Interaction Parameters Research Articles

Quantifying surface wettability in textured surfaces using two-dimensional pseudo-potential multiphase lattice Boltzmann model

Surface wettability plays a critical role in microfluidic applications, enabling enhanced fluid flow control, minimizing sample waste, and improving efficiency across various fields, including drying technology, food processing, chemical manufacturing, and ­environmental engineering. This study presents a numerical investigation of surface wettability on textured surfaces utilizing a two-dimensional (2D) pseudo-potential multiphase lattice Boltzmann method (LBM) with a D2Q9 model. The analysis is conducted for a range of solid-fluid interaction parameters (Gads ), varying between −2.50 and −1.40. Initially, the equilibrium state of a water droplet on a flat surface is simulated for different interaction parameters to validate the accuracy of the numerical model. Subsequently, micropillars are introduced on the bottom wall of the surface with varying heights and spacings to create hydrophobic and superhydrophobic textures, resulting in enhanced contact angles. The wettability of these surfaces is analyzed by placing a water droplet with a radius of 30 lattice units at the center of a computational domain sized 200 × 200 lattice units. The findings reveal that increasing the interaction parameter on textured surfaces significantly reduces the contact area between the droplet and the solid surface due to the momentum redirection effect, thereby increasing surface surface wettability. Similarly, greater spacing between micropillars enhances surface surface wettability. The simulated contact angles for various interaction strengths have been qualitatively validated with previously reported results, confirming the robustness of the present numerical model.

Ab Initio Rotational and Vibrational Spectroscopy of C3H5 Radicals at the Coupled Cluster Level.

Combustion and pyrolysis processes of allene and propyne are known to involve radicals with the structural formula C3H5, the most stable of which is the classic resonance-stabilized allyl radical. In addition to allyl, four other isomers of C3H5 are possible: the propene derivatives Z-1-propenyl, E-1-propenyl, and 2-propenyl, as well as the cyclopropane derivative cyclopropyl. Among these 5 species, the allyl radical has been extensively studied both theoretically and spectroscopically; however, little is known about the spectroscopy of the cyclopropyl radical, and virtually no experimental spectroscopic data are available for the remaining three. Here, we carry out an ab initio investigation of the C3H5 radicals at the coupled cluster level of theory with a focus on computing the spectroscopic parameters relevant for pure rotational and rotationally resolved vibrational spectroscopy. The rotational constants, dipole moments, spin-spin tensors, and Fermi contact parameters are evaluated at the CCSD(T)/cc-pwCVQZ level of theory, while vibrational properties such as vibration-rotation interaction parameters and centrifugal distortion constants are calculated at the frozen-core CCSD(T)/ANO1 level. Vibrational analysis was carried out using second-order vibrational perturbation theory with an explicit treatment of resonances. Finally, the inversion tunneling potential in cyclopropyl as well as the methyl internal rotation potentials in the 1- and 2-propenyl isomers are computed and relevant spectroscopic parameters for modeling their resultant tunneling splittings are derived. Results from the calculations compare favorably with the extensive body of spectroscopic literature on the allyl radical, giving confidence that the computed parameters for the remaining isomers will be useful for guiding the interpretation of future high-resolution experimental spectroscopy of these radicals.

Study on the Prediction Model of Swelling Response of EPDM in Liquid Mixture by Using the Modified Flory–Huggins Interaction Parameter (χHSP)

ABSTRACTThe swelling responses of ethylene propylene diene monomers (EPDM) in cyclohexane/xylene (CYH/X) and cyclohexane/cyclohexanone (CYH/C) binary systems were studied by using equilibrium swelling method, and the co‐solvent effect was further analyzed. The results show that the swelling responses of EPDM in CYH/X and CYH/C binary systems are significantly different. EPDM exhibits more obvious co‐solvent effect in CYH/C binary system which may be generated by the self‐association of cyclohexanone. In addition, the modified Flory–Huggins interaction parameter (χHSP) calculated by three‐dimensional solubility parameters (HSP) was used to establish the prediction model from the correlation with the swelling ratio (qm) of EPDM. The prediction model can be represented by an exponential equation with high degree of fitting, and the calculated qm values from this model are comparable with the experimental values. The prediction model has been employed to evaluate the swelling responses (q‐fitting) of EPDM in IRM 903 test oil/ethanol mixtures theoretically. It reveals that lower χHSP values result in higher swelling responses of EPDM, following the same rule of q–χHSP. Potentially, the prediction model based on χHSP provides a new way to determine the swelling responses of EPDM based rubber parts in any possible fluids.

