Coarse-grained Molecular Dynamics Simulations Research Articles

A Gauss-Newton method for iterative optimization of memory kernels for generalized Langevin thermostats in coarse-grained molecular dynamics simulations.

In molecular dynamics simulations, dynamically consistent coarse-grained (CG) models commonly use stochastic thermostats to model friction and fluctuations that are lost in a CG description. While Markovian, i.e., time-local, formulations of such thermostats allow for an accurate representation of diffusivities/long-time dynamics, a correct description of the dynamics on all time scales generally requires non-Markovian, i.e., non-time-local, thermostats. These thermostats typically take the form of a Generalized Langevin Equation (GLE) determined by a memory kernel. In this work, we use a Markovian embedded formulation of a position-independent GLE thermostat acting independently on each CG degree of freedom. Extracting the memory kernel of this CG model from atomistic reference data requires several approximations. Therefore, this task is best understood as an inverse problem. While our recently proposed approximate Newton scheme allows for the iterative optimization of memory kernels (IOMK), Markovian embedding remained potentially error-prone and computationally expensive. In this work, we present an IOMK-Gauss-Newton scheme (IOMK-GN) based on IOMK that allows for the direct parameterization of a Markovian embedded model.

Systematic evaluation of lecithin:Cholesterol acyltransferase binding sites in apolipoproteins via peptide based nanodiscs: Regulatory role of charged residues at positions 4 and 7.

Lecithin:cholesterol acyltransferase (LCAT) exhibits α-activity on high-density and β-activity on low-density lipoproteins. However, the molecular determinants governing LCAT activation by different apolipoproteins remain elusive. Uncovering these determinants would offer the opportunity to design and explore advanced therapies against dyslipidemias. Here, we have conducted coarse-grained and all-atom molecular dynamics simulations of LCAT with nanodiscs made with α-helical amphiphilic peptides either derived from apolipoproteins A1 and E (apoA1 and apoE) or apoA1 mimetic peptide 22A that was optimized to activate LCAT. This study aims to explore what drives the binding of peptides to our previously identified interaction site in LCAT. We hypothesized that this approach could be used to screen for binding sites of LCAT in different apolipoproteins and would provide insights to differently localized LCAT activities. Our screening approach was able to discriminate apoA1 helixes 4, 6, and 7 as key contributors to the interaction with LCAT supporting the previous research data. The simulations provided detailed molecular determinants driving the interaction with LCAT: the formation of hydrogen bonds or salt bridges between peptides E4 or D4 and LCAT S236 or K238 residues. Additionally, salt bridging between R7 and D73 was observed, depending on the availability of R7. Expanding our investigation to diverse plasma proteins, we detected novel LCAT binding helixes in apoL1, apoB100, and serum amyloid A. Our findings suggest that the same binding determinants, involving E4 or D4 -S236 and R7-D73 interactions, influence LCAT β-activity on low-density lipoproteins, where apoE and or apoB100 are hypothesized to interact with LCAT.

Comment on "Effects of topological constraints on linked ring polymers in solvents of varying quality" by Z. A. Dehaghani, I. Chubak, C. N. Likos and M. R. Ejtehadi, Soft Matter, 2020, 16, 3029.

This comment critically evaluates the work of Dehaghani et al., who investigated the conformational behavior of catenated polymers under diverse solvent conditions using coarse-grained molecular dynamics simulations. While their study provides valuable insights into the scaling behavior of poly[n]catenane's radius of gyration in a good solvent, significant discrepancies arise, particularly concerning the reported θ-temperature trends. The validity of their methodology in determining θ-temperatures for linear and ring polymers is questioned, given observed disparities in chosen number of bead ranges that imply varying molecular weights. This comment underscores the need for a meticulous reassessment of the methodologies and interpretations presented in Dehaghani et al.'s study, emphasizing the importance of rigorous considerations in the investigation of the physical properties of catenated polymers.

Structural Analysis of the Linear Elasticity of End-Cross-Linked Star Elastomers with a Number of Trapped Entanglements via Coarse-Grained Molecular Dynamics Simulations

Structural Analysis of the Linear Elasticity of End-Cross-Linked Star Elastomers with a Number of Trapped Entanglements via Coarse-Grained Molecular Dynamics Simulations

Long-Chain Lipids Facilitate Insertion of Large Nanoparticles into Membranes of Small Unilamellar Vesicles.

