Aggregation Kinetics Research Articles

Molecular Dynamics Simulations Reveal How Competing Protein-Surface Interactions for Glycine, Citrate, and Water Modulate Stability in Antibody Fragment Formulations.

The design of stable formulations remains a major challenge for protein therapeutics, particularly the need to minimize aggregation. Experimental formulation screens are typically based on thermal transition midpoints (Tm), and forced degradation studies at elevated temperatures. Both approaches give limited predictions of long-term storage stability, particularly at low temperatures. Better understanding of the mechanisms of action for formulation of excipients and buffers could lead to improved strategies for formulation design. Here, we identified a complex impact of glycine concentration on the experimentally determined stability of an antibody Fab fragment and then used molecular dynamics simulations to reveal mechanisms that underpin these complex behaviors. Tm values increased monotonically with glycine concentration, but associated ΔSvh measurements revealed more complex changes in the native ensemble dynamics, which reached a maximum at 30 mg/mL. The aggregation kinetics at 65 °C were similar at 0 and 20 mg/mL glycine, but then significantly slower at 50 mg/mL. These complex behaviors indicated changes in the dominant stabilizing mechanisms as the glycine concentration was increased. MD revealed a complex balance of glycine self-interaction, and differentially preferred interactions of glycine with the Fab as it displaced hydration-shell water, and surface-bound water and citrate buffer molecules. As a result, glycine binding to the Fab surface had different effects at different concentrations, and led from preferential interactions at low concentrations to preferential exclusion at higher concentrations. During preferential interaction, glycine displaced water from the Fab hydration shell, and a small number of water and citrate molecules from the Fab surface, which reduced the protein dynamics as measured by root-mean-square fluctuation (RMSF) on the short time scales of MD. By contrast, the native ensemble dynamics increased according to ΔSvh, suggesting increased conformational changes on longer time scales. The aggregation kinetics did not change at low glycine concentrations, and so the opposing dynamics effects either canceled out or were not directly relevant to aggregation. During preferential exclusion at higher glycine concentrations, glycine could only bind to the Fab surface through the displacement of citrate buffer molecules already favorably bound on the Fab surface. Displacement of citrate increased the flexibility (RMSF) of the Fab, as glycine formed fewer bridging hydrogen bonds to the Fab surface. Overall, the slowing of aggregation kinetics coincided with reduced flexibility in the Fab ensemble at the very highest glycine concentrations, as determined by both RMSF and ΔSvh, and occurred at a point where glycine binding displaced neither water nor citrate. These final interactions with the Fab surface were driven by mass action and were the least favorable, leading to a macromolecular crowding effect under the regime of preferential exclusion that stabilized the dynamics of Fab.

Efficient removal of nanoplastics by iron-modified biochar: Understanding the removal mechanisms

Tiny plastic particles, particularly nanoplastics, are becoming major threats to aquatic and biotic life owing to their unique physico-chemical characteristics. Thus, in the present work, biochar (BC) was fabricated using “Ulva prolifera green tide” as a biowaste raw material by slow pyrolysis technique to examine its potential in removing nanoplastics from the environment. The findings depicted that nanoplastics removal efficiency by BC was V-shaped with initial pH increased from 2 to 11, and the main removal mechanism changed from adsorption to heterogeneous aggregation between nanoplastics, biochar colloids, and leached substances from BC. When the solution pH crossed the pHpzc of BC (2.3), the aggregation kinetics were well-fitted by the logistic model and displayed as an S-shaped curve with a lag period. Characterization results indicated that biochar colloids were the key enabler with a critical concentration of 72.01 mg L−1 at neutral pH. Keeping in mind the removal mechanisms and contribution of biochar colloids, iron-modified biochar (Fe-BC) was produced to enhance the overall removal efficiency. The Fe-BC demonstrated a two-phase removal process of pre-adsorption and post-aggregation, successfully realized to minimize lag time and enhance aggregation performance. The theoretical removal capacity of Fe-BC against nanoplastics could reach up to 1626.3 mg g−1, which was three-fold higher than that of BC. Further, the Fe-BC was suggested to be recycled and reused at least three times by ultrasound, followed by co-pyrolysis for green and efficient degradation of nanoplastics. Overall, the findings offer a promising approach for removing and recycling nanoplastics in the environment.

Disruption of PHF6 Peptide Aggregation from Tau Protein: Mechanisms of Palmatine Chloride in Preventing Early PHF6 Aggregation.

