Self-assembly and mesophase formation in a non-ionic chromonic liquid crystal: insights from bottom-up and top-down coarse-grained simulation models

Potter, Thomas D.; Walker, Martin; Wilson, Mark R.

doi:10.1039/d0sm01157f

Cited by 22 publications

(23 citation statements)

References 69 publications

(76 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…are a common solution to alleviate these problems. [61][62][63][64][65] The simplified representation of the atomistic coordinates and the smaller number of interactions that need to be calculated in CG simulations offer significant speed-ups and smoothen the free energy landscape, facilitating the formation of self-assembled aggregates. 66 Similar approaches could be used to study the early steps of nucleation of the C8S3 aggregates, the preferred arrangement in self-assembled structures and, ultimately, the formation of bundles from merging nanotubes.…”

Section: Pccp Papermentioning

confidence: 99%

Structural characterization of supramolecular hollow nanotubes with atomistic simulations and SAXS

Patmanidis

Vries

Wassenaar

et al. 2020

Phys. Chem. Chem. Phys.

View full text Add to dashboard Cite

show abstract

Section: Pccp Papermentioning

confidence: 99%

Structural characterization of supramolecular hollow nanotubes with atomistic simulations and SAXS

Patmanidis

Vries

Wassenaar

et al. 2020

Phys. Chem. Chem. Phys.

View full text Add to dashboard Cite

show abstract

“…With lipids being one special class of surfactants, early on Martini was extended to simulate the assembly and interaction of other synthetic ionic and nonionic surfactants. [ 35,83,113,278–283 ] Recently, interest in surfactants has renewed as ionic liquids (ILs) have attracted much attention for their use as biocompatible and green solvents and co‐solvents. This has led several authors to use Martini to simulate the self‐assembly of IL mesophases, [ 284,285 ] the process of IL‐mediated extractions, [ 285,286 ] as well as to guide the design of de novo molecules.…”

Section: Example Applicationsmentioning

confidence: 99%

“…Only with Martini they were able to simulate the complete phase diagram, whereas the structural CG model showed severe limitations at higher concentrations. [ 283 ]…”

Section: Example Applicationsmentioning

confidence: 99%

The Martini Model in Materials Science

2021

View full text Add to dashboard Cite

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.

show abstract

“…As a matter of fact, CG is usually used to denote modeling with particles that representing multiple atoms in contrast to atomistic simulations, and the same convention will be adopted in the remaining part of this review unless stated otherwise. Both “Top-down” (that based on reproducing experimental data) and “bottom-up” ( that based on reproducing certain properties of atomistic simulations) approaches are utilized [ 21 , 77 ]. For polymeric materials, beads are either utilized to represent monomers or defined on consideration of persistent length [ 78 ], and dissipative particle dynamics (DPD) were proposed to deal with complexities arise from much larger particles [ 79 ].…”

Section: DC and “Caching” In Traditional Molecular Modelingmentioning

confidence: 99%

“Dividing and Conquering” and “Caching” in Molecular Modeling

Cao

Tian

2021

IJMS

View full text Add to dashboard Cite

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes “dividing and conquering” and/or “caching” in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but results are not transferable. Deep learning has been utilized to realize more efficient and accurate ways of “dividing and conquering” and “caching” along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science. This framework is based on a third class of algorithm that facilitates molecular modeling through partially transferable in resolution “caching” of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for “dividing and conquering” and “caching” in complex molecular systems.

show abstract

Self-assembly and mesophase formation in a non-ionic chromonic liquid crystal: insights from bottom-up and top-down coarse-grained simulation models

Abstract: New coarse-grained models are introduced for a non-ionic chromonic molecule, TP6EO2M, in aqueous solution. The multiscale coarse-graining (MS-CG) approach is used, in the form of hybrid force matching (HFM), to...

Cited by 22 publications

References 69 publications

Structural characterization of supramolecular hollow nanotubes with atomistic simulations and SAXS

Structural characterization of supramolecular hollow nanotubes with atomistic simulations and SAXS

The Martini Model in Materials Science

“Dividing and Conquering” and “Caching” in Molecular Modeling

Contact Info

Product

Resources

About