Insertion of hydrophobic nanoparticles into phospholipid bilayers is limited to small particles that can incorporate into a hydrophobic membrane core between two lipid leaflets. Incorporation of nanoparticles above this size limit requires the development of challenging surface engineering methodologies. In principle, increasing the long-chain lipid component in the lipid mixture should facilitate incorporation of larger nanoparticles. Here, we explore the effect of incorporating very long phospholipids (C24:1) into small unilamellar vesicles on the membrane insertion efficiency of hydrophobic nanoparticles that are 5-11 nm in diameter. To this end, we improve an existing vesicle preparation protocol and utilized cryogenic electron microscopy imaging to examine the mode of interaction and evaluate the insertion efficiency of membrane-inserted nanoparticles. We also perform classical coarse-grained molecular dynamics simulations to identify changes in lipid membrane structural properties that may increase insertion efficiency. Our results indicate that long-chain lipids increase the insertion efficiency by preferentially accumulating near membrane-inserted nanoparticles to reduce the thermodynamically unfavorable disruption of the membrane.

Coarse-grained molecular dynamics model of AB diblock copolymers composed of blocks with different Lennard-Jones parameters forming lamellar structures

In thermoplastic elastomers, the structure formation of hard and soft domains and the mechanical response to deformation remain vital areas of interest. To realize the coarse-grained molecular dynamics (CGMD) simulations of systems incorporating the difference in glass transition temperature Tg between domains, we studied AB diblock copolymers (di-BCPs) with asymmetric Lennard-Jones (LJ) parameters (the strength coefficient εLJ and cutoff length rc). For instance, hard and soft domains were realized by assigning the cutoff lengths of each segment to rc,(A,A) = 2.5 (high Tg) and rc,(B,B) = 1.5 (low Tg), respectively. To identify how the cutoff length rc,(B,B) corresponds to the strength coefficient ε(B,B) in the phase separation behavior against the fixed LJ parameters for the A block (rc,(A,A) = 2.5 and ε(A,A) = 1.0), we focused on lamellar structures in which the A and B blocks possess equal segment numbers. For the asymmetric cases with rc,(B,B) < rc,(A,A), we estimated the effective ε(B,B)' on the basis of the DA/DB ratio of the partial domain spacings. We confirmed that the scaling relations (D ∼ Δε1/6, D/N0.7 ∼ Δε, and D/N1/2 ∼ ΔεN) hold, where ε(A,A) = 1, Δε = ((1 + ε(B,B)')/2 – ε(A,B)), and N denotes the number of segments per AB di-BCP chain. Therefore, this work will provide valuable insights for guiding applied research on BCPs.

The effect of polymer with tunable alkyl spacers on the microstructure of amphoteric membrane for vanadium redox flow battery (VRB)

Amphoteric membranes, as promising candidates for VRBs, have attracted more attention. The side-chain-type polymers go far towards improving ion exchange capacity and further enhancing ion conductivity. A kind of Amphoteric ion exchange membranes (AIEMs) with different alkyl chain lengths (C2, C6, and C12 spacers) were synthesized by using ring-opening metathesis polymerization (ROMP). In addition, the interactions between N-containing groups with positively charged and -SO3- groups prevent swelling and vanadium crossover. The microphase separation structure through side chain induction was regulated, to respond to the ionic mobility of the membrane. The effect of the spacer lengths on the ion selectivity of AIEMs is investigated. In addition, the size and matrix of the constructed ion channel were calculated by using coarse-grained molecular dynamics (CGMD) simulation, which further verified the experiment.

Influence of the Dielectric Constant on the Ionic Current Rectification of Bipolar Nanopores.

