Article
Polymer Science
Xiangning Wen, Yunlan Su, Shaofan Li, Weilong Ju, Dujin Wang
Summary: The study demonstrated that PEG-g-SiO2 can significantly increase the crystallinity and crystallization temperature of PEO matrix, affecting the crystalline morphology and rate of PEO. The good dispersion of PEG-g-SiO2 in the PEO matrix contributes to enhancing the primary nucleation rate.
Article
Chemistry, Physical
Albert J. Power, Hellen Papananou, Anastassia N. Rissanou, Massimiliano Labardi, Kiriaki Chrissopoulou, Vagelis Harmandaris, Spiros H. Anastasiadis
Summary: The dynamics of polymer chains in PEO/SiO2 nanoparticle nanohybrids were investigated using computational and experimental methods. The study revealed that spatial confinement and chain adsorption affect the structure and dynamics of the polymer. The research also found differences in the dynamics of the polymer chains under different conditions.
JOURNAL OF PHYSICAL CHEMISTRY B
(2022)
Article
Chemistry, Physical
Nicholas C. Craven, Justin B. Gilmer, Caroline J. Spindel, Andrew Z. Summers, Christopher R. Iacovella, Clare McCabe
Summary: This study utilizes molecular dynamics simulations to investigate the self-assembly of anisotropically coated patchy nanoparticles, revealing different phases formed based on various parameters. Correlation analysis identifies key predictors of bulk phase behavior, offering a powerful approach for future screening of these materials.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Chemistry, Physical
Jan Mees, Thomas C. O'Connor, Lars Pastewka
Summary: In this study, we investigate the response of grafted polymer chains in shear flow using molecular dynamics simulations. Our results show that the penetration of solvent flow into the brush depends on the brush type, and the external stress is related to the distorted polymer conformations. At low shear rates, the external stress increases linearly with shear rate, while at high rates, it increases sublinearly.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Multidisciplinary
Zuzana Benkova, Peter Cakanek, Maria Natalia D. S. Cordeiro
Summary: This study investigates the interactions between CNTs covered with different densities of PEO chains and peptides using molecular dynamics simulations. The adsorption strength of peptides on CNTs is reduced in water, and the addition of NaCl has little effect on adsorption and structure. The flexibility of the peptide backbone allows for deeper insertion into the PEO layer.
Article
Chemistry, Multidisciplinary
Sarah Cohen, Itamar Chejanovsky, Ran Yosef Suckeveriene
Summary: This article describes an innovative method of grafting PEI to silica nanoparticles using ultrasonics to remove odor from recycled plastic materials. The results show a substantial reduction in odor intensity and volatile organic compounds, indicating the potential commercial use of this PEI/Si nanocomposite.
Article
Polymer Science
Shaofan Li, Weilong Ju, Guoming Liu, Yunlan Su, Alejandro J. Muller, Dujin Wang
Summary: The properties of polymer nanocomposites (PNCs) are dependent on the dispersion of nanoparticles within the polymer matrix. This study investigates the dispersion and crystallization behaviors of PE/HDPE1289-g-SiO2 PNCs in different polyethylene (PE) matrices. The results show that the dispersion of HDPE1289-g-SiO2 nanoparticles is influenced by the P/N parameter and the similarity between the grafted and matrix polymer chain structures.
Article
Electrochemistry
Michal Marzantowicz, Abeer Sami, Karol Pozyczka, Agnieszka Chodara, Dorota Gladka, Ewa Zygadlo-Monikowska, Franciszek Krok
Summary: Polymer electrolytes composed of lithium borate salts and poly(ethylene oxide) PEO are prepared and their characteristics are investigated. It is found that these electrolytes exhibit lower glass transition temperature and higher characteristic frequencies of dielectric relaxations. Moreover, the mixed systems show higher transference numbers than pure borate salt.
