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A molecular dynamics study on coalescence-induced jumping of moving and static droplets
In this paper, molecular dynamics simulations are employed to investigate the coalescence-induced jumping behavior of moving and stationary droplets at the nanoscale on superhydrophobic surfaces. The results show that the initial velocity of the droplets significantly influences the coalescence time and jumping characteristics. As the initial velocity increases, the coalescence time decreases, and the horizontal velocity increases, suggesting that controlling the initial velocity can adjust droplet motion behavior. In terms of energy conversion, the total energy conversion rate remains relatively constant at lower initial velocities but increases significantly as the velocity rises. This is primarily due to the reduced coalescence time and viscous dissipation caused by the increased initial kinetic energy, allowing more energy to be converted into the kinetic energy of jumping. The energy conversion rate in the horizontal direction increases with initial velocity, while in the vertical direction, it tends to decrease. This study deepens the understanding of coalescence-induced jumping phenomena at the nanoscale and provides a theoretical basis for engineering applications, showing that droplet behavior can be effectively modulated by controlling the initial velocity.
Structural and dynamical properties of aqueous NaCl brines confined in kaolinite nanopores
Quantifying thermodynamics, structural, and dynamical properties of brine confined in clay pores is critical for a variety of geo-energy applications, including underground hydrogen storage (UHS) and carbon capture and sequestration (CCS). Atomistic molecular dynamics simulations are applied here to study aqueous NaCl brines within 10-Å kaolinite slit pores. NaCl concentrations are chosen at 5, 10, 12.5, and 15 wt. %, all below the solubility limit and high enough to provide statistically relevant information. The distribution of the ions within the nanopores is found not to be homogeneous. Explicitly, Na+ cations, preferentially attracted to the siloxane surface, accumulate in regions with low water density, whereas Cl− anions, attracted to the gibbsite surface of kaolinite, are found within the hydration layers. Confinement affects the properties of ions, with ion pairing being more pronounced within the pore than in bulk aqueous solutions at similar temperatures, pressures, and compositions. Conversely, the ions affect the properties of confined water. For example, the lifetime of water–water hydrogen bonds in confinement is shortened within the hydration shells; increasing salinity from 5 to 12.5 wt. % reduces the likelihood of water density fluctuations near the kaolinite surfaces, although when the NaCl concentration rises from 12.5 to 15 wt. %, Cl− anions enhance the likelihood of density fluctuations for the hydration layer near the gibbsite surface. The simulated molecular trajectories are studied further to extract diffusion coefficients. While confinement in the kaolinite nanopore reduces the mobility of all species, non-monotonic trends are observed as a function of salt concentration. The trends seem associated with the likelihood of ion pairing. Furthermore, the diffusion coefficients for the cations are predicted to be higher than those for the anions, which is contrary to what is typically observed in bulk brines. Because density fluctuations are correlated with properties such as the solubility of gases in confined water, our observations may have important implications for geo-energy applications such as UHS and CCS.
Real-time propagation of adaptive sampling selected configuration interaction wave functions
We have developed a new time propagation method, time-dependent adaptive sampling configuration interaction (TD-ASCI), to describe the dynamics of a strongly correlated system. We employ the short iterative Lanczos method as the time-integrator, which provides a unitary, norm-conserving, and stable long-time propagation scheme. We used the TD-ASCI method to evaluate the time-domain correlation functions of molecular systems. The accuracy of the correlation function was assessed by Fourier transforming into the frequency domain to compute the dipole-allowed absorption spectra. The Fourier transform (FT) has been carried out with a short-time signal of the correlation function to reduce the computation time, using an efficient alternative FT scheme based on the ESPRIT signal processing algorithm. We have applied the TD-ASCI method to prototypical strongly correlated molecular systems and compared the absorption spectra to spectra evaluated using the equation of motion coupled cluster method with a truncation at the singles, doubles, and triples level.
Modeling the time-resolved Coulomb explosion imaging of halomethane photodissociation with <i>ab initio</i> potential energy curves
We present an effective theoretical model to simulate observables in time-resolved two-fragment Coulomb explosion experiments. The model employs the potential energy curves of the neutral molecule and the doubly charged cation along a predefined reaction coordinate to simulate the photodissociation process followed by Coulomb explosion. We compare our theoretical predictions with pump–probe experiments on iodomethane and bromoiodomethane. Our theory successfully predicts the two reaction channels in iodomethane photodissociation that lead to I(P3/22) and I*(P1/22) products, showing excellent agreement with experimental delay-dependent kinetic energy release signals at large pump–probe delays. The theoretical kinetic energy release at small delays depends significantly on the choice of ionic states. By accounting for internal rotation, the kinetic energies of individual fragments in bromoiodomethane align well with experimental results. Furthermore, our theory confirms that two-fragment Coulomb explosion imaging cannot resolve different spin channels in bromoiodomethane photodissociation.