In this paper, we investigate how the dielectric constant, ϵ, of an electrolyte solvent influences the current rectification characteristics of bipolar nanopores. It is well recognized that bipolar nanopores with two oppositely charged regions rectify current when exposed to an alternating electric potential difference. Here, we consider dilute electrolytes with NaCl only and with a mixture of NaCl and charged nanoparticles. These systems are studied using two levels of description, all-atom explicit water molecular dynamics (MD) simulations and coarse-grained implicit solvent MD simulations. The charge density and electric potential profiles and current-voltage relationship predicted by the implicit solvent simulations with ϵ = 11.3 show good agreement with the predictions from the explicit water simulations. Under nonequilibrium conditions, the predictions of the implicit solvent simulations with a dielectric constant closer to the one of bulk water are significantly different from the predictions obtained with the explicit water model. These findings are closely aligned with experimental data on the dielectric constant of water when confined to nanometric spaces, which suggests that ϵ decreases significantly compared to its value in the bulk. Moreover, the largest electric current rectification is observed in systems containing nanoparticles when ϵ = 78.8. Using enhanced sampling, we have shown that this larger rectification arises from the presence of a significantly deeper minimum in the free energy of the system with a larger ϵ, and when a negative voltage bias is applied. Since implicit solvent models and mean-field continuum theories are often used to design Janus membranes based on bipolar nanopores, this work highlights the importance of properly accounting for the effects of confinement on the dielectric constant of the electrolyte solvent. The results presented here indicate that the dielectric constant in implicit solvent simulations may be used as an adjustable parameter to approximately account for the effects of nanometric confinement on aqueous electrolyte solvents.

Manufacturing process of liposomal Formation: A coarse-grained molecular dynamics simulation

A method of producing liposomes has been previously developed using a continuous manufacturing technology that involves a co-axial turbulent jet in co-flow. In this study, coarse-grained molecular dynamics (CG-MD) simulations were used to gain a deeper understanding of how the self-assembly process of liposomes is affected by the material attributes (such as the concentration of ethanol) and the process parameters (such as temperature), while also providing detailed information on a nano-scale molecular level. Specifically, the CG-MD simulations yield a comprehensive internal view of the structure and formation mechanisms of liposomes containing DPPC, DPPG, and cholesterol molecules. The importance of this work is that structural details on the molecular level are proposed, and such detail is not possible to obtain through experimental studies alone. The assessment of structural properties, including the area per lipid, diffusion coefficient, and order parameters, indicated that a thicker bilayer was observed at higher ethanol concentrations, while a thinner bilayer was present at higher temperatures. These conditions led to more water penetrating the interior of the bilayer and an unstable structure, as indicated by a larger contact area between lipids and water, and a higher coefficient of lipid lateral diffusion. However, stable liposomes were found through these evaluations at lower ethanol concentrations and/or lower process temperatures. Furthermore, the CG-MD model was further compared and validated with experimental and computational data including liposomal bilayer thickness and area per lipid measurements.

Molecular dynamics simulations of lipid-protein interactions in SLC4 proteins

The SLC4 family of secondary bicarbonate transporters is responsible for the transport of HCO3¯, CO32¯, Cl¯, Na+, K+, NH3 and H+ necessary for regulation of pH and ion homeostasis. They are widely expressed in numerous tissues throughout the body and function in different cell types with different membrane properties. Potential lipid roles in SLC4 function have been reported in experimental studies, focusing mostly on two members of the family: AE1 (Cl¯/HCO3¯ exchanger) and NBCe1 (Na+-CO32¯cotransporter). Previous computational studies of the outward facing (OF) state of AE1 with model lipid membranes revealed enhanced protein-lipid interactions between cholesterol (CHOL) and phosphatidylinositol bisphosphate (PIP2). However, the protein-lipid interactions in other members of the family and other conformation states are still poorly understood and this precludes the detailed studies of a potential regulatory role for lipids in the SLC4 family. In this work, we performed coarse-grained and atomistic molecular dynamics simulations on three members of the SLC4 family with different transport modes: AE1, NBCe1 and NDCBE (a Na+-CO32¯/Cl¯ exchanger), in model HEK293 membranes consisting of CHOL, PIP2, phosphatidylcholine (POPC), phosphatidylethanolamine (POPE), phosphatidylserine (POPS), and sphingomyelin (POSM). The recently resolved inward-facing (IF) state of AE1 was also included in the simulations. Lipid-protein contact analysis of the simulated trajectories was performed with the ProLint server, which provides a multitude of visualization tools for illustration of areas of enhanced lipid-protein contact and identification of putative lipid binding sites within the protein matrix. We observed enrichment of CHOL and PIP2 around all proteins with subtle differences in their distribution depending on the protein type and conformation state. Putative binding sites were identified for CHOL, PIP2, POPC, and POSM in the three studied proteins and their potential roles in the SLC4 transport function, conformational transition and protein dimerization were discussed.