A comparative study of LQU and LQFI in general qubit-qutrit axially symmetric states.

We derive the compact closed forms of local quantum uncertainty (LQU) and local quantum Fisher information (LQFI) for hybrid qubit-qutrit axially symmetric (AS) states. This allows us to study the quantum correlations in detail and present some essentially novel results for spin-(1/2, 1) systems, the Hamiltonian of which contains ten independent types of physically important parameters. As an application of the derived formulas, we study the behavior of these two quantum correlation measures at thermal equilibrium. New features are observed in their behavior that are important for quantum information processing. Specifically, cascades of sudden changes in the behavior of LQU and LQFI are found with a smooth change in temperature or interaction parameters. Interestingly, in some cases, sudden transitions are observed in the behavior of LQU but not in LQFI, and vice versa. Moreover, our compact formulas open a way to apply them to other problems, for instance, when investigating the environmental effects on quantum correlations in open systems.

Plasma Optimization as a Novel Tool to Explore Plant–Microbe Interactions in Climate Smart Agriculture

Plasma treatment has emerged as a promising tool for manipulating plant microbiomes and metabolites. This review explores the diverse applications and effects of plasma on these biological systems. It is hypothesized that plasma treatment will not induce substantial changes in the composition of plant microbiomes or the concentration of plant metabolites. We delve into the mechanisms by which plasma can regulate microbial communities, enhance antimicrobial activity, and recruit beneficial microbes to mitigate stress. Furthermore, we discuss the optimization of plasma parameters for effective microbiome interaction and the role of plasmids in plant–microbe interactions. By characterizing plasmidome responses to plasma exposure and investigating transcriptional and metabolomic shifts, we provide insights into the potential of plasma as a tool for engineering beneficial plant–microbe interactions. The review presented herein demonstrates that plasma treatment induces substantial changes in both microbial community composition and metabolite levels, thereby refuting our initial hypothesis. Finally, we integrate plasmidome, transcriptome, and metabolome data to develop a comprehensive understanding of plasma’s effects on plant biology and explore future perspectives for agricultural applications.

Coopetitive cannibalization on ICT channel: empirical evidence from the expansion of online-based games to mobile platform

Coopetitive cannibalization on ICT channel: empirical evidence from the expansion of online-based games to mobile platform

Transition state theoretical modelling of molecular diffusion within the narrow pores of brewsterite zeolite.

Based on the transition state theory, a molecular diffusion model in the narrow channels of Brewsterite zeolite was established. In this model, the molecular interaction at the potential barrier was simplified to only consider the repulsive potential, so that the analytical relationship between the diffusion coefficient and the temperature and the Lennard-Jones interaction parameter was derived. We used the molecular dynamics method to simulate the diffusion of four molecules, CF4, CH4, Ar, and Ne, in Brewsterite zeolite and evaluated the rationality of the model. The results show that the three molecules CF4, CH4, and Ar meet the predictions of the model, while the Ne molecule does not. At the same time, by analyzing the trend of the diffusion coefficient with the load, we further explain the reason for this difference. In short, this study reveals the diffusion mechanism of molecules in the narrow pores of Brewsterite zeolite. This provides new ideas for optimizing the performance of zeolite materials and applying them to catalysis and separation processes. The simulations were carried out with Refson's MOLDY code in the NVT ensemble. The short-range Lennard-Jones forces were calculated with the link cell method. A Nose-Hoover thermostat was used to realize the thermal equilibrium state of the samples. In the simulation, the time steps were 1fs and the total simulation time was 51ns. The initial temperature was set to 300K.

Label-free determination of diffusion coefficients at the nanoscale through modelling of the Surface Plasmon Resonance signal.