The formation of neurofibrillary tangles (NFTs), composed of tau protein aggregates, is a hallmark of neurodegenerative diseases known as tauopathies, including Alzheimer's disease (AD). NFTs consist of paired helical filaments (PHFs) of tau protein with a dominant β-sheet secondary structure. Within these PHFs, the PHF6 hexapeptide (Val306-Gln-Ile-Val-Tyr-Lys311) has been commonly highlighted as a key site for tau protein nucleation. Palmatine chloride (PC) has been identified as an inhibitor of PHF6 aggregation, capable of reducing aggregation propensity at submicromolar concentrations. In pursuit of novel anti-AD drugs targeting early tau aggregation stages, we conducted an in silico study to elucidate PC's mechanism of action during PHF6 aggregation. Our observations suggest that while PHF6 can still initiate self-aggregation in the presence of PC, PC molecules subtly influence PHF6 aggregation dynamics, favoring smaller aggregates over larger complexes. The study underlined the key roles of aromatic rings in PC binding to different PHF6 aggregates by interacting through π-π stacking with the PHF6 Tyr310 side chain. The presence of aromatic rings in compounds to be able to inhibit the earlier complexation phase seems to be essential. These in silico findings lay a foundation for the design of compounds that could intervene in resolving the neurotoxicity of protein aggregates in AD.

Size distribution of aggregates across different aquatic systems around Japan shows that stronger aggregates are formed under turbulence

AbstractMarine aggregates, composed of various particles, play a crucial role in ocean carbon storage. The overall size distribution of the aggregates (number size spectra) is controlled by the balance between aggregation and disaggregation processes. Turbulence has been proposed to facilitate both aggregation and disaggregation by increasing the collision rate of aggregates or sometimes directly tearing them apart. Predominant processes driven by turbulence typically depend on the level of turbulence—relatively weak turbulence is associated with aggregation while stronger turbulence promotes disaggregation. Aggregate strength also plays a key role, as strongly bonded aggregates can withstand turbulence better, leading to lower disaggregation rates. While the relationship between turbulence and aggregate strength has been studied numerically and experimentally, field measurements remain limited. Here, we compare our number size spectra to turbulence intensity from the field measurements across different environmental settings around Japan to determine the effect of turbulence on aggregate strength. We combined measurements from 10 sites with different environmental settings and observed the flatter slopes (higher net aggregation rate) and shifts in the intersection lengths with an increase of turbulence, while strong turbulence is typically linked with disaggregation. Our findings suggested that stronger aggregates are formed under stronger turbulence and the overall population of strong aggregates also increases with an increase of turbulence intensity. We also compared our number size spectra with three other confounding factors (fluorescence, salinity, and aggregate compositions) to confirm the effects of turbulence are dominant in our aggregate dynamics.

Unraveling the Molecular Jam: How Crowding Shapes Protein Aggregation in Neurodegenerative Disorders.

Protein misfolding and aggregation are the hallmarks of neurodegenerative diseases including Huntington's disease, Parkinson's disease, Alzheimer's disease, and prion diseases. A crowded cellular environment plays a crucial role in modulating protein aggregation processes in vivo and the pathological aggregation of proteins linked to different neurodegenerative disorders. Here, we review recent studies examining the effects of various crowding agents, such as polysaccharides, polyethylene glycol, and proteins like BSA and lysozyme on the behaviors of aggregation of several amyloidogenic peptides and proteins, including amylin, huntingtin, tau, α-synuclein, prion, and amyloid-β. We also summarize how the aggregation kinetics, thermodynamic stability, and morphology of amyloid fibrils are altered significantly in the presence of crowding agents. In addition, we also discuss the molecular basis underlying the modulation of amyloidogenic aggregation, focusing on changes in the protein conformation, and the nucleation mechanism. The molecular understanding of the effects of macromolecular crowding on amyloid aggregation is essential for revealing disease pathologies and identifying possible therapeutic targets. Thus, this review offers a perspective on the complex interplay between protein aggregation and the crowded cellular environment in vivo and explains the relevance of crowding in the context of neurodegenerative disorders.

Molecular Interactions between Tau Protein and TIA1: Distinguishing Physiological Condensates from Pathological Fibrils.

