FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3017367712> ?p ?o ?g. }

• W3017367712 endingPage "4401" @default.
• W3017367712 startingPage "4392" @default.
• W3017367712 abstract "In cluster physics, the determination of the ground-state structure of medium-sized and large-sized clusters is a challenge due to the number of local minimal values on the potential energy surface growing exponentially with cluster size. Although machine learning approaches have had much success in materials sciences, their applications in clusters are often hindered by the geometric complexity clusters. Persistent homology provides a new topological strategy to simplify geometric complexity while retaining important chemical and physical information without having to “downgrade” the original data. We further propose persistent pairwise independence (PPI) to enhance the predictive power of persistent homology. We construct topology-based machine learning models to reveal hidden structure–energy relationships in lithium (Li) clusters. We integrate the topology-based machine learning models, a particle swarm optimization algorithm, and density functional theory calculations to accelerate the search of the globally stable structure of clusters." @default.
• W3017367712 created "2020-04-24" @default.
• W3017367712 creator A5034454937 @default.
• W3017367712 creator A5038778212 @default.
• W3017367712 creator A5042741171 @default.
• W3017367712 creator A5046982010 @default.
• W3017367712 creator A5061555601 @default.
• W3017367712 creator A5067332736 @default.
• W3017367712 date "2020-04-22" @default.
• W3017367712 modified "2023-10-11" @default.
• W3017367712 title "Topology-Based Machine Learning Strategy for Cluster Structure Prediction" @default.
• W3017367712 cites W1865667476 @default.
• W3017367712 cites W1964926949 @default.
• W3017367712 cites W1967108496 @default.
• W3017367712 cites W1968893381 @default.
• W3017367712 cites W1970127494 @default.
• W3017367712 cites W1971920777 @default.
• W3017367712 cites W1975997599 @default.
• W3017367712 cites W1979544533 @default.
• W3017367712 cites W1981368803 @default.
• W3017367712 cites W1989272896 @default.
• W3017367712 cites W2006102096 @default.
• W3017367712 cites W2013795311 @default.
• W3017367712 cites W2024060531 @default.
• W3017367712 cites W2024330948 @default.
• W3017367712 cites W2027130342 @default.
• W3017367712 cites W2046176366 @default.
• W3017367712 cites W2046665435 @default.
• W3017367712 cites W2047930686 @default.
• W3017367712 cites W2055639942 @default.
• W3017367712 cites W2056319595 @default.
• W3017367712 cites W2058370262 @default.
• W3017367712 cites W2062212701 @default.
• W3017367712 cites W2065586875 @default.
• W3017367712 cites W2071391326 @default.
• W3017367712 cites W2078290150 @default.
• W3017367712 cites W2082737816 @default.
• W3017367712 cites W2083222334 @default.
• W3017367712 cites W2083415705 @default.
• W3017367712 cites W2083505163 @default.
• W3017367712 cites W2085907003 @default.
• W3017367712 cites W2086702546 @default.
• W3017367712 cites W2092188627 @default.
• W3017367712 cites W2092204065 @default.
• W3017367712 cites W2096736341 @default.
• W3017367712 cites W2104339857 @default.
• W3017367712 cites W2106281763 @default.
• W3017367712 cites W2109364787 @default.
• W3017367712 cites W2113792310 @default.
• W3017367712 cites W2