.png){kind=icon}
返回
SAMPLE: Surface structure search enabled by coarse graining and statistical learning
.png){kind=icon}
OA
AI
DOI：10.1016/j.cpc.2019.06.010.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this publication we introduce SAMPLE, a structure search approach for commensurate organic monolayers on inorganic substrates. Such monolayers often show rich polymorphism with diverse molecular arrangements in differently shaped unit cells. Determining the different commensurate polymorphs from first principles poses a major challenge due to the large number of possible molecular arrangements. To meet this challenge, SAMPLE employs coarse-grained modeling in combination with Bayesian linear regression to efficiently map the minima of the potential energy surface. In addition, it uses ab initio thermodynamics to generate phase diagrams. Using the example of naphthalene on Cu(111), we comprehensively explain the SAMPLE approach and demonstrate its capabilities by comparing the predicted with the experimentally observed polymorphs. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Hybrid organic/inorganic interface
Bayesian linear regression
Polymorphism
Surface induced phase
First principles simulation
Naphthalene on Cu(111)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.4
论文数:
1.2W
被引数:
3.7W
机构
引用论文
分享收藏分享收藏Global structure search for molecules on surfaces: Efficient sampling with curvilinear coordinatesOAAI
OAAI分享收藏Observations on Apis cerana colonies surviving from Thai Sacbrood Virus infestation.png)
ApidologieOAAI
ApidologieIF0
OAAI分享收藏Structure and Stoichiometry Prediction of Surfaces Reacting with Multicomponent GasesADVANCED MATERIALS
ADVANCED MATERIALSIF26.8
PREAI
分享收藏Robust Optimization of Power Consumption for Public Buildings Considering Forecasting Uncertainty of Environmental Factors考虑环境因素预测不确定性的公共建筑用电鲁棒优化EnergiesOAAI
EnergiesIF0
OAAI分享收藏Identifying the minimum-energy atomic configuration on a lattice: Lamarckian twist on Darwinian evolutionPHYSICAL REVIEW B
PHYSICAL REVIEW BIF3.7
PREAI
分享收藏
查看更多内容