The interaction of tau protein with other key proteins essential for stress granule formation determines their functional and pathological impact. In a biological framework, the synergy between Alzheimer's associated tau protein and the stress granule core protein TIA1 is widely recognized. However, the molecular details of this association remain unclear. In this study, we throw light on the importance of the state in which the TIA1 exists in mediating its association with the tau protein. Investigations were carried out on the three repeat constructs of tau (K19) and different structures formed by TIA1. Specifically, the condensate formed by TIA1 full-length (TIA1-FL) protein as well as fibril formed by low complexity domain of TIA1 (TIA1-LCD). The dynamics of K19 inside TIA1-FL condensates and the aggregation kinetics of K19 in the presence of TIA1-LCD fibrils were examined using various biophysical techniques. Relaxation-based solution NMR spectroscopic investigations suggest a weak interaction with TIA1 condensates and indicated a reduction in the dynamics of K19 within these TIA1 condensates. In contrast, a significant interaction was observed between K19, and TIA1-LCD fibrils primarily mediated through 321KCGS324 and 306VQIVYKPVDLSKV317. Our findings emphasize that the interaction between Tau and TIA1 varies depending on whether TIA1 is in its physiological condensate form or its pathological fibril state.

Degradation Mechanism and Enhanced Stability of Organolithium for Chemical Lithiation

AbstractOrganolithium solutions, especially Li‐arene solutions (LASs) with high reactivity and controllable redox potentials, have gained significant attention because of their wide applications in chemical lithiation, liquid anodes, and battery recycling. However, the sudden loss of reactivity when stored or applied at room temperature is still puzzling and inhibits the application of LASs. In this work, the degradation mechanism of LASs is fully investigated and revealed by combining various experimental characterization and computational simulations. A hierarchical reaction mechanism for lithium biphenyl/2‐methyl tetrahydrofuran (Li‐Bp‐2MT), a lithiation solution used for most anodes, explains degradation and side product formation. Specifically, the dimerization of the active component Li1Bp[2MT]1 forms an inactive dimer that is irreversibly reduced in the presence of locally accumulated highly reductive Li0. This reaction mechanism reveals the atomic origins of lithiation solution deactivation and accounts for all solid and gaseous byproducts. LiH is identified as the dominating solid byproduct, indicating irreversible destruction of the active components and facilitating side reactions producing H2 and CH4. Based on reaction mechanism insights, modifying molecular interactions and reaction kinetics are experimentally shown to inhibit Li0 aggregation kinetics, enhancing long‐term prelithiation performance. This research provides comprehensive guidelines for practical applications of LASs.

Distance-Dependent Tryptophan-Induced Quenching of Thioflavin T Defines the Amyloid Core Architecture.

Thioflavin T (ThT) is widely employed as a fluorogenic marker for amyloid formation. ThT fluorescence is utilized to detect amyloid fibrils as well as to follow aggregation kinetics. Here, we make a unique case to demonstrate that site-specific tryptophan-induced fluorescence quenching of ThT bound to the α-synuclein amyloid can define the central amyloid core. We show that distance-dependent quenching of amyloid-bound ThT by site-specifically incorporated tryptophan maps the proximal and distal locations of the polypeptide chain within amyloid fibrils. Our studies indicate that tryptophan-induced fluorescence quenching is dominated by the static quenching mechanism. Our findings underscore the utility of site-specific amino acid-based quenching of ThT fluorescence to characterize the core architecture of amyloid derived from a wide range of proteins.

RFCSC: Communication efficient reinforcement federated learning with dynamic client selection and adaptive gradient compression

In the field of public safety, high-quality data is often owned by governments, companies, and organizations, making it difficult to train effective models through centralized datasets. This paper leverages federated learning as a mechanism to address data privacy concerns. Within the federated learning framework, the data across different clients is typically Non-IID (non-Independently and Identically Distributed). Furthermore, The complexity of sensitive image recognition tasks in public safety, along with the large number of model parameters, can lead to communication congestion issues in federated learning. To solve these challenges, this paper proposes a Reinforcement Federated Client Selection and Gradient Compression Method(RFCSC). By integrating client data prototypes with accuracy metrics, we dynamically assess the contribution of each client in federated learning. Through an intelligent dynamic incentive mechanism based on reinforcement learning, high-quality client nodes are dynamically selected to participate in federated learning, achieving dynamic adaptive aggregation, reducing the influence of Non-IID data, reducing communication cost, enhancing model accuracy, and achieving a balance between quality and efficiency. To address the issue of high communication cost for parameter transmission, we propose an adaptive model compression strategy in reinforcement federated learning which make local clients find an appropriate compression rate. This approach not only reduces gradient communication overhead but also minimizes the impact of compression on model accuracy. The effectiveness of our proposed approach are corroborated through comprehensive experiments conducted on one private dataset and two public datasets.