Surface plasmon resonance (SPR) is normally used to measure the kinetic parameters of biomolecular interactions between a molecule immobilized on a gold surface and another one flowing in a microfluidic channel above the surface. During the SPR measurements, convection-diffusion phenomena occur inside the microfluidic channels, but they are generally minimized by appropriate experimental setup in order to obtain diffusion free kinetic parameters of the molecular interactions. In this work, for the first time, a commercial SPR apparatus has been used to obtain non canonical scientific parameters. Indeed, a specifically designed SPR experimental setup is described for carrying out measurements of the diffusion coefficient (D) of molecules in solutions. The high precision and reproducibility of the approach, as well as the wide applicability of the newly proposed SPR based method for the measurement of D of many different molecules and biomolecules, are here demonstrated and illustrated in detail.

TIP 4 P 2005 Ice : Simulating water with two molecular states.

Rigid, non-polarizable water models are very efficient from a computational point of view, and some of them have a great ability in predicting experimental properties. There is, however, little room for improvement in simulating water with this strategy, whose main shortcoming is that water molecules do not change their interaction parameters in response to the local molecular landscape. In this work, we propose a novel modeling strategy that involves using two rigid non-polarizable models as states that water molecules can adopt depending on their molecular environment. During the simulation, molecules dynamically transition from one state to another depending on a local order parameter that quantifies some local structural feature. In particular, molecules belonging to low- and high-tetrahedral order environments are represented with the TIP4P/2005 and TIP4P/Ice rigid models, respectively. In this way, the interaction between water molecules is strengthened when they acquire a tetrahedral coordination, which can be viewed as an effective way of introducing polarization effects. We call the resulting model TIP4P2005Ice and show that it outperforms either of the rigid models that build it. This multi-state strategy only slows down simulations by a factor of 1.5 compared to using a standard non-polarizable model and holds great promise for improving simulations of water and aqueous solutions.

Optimization of design parameters and operation conditions of solar-air source heat pump coupled system for rural buildings in cold and severe cold regions

Integrating solar energy utilization into air source heat pump heating systems can effectively cut down on energy consumption. However, the complexity of coupled systems poses a challenge to system performance optimization. In this paper, a solar-air source heat pump coupled system designed for heating in cold (Beijing) and severe cold (Changchun) regions is developed and analyzed by TRNSYS software. Response surface methodology (RSM) is employed to establish regression models for different performance indicators, and then the non-dominated sorting genetic algorithm-II (NSGA-II) is adopted to solve the multi-objective optimization of interactive performance parameters through Pareto optimal solution set. The regression models of the performance indicators, i.e., the energy consumption (P), the solar energy assurance rate (Ar) and the ratio of heating supply from solar energy storage tank to building load (Hs), are found to be closely related to the area of solar collectors (A) and the volumes of storage tanks (Vl for solar collector loop and Vs for ASHP loop). The obtained Pareto set successfully balances the optimal values of interactive performance indicators. In cold regions, P, Ar, Hs of the coupled system can be improved respectively by 31.79%, 33.00% and 40.07% compared to the single air source heat pump system. While in severe cold regions, these improvements are 16.25%, 15.35% and 28.38%, respectively. The design method and optimization procedure of this study provide a basis for the optimization of the solar and auxiliary heat source coupled heating systems.

Prompt-engineering enabled LLM or MLLM and instigative bioinformatics pave the way to identify and characterize the significant SARS-CoV-2 antibody escape mutations.

The research aims to identify and characterize the antibody escape mutations of NTD and RBD regions of SARS-CoV-2 using prompt-engineering-enabled combined LLMs (large language models) and instigative bioinformatics techniques. We used two LLMs (ChatGPT and Mistral 7B) and one MLLM (Gemini model) to retrieve the significant NTD and RBD mutations. The retrieved significant mutations were characterized through the in silico servers. The retrieved 15 NTD significant mutations (six deletions and nine-point mutations) and 17 RBD point mutations were noted. We further characterized the in terms of distribution, count, ΔΔG of mutation (ΔΔG stability mCSM, ΔΔGstability DUET, ΔΔGstabilitySDM) to understand the stabilized or destabilized mutation, interaction interface, distance to PPI interface, Δ Vibrational Entropy Energy (ΔΔSVib ENCoM), and change in the flexibility. Here, we analyzed every mutation's ΔΔG, interaction, and related parameters using the trimeric spike protein complex. In NDT mutations, our five analyzed NTD mutations show two destabilising (G142D, R190S) and three showing stabilising properties (D215G, A222V, and R246I). Some RBD mutations are noted as entirely destabilising (K417N; K417T; L452R, F490S). N440K, N460K, and Q493R show stabilising and neutral properties. Combined LLMs and instigative bioinformatics techniques were used to identify and characterize the antibody escape mutations. With our strategy, the LLM can help to fight future pandemic viruses by quickly identifying mutations and their significance.