How many distinct and reliable multireference diagnostics are there?
Economical multireference (MR) diagnostics are essential for high-throughput computational studies, enabling the rapid and accurate identification of molecules affected by nondynamic correlation within large molecular datasets. Although various MR diagnostics have been proposed, benchmarking studies that help identify the criteria for an effective diagnostic are still scarce. In this article, we examine a wide range of correlation measures to evaluate their potential as MR diagnostics. We identify a small set of valid size-intensive correlation measures based on maximum metrics, exhibiting similar predictive values. Among these, we highlight INDmax, which offers an easy interpretation: it captures the largest deviation of a natural orbital occupancy from the boundary values corresponding to a single-reference wave function. No energy-based correlation measure was found suitable for constructing MR diagnostics. Finally, we demonstrate how average correlation measures, although not suitable as MR diagnostics, can provide a more comprehensive view of electron correlation within the molecule.
Isotopic separation in mixed clusters of molecular hydrogen
We investigate mixed (50/50) clusters of parahydrogen and orthodeuterium at low temperatures, by means of quantum Monte Carlo simulations. Our results provide evidence of liquid-like behavior and partial isotopic separation in a cluster of 640 molecules, at temperature T = 10 K. As the temperature is lowered below ∼6 K, crystallization occurs, with no indication that the liquid phase is more resilient at low temperatures in a mixed cluster. Isotopic separation is therefore predicted to take place at low temperatures only through the slow process of molecular self-diffusion in a crystalline matrix.
Structure of molten ytterbium aluminum garnet
Rare earth aluminum garnets are important materials in optical, dielectric, and thermal barrier applications. To advance the understanding of their melt processing and glass forming ability, we report the atomic structure of molten Yb3Al5O12 over 1770–2630 K, which spans the equilibrium and supercooled liquid regimes. The melt density at Tm = 2283 K is 5.50 g cm−3, measured via silhouette imaging of electrostatically levitated drops over 1010–2420 K. Four separate structure measurements were made with aerodynamically levitated melts using x-ray and neutron diffraction with isotope substitution of Yb (172Yb, 174Yb, or natYb). Empirical potential structure refinement models were developed, which are in excellent agreement with the experiments. Coordination environments for Al–O are predominantly 4- and 5-coordinate, with a mean coordination of nAlO = 4.43(8), while Yb–O environments mostly range from 5- to 8-coordinate, with nYbO = 6.26(8). The cation–oxygen polyhedra are connected primarily by corner-sharing, with edge-sharing constituting up to ∼1/3 of the connectivity among polyhedra with Yb or higher-coordinated Al–O. Structurally, the –Al–O– network in molten Yb3Al5O12 appears conducive to glass formation: nOAl = 1.85(3), there are 1.86 AlOx–AlOx connections per Al atom (e.g., a mixture of Q3 and Q4 units), and the modal ring size is six cations. These characterize a network that is somewhat less constrained compared to SiO2 glass, yet Yb3Al5O12 cannot be quenched into crystal-free glass. Aluminum garnet compositions with larger rare earth cations do form glass, so these characterizations help reveal the structural characteristics corresponding to the limit of glass forming ability in rare earth aluminates.
Influence of defect-state on the carrier dynamics in MAPbI3 polycrystalline films
In this paper, a transient absorption microscope with submicron resolution is used to detect the internal and grain boundary regions of the prepared polycrystalline thin film grains, and the obtained transient absorption spectra are subjected to singular value decomposition and global fitting. The contributions of hot carriers, cooled carriers, and defect-trapped carriers to the transient absorption signals and the dynamic evolution of the carriers among themselves are elucidated. By comparing the carrier dynamics taking place at the boundary and internal regions, we find that the benign shallow defect state in the grain boundary region has a positive effect on accelerating the cooling of hot carriers, while the deep energy level defects induce excited state absorption signals. This study provides a basis for further understanding the effect of grain boundary defects on the performance of polycrystal perovskite devices.