Unravelling a diversity of cellular structures and aggregation dynamics during the early development of Myxococcus xanthus.

Aggregation underlies the collective dynamics of a diversity of organisms, enabling the formation of complex structures and emergent behaviours on interaction with the environment. Cellular aggregation constitutes one of the routes to collective motility and multicellular development. Myxococcus xanthus, a social bacterium, is a valuable model for studying the aggregative path to multicellularity, a major transition in the evolutionary history of life. While the collective developmental behaviour of M. xanthus has been largely studied in high cellular densities, there is a lack of understanding at low-density conditions that can be ecologically relevant. In this work, we study the early stages of emergent collective behaviour of M. xanthus under nutrient-poor and low-density conditions, uncovering the formation of diverse cellular structures with different shapes and sizes, ranging from individual cells to networks comprising thousands of cells. We study their motility patterns and their prevalence along development and discuss their cross-scale role on the population's exploratory dynamics. This work contributes to understanding key, yet largely understudied, aspects in the early stages of multicellular development in myxobacteria, shedding light on the dynamics underlying aggregative processes in this and other taxa and study systems.

Small Object Detection Method Based on Global Multi-Level Perception and Dynamic Region Aggregation

Small Object Detection Method Based on Global Multi-Level Perception and Dynamic Region Aggregation

Theoretical Analysis of Self-Shrinkage Spheroidization of Irregular Degradable Polymer Powder under Thermodynamic Nonequilibrium State

Laser three-dimensional (3D) printing offers significant advantages in integrating the shape and function of regenerative tissues through biomimetic manufacturing. However, its effectiveness is limited by the lack of specialized biopolymer powders—while solvent methods that use residual solvents produce powders with poor biocompatibility, mechanical methods result in irregularly shaped crystals. In this study, a biopolymer powder spheroidization and shaping technology, which utilizes the evolution of irregular powders into spheres with minimal surface free energy in the molten state, is proposed based on the thermodynamic principle of minimum energy. Initially, the motion trajectory and temperature field of the poly(L-lactic acid) (PLLA) powder during spheroidization were quantitatively assessed and optimized using Stokes’ law and Fourier's principle. Subsequently, the cohesive forces and aggregation kinetics of the polymer chains were calculated using molecular dynamics. Finally, based on these calculations, a phase-field model was constructed to simulate the evolution of the spheroidization rate and deduce the optimal parameters for the process. This precise approach enhances PLLA spheroidization control for laser 3D printing, improves part densification and surface quality, and offers a clean and efficient path for preparing high-quality PLLA spheroidized powder for laser 3D printing.

Dynamic protein hydration water mediates the aggregation kinetics of amyloid β peptides at interfaces

Protein hydration water is essential for protein misfolding and amyloid formation, but how it directs the course of amyloid formation has yet to be elucidated. Here, we experimentally demonstrated that femtosecond sum frequency generation vibrational spectroscopy (SFG–VS) and the femtosecond IR pump–SFG probe technique can serve as powerful tools for addressing this issue. Using amyloid β(1–42) peptide as a model, we determined the transient misfolding intermediates by probing the amide band spectral features and the local hydration water changes by measuring the ultrafast vibrational dynamics of the amide I band. For the first time, we established a correlation between the dynamic change in protein hydration water and aggregation propensity. The aggregation propensity depends on the dynamic change in the hydration water, rather than the static hydration water content of the initial protein state. Water expulsion enhances the aggregation propensity and promotes amyloid formation, while protein hydration attenuates the aggregation propensity and inhibits amyloid formation. The suppression of water expulsion and protein hydration can prevent protein aggregation and stabilize proteins. These findings contribute to a better understanding of the underlying effect of hydration water on amyloid formation and protein structural stability and provide a strategy for maintaining long–term stabilization of biomolecules.