Probing dark relativistic species and their interactions with dark matter through CMB and 21 cm surveys

We investigate the sensitivity of the 21 cm power spectrum from cosmic dawn and the epoch of reionization to models of free-streaming dark radiation (parameterized through N eff) and interacting dark radiation-dark matter models (DM-DR). The latter models have gained attention for their potential in addressing recent cosmological tensions and structure formation challenges.We perform a Fisher matrix analysis under different assumptions regarding the astrophysical modeling, and forecast the sensitivity of HERA observations, combined with CMB data from Planck and the Simons Observatory (SO), to N eff and DM-DR interaction modeled using the ETHOS framework assuming a constant scattering rate between the two components.Most importantly, we find that 21 cm observations can improve the sensitivity to the DM-DR interaction rate by up to four order of magnitude compared to Planck and SO. Conversely, in the limit of low interaction rate (which asymptotically matches N eff), CMB data dominates the constraining power, but the inclusion of HERA data can provide a ∼ 20% improvement in sensitivity over CMB data alone.Moreover, we find that HERA observations will be able to probe a region of the DM-DR interaction parameter space which is promising to explain the weak lensing amplitude `S 8' tension. Our results demonstrate the complementarity of 21 cm and CMB data in exploring dark sector interactions.

Correlated Dirac Fermions in Twisted Bilayers of MoS2.

Artificial honeycomb lattices are essential for understanding exotic quantum phenomena arising from the interplay between Dirac physics and electron correlation. This work shows that the top two moiré valence bands in rhombohedral-stacked twisted MoS2 bilayers (tb-MoS2) form a honeycomb lattice with massless Dirac fermions. The hopping and Coulomb interaction parameters are explicitly determined based on large-scale ab initio calculations. The system exhibits significant nonlocal Coulomb repulsion and can be described by the extended Hubbard model. At half-filling, strong Coulomb repulsion in free-standing tb-MoS2 drives the system away from the semimetal phase, resulting in strongly correlated Dirac fermions. By varying the twist angle and dielectric environment, the Hamiltonian parameters can be tuned in a wide range, enabling transitions between distinct quantum phases. The high tunability makes tb-MoS2 a promising simulator for exploring many-body effects of Dirac fermions.

Эффективность преподавания шахмат и установки к предмету в учебных группах с игровым подходом к обучению

<p>The purpose of the study is to identify the impact of the use of educational games in chess lessons as a general education subject on the solution of chess problems and students’ attitudes towards the subject. We hypothesized, drawing from the classic works of L.S. Vygostky, Elkonin, R.M. Ryan, E. Deci, and others, that educational games successfully shape educational motivation in chess lessons among younger schoolchildren. By conducting a comparative analysis of gaming and traditional approaches, considering their impact on the teaching of chess and students' attitudes towards the subject, we can significantly enhance student motivation and educational initiative, thereby improving the quality of chess teaching. This can be achieved by incorporating scientifically based teaching technologies into the educational process. Methods. One of the schools in the Republic of Armenia tested the chess game method of teaching. Four second graders participated in the experiment. The same teacher taught the subject of chess in all classes. We define two classes as control classes, where we taught chess using the usual or traditional method, and the other two classes as experimental classes, where we taught chess using a new game method. Eight students were members of a chess school or club. We did not consider their results when processing the experimental data. We conducted the experiment for nine months, from September 2021 to May 2022. Results and conclusions. Analysis of the characteristics demonstrated a fundamental difference between learning with game elements and the traditional approach, particularly in terms of the parameters of social interaction in learning, where the game approach offers significant advantages. Given the impact of the game approach on chess teaching attitudes, we found that the experimental group had a higher percentage of students (96.0%) wishing for "more chess lessons" compared to the control group (69.4%), and a lower percentage (4.0%) wishing for "as many chess lessons as there are now" compared to the control group (27.4%). The z-test comparing proportions in Table 5 showed that the identified differences in attitudes were statistically significant at the 95% level. The data we obtained allows us to confirm the hypothesis that the gaming method of teaching creates more positive attitudes towards chess lessons.</p>

