Article
Chemistry, Physical
Aditi Khot, Brett M. Savoie
Summary: Coarse-grained molecular dynamics (CGMD) simulations address critical lengthscales and timescales in chemical and material applications. The development of black-box CGMD methodologies similar to density functional theory for electronic structure is still lacking. Machine learning (ML)-based CGMD potentials show promise in simplifying model development, but they have yet to outperform physics-based CGMD methods. In this study, λ-learning models are explored to combine the advantages of both approaches. The λ-models outperform ML-only CGMD models and provide essentially free gains in reproducing atomistic properties. However, neither the λ-learning models nor the ML-only models significantly outperform elementary pairwise models in reproducing atomistic properties due to the large irreducible force errors associated with coarse-graining.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Review
Biochemistry & Molecular Biology
Tiedong Sun, Vishal Minhas, Nikolay Korolev, Alexander Mirzoev, Alexander P. Lyubartsev, Lars Nordenskiold
Summary: This review presents some well-developed bottom-up coarse-graining methods for effective modeling of DNA properties, such as DNA flexibility, conformation, melting, and condensation, based on underlying atomistic force field simulations. These methods separate fast and slow dynamic processes in molecular systems and construct coarse-grained Hamiltonian using pair-wise additive potential for efficiency in computer simulation.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2021)
Article
Chemistry, Physical
Jaehyeok Jin, Kenneth S. Schweizer, Gregory A. Voth
Summary: The first paper of this series demonstrated the scalability of excess entropy for both fine-grained and coarse-grained systems. However, a more precise determination of the scaling relationship was not possible due to its semi-empirical nature. In this second paper, an analytical scaling relation for excess entropy is derived for bottom-up coarse-grained systems. By constructing effective hard sphere systems at the single-site resolution, the dynamics and excess entropy of the target coarse-grained systems can be accurately approximated.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Ganesh Sivaraman, Nicholas E. Jackson
Summary: Scalable electronic predictions are critical for soft materials design. The Electronic Coarse-Graining (ECG) method uses deep neural networks (DNNs) to renormalize all-atom quantum chemical (QC) predictions to coarse-grained (CG) resolutions. The GPU-accelerated Deep Kernel Learning (DKL) framework enables CG QC predictions with a significant speedup, accurately reproducing molecular orbital energies.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Polymer Science
Christopher Balzer, Amalie L. Frischknecht
Summary: The structure and morphology of ionic aggregates in ionomer melts significantly affect their ion transport properties. By incorporating polarization in ionomer melts, this study examines the role of polarization in the structure and dynamics of pendant ionomers and compares it to non-polarizable systems. The results show that polarization leads to smaller ionic aggregates and less overall ion structuring. Additionally, the time scale for free counterion diffusion is found to be independent of the morphology under certain conditions.
Article
Biochemistry & Molecular Biology
Martina Pannuzzo, Alessia Felici, Paolo Decuzzi
Summary: In this study, a computational model for poly-lactic-glycolic-acid (PLGA) was developed and validated to analyze the mesoscopic characteristics of PLGA-based delivery systems. The model, using coarse grained (CG) models and molecular dynamics (MD) simulations, predicted the translocation free energy barrier of drugs in the PLGA matrix and compared it with experimental release data. The proposed computational framework allows for predicting the pharmacological behavior of polymeric implants with different drug payloads under various conditions, reducing experimental workload and costs.