Bisdemethoxycurcumin, a novel potent polyphenolic compound, effectively inhibits the formation of amyloid aggregates in ALS-associated hSOD1 mutant (L38R)

Protein misfolding is a biological process that leads to protein aggregation. Anomalous misfolding and aggregation of human superoxide dismutase (hSOD1) into amyloid aggregates is a characteristic feature of amyotrophic lateral sclerosis (ALS), a neurodegenerative illness. Thus, focusing on the L38R mutant may be a wise decision to comprehend the SOD1 disease process in ALS. We suggest that Bisdemethoxycurcumin (BDMC) may be a strong anti-amyloidogenic polyphenol against L38R mutant aggregation. Protein stability, hydrophobicity, and flexibility were altered when BDMC was bound to the L38R mutant, as shown by molecular dynamic (MD) simulations and molecular docking. FTIR data shows α-Helix dominance in BDMC-containing samples, with reduced β-sheet and disordered peaks, indicating the decrease of aggregate species. ThT aggregation kinetics curves show BDMC reduces L38R mutant aggregation dose-dependently, with higher BDMC concentrations yielding greater reductions. TEM images showed various quantities of amorphous aggregates, but notably, 60 μM BDMC markedly reduced aggregate density, underscoring BDMC's inhibitory effect. Hemolysis tests revealed aggregate species in BDMC-treated samples were less toxic than in L38R mutant samples alone at the same concentrations and exposure times. Overall, BDMC has substantial potential to develop highly effective inhibitors that mitigate the risk of fatal ALS.

Predictive Model Building for Aggregation Kinetics Based on Molecular Dynamics Simulations of an Antibody Fragment.

Computational methods including machine learning and molecular dynamics simulations have strong potential to characterize, understand, and ultimately predict the properties of proteins relevant to their stability and function as therapeutics. Such methods would streamline the development pathway by minimizing the current experimental testing required for many protein variants and formulations. The molecular understanding of thermostability and aggregation propensity has advanced significantly along with predictive algorithms based on the sequence-level or structural-level information on a protein. However, these approaches focus largely on a comparison of protein sequence variations to correlate the properties of proteins to their stability, solubility, and aggregation propensity. For therapeutic protein development, it is of equal importance to take into account the impact of the formulation conditions to elucidate and predict the stability of the antibody drugs. At the macroscopic level, changing temperature, pH, ionic strength, and the addition of excipients can significantly alter the kinetics of protein aggregation. The mechanisms controlling aggregation kinetics have been traced back to a combination of molecular features, including conformational stability, partial unfolding to aggregation-prone states, and the colloidal stability governed by surface charges and hydrophobicity. However, very little has been done to evaluate these features in the context of protein dynamics in different formulations. In this work, we have combined a range of molecular features calculated from the Fab A33 protein sequence and molecular dynamics simulations. Using the power of advanced, yet interpretable, statistical tools, it has been possible to uncover greater insights into the mechanisms behind protein stability, validating previous findings, and also develop models that can predict the aggregation kinetics within a range of 49 different solution conditions.

A simple model linking radiative–convective instability, convective aggregation and large-scale dynamics

Abstract. A simple model is presented which is designed to analyse the relation between the phenomenon of convective aggregation at small scales and larger-scale variability that results from coupling between dynamics and moisture in the tropical atmosphere. The model is based on single-layer dynamical equations coupled to a moisture equation to represent the dynamical effects of latent heating and radiative heating. The moisture variable q evolves through the effect of horizontal convergence, nonlinear horizontal advection and diffusion. Following previous work, the coupling between moisture and dynamics is included in such a way that a horizontally homogeneous state may be unstable to inhomogeneous disturbances, and, as a result, localised regions evolve towards either dry or moist states, with divergence or convergence respectively in the horizontal flow. The time evolution of the spatial structure of the dry and moist regions is investigated using a combination of theory and numerical simulation. One aspect of the evolution is a spatial coarsening that, if moist regions and dry regions are interpreted as convecting and non-convecting respectively, represents a form of convective aggregation. When the weak temperature gradient (WTG) approximation (i.e. a local balance between heating and convergence) applies, and horizontal advection is neglected, the system reduces to a nonlinear reaction–diffusion equation for q, and the coarsening is a well-known aspect of such systems. When nonlinear advection of moisture is included, the large-scale flow that arises from the spatial pattern of divergence and convergence leads to a distinctly different coarsening process. When thermal and frictional damping and f-plane rotation are included in the dynamics, there is a dynamical length scale Ldyn that sets an upper limit for the spatial coarsening of the moist and dry regions. The f-plane results provide a basis for interpreting the behaviour of the system on an equatorial β plane, where the dynamics implies a displacement in the zonal direction of the divergence relative to q and hence to coherent equatorially confined zonally propagating disturbances, comprising separate moist and dry regions. In many cases the propagation speed and direction depend on the equatorial wave response to the moist heating, with the relative strength of the Rossby wave response to the Kelvin wave response determining whether the propagation is eastward or westward. Within this model, the key overall properties of the propagating disturbances, the spatial scale and the phase speed, depend on nonlinearity in the coupling between moisture and dynamics, and any linear theory for such disturbances therefore has limited usefulness. The model described here, in which the moisture and dynamical fields vary in two spatial dimensions and important aspects of nonlinearity are captured, provides an intermediate model between theoretical models based on linearisation and one spatial dimension and general circulation models (GCMs) or convection-resolving models.