ELECTROCHIMICA ACTA
(2023)
Article
Chemistry, Physical
Cristina Carucci, Giulia Sechi, Marco Piludu, Maura Monduzzi, Andrea Salis
Summary: This study focuses on optimizing the loading and release processes of the flavonoid quercetin by changing the solvent composition, leading to a more sustained release and improved stability and release concentration of quercetin in a pH-sensitive antimicrobial drug delivery system based on Mesoporous silica nanoparticles (MSN) functionalized with different compounds.
COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS
(2022)
Article
Polymer Science
Christopher B. Keller, Susan E. Walley, Curtis W. Jarand, Jibao He, Muhammad Ejaz, Daniel A. Savin, Scott M. Grayson
Summary: By grafting linear-bottlebrush amphiphilic copolymers onto the surface of silica nanoparticles, nanoparticle micelles with the ability to encapsulate and stabilize non-polar structures in aqueous media were successfully formed. These nanoparticles not only enhance oil encapsulation, but also provide an alternative dispersant system to address oil pollution in the environment.
Article
Biochemistry & Molecular Biology
Aleksandra Wypych-Puszkarz, Onur Cetinkaya, Jiajun Yan, Ruslana Udovytska, Jaroslaw Jung, Jacek Jenczyk, Grzegorz Nowaczyk, Stefan Jurga, Jacek Ulanski, Krzysztof Matyjaszewski, Joanna Pietrasik, Marcin Kozanecki
Summary: Core-shell nanocomposites consisting of barium titanate nanocrystals grafted onto poly(methyl methacrylate) chains were prepared. The nanocomposites exhibited enhanced dielectric permittivity and improved thermal stability. The presence of ceramic nanoparticles affected the molecular dynamics and structure of the polymer chains.
Article
Polymer Science
Ruibin Ma, Wenfeng Zhang, Yimin Wang, Haoxiang Li, Xiuying Zhao, Xiaolin Li, Liqun Zhang, Yangyang Gao
Summary: This study provides a clear and novel understanding of how grafted chains manipulate the rupture toughness of silica nanoparticle/polyisoprene nanocomposites at the molecular scale. The mechanics and deformation of the nanocomposites are analyzed, and the influence of grafted chains on the rupture toughness and void formation is quantified. The findings contribute to the design and fabrication of nanocomposites with enhanced mechanical properties.
Article
Polymer Science
Aakash Sharma, Margarita Kruteva, Sascha Ehlert, Martin Dulle, Stephan Foerster, Dieter Richter
Summary: Small-angle X-ray scattering is a powerful technique for investigating the spatial arrangements of polymer-grafted nanoparticles in nanocomposites. However, the commonly used hard sphere model fails to accurately describe the density of the grafted polymer, leading to inappropriate quantitative descriptions of nanoparticle assemblies. By analyzing the scattering data and considering the polymer-induced interactions, we are able to establish quantitative relations between the nanoparticle assembly and the polymer structure in the nanocomposites.
Article
Polymer Science
Mina Ahsani, Reza Sabouri, Mathias Ulbricht, Hossein Hazrati, Abbas Jafarizad, Reza Yegani
Summary: The hydrophilic and antibacterial Ag-SiO2-PVP nanoparticles were successfully synthesized through multiple steps. The vinyl groups and PVP brushes were successfully generated onto the silica nanoparticles using silanization and grafting-through polymerization methods. The Ag-SiO2-PVP nanoparticles showed outstanding bactericidal properties when assessed using the plate colony counting method.