Simulation-Guided Rational Design of DNA Walker-Based Theranostic Platform.

Biomolecule-functionalized nanoparticles represent a type of promising biomaterials in biomedical applications owing to their excellent biocompatibility and versatility. DNA-based reactions on nanoparticles have enabled emerging applications including intelligent biosensors, drug delivery, and biomimetic devices. Among the reactions, strand hybridization is the critical step to control the sensitivity and specificity of biosensing, and the efficiency of drug delivery. However, a comprehensive understanding of DNA hybridization on nanoparticles is still lacking, which may differ from the process in homogeneous solutions. To address this limitation, coarse-grained model-based molecular dynamic simulation is harnessed to disclose the critical factors involved in intermolecular hybridization. Based on simulation guidance, DNA walker-based smart theranostic platform (DWTP) based on "on-particle" hybridization is developed, showing excellent consistency with simulation. DWTP is successfully applied for highly sensitive miRNA 21 detection and tumor-specific miRNA 21 imaging, driven by tumor-endogenous APE 1 enzyme. It enables the precise release of antisense oligonucleotide triggered by tumor-endogenous dual-switch miRNA 21 and APE 1, facilitating effective gene silencing therapy with high biosafety. The simulation of "on-particle" DNA hybridization has improved the corresponding biosensing performance and the release efficiency of therapeutic agents, representing a conceptually new approach for DNA-based device design.

Molecular Dynamics Study on the Stress Concentration in Polymer Networks with Dangling Chains.

Owing to structural defects, stress concentration frequently occurs in polymer network materials (PEMs), significantly altering their overall mechanical properties. Here, we investigate the impact of dangling chain defects on the stress concentration in PEMs using coarse-grained molecular dynamics simulation. Stress distributions on the network structure are calculated by using graph theory, with considering the effects of defect ratio (ϕ) and the distance from defects. It is found that the existence of dangling chains can alleviate stress by dissipating more internal energy. When considering the effects of all defects statistically, the stress concentration consistently occurs near the joint segments between dangling chains and the bare network (i.e., removing all of the dangling chains from the network). The stress concentration effect is significant when defects are in the region near the network edges. Stress tends to concentrate more on the dangling chains at low ϕ, while it tends to concentrate more on the bare network at high ϕ because of the enhanced chain motions in bare network. This implies that the stress concentration effect near the joint segment is predominant at low ϕ, and it is slightly weak as ϕ increased.

Simulating Brownian motion in thermally fluctuating viscoelastic fluids by using the smoothed profile method

To investigate the Brownian motion of individual particles suspended in viscoelastic fluids, the stochastic smoothed profile method (SPm) for direct numerical simulation is developed by extending deterministic SPm for suspensions in viscoelastic media. To simulate viscoelastic flow driven by thermal fluctuations in the suspending medium, the random stress in the fluid momentum equation as well as the random driving force for the conformation tensor in the Oldroyd-B model are incorporated according to the fluctuating hydrodynamics and fluctuating viscoelasticity formalisms. The thermal equilibrium and dynamical properties calculated by using numerical simulations successfully reproduce the analytic predictions, validating the direct simulation for the coupled fluctuating Navier–Stokes and Oldroyd-B equations and for the coupling between the stochastic viscoelastic medium and individual particles. As an application of the stochastic SPm, we investigate finite system-size effects under periodic boundary conditions (PBCs) on the passive microrheological relationship between the mean-square displacement (MSD) of a Brownian particle and the medium's dynamic modulus. Comparing the modulus that was microrheologically calculated from the MSD with the input modulus reveals that the effect of periodic image cell interaction appears not only in the long-time diffusive regime but also in the short-time region. A frequency-dependent finite system-size correction is implemented by phenomenologically extending the long-time diffusive regime correction, allowing passive microrheology analysis under PBCs. This result can be directly applied to other mesoscale numerical simulations including coarse-grained molecular dynamics and dissipative particle dynamics simulations.

GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems.

Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution. These schemes are applied to the dynamics of intrinsically disordered protein (IDP) droplets. During the fusion of two droplets, we find that the changes in droplet shape correlate with the mixing of IDP chains. Additionally, we simulate large systems with multiple IDP droplets, achieving simulation sizes comparable to those observed in microscopy. In our MD simulations, we directly observe Ostwald ripening, a phenomenon where small droplets dissolve and their molecules redeposit into larger droplets. These methods have been implemented in CGDYN of the GENESIS software, offering a tool for investigating mesoscopic biological processes using the residue-level CG models.

Unveiling the Nanoconfinement Effect on Crystallization of Semicrystalline Polymers Using Coarse-Grained Molecular Dynamics Simulations.

Semicrystalline polymers under nanoconfinement show distinct structural and thermomechanical properties compared to their bulk counterparts. Despite extensive research on semicrystalline polymers under nanoconfinement, the nanoconfinement effect on the local crystallization process and the unique structural evolution of such polymers have not been fully understood. In this study, we unveil such effects by using coarse-grained molecular dynamics simulations to study the crystallization process of a model semicrystalline polymer-polyvinyl alcohol (PVA)-under different levels of nanoconfinement induced by nanoparticles that are represented implicitly. We quantify in detail the evolution of the degree of crystallinity (XC) of PVA and examine distinct crystalline regions from simulation results. The results show that nanoconfinement can promote the crystallization process, especially at the early stage, and the interfaces between nanoparticles and polymer can function as crystallite nucleation sites. In general, the final XC of PVA increases with the levels of nanoconfinement. Further, nanoconfined cases show region-dependent XC with higher and earlier increase of XC in regions closer to the interfaces. By tracking region-dependent XC evolution, our results indicate that nanoconfinement can lead to a heterogenous crystallization process with a second-stage crystallite nucleation in regions further away from the interfaces. In addition, our results show that even under very high cooling rates, the nanoconfinement still promotes the crystallization of PVA. This study provides important insights into the underlying mechanisms for the intricate interplay between nanoconfinement and the crystallization behaviors of semicrystalline polymer, with the potential to guide the design and characterization of semicrystalline polymer-based nanocomposites.

Degradation of molecular structure and residual strength of polycarbonate under cyclic loading: Insights from coarse-grained molecular dynamics simulation

Coarse-grained molecular dynamics simulations have been employed to provide insights into the molecular behavior and degradation of monodisperse polycarbonate subjected to cyclic loading with varying molecular structures characterized by two distinct parameters: radius of gyration and molecular entanglement. The fatigued polycarbonate structures were subjected to monotonic deformation in order to assess their residual strength. Our findings reveal that structures characterized by a higher degree of molecular entanglement exhibit a more significant loss of residual strength, attributable to the disentanglement induced by cyclic deformation. Furthermore, an increase in the radius of gyration contributes to greater resilience against cyclic loading, resulting in a higher level of residual strength compared to the impact of molecular entanglement.

Beyond nothingness in the formation and functional relevance of voids in polymer films

Voids—the nothingness—broadly exist within nanomaterials and impact properties ranging from catalysis to mechanical response. However, understanding nanovoids is challenging due to lack of imaging methods with the needed penetration depth and spatial resolution. Here, we integrate electron tomography, morphometry, graph theory and coarse-grained molecular dynamics simulation to study the formation of interconnected nanovoids in polymer films and their impacts on permeance and nanomechanical behaviour. Using polyamide membranes for molecular separation as a representative system, three-dimensional electron tomography at nanometre resolution reveals nanovoid formation from coalescence of oligomers, supported by coarse-grained molecular dynamics simulations. Void analysis provides otherwise inaccessible inputs for accurate fittings of methanol permeance for polyamide membranes. Three-dimensional structural graphs accounting for the tortuous nanovoids within, measure higher apparent moduli with polyamide membranes of higher graph rigidity. Our study elucidates the significance of nanovoids beyond the nothingness, impacting the synthesis‒morphology‒function relationships of complex nanomaterials.

Synthetic Force-Field Database for Training Machine Learning Models to Predict Mobility-Preserving Coarse-Grained Molecular-Simulation Potentials.

