We have developed a coarse-grained multiscale molecular simulation method for soft matter systems that directly incorporates stereochemical information. We divide the material into disjoint groups of atoms or particles that move as separate rigid bodies; we call these groups "rigid blobs," hence the name coarse-grained rigid blob model. The method is enabled by the construction of transferable interblob potentials that approximate the net intermolecular interactions, as obtained from ab initio electronic structure calculations, other all-atom empirical potentials, experimental data, or any combination of the above. We utilize a multipolar expansion to obtain the interblob potential-energy functions. The series, which contains controllable approximations that allow us to estimate the errors, approaches the original intermolecular potential as the number of terms increases. Using a novel numerical algorithm, we can calculate the interblob potentials very efficiently in terms of a few interaction moment tensors. This reduces the labor well beyond what is required in standard molecular-dynamics calculations and allows large-scale simulations for temporal scales commensurate with characteristic times of nano- and mesoscale systems. A detailed derivation of the formulas is presented, followed by illustrative applications to several systems showing that the method can effectively capture realistic microscopic details and can easily extend to large-scale simulations.
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http://dx.doi.org/10.1063/1.1938193 | DOI Listing |
Phys Chem Chem Phys
January 2025
Department of Chemical Engineering, Indian Institute of Technology Gandhinagar, India.
Self-assembly of nanoparticles (NPs) in solution has garnered tremendous attention among researchers because of their electrical, chemical, and optoelectronic properties at the macroscale with potential applications in bio-imaging, bio-medicine, and therapeutics. Control of size, shape, and composition at the nanoscale is important in tuning the material's bulk properties. The grafting of NPs with polymers enables us to tune such bulk material properties at the nano level by controlling their assemblies, especially in solutions.
View Article and Find Full Text PDFInt J Pharm
December 2024
State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China; Faculty of Health Sciences, University of Macau, Macau 999078, China. Electronic address:
Messenger RNA (mRNA) encapsulated in lipid nanoparticles (LNPs) represents a cutting-edge delivery technology that played a pivotal role during the COVID-19 pandemic and in advancing vaccine development. However, molecular structure of mRNA-LNPs at real size remains poorly understood, with conflicting results from various experimental studies. In this study, we aim to explore the assembly process and structural characteristics of mRNA-LNPs at realistic sizes using coarse-grained molecular dynamic simulations.
View Article and Find Full Text PDFPhys Rev E
November 2024
Department of Fibre and Polymer Technology, KTH Royal Institute of Technology, SE10044 Stockholm, Sweden and Wallenberg Wood Science Center, KTH Royal Institute of Technology, SE10044 Stockholm, Sweden.
Motivated by the limitations of conventional coarse-grained molecular dynamics for simulation of large systems of nanoparticles and the challenges in efficiently representing general pair potentials for rigid bodies, we present a method for approximating general rigid body pair potentials based on a specialized type of deep neural network that maintains essential properties, such as conservation of energy and invariance to the chosen origins of the particles. The network uses a specialized geometric abstraction layer to convert the relative coordinates of the rigid bodies to input more suitable to a conventional artificial neural network, which is trained together with the specialized layer. This results in geometric representations of the particles optimized for the specific potential.
View Article and Find Full Text PDFMacromolecules
November 2024
School of Polymer Science and Engineering, Center for Optoelectronic Materials and Devices, The University of Southern Mississippi, Hattiesburg, Mississippi 39406, United States.
The conjugated polymer's backbone conformation dictates the delocalization of electrons, ultimately affecting its optoelectronic properties. Most conjugated polymers can be viewed as semirigid rods with their backbone embedded among long alkyl side chains. Thus, it is challenging to experimentally quantify the conformation of a conjugated backbone.
View Article and Find Full Text PDFBiomacromolecules
December 2024
Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Computationally designed homotetrameric helical peptide bundles have been functionalized at their N-termini to achieve supramolecular polymers, wherein individual bundles ("bundlemers") are the monomeric units. Adjacent bundles are linked via two covalent cross-links. The polymers exhibit a range of conformational properties, including formation of rigid-rods with micrometer-scale persistence lengths.
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