Organosilicon Polymeric Acetylene Derivatives: X-Ray Spectral Study and Quantum-Chemical Calculations

The atomic and electronic structure of two organosilicon polymers [–Ph2Si–(C≡C)2–]n (P1) and [–Ph2Si–(C≡C–C≡C)2–]m (P2) (where Ph — is phenyl group) of acetylene and diacetylene types by methods of density functional theory and X-ray emission spectroscopy. The interpretation of X-ray emission SiKβ1-spectra of these polymers was carried out based on an analysis of the distribution of partial electronic states obtained from quantum chemical calculations. Quantitative characteristics of the parameters of the chemical interaction of atoms, such as populations, natural charges, and electronic configurations in the studied polymers, were obtained based on the analysis of hybrid natural bond orbitals. The obtained values of the natural bond orbitals polarization coefficients indicate that the electron density is localized predominantly on carbon atoms. The electronic configurations for carbon atoms in different fragments differ significantly. For C atoms of ethynyl (diethynyl) fragments, they are close to linear σ-bond with sp1.03 (P1) and sp0.95 (P2) configurations, while for C atoms of phenyl fragments it is sp2.42, intermediate between sp2 and sp3 configurations. The natural charges on Si in both polymers are almost the same: +1.58e, +1.59e, while the natural charges on the carbon atoms of the diethynyl group decrease in comparison with the charge on the carbon atom of the ethynyl group from –0.42e to –0.36e.

Simulation of Triglyceride Purification from Crude Palm Oil using Single Solvent Continuous Counter Current Extraction

As the world’s largest crude palm oil (CPO) producer, Indonesia focuses on palm research, such as CPO-based cooking oil production. Generally, the widely applied production process in the industry is refining, which has several disadvantages, such as low energy efficiency and monochloropropane-1,2-diol (MCPD) formation. Under such conditions, CPO-based cooking oil production methods have been developed, with the continuous countercurrent extraction (CCE) method is considered the most effective for purifying triglyceride (TAG) as the main content of CPO-based cooking oil. The minimum content of TAG in cooking oil is 96% by mass according to SNI 7709:2019 (Indonesian cooking oil standard). Hence, to obtain the optimal production process that meets that standard, a simulation of TAG purification from CPO using the CCE method with a single solvent was conducted. This simulation obtained thermodynamic properties that correspond to the experimental extraction process, in which an industrial scale up can be acquired. The precise thermodynamic properties resulted from the precise selection of property package and Binary Interaction Parameter (BIP) estimation, and those are important because in this extraction process, liquid-liquid equilibrium works. This research used combinations of two property packages: Non-Random Two Liquid (NRTL) and Universal Quasi Chemical (UNIQUAC) and three BIP estimation methods: UNIQUAC functional activity coefficients (UNIFAC), UNIFAC-Lyngby, and UNIFAC-Dortmund. The simulation results were validated using existing experiments with statistical analysis such as relative error, R-Square, and p-value. The most valid simulation results were obtained by NRTL property package and UNIFAC-Lyngby BIP estimation and can be used to develop this TAG purification.

Optimally Miscible Polymer Bulk-Heterojunction-Particles for Nonsurfactant Photocatalytic Hydrogen Evolution.

