innovative solutions. One promising option is the conversion of electrical energy into hydrogen through Anion Exchange Membrane Water Electrolysis (AEM-WE).AEM-WE combines high hydrogen production rates per electrode area and little production site footprint of Proton Exchange Membrane Water Electrolysis (PEM-WE) with cost-effectiveness of non-noble electrode materials utilized in Alkaline Water Electrolysis (A-WE). To further optimize AEM-WE, it is essential to improve hydrogen production while reducing material costs. This can be achieved through innovative approaches to electrocatalyst and electrode design. However, developing cost-effective catalysts that combine superior efficiency and robustness in aqueous environments, ideally in alkaline conditions, remains a big challenge. In this work, two electrode preparation approaches are investigated. For the anodic OER a corrosion synthesis is been developed to form highly active NiFe-layered double hydroxide (LDH) structures on nickel non-woven porous transport layers (PTL). A highly active cell can be combined with a cathodic HER catalyst, prepared by electrochemical deposition Ni-S on a stainless steel non-woven PTL.In single cell AEM water electrolysis using 1 M KOH-solution utilizing the prepared NiFe-LDH anode and Pt/C cathode, 2.7 A/cm² at 2 V were achieved, surpassing commercially available powder catalysts like NiFe-oxide. Comparative analysis of Ni-S cathode with NiFe-LDH, integrated into a membrane electrode assembly demonstrated superior AEM-WE performance, outperforming the mentioned platinum on carbon catalysts. Electrochemical impedance spectra indicated higher charge transfer activity of Ni-S cathode compared to Pt/C. Importantly, the electrodes prepared in this study exhibited stability under accelerated electrochemical stress tests for 1000 cycles.These approaches provide a simple, inexpensive, scalable and therefore industry-relevant fabrication method with improved active areas and excellent catalytic activity during AEM water electrolysis. Figure 1

Reversible Performance Dynamics in PEM Water Electrolysis: An Electrochemical Study

In Proton Exchange Membrane Water Electrolysis (PEMWE) systems, a notable phenomenon occurs following voltage transitions from low to high, such as after a shutdown and subsequent startup: the cell performance initially improves, higher currents are achieved, then gradually returns to baseline (s. Figure 1). This reversible performance behavior remains poorly understood despite documentation in the literature, see e.g., ref. [1, 2], and laboratory observations. However, distinguishing between reversible and irreversible performance losses is essential for accurate degradation assessments, emphasizing the need for detailed exploration of the underlying mechanisms.The activity and stability of iridium-based electrocatalysts, crucial for the oxygen evolution reaction (OER) within PEMWE systems, depend on their iridium oxidation state, which varies with the applied voltage. While studies typically explore these oxidation state changes in aqueous model systems such as rotating disk electrodes (RDE) and scanning flow cells (SFC), the focus is often more on stability than on activity changes [2]. However, the current understanding of the catalysts' dynamic performance in PEMWE full-cell configurations remains incomplete.In this study, a systematic experimental investigation of the reversible performance behavior of PEMWE cells was conducted. Tests were performed with single PEM water electrolysis cells with an active area of 4 cm², using a Nafion™ 115 catalyst-coated membrane. The anode and cathode loadings were 2.0 mgIr/cm² and 1.0 mgPt/cm², respectively. The voltage-driven experiments aimed to identify the voltage level that triggers performance recovery, evaluate the significance of this improvement depending on the low-voltage level, and assess how the duration of low-voltage phases affects recovery.The results demonstrated that a recovery effect occurred once the low-voltage level dropped below 1.5 V, with further enhancements in recovery observed as the voltage continued to decrease. This effect was evident even with a brief holding time of 0.1 s at the lower voltage level. The reversible recovery is primarily driven by increased kinetics, likely influenced by voltage-dependent changes in iridium oxidation states. These observations are strongly supported by a robust alignment between the experimental data and a novel dynamic 0D model, which links iridium oxidation/reduction processes to performance metrics.By investigating the dynamic behavior of iridium-based electrocatalysts in full-cell configurations, this research enriches the understanding of reversible performance phenomena in PEMWE cells. It provides an essential foundation for future studies to understand the mechanisms behind these reversible phenomena.We gratefully acknowledge the financial support of the HyThroughGen project (BMBF 03HY108C) and the Deriel project (BMBF 03HY122A).