JOURNAL OF APPLIED POLYMER SCIENCE
(2021)
Article
Chemistry, Physical
Matthew Mears, Zhenyu J. Zhang, Ryan C. D. Jackson, Yuchen Si, Tigerlily J. B. Bradford, John M. Torkelson, Mark Geoghegan
Summary: Fluorescence correlation spectroscopy was used to study the temperature-dependent diffusion coefficient of PEO on various surfaces, showing an increase in diffusion below T-gs for certain surfaces, accompanied by an unexpected increase in friction at the same temperature.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Chemistry, Physical
Shuwen Yue, Marc Riera, Raja Ghosh, Athanassios Z. Panagiotopoulos, Francesco Paesani
Summary: Building upon previous work, this study introduces a second generation of data-driven many-body models for CO2 and systematically assesses the impact of CO2-CO2 interactions on the models' ability to predict equilibrium properties. By fitting reference energies calculated at the coupled cluster level, a series of models are constructed. The use of charge model 5 and scaling of two-body energies lead to more accurate descriptions of CO2 properties. The findings highlight the importance of training set quality in developing transferable, data-driven models.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Multidisciplinary Sciences
Chunyi Zhang, Shuwen Yue, Athanassios Z. Panagiotopoulos, Michael L. Klein, Xifan Wu
Summary: By using advanced machine learning techniques, researchers have found that dissolving salt in water does not lead to drastic changes in the structure of water. Contrary to previous beliefs about the pressure effect, the study shows that the ions in salt water only disrupt the hydrogen bond network within the first solvation shells, without significantly altering the oxygen radial-distribution function. This finding challenges the widely accepted pressure-like effect in Hofmeister series ionic solutions.
NATURE COMMUNICATIONS
(2022)
Article
Chemistry, Physical
Linfeng Zhang, Han Wang, Maria Carolina Muniz, Athanassios Z. Panagiotopoulos, Roberto Car, Weinan E
Summary: Researchers have extended the deep potential model to approximate the long-range electrostatic interaction between ions and valence electrons, improving the accuracy and predictive power of the model.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Sina Hassanjani Saravi, Athanassios Z. Panagiotopoulos
Summary: This study obtained activity coefficients and solubilities of NaCl in water-methanol solutions using molecular dynamics simulations. The selection of appropriate combining rules was found to be important in obtaining realistic solubilities. The study demonstrates that good predictions for these phase equilibrium properties can be achieved for mixed-solvent electrolyte solutions using existing models.
JOURNAL OF PHYSICAL CHEMISTRY B
(2022)
Article
Chemistry, Physical
Thomas E. Gartner, Kelly M. Hunte, Eleftherios Lambros, Alessandro Caruso, Marc Riera, Gregory R. Medders, Athanassios Z. Panagiotopoulos, Pablo G. Debenedetti, Francesco Paesani
Summary: In this study, molecular dynamics simulations with the many-body MB-pol model were used to investigate the thermodynamic response and local structure of liquid water at different temperatures. The results suggest that the MB-pol model has predictive capability for the physical properties of liquid water across a wide range of thermodynamic states, including the difficult-to-probe "water's no man's land."
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2022)
Article
Chemistry, Physical
Jack Weis, Francesco Sciortino, Athanassios Z. Panagiotopoulos, Pablo G. Debenedetti
Summary: Recent experiments and numerical simulations have provided support to the hypothesis that a second critical point exists in deeply supercooled water. In particular, a study has found that a liquid-liquid critical point can be located using a model parameterized solely based on ab initio calculations. This finding is important for understanding the phase behavior of supercooled water.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Multidisciplinary Sciences
Pablo M. Piaggi, Jack Weis, Athanassios Z. Panagiotopoulos, Pablo G. Debenedetti, Roberto Car
Summary: Molecular simulations based on machine-learning models and density-functional theory have provided insights into the mechanism of homogeneous ice nucleation. The results are in good agreement with experimental measurements, and the impact of factors such as thermodynamic driving force, interfacial free energy, and stacking disorder on nucleation rates has been studied.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Chemistry, Physical
Athanassios Z. Panagiotopoulos, Shuwen Yue