Balancing accuracy and efficiency is a common problem in molecular simulation. This tradeoff is evident in coarse-grained molecular dynamics simulation, which prioritizes efficiency, and all-atom molecular simulation, which prioritizes accuracy. Despite continuous efforts, creating a coarse-grained model that accurately captures both the system's structure and dynamics remains elusive. In this article, we present a data-driven approach for constructing coarse-grained models that aim to describe both the structure and dynamics of the system equally well. While the development of machine learning models is well-received in the scientific community, the significance of dataset creation for these models is often overlooked. However, data-driven approaches cannot progress without a robust dataset. To address this, we construct a database of synthetic coarse-grained potentials generated from unphysical all-atom models. A neural network is trained with the generated database to predict the coarse-grained potentials of real liquids. We evaluate their quality by calculating the combined loss of structural and dynamical accuracy upon coarse-graining. When we compare our machine learning-based coarse-grained potential with the one from iterative Boltzmann inversion, the machine learning prediction turns out better for all eight hydrocarbon liquids we studied. As all-atom surfaces turn more nonspherical, both ways of coarse-graining degrade. Still, the neural network outperforms iterative Boltzmann inversion in constructing good quality coarse-grained models for such cases. The synthetic database and the developed machine learning models are freely available to the community, and we believe that our approach will generate interest in efficiently deriving accurate coarse-grained models for liquids.

Structural heterogeneity in tetra-armed gels revealed by computer simulation: Evidence from a graph theory assisted characterization.

Designing homogeneous networks is considered one typical strategy for solving the problem of strength and toughness conflict of polymer network materials. Experimentalists have proposed the hypothesis of obtaining a structurally homogeneous hydrogel by crosslinking tetra-armed polymers, whose homogeneity was claimed to be verified by scattering characterization and other methods. Nevertheless, it is highly desirable to further evaluate this issue from other perspectives. In this study, a coarse-grained molecular dynamics simulation coupled with a stochastic reaction model is applied to reveal the topological structure of a polymer network synthesized by tetra-armed monomers as precursors. Two different scenarios, distinguished by whether internal cross-linking is allowed, are considered. We introduce the Dijkstra algorithm from graph theory to precisely characterize the network structure. The microscopic features of the network structure, e.g., loop size, dispersity, and size distribution, are obtained via the Dijkstra algorithm. By comparing the two reaction scenarios, Scenario II exhibits an overall more idealized structure. Our results demonstrate the feasibility of the Dijkstra algorithm for precisely characterizing the polymer network structure. We expect this work will provide a new insight for the evaluation and description of gel networks and further help to reveal the dynamic process of network formation.

Coarse-Grained Simulations on Polyethylene Crystal Network Formation and Microstructure Analysis.

Understanding and characterizing semi-crystalline models with crystalline and amorphous segments is crucial for industrial applications. A coarse-grained molecular dynamics (CGMD) simulations study probed the crystal network formation in high-density polyethylene (HDPE) from melt, and shed light on tensile properties for microstructure analysis. Modified Paul-Yoon-Smith (PYS/R) forcefield parameters are used to compute the interatomic forces among the PE chains. The isothermal crystallization at 300 K and 1 atm predicts the multi-nucleus crystal growth; moreover, the lamellar crystal stems and amorphous region are alternatively oriented. A one-dimensional density distribution along the alternative lamellar stems further confirms the ordering of the lamellar-stack orientation. Using this plastic model preparation approach, the semi-crystalline model density (ρcr) of ca. 0.913 g·cm-3 and amorphous model density (ρam) of ca. 0.856 g·cm-3 are obtained. Furthermore, the ratio of ρcr/ρam ≈ 1.06 is in good agreement with computational (≈1.096) and experimental (≈1.14) data, ensuring the reliability of the simulations. The degree of crystallinity (χc) of the model is ca. 52% at 300 K. Nevertheless, there is a gradual increase in crystallinity over the specified time, indicating the alignment of the lamellar stems during crystallization. The characteristic stress-strain curve mimicking tensile tests along the z-axis orientation exhibits a reversible sharp elastic regime, tensile strength at yield ca. 100 MPa, and a non-reversible tensile strength at break of 350%. The cavitation mechanism embraces the alignment of lamellar stems along the deformation axis. The study highlights an explanatory model of crystal network formation for the PE model using a PYS/R forcefield, and it produces a microstructure with ordered lamellar and amorphous segments with robust mechanical properties, which aids in predicting the microstructure-mechanical property relationships in plastics under applied forces.