An Extendible Multiphysics Model of a Single Water Electrolysis Cell

The important role that renewable hydrogen has in the energy transition is undeniable given the capability of decarbonizing sectors difficult to electrify acting as the link between electrical energy from renewable sources and molecules for future energy systems. Therefore, improvement of the efficiency, cost and durability of electrolyzer systems is key. The discovery of new materials is one of the research areas in which a lot of effort is focused given that finding more electrochemically active materials allows to reduce overvoltages improving the electrical performance of the electrolyzers. The requirement for these materials is also that they are durable under operating conditions and cheap to produce in order to achieve improvements in all relevant aspects of the technology.In water electrolysis systems, kinetics, heat management, gas quality, among others, are relevant aspects to understand in order to achieve performance gains. In this line, computational modeling plays an important role in analyzing and understanding the performance of such systems, as well as the effect that different variables have on it. Given the nature of the water electrolysis process, a multiphysics approach is necessary to account for electrochemical, mass transfer, thermal and fluidic processes, as well as their interactions.Computational models and digital twins are gaining great momentum in electrolysis systems applications, but its availability is limited as its development requires of deep physical knowledge of the different phenomena and their interactions, or large amounts of data. When data is available data-driven models are very useful but the results are not easy to extrapolate when a change in design or materials happens. Therefore, physics-based modelling is a useful tool, as characterization at small scale and short-term is the first step in the discovery of new materials, which allows to obtain physical parameters that act as input for the computational model. This way it is clear that the advantage of developing a physical model is that the model becomes generic, which means that by changing the corresponding design parameters, the performance of a different design can be analyzed.The current project aims to develop an extendible physics-based model of a single water electrolysis cell. This development will allow to modify different parameters or operating conditions of the cell design and analyze the effect of those changes in the performance. Additionally, the extendible nature allows for its use as single element for analyses in 1D if desired.The model, developed in OpenModelica, is capable of reproducing the polarization curve of an electrolysis cell, the temperature change between inlet and outlet, the gas crossover and the pressure loss.

Mathematical Approach for Directly Solving Air–Water Interfaces in Water Emptying Processes

Emptying processes are operations frequently required in hydraulic installations by water utilities. These processes can result in drops to sub-atmospheric pressure pulses, which may lead to pipeline collapse depending on soil characteristics and the stiffness of a pipe class. One-dimensional mathematical models and 3D computational fluid dynamics (CFD) simulations have been employed to analyse the behaviour of the air–water interface during these events. The numerical resolution of these models is challenging, as 1D models necessitate solving a system of algebraic differential equations. At the same time, 3D CFD simulations can take months to complete depending on the characteristics of the pipeline. This presents a mathematical approach for directly solving air–water interactions in emptying processes involving entrapped air, providing a predictive tool for water utilities. The proposed mathematical approach enables water utilities to predict emptying operations in water pipelines without needing 2D/3D CFD simulations or the resolution of a differential algebraic equations system (1D model). A practical application is demonstrated in a case study of a 350 m long pipe with an internal diameter of 350 mm, investigating the influence of air pocket size, friction factor, polytropic coefficient, pipe diameter, resistance coefficient, and pipe slope. The mathematical approach is validated using an experimental facility that is 7.36 m long, comparing it with 1D mathematical models and 3D CFD simulations. The results confirm that the derived mathematical expression effectively predicts emptying operations in single water installations.

Effects of varied inundation characteristics on early life stages of a salt marsh plant

Tidal inundation is a major stress in salt marshes that regulates the patterns of plant distribution and the associated functions provided by vegetation communities. Usually, frequency is used to represent inundation intensity and can be estimated using elevation. However, frequency is only a statistical indicator of tidal inundation conditions during a given period, which ignores many details of tidal inundation characteristics based on a single tidal event. On the scale of a single tidal event, duration and water depth are important characteristics for describing inundation conditions, which vary along the elevation gradient. The frequency of tidal events of a specific duration and water depth also varied. To unravel the impact of varied inundation characteristics on the key life stages of a foundation plant, we designed an experiment with varied inundation treatments of different frequencies, durations, and depths. Our results showed that the frequency, duration, and depth of inundation events significantly influenced seed emergence, seedling survival, and growth. Stress can be strengthened by a higher frequency with a longer duration and larger depth. Among these factors, frequency had a dominant impact, followed by duration and water depth. Specifically, there is a trade-off between frequency, duration, and depth, suggesting that an inundation event with shallower depth and/or shorter duration would reduce the stress from higher frequency. The findings fill a gap in the loss of details of varied inundation characteristics on plant establishment on a fine scale. Further, it will help explicit inundation stress more accurately and clearly and provide important implications for stress relief solutions in coastal ecological restoration.