Publisher’s Note: “Vibrational signatures of dynamic excess proton storage between primary amine and carboxylic acid groups” [J. Chem. Phys. 160, 094311 (2024)]
A randomized controlled trail comparing the visual stylet and visual laryngoscope for transoral single lumen tracheal intubation
Identifying risk factors and predicting long COVID in a Spanish cohort
Enhancing accuracy in modelling highly multicollinear data using alternative shrinkage parameters for ridge regression methods
PKM2 accelerated the progression of chronic fatigue syndrome via promoting the H4K12la/ NF-κB induced neuroinflammation and mitochondrial damage
Exploring blood immune cells in the protective effects of gut microbiota on rheumatic heart disease based on Mendelian randomization analysis
Comparative analysis of daily global solar radiation prediction using deep learning models inputted with stochastic variables
Abstract Photovoltaic power plant outputs depend on the daily global solar radiation (DGSR). The main issue with DGSR data is its lack of precision. The potential unavailability of DGSR data for several sites can be attributed to the high cost of measuring instruments and the intermittent nature of time series data due to equipment malfunctions. Therefore, DGSR prediction research is crucial nowadays to produce photovoltaic power. Different artificial neural network (ANN) models will give different DGSR predictions with varying levels of accuracy, so it is essential to compare the different ANN model inputs with various sets of meteorological stochastic variables. In this study, radial basis function neural network (RBFNN), long short-term memory neural network (LSTMNN), modular neural network (MNN), and transformer model (TM) are developed to investigate the performances of these algorithms for the DGSR prediction using different combinations of meteorological stochastic variables. These models employ five stochastic variables: wind speed, relative humidity, minimum, maximum, and average temperatures. The mean absolute relative error for the transformer model with input variables as average, maximum, and minimum temperatures is 1.98. ANN models outperform traditional models in predictive accuracy.
Random mechanisms govern bacterial succession in bioinoculated beet plants
Abstract Plant colonization by microbes is an example of succession, with its distinct phases differing in community structure and diversity. This process needs to be studied to improve bioinoculation strategies. Here, we show that, regardless of bioinoculation, soil type and plant genotype, bacteria colonize the rhizosphere and tissues of axenic beets in two phases associated with taproot development. Communities remained stable after five weeks of growth in soil. Time, soil type and genotype determined community structure both in the rhizosphere and in the endosphere. Inoculation changed the community structure, and members of Pseudomonadota and Bacillota were recruited by beets. Axenic beet colonization runs through phases similar to colonization of a glacier forefront, and bacteria are recruited mostly randomly. The transition from the early to late phase involves a decrease in the bacterial load in plant tissues, which may be linked to plant growth and the arrest of bacterial cell division. Therefore, early inoculation seems to be favourable. Five weeks of growth in soil enabled formation of stable bacterial communities in both the rhizosphere and the endosphere. The influence of inoculation seems to be indirect, probably due to microbe-microbe interactions.
Generalizing the similitude approach for laboratory astrophysics through equivalence symmetries for the example of radiative waves
Mathematical analysis of scrub typhus seasonal infection with re-scaled transmission rate considering Northeast India reported data from 2010 to 2022
Effect of splitting the sub-lethal dose of glyphosate on plant growth shikimate pathway-related metabolites and antioxidant status in faba beans
Abstract Glyphosate exerts its herbicidal activity by inhibiting the shikimate pathway, the main source of many primary and secondary metabolites. Application of a low dose of glyphosate to faba bean plants was effective in controlling Orobanche crenata infestation, but some toxic effects on host plants can occur. Splitting the low glyphosate dose can serve as a mitigation strategy to reduce the host toxicity. Under parasitic-free conditions, a greenhouse experiment was conducted during two seasons to study the effect of dividing the recommended glyphosate dose (170 g a.i. ha-1) into two-five sprays on the growth, shikimate-related metabolites, and antioxidant status of three faba bean varieties. After 40 days, splitting treatments tended to cause cumulative inhibition effects on the growth and productivity traits of faba beans depending on the tested varieties, seasons, and the number of sprays applied. The maximum reduction effect was noticed for twice- sprayed treatment in the first season and for five-sprayed treatment in the second one. The cumulative effect of splitting glyphosate treatments on the shikimate pathway metabolites and the antioxidant status was measured after a week of spraying. Splitting treatments induced great increases in shikimic acid and phenylalanine contents compared with control. These treatments continued to exert their oxidative stress on faba bean plants by reducing antioxidant activity and antioxidant compounds such as total phenolics, flavonoids, and the detected phenolic acids (p-hydroxybenzoic, syringic, vanillic, coumaric, and ferulic). A significant increase in the activities of antioxidant enzymes (superoxide dismutase, peroxidase, and polyphenol oxidase) was recorded for all splitting treatments.