Benzofuran and Benzo[b]thiophene-2-Carboxamide Derivatives as Modulators of Amyloid Beta (Aβ42) Aggregation.

A group of N-phenylbenzofuran-2-carboxamide and N-phenylbenzo[b]thiophene-2-carboxamide derivatives were designed and synthesized as a novel class of Aβ42 aggregation modulators. In the thioflavin-T based fluorescence aggregation kinetics study, compounds 4 a, 4 b, 5 a and 5 b possessing a methoxyphenol pharmacophore were able to demonstrate concentration dependent inhibition of Aβ42 aggregation with maximum inhibition of 54 % observed for compound 4 b. In contrast, incorporation of a 4-methoxyphenyl ring in compounds 4 d and 5 d led to a significant increase in Aβ42 fibrillogenesis demonstrating their ability to accelerate Aβ42 aggregation. Compound 4 d exhibited 2.7-fold increase in Aβ42 fibrillogenesis when tested at the maximum concentration of 25 μM. These results were further confirmed by electron microscopy studies which demonstrates the ability of compounds 4 a, 4 b, 4 d, 5 a, 5 b and 5 d to modulate Aβ42 fibrillogenesis. Compounds 5 a and 5 b provided significant neuroprotection to mouse hippocampal neuronal HT22 cells against Aβ42-induced cytotoxicity. Molecular docking studies suggest that the orientation of the bicyclic aromatic rings (either benzofuran or benzo[b]thiophene) plays a major role in moderating their ability to either inhibit or accelerate Aβ42 aggregation. Our findings support the application of these novel derivatives as pharmacological tools to study the mechanisms of Aβ42 aggregation.

Mpsqd: A matrix product state based Python package to simulate closed and open system quantum dynamics.

We introduce a Python package based on matrix product states (MPS) to simulate both the time-dependent Schrödinger equation (TDSE) and the hierarchical equations of motion (HEOM). The wave function in the TDSE or the reduced density operator/auxiliary density operators in the HEOM are represented using MPS. A matrix product operator (MPO) is then constructed to represent the Hamiltonian in the TDSE or the generalized Liouvillian in the HEOM. The fourth-order Runge-Kutta method and the time-dependent variational principle are used to propagate the MPS. Several examples, including the nonadiabatic interconversion dynamics of the pyrazine molecule, excitation energy transfer dynamics in molecular aggregates and photosynthetic light-harvesting complexes, the spin-boson model, a laser driven two-state model, the Holstein model, and charge transport in the Anderson impurity model, are presented to demonstrate the capability of the package.

Trade liberalization and labor monopsony: Evidence from Chinese firms

We document that larger input tariff reductions were associated with lower labor markdowns in China, especially for skill-intensive firms. Guided by a stylized model of equilibrium labor market power, we leverage differences in the aggregate labor supply dynamics across labor markets—such as regional variations in China’s contemporaneous college expansion reforms—to that show trade-induced labor markdown decreased more in labor markets with more labor supply growth. Our estimates suggest that lower labor markdowns due to input trade liberalization offset China’s aggregate labor share decline by almost one-half percentage point in the early 2000s.

Analysis of the motion and deformation of water-in-oil emulsion droplets under the action of an electric field

Molecular dynamics simulations are used to study the aggregation dynamics of water-in-oil emulsion droplets under an electric field, and to analyze the effects of electric field strength, type, droplet position, and ionic concentration on their kinematic properties. The best droplet aggregation is observed at E=0.03V/Å for DC field condition, and E=0.045V/Å - 80ps for rectangular AC field condition. The rectangular alternating current (AC) field is able to merge the droplets farther away from the center of mass, but the two fields are not able to merge when the angle between the center of mass of the droplets and the electric field force is ≥35.54°. For different ion concentrations, t40N < t20N < t60N < t0N in the DC field and t20N < t40N < t0N < t60N in the rectangular AC field, and for the same ion concentration, the rectangular AC field takes longer time to merge.