Article
Chemistry, Physical
Aleksander E. P. Durumeric, Gregory A. Voth
Summary: Bottom-up CG molecular dynamics models, parameterized using complex effective Hamiltonians, are often optimized to approximate high dimensional data from atomistic simulations. However, human validation of these models may not differentiate between the CG model and the atomistic simulations. We propose using classification to estimate high dimensional errors and utilizing explainable machine learning to convey this information to scientists. This approach is demonstrated using Shapley additive explanations and two CG protein models, and may be valuable for assessing the accuracy of allosteric effects in CG models at the atomistic level.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Umashankar Erigi, Umesh Dhumal, Mukta Tripathy
Summary: The study uses PRISM theory and molecular dynamics simulations to investigate the structure and phase behavior of polymer nanocomposites with nanorods. Both methods predict the formation of different aggregates based on the strength of polymer-nanorod interactions and show that the miscible region narrows with increasing nanorod aspect ratio. Results suggest that theory and simulations qualitatively complement each other but display quantitative differences.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Polymer Science
Kuan-Hsuan Shen, Mengdi Fan, Lisa M. Hall
Summary: Molecular dynamics simulations with generic bead-spring models have been used to study the molecular-scale behavior and structure-property relationships of various polymeric systems. While this coarse-grained modeling approach provides computational efficiency and flexibility in considering different chemistries, additional complexity may be needed to appropriately describe phenomena in ion-containing polymeric systems.
Article
Polymer Science
Yaguang Sun, Kaiwei Wan, Wenhui Shen, Jianxin He, Tong Zhou, Hui Wang, Hua Yang, Xinghua Shi
Summary: Recycling and reprocessing of conventional thermosetting polymers have gained attention due to environmental concerns. This study focuses on covalent adaptable networks (CANs) which incorporate functional groups capable of reversible exchange reactions into polymer networks, altering the topology arrangement and achieving stress relaxation. The researchers developed a machine-learning force field to describe the exchange reactions of polyimine CANs and provided insights into reaction mechanisms and energy profiles through enhanced sampling methods.
Article
Polymer Science
Emmanuel N. Skountzos, Katerina S. Karadima, Vlasis G. Mavrantzas
Summary: The study investigates the impact of adsorbed domains and nanoparticle bridging chains on the properties of attractive polymer nanocomposite melts through MD simulations. The presence of adsorbed polymer significantly affects the dynamic and conformational properties of the nanocomposite, especially under conditions favoring higher surface-to-volume ratios. Moreover, the bridging chains drive the formation of a nanoparticle network which becomes denser and stronger with increasing concentration of the polymer matrix in nanoparticles.
Article
Polymer Science
Yijing Nie, Jun Yang, Zongfa Liu, Zhiping Zhou, Yongqiang Ming, Tongfan Hao
Summary: Based on molecular dynamics simulations, this study focused on the stretch-induced precursor formation and nucleation process in carbon nanotube (CNT) filled polyethylene. It was found that CNTs can orient polymer segments along the stretching direction, leading to higher degree of orientation and higher content of special conformational segments in the interfacial regions.
Article
Chemistry, Physical
A. Arjun, Peter G. Bolhuis
Summary: This study investigates the homogenous nucleation rate of CO2 hydrates at low temperatures using transition interface sampling simulations, revealing the differences in hydrate formation processes at different temperatures and shedding light on the kinetics of nucleation processes.
JOURNAL OF CHEMICAL PHYSICS
(2021)
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
Polymer Science
Chia-Cheng Chu, Pai-Yi Hsiao
Summary: This article proposes a two-stage model to explain the phenomena of chain expansion released from a confining cavity. In the first stage, the chain is assumed to expand as a sphere, while in the second stage it expands like a coil. The kinetic equations for the variation of chain size are derived in the two stages by balancing the rate of the free energy change with the rate of energy dissipation. Langevin dynamics simulations are performed to examine the theory. The simulation results support the theory and reveal that the expansion process is dominated by the second stage, confirming the predicted curve for coil expansion.
Article
Polymer Science
Ruisi Chen, Zhiyu Zhang, Mengyu Zhou, Yue Han, Fanzhu Li, Jun Liu, Liqun Zhang
Summary: Through coarse-grained molecular dynamics simulation, the welding interfacial structure, dynamics, and strength of polymer nanocomposites (PNCs) were investigated. The migration of nanoparticles, the anisotropy of polymer chain dimensions, and the diffusion depth of welding interlayers were found to vary with the polymer-nanoparticle interaction strength. The welding efficiency was found to be highest at low interaction strength.
