The Martini Model in Materials Science.
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In this article, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3.Abstract:
The Martini model, a coarse-grained force field initially developed with biomolecular simulations in mind, has found an increasing number of applications in the field of soft materials science. The model's underlying building block principle does not pose restrictions on its application beyond biomolecular systems. Here, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3.read more
Citations
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Chemically specific coarse-graining of polymers: Methods and prospects
Satyen Dhamankar,Michael A. Webb +1 more
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Two decades of Martini: Better beads, broader scope
Siewert J. Marrink,Luca Monticelli,Manuel N. Melo,Riccardo Alessandri,D. Peter Tieleman,Paulo C. T. Souza +5 more
TL;DR: The Martini model as mentioned in this paper is a coarse-grained force field for molecular dynamics simulations, originally developed for lipid-based systems by the groups of Marrink and Tieleman, has over the years been extended as a community effort to the current level of a general-purpose force field.
Journal ArticleDOI
Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials
Fabian Grünewald,Riccardo Alessandri,Peter C. Kroon,Luca Monticelli,Paulo C. T. Souza,Siewert J. Marrink +5 more
TL;DR: The polyply software suite as mentioned in this paper leverages a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and a generic multiscale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution.
Journal ArticleDOI
Theory and Practice of Coarse-Grained Molecular Dynamics of Biologically Important Systems
Adam Liwo,Cezary Czaplewski,Adam K. Sieradzan,Agnieszka G. Lipska,Sergey A. Samsonov,Rajesh K. Murarka +5 more
TL;DR: In this article, the physical basis of coarse-grained molecular dynamics, the coarsegrained force fields, the equations of motion and the respective numerical integration algorithms, and selected practical applications are discussed.
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Nonconverged Constraints Cause Artificial Temperature Gradients in Lipid Bilayer Simulations
Sebastian Thallmair,Sebastian Thallmair,Matti Javanainen,Balázs Fábián,Hector Martinez-Seara,Siewert J. Marrink +5 more
TL;DR: In this paper, the authors show that a significant temperature difference between molecule types can artificially arise in CG MD simulations with the standard Martini simulation parameters in GROMACS, and demonstrate that the underlying reason for this behavior is the presence of highly constrained moieties, such as cholesterol.
References
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Control of the hierarchical assembly of π-conjugated optoelectronic peptides by pH and flow
TL;DR: This work provides new fundamental understanding of the effects of pH and flow to control the morphology and kinetics of early-stage assembly of π-conjugated peptides and lays the groundwork for the rational manipulation of environmental conditions to direct assembly and the attendant emergent optoelectronic properties.
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MARTINI Coarse-Grained Model of Triton TX-100 in Pure DPPC Monolayer and Bilayer Interfaces.
TL;DR: The coarse-grained MARTINI model of Triton TX-100 has been validated by direct comparison of the experimental and calculated area increase in pure DPPC lipid bilayers and monolayers at water/air interfaces in the presence of surfactant and by comparison of electron density profiles calculated with more detailed atomistic models based on the CHARMM force field.
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Ligand dynamics control structure, elasticity, and high-pressure behavior of nanoparticle superlattices.
Tarak K. Patra,Henry Chan,Paul Podsiadlo,Elena V. Shevchenko,Subramanian K. R. S. Sankaranarayanan,Badri Narayanan,Badri Narayanan +6 more
TL;DR: Above the threshold ligand coverage density, NPSLs surprisingly preserve their crystalline order even under high applied pressures, and show a completely reversible pressure behavior, which opens the possibility of reversibly manipulating lattice spacing of N PSLs, and in turn, finely tuning their collective electronic, optical, thermo-mechanical, and magnetic properties.
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Predicting optical spectra for optoelectronic polymers using coarse-grained models and recurrent neural networks.
TL;DR: A machine-learning model relating coarse-grained conjugated polymer conformations and absorption spectroscopy and demonstrating that it can bridge between these is developed, based on a generative deep learning model: the long-short-term memory recurrent neural network (LSTM-RNN).