Mini-emulsion and nanoprecipitation techniques relied on large amounts of surfactants, and unresolved miscibility issues of heterojunction materials limited their efficiency and applicability in the past. Through our molecular design and developed surfactant-free precipitation method, we successfully fabricated the best miscible bulk-heterojunction-particles (BHJP) ever achieved, using donor (PS) and acceptor (PSOS) polymers. The structural similarity ensures optimal miscibility, as supported by the interaction parameter of the PS/PSOS blend is positioned very close to the binodal curve. Experimental studies and molecular dynamics simulations further revealed that surfactants hinder electron output sites and reduce the concentration of sacrificial agents at the interface, slowing polaron formation. Multiscale experiments verified that these BHJP, approximately 12 nm in diameter, further form cross-linked fractal networks of several hundred nanometers. Transient absorption spectroscopy showed that BHJP facilitates polaron formation and electron transfer. Our BHJP demonstrated a superior hydrogen evolution rate (HER) compared to traditional methods. The most active BHJP achieved an HER of 251.2 mmol h-1 g-1 and an apparent quantum yield of 26.2% at 500 nm. This work not only introduces a practical method for preparing BHJP but also offers a new direction for the development of heterojunction materials.

Exploring the role of nonlocal Coulomb interactions in perovskite transition metal oxides

Employing the density functional theory incorporating on-site and inter-site Coulomb interactions (DFT + U + V), we have investigated the role of the nonlocal interactions on the electronic structures of the transition metal oxide perovskites. Using constrained random phase approximation calculations, we derived screened Coulomb interaction parameters and revealed a competition between localization and screening effects, which results in nonmonotonic behavior with d-orbital occupation. We highlight the significant role and nonlocality of inter-site Coulomb interactions, V, comparable in magnitude to the local interaction, U. Our DFT + U + V results exemplarily show the representative band renormalization, and deviations from ideal extended Hubbard models due to increased hybridization between transition metal d and oxygen p orbitals as occupation increases. We further demonstrate that the inclusion of the inter-site V is essential for accurately reproducing the experimental magnetic order in transition metal oxides.

Connecting Dynamics and Thermodynamics in Polymer-Resin Cured Systems.

This work connects the calorimetric responses of different rubber-resin blends with varying resin contents with their alpha relaxation dynamics. We used differential scanning calorimetry and broadband dielectric spectroscopy to characterize the calorimetric and dielectric responses of styrene-butadiene, polybutadiene, and polyisoprene with different resin contents. To model the results, we used the Gordon-Taylor equation combined with an extension of the Adam-Gibbs approach. Thus, we propose a simple and effective model that allows us to estimate the blend dynamics from the temperature dependence of the relaxation times of the pure components and the calorimetric measurement of the glass transition temperature of only one blend composition. By estimating an effective interaction parameter from calorimetry, we achieved accurate alpha relaxation dynamics predictions for different resin concentrations. Our highly predictive approach provides a realistic description of the expected dynamics. This study offers valuable insights into the dynamic properties of polymer compounds, paving the way for the fast and effective development of advanced and more sustainable materials.

An Underlying Cause and Solution to the Poor Size Exclusion Chromatography Performance of Antibody-Drug Conjugates.

Antibody-drug conjugate (ADC) size variants are frequently assessed by size exclusion chromatography (SEC). However, poor chromatography performance is often observed during SEC analysis. Existing studies have primarily focused on qualitatively describing non-specific interactions between ADCs and the column matrix. The purposes of the current study are to introduce an underlying cause from a novel perspective on the protein-protein interaction (PPI) mechanism, characterized by quantifying diffusion interaction parameter (kD) values, and to provide several strategies to reduce PPI and improve column performance during SEC analysis. Two kinds of ADCs with varying hydrophobicity properties and their corresponding monoclonal antibodies are used as models. The hydrophobicity of these products was verified using the relative calculated logarithm of the partition coefficient of a substance in n-octanol (oil) and water (rCLogP) and reversed-phase high performance liquid chromatography (RP-HPLC), and the size variants were analyzed using SEC. Finally, the PPI was characterized by kD values of these four products. The results of rCLogP and RP-HPLC indicated that ADC-1 is relatively hydrophobic, whereas ADC-2 is relatively hydrophilic. In the SEC analysis of the ADC-1, substituting sodium chloride with L-arginine hydrochloride or adding a specific concentration of acetonitrile as an organic solvent to the mobile phase resulted in reduced PPI and enhanced column performance. Conversely, the impact on ADC-2 was negligible. This study provides insights into improving the performance of SEC analysis for ADCs through strategies involving alterations in mobile phase composition. The changes in column performance can be quantitatively explained by the PPI mechanism.