MACROMOLECULAR RAPID COMMUNICATIONS
(2022)
Article
Chemistry, Physical
Ernesto Suarez, Rafal P. Wiewiora, Chris Wehmeyer, Frank Noe, John D. Chodera, Daniel M. Zuckerman
Summary: Markov state models (MSMs) are widely used in studying protein conformational dynamics, accurately reproducing correlation functions for states with longer lifetimes but facing stricter requirements for path-based observables; history-augmented MSMs (haMSMs) show more reliable performance in reproducing path-based observables, even in the presence of short-lived states.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2021)
Article
Chemistry, Physical
Fuchun Ge, Lina Zhang, Yi-Fan Hou, Yuxinxin Chen, Arif Ullah, Pavlo O. Dral
Summary: This article demonstrates that AI can learn atomistic systems in the four-dimensional spacetime by introducing the 4D-spacetime GICnet model. This model can predict nuclear positions and velocities as a continuous function of time up to the distant future based on given initial conditions. It provides long-time high-resolution molecular dynamics trajectories, improves efficiency and accuracy compared to traditional methods.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Article
Mechanics
N. Moreno, M. Ellero
Summary: This work presents a methodology for conducting rheological studies on smoothed dissipative particle dynamics under arbitrary flow configurations. It evaluates the accuracy and flexibility of the method through viscometric studies on Newtonian fluids in various flow conditions, and demonstrates its applicability in obtaining viscoelastic properties of non-Newtonian fluids. The new computational approach offers significant advantages in a range of applications, from multiscale simulations to characterizing complex flows.
Article
Polymer Science
Dominic Wadkin-Snaith, Paul Mulheran, Karen Johnston
Summary: This study used molecular dynamics simulations to investigate the nucleation and crystallization of polymers under homogeneous and heterogeneous conditions. The presence of a surface was found to affect the crystallization behavior of the polymers. Polymers with stiff chains crystallized more readily than flexible polymers in the absence of a surface, while the presence of an isotropic surface promoted crystallization in flexible systems. The model provides insight into the mechanisms of polymer crystallization and can help in the design of nucleants for controlling polymer crystallization.
Article
Polymer Science
Carlo Andrea Massa, Francesco Puosi, Antonio Tripodo, Dino Leporini
Summary: The vibrational dynamics of a model polymer glass is studied using Molecular Dynamics simulations, focusing on the soft monomers and their tendency to form quasi-local clusters with strong anisotropy in shape. Limited size systems were used to better understand the role of these soft monomers.
Article
Biochemistry & Molecular Biology
Reinke T. Mueller, Timothy Travers, Hi-jea Cha, Joshua L. Phillips, S. Gnanakaran, Klaas M. Pos
JOURNAL OF MOLECULAR BIOLOGY
(2017)
Meeting Abstract
Infectious Diseases
K. Ganguly, J. L. Phillips, M. S. Wren, P. E. Pardington, S. Gnanakaran, M. E. Wall, G. Gupta
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2014)
Article
Biochemistry & Molecular Biology
Joshua L. Phillips, S. Gnanakaran
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
(2015)
Article
Environmental Sciences
Kristin A. Connors, Amy Beasley, Mace G. Barron, Scott E. Belanger, Mark Bonnell, Jessica L. Brill, Dick de Zwart, Aude Kienzler, Jesse Krailler, Ryan Otter, Joshua L. Phillips, Michelle R. Embry
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
(2019)
Article
Evolutionary Biology
Scott P. Morton, Julie B. Phillips, Joshua L. Phillips
EVOLUTIONARY BIOINFORMATICS
(2019)
Article
Chemistry, Medicinal
Ivan Syzonenko, Joshua L. Phillips
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
David W. Ludwig, Lucas W. Remedios, Joshua L. Phillips
Summary: A new framework integrating working memory-inspired mechanisms into neural network architectures allows models to autonomously learn multiple tasks successfully. The experiments demonstrate the integration of these mechanisms with various network architectures and tasks, showcasing the framework's generalizability.
2021 IEEE 33RD INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Arthur S. Williams, Joshua L. Phillips
THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Nibraas Khan, Joshua Phillips
2020 IEEE 32ND INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI)
(2020)
Proceedings Paper
Mathematical & Computational Biology
Jonathan Howton, Joshua L. Phillips
ACM-BCB' 2017: PROCEEDINGS OF THE 8TH ACM INTERNATIONAL CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY,AND HEALTH INFORMATICS
(2017)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Scott P. Morton, Julie B. Phillips, Joshua L. Phillips
2017 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM)
(2017)
Meeting Abstract
Biophysics
Jonathan Howton, Joshua L. Phillips
BIOPHYSICAL JOURNAL
(2017)
Meeting Abstract
Biophysics
Cesar A. Lopez Bautista, Joshua Phillips, S. Gnanakaran
BIOPHYSICAL JOURNAL
(2015)
Meeting Abstract
Chemistry, Multidisciplinary
Cesar Lopez, Joshua Phillips, Boian Alexandrov, Gnana Gnanakaran
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2015)
Meeting Abstract
Chemistry, Multidisciplinary
Joshua L. Phillips, Steven P. Harvey, Sandrasegaram Gnanakaran
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2014)