Article
Chemistry, Physical
Selim Sami, Siewert J. Marrink
Summary: This paper presents a new approach for modeling chemical reactivity in the Martini coarse-grained (CG) model, using tabulated potentials and an extra particle for capturing changes in bonded topology. The reactive Martini model is demonstrated by studying the macrolcycle formation of benzene-1,3-dithiol molecules, where macrocycles of sizes consistent with experimental results are obtained from monomers. The framework is general and can be easily extended to other systems.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Physical
Yangyang Zhang, Donghui Liu, Yiyang Zhang, Yachong Guo, Wenfei Li, Fabrice Thalmann
Summary: This article describes a coarse-grained model of POPC and DOPC lipid peroxides and discusses their predicted structure and the influence of hydration. In addition, electron and neutron scattering length density profiles of the simulated bilayers are provided.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Michael R. DeLyser, W. G. Noid
Summary: Investigated a new class of one-body potentials called square gradient (SG) potentials that can improve the accuracy and transferability of coarse-grained (CG) models. These SG potentials can tune interfacial properties and enhance the performance of various models.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Physics, Fluids & Plasmas
Enrico Skoruppa, Aderik Voorspoels, Jocelyne Vreede, Enrico Carlon
Summary: Investigations on the influence of nonlocal couplings on DNA torsional and bending elasticities revealed strong off-site couplings for tilt-tilt and twist-twist, while they were weaker in the roll-roll case. Analysis indicated that off-site interactions generate a length-scale-dependent elasticity in DNA models. Simulation-generated data predicted significant length-scale-dependent effect on torsional fluctuations, but only a modest effect on bending fluctuations, consistent with experimental observations probing DNA mechanics.
Article
Chemistry, Physical
Ming Ma, Junjie Song, Yi Dong, Weihai Fang, Lianghui Gao
Summary: In this study, a novel coarse-grained force field was developed to reproduce the structural and thermodynamic properties of triglycerides in bulk phase, as well as at air and water interfaces. The force field accurately reproduced the self-assembled network and diverse molecular conformations of triglycerides in water, and correctly predicted experimental macroscopic thermodynamic properties. This work paves the way for studying complex systems involving triglycerides on a larger scale.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Stephan Thaler, Maximilian Stupp, Julija Zavadlav
Summary: Neural network potentials are a natural choice for coarse-grained models, but they suffer from finite data effects when trained bottom-up via force matching. In this work, the authors demonstrate that relative entropy training is more data efficient and improves free energy surfaces and sensitivity to prior potentials. The findings support the use of training objectives beyond force matching for improving the accuracy and reliability of coarse-grained neural network potentials.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Polymer Science
Heyi Liang, Juan J. de Pablo
Summary: In this study, the properties of polyelectrolyte coacervates under different salt concentrations were investigated using molecular dynamics simulations. The interfacial tension and microscopic structure of the coacervates were found to be affected by the salt concentration. Similar to neutral polymer solutions, the structure and dynamics of the coacervates were influenced by the screening of electrostatic interactions. The polyelectrolyte chains adopted ideal conformations and their relaxation behavior could be described by the Rouse model. The stress relaxation modulus of coacervates with different salt and polymer concentrations could be superimposed to form a master curve, in agreement with experimental observations of the "salt-time superposition" principle.
Article
Chemistry, Physical
Maziar Fayaz-Torshizi, Edward J. Graham, Claire S. Adjiman, Amparo Galindo, George Jackson, Erich A. Muller
Summary: Coarse-grained models of polyaromatic hydrocarbons parametrized by the SAFT-c Mie approach are evaluated for their ability to predict liquid properties and structural behavior. The models show quantitative accuracy and offer significant computational speedups compared to all-atom models.