Summary: This article summarizes recent simulation work on the dynamics of aqueous electrolytes. It shows that full-charge, nonpolarizable models for water and ions predict solution dynamics that are too slow, while models with reduced charges have issues describing certain dynamic phenomena. Polarizable models, when appropriately parametrized, show promise but may miss important physical effects. First-principles calculations are emerging to capture polarization, charge transfer, and chemical transformations in solution. Machine-learning models trained on first-principles data offer promise for accurate and transferable modeling of electrolyte solution dynamics.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)
Article
Chemistry, Physical
Athanassios Z. Panagiotopoulos
Summary: This paper investigates the phase and aggregation behavior of linear chains composed of hydrophilic and hydrophobic blocks. The phase and conformational transitions of patterned chains are important for understanding liquid-liquid separation of biomolecular condensates and have applications in cellular biophysics, surfactants, and polymers. The key finding of this study is that certain chain architectures can exhibit both finite-size aggregate formation and phase separation under appropriate conditions of temperature and concentration. The computational approach used in this study involves histogram-reweighting grand canonical Monte Carlo simulations, which are described in detail.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Ignacio Sanchez-Burgos, Maria Carolina Muniz, Jorge R. Espinosa, Athanassios Z. Panagiotopoulos
Summary: In this study, the Deep Potential methodology was used to investigate the phase transition of liquid water to vapor. The machine learning model was trained on ab initio energies and forces based on the SCAN density functional. Various properties, such as surface tension, saturation pressure, and enthalpy of vaporization, were computed and compared with experimental data and a classical model. The results showed a deviation in nucleation rates due to an underestimation of surface tension in the Deep Potential model, and also revealed a preferential orientation of water molecules in the liquid-vapor interface.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Reha Mathur, Maria Carolina Muniz, Shuwen Yue, Roberto Car, Athanassios Z. Panagiotopoulos
Summary: In this work, distinct first-principles-based machine-learning models of CO2 were constructed, allowing for stable interfacial system simulation, prediction of vapor-liquid equilibrium properties, and improved computational efficiency. The SCAN and SCAN-rvv10 models exhibit temperature shifts, while the BLYP-D3 model performs better for liquid phase and vapor-liquid equilibrium properties, and the PBE-D3 model is better suited for predicting transport properties.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)
Article
Chemistry, Physical
Maria Carolina Muniz, Roberto Car, Athanassios Z. Panagiotopoulos
Summary: A deep potential neural network (DPMD) model based on the MB-pol potential for water was developed, which can combine accuracy and transferability if sufficient attention is given to the construction of a representative training set for the target system.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)
Article
Physics, Multidisciplinary
Chunyi Zhang, Shuwen Yue, Athanassios Z. Panagiotopoulos, Michael L. Klein, Xifan Wu
Summary: The dielectric permittivity of salt water decreases as more salt is dissolved, which is explained by saturation in the dielectric response of solvent water molecules. By using an advanced deep neural network (DNN) based on density functional theory data, the dielectric permittivity of sodium chloride solutions is studied. The computed decrease in dielectric permittivity as a function of concentration, using the DNN approach, agrees well with experimental results. The dominant effect causing this decrease is the intrusion of ionic hydration shells into the solvent hydrogen-bond network, disrupting dipolar correlations among water molecules and suppressing the collective response of solvent waters.
PHYSICAL REVIEW LETTERS
(2023)
Meeting Abstract
Biophysics
Ushnish Rana, Ke Xu, Amal Narayanan, Mackenzie T. Walls, Jose L. Avalos, Athanassios Z. Panagiotopoulos, Clifford P. Brangwynne
BIOPHYSICAL JOURNAL
(2023)
Article
Chemistry, Physical
Athanassios Z. Panagiotopoulos, Shuwen Yue
Summary: This Perspective article discusses recent simulation work on aqueous electrolyte dynamics. Full-charge, nonpolarizable models for water and ions tend to underestimate solution dynamics compared to experiments. Models with reduced charges perform better for diffusivities and viscosities, but struggle with other dynamic phenomena like crystal nucleation rates. Polarizable models show promise, but may still miss important effects like charge transfer. First-principles calculations are emerging to capture polarization, charge transfer, and transformations in solution, while machine-learning models trained on such data can accurately model electrolyte solution dynamics.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)