Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Perspective: Advances, challenges, and insight for predictive coarse-grained models
WG Noid - The Journal of Physical Chemistry B, 2023 - ACS Publications
By averaging over atomic details, coarse-grained (CG) models provide profound
computational and conceptual advantages for studying soft materials. In particular, bottom …
computational and conceptual advantages for studying soft materials. In particular, bottom …
A review of advancements in coarse-grained molecular dynamics simulations
Over the last few years, coarse-grained molecular dynamics has emerged as a way to model
large and complex systems in an efficient and inexpensive manner due to its lowered …
large and complex systems in an efficient and inexpensive manner due to its lowered …
Coarse-grained protein models and their applications
The traditional computational modeling of protein structure, dynamics, and interactions
remains difficult for many protein systems. It is mostly due to the size of protein …
remains difficult for many protein systems. It is mostly due to the size of protein …
Perspective: Coarse-grained models for biomolecular systems
WG Noid - The Journal of chemical physics, 2013 - pubs.aip.org
By focusing on essential features, while averaging over less important details, coarse-
grained (CG) models provide significant computational and conceptual advantages with …
grained (CG) models provide significant computational and conceptual advantages with …
Chemically specific coarse‐graining of polymers: methods and prospects
Coarse‐grained (CG) modeling is an invaluable tool for the study of polymers and other soft
matter systems due to the span of spatiotemporal scales that typify their physics and …
matter systems due to the span of spatiotemporal scales that typify their physics and …
Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation,
and optimization under uncertainty, typically require several thousand evaluations of the …
and optimization under uncertainty, typically require several thousand evaluations of the …
[HTML][HTML] Inverse methods for design of soft materials
Functional soft materials, comprising colloidal and molecular building blocks that self-
organize into complex structures as a result of their tunable interactions, enable a wide array …
organize into complex structures as a result of their tunable interactions, enable a wide array …
Utilizing machine learning to greatly expand the range and accuracy of bottom-up coarse-grained models through virtual particles
Coarse-grained (CG) models parametrized using atomistic reference data, ie,“bottom up”
CG models, have proven useful in the study of biomolecules and other soft matter. However …
CG models, have proven useful in the study of biomolecules and other soft matter. However …
Coarse‐Graining with the Relative Entropy
This chapter describes that has sought to use information loss concepts and the relative
entropy as a thermodynamic framework for multiscale modeling, with a particular focus on …
entropy as a thermodynamic framework for multiscale modeling, with a particular focus on …
Adversarial-residual-coarse-graining: Applying machine learning theory to systematic molecular coarse-graining
We utilize connections between molecular coarse-graining (CG) approaches and implicit
generative models in machine learning to describe a new framework for systematic …
generative models in machine learning to describe a new framework for systematic …