JOURNAL OF MOLECULAR LIQUIDS
(2023)
Article
Chemistry, Multidisciplinary
Ping Gao, Julien Nicolas, Tap Ha-Duong
Summary: This study utilized coarse-grained molecular dynamics simulations to investigate the self-assembly of four representative drug-polymer conjugates, revealing the spatial organization of components within the nanoparticles. It was observed that the linkers were not fully accessible to the solvent, which may account for the low drug release efficiency from the nanoparticles.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2021)
Article
Chemistry, Physical
Dorian Bruch, Christopher Balzer, Zhen-Gang Wang
Summary: Electric double layers are widely used in science and engineering, but calculating thermodynamic properties from the free energy of a system with charged surfaces can be complicated. In this study, a systematic framework is presented to properly account for the different specifications on charged bodies in electrolyte solutions. The approach is demonstrated using the Poisson-Boltzmann theory and emphasizes the importance of using the proper thermodynamic potential, providing a general framework for calculating thermodynamic properties of electrolyte solutions near charged surfaces.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Baicheng Mei, Bilin Zhuang, Yuyuan Lu, Lijia An, Zhen-Gang Wang
Summary: By introducing the concept of local-average free volume, this study reveals the correlation between dynamic heterogeneity and the average local free volume in glass formers, resolving the controversy regarding the role of free volume in particle rearrangements.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2022)
Article
Polymer Science
Pengfei Zhang, Zhen-Gang Wang
Summary: This work investigates the structure and thermodynamics of the supernatant phase in polyelectrolyte complex coacervation. By combining cluster theory and mean-field theory, the study explores the structure of clusters formed by oppositely charged polyions and their impact on phase separation in polyelectrolyte complex coacervation. The results show that the polyion concentration and interfacial tension decrease with increasing cluster size, while the concentration of polyions in the supernatant phase at coexistence is significantly higher than predicted by the uniform mixing approximation. The study also reveals the existence of a pseudo-spinodal in supersaturated solutions, with a concentration higher than predicted by the uniform mixing approximation. Simple analytical expressions for cluster formation free energy, modified binodal, and pseudo-spinodal are derived, and an approximate formula for estimating the concentration of the coexisting supernatant phase is proposed.
Article
Polymer Science
Shensheng Chen, Pengfei Zhang, Zhen-Gang Wang
Summary: In this study, dissipative particle dynamics was used to investigate the behavior of polyelectrolyte complexes in dilute solutions. The results show that net-charged macromolecular clusters are formed in the systems, which depends on the overall charge asymmetry. When the charge ratio reaches a threshold value, the polyions condense into a single large coacervate cluster. The addition of salt leads to salting-out and salting-in phenomena, and the length and concentration asymmetry play significant roles in polyelectrolyte complex coacervation.
Article
Polymer Science
Zhenhua Wang, Ruishu Wang, Yuyuan Lu, Lijia An, An-Chang Shi, Zhen-Gang Wang
Summary: The study found that different capture mechanisms exist for linear and ring polymers under flow induction, and the critical flux is affected by the increase in channel size. Additionally, the conformation of the polymer undergoes a flow-induced transition, and monomers inside and outside the channel exhibit independent dynamics.
Article
Engineering, Chemical
Andrew S. Ylitalo, Huikuan Chao, Pierre J. Walker, Jacob Crosthwaite, Thomas C. Fitzgibbons, Valeriy G. Ginzburg, Weijun Zhou, Zhen-Gang Wang, Ernesto Di Maio, Julia A. Kornfield
Summary: This study investigates the factors affecting the solubility of carbon dioxide in polyether polyols through experimental measurements and modeling. The results show that the solubility of carbon dioxide in polyether polyols decreases with molecular weight and functionality.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)
Article
Chemistry, Physical
Ashesh Ghosh, Quinn MacPherson, Zhen-Gang Wang, Andrew J. Spakowitz
Summary: We studied the collective elastic behavior of semiflexible polymer solutions in a nematic liquid-crystalline state using polymer field theory. Our results show that the twist elastic constant is smaller than the bend and splay constants and there are dominance regimes for the bend and splay constants depending on the polymer rigidity.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Polymer Science
Pengfei Zhang, Zheng Wang, Zhen-Gang Wang
Summary: Based on a minimal lattice model, this study applies the Wang-Landau Monte Carlo algorithm and a Flory-type mean-field theory to investigate the conformation of a homopolymer chain in a mixture of binary solvents A and B. The results show that adding a small amount of better solvent B in a good solvent A causes a continuous collapse transition when the difference in the solvent quality is large. Increasing the fraction of solvent B results in a smooth reswelling of the chain. These findings are explained by the delicate interplay among the mixing entropy of binary solvents, the chain conformational entropy, and the competition in the interactions between the monomer and the two solvents.