Releasing Preferentially Sequestered Na+ from Its Confinement by Beauvericin: A Single Water Molecule is the Accomplice.

Beauvericin (Bv) is a natural ionophore capable of transporting ions across biological membranes. Mass spectrometry and infrared spectroscopy show that Bv specifically captures sodium ions with a unique 6-fold coordination in its cavity, which illustrates how ions are carried through the membrane. But with no reports on how ions are released from Bv at the interface, a complete picture of the ion transport process has yet to be established. In this study, conformational changes of Bv complexes with alkali metal ions upon hydration were investigated using infrared spectroscopy and computational calculations. The addition of a single water molecule to Na+Bv pries the ion away from the 6-fold cavity to the amide face of the ionophore, evidence of the first step of ion release. In contrast, there is little impact on the other M+Bv complexes, with the ion bound to the three carbonyl groups on the amide face. Analysis of the carbonyl C═O and water OH stretching modes reveals the competition between ion-ionophore, ion-water, and water-ionophore interactions and demonstrates how water actively participates in ion transport by initiating ion release from the ionophore.

Chitosan supported hetero-metallic bio-nanocomposites for paracetamol removal from homogeneous solutions and heterogeneous mixtures with focused antibacterial studies

Biopolymers infused with bimetallic nanoparticles exhibit a wide range of functionalities necessary for efficiently eliminating diverse water contaminants. However, the protracted production process requires further exploration. As such, present study seeks to optimize microwave-assisted technique for the facile synthesis of cross-linked chitosan (CTS) supported bimetallic-oxide nanoparticles, specifically zinc oxide (ZnO) and iron-oxide (Fe3O4), denoted as CTS-TTP/Zn-Fe. The primary objective is to investigate the efficacy of these beads in the removal of Paracetamol (PCM) from single and complex water matrices while also assessing their antibacterial properties. Characterization includes chemical composition, surface structures, thermal stability, and magnetic properties. The experimental results demonstrated that CTS-TPP/Zn-Fe beads achieved a remarkable PCM removal efficiency of ~99 % (qm = 4.98 mg g−1), with a Zn:Fe mole ratio of 1:1. The experimental data showed good applicability with Freundlich isotherm and chemisorption-supported rate models (R2 > 0.9). To evaluate the long-term viability and practicality of these beads, three crucial field applicability tests were conducted. These encompassed competition studies with other pharmaceuticals, desorption investigations for repeated use, and efficiency evaluations in an ionic solution. Collectively, this research provides a comprehensive understanding, spanning from material design to practical applications, with potential relevance for large-scale wastewater treatment when coupled with appropriate flux control measures.

Accurate nuclear quantum statistics on machine-learned classical effective potentials.

The contribution of nuclear quantum effects (NQEs) to the properties of various hydrogen-bound systems, including biomolecules, is increasingly recognized. Despite the development of many acceleration techniques, the computational overhead of incorporating NQEs in complex systems is sizable, particularly at low temperatures. In this work, we leverage deep learning and multiscale coarse-graining techniques to mitigate the computational burden of path integral molecular dynamics (PIMD). In particular, we employ a machine-learned potential to accurately represent corrections to classical potentials, thereby significantly reducing the computational cost of simulating NQEs. We validate our approach using four distinct systems: Morse potential, Zundel cation, single water molecule, and bulk water. Our framework allows us to accurately compute position-dependent static properties, as demonstrated by the excellent agreement obtained between the machine-learned potential and computationally intensive PIMD calculations, even in the presence of strong NQEs. This approach opens the way to the development of transferable machine-learned potentials capable of accurately reproducing NQEs in a wide range of molecular systems.