Article
Chemistry, Physical
Samuel Varner, Christopher Balzer, Zhen-Gang Wang
Summary: Implicit solvent models are commonly used to study soft materials and biophysical systems by simplifying solvent degrees of freedom into effective interaction potentials. In electrolyte and polyelectrolyte solutions, the solvent degrees of freedom are coarse-grained into an effective dielectric constant, which incorporates the entropic contributions into the temperature dependence of the dielectric constant. Properly considering the electrostatic entropy is crucial for differentiating between enthalpically and entropically driven free energy changes. In this study, we investigate the entropic origin of electrostatic interactions in a dipolar solvent and provide a clearer physical understanding of the solvent dielectric response. We calculate the potential of mean force (PMF) between oppositely charged ions in a dipolar solvent using molecular dynamics and dipolar self-consistent field theory, and find that the PMF is primarily governed by the entropy gain from dipole release, resulting from reduced orientational polarization of the solvent. We also observe a nonmonotonic temperature dependence of the relative contribution of entropy to the free energy change. Our findings are expected to be applicable to a wide range of problems involving ionic interactions in polar solvents.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)
Article
Polymer Science
Zhenhua Wang, Zhen-Gang Wang, An-Chang Shi, Yuyuan Lu, Lijia An
Summary: The effects of confinement and hydrodynamic interactions on single-chain diffusion behaviors are studied using molecular dynamics and multiparticle collision dynamics simulations. It is found that long chains exhibit diffusion behavior consistent with Zimm dynamics, while short chains deviate from it. For confined chains, the diffusion behavior undergoes a crossover from Zimm to Rouse dynamics as the channel size decreases. The transition can be quantitatively described by extending the partially permeable sphere model to the blob scale.
Article
Chemistry, Physical
Christopher Balzer, Zhen-Gang Wang
Summary: End-tethered polyelectrolytes are commonly used to modify substrate properties, and external stimuli can further tune these modifications. This study investigates the structure and electroresponsiveness of weak polyacid brushes using an inhomogeneous theory, and explores the relationship between swelling behavior and differential capacitance.
EUROPEAN PHYSICAL JOURNAL E
(2023)
Article
Chemistry, Physical
Shensheng Chen, Zhen-Gang Wang
Summary: Biomolecular assembly often exhibits enthalpy-entropy compensation behavior, but its molecular origin and the contribution of water restructuring to entropy and enthalpy changes in this process have been poorly understood. This study shows that water reorganization entropy/enthalpy can be obtained by exploiting the temperature dependence in effective, implicit-solvent potentials. The temperature dependencies in hydrophobic interactions, resulting from water reorganization, significantly contribute to the variations in entropy/enthalpy change and are responsible for the observed enantioselective enrichment.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)
Article
Polymer Science
Ruochao Wang, Valeriy V. Ginzburg, Jian Jiang, Zhen-Gang Wang
Summary: The characteristics of surfaces have significant effects on polyelectrolyte adsorption. Random charge distribution results in the strongest adsorption, while uniform distribution shows the weakest. In the presence of dielectric contrast, image repulsion inhibits adsorption onto uniformly charged surfaces, while surfaces with discrete charge distributions exhibit enhanced adsorption.
Article
Polymer Science
Kevin. D. D. Dorfman, Zhen-Gang Wang
Summary: The Largecell self-consistent field theory (SCFT) solutions, initialized using the structure of a Lennard-Jones fluid, show the existence of numerous liquid-like states with higher free energies compared to the body-centered cubic (bcc) state near the order-disorder transition (ODT). The structure factor calculation indicates a slightly swollen intermicellar distance for these liquid-like states at temperatures below ODT. The presence of multiple liquid-like states and their near-degeneracy with the equilibrium bcc morphology explains the slow ordering kinetics observed in particle-forming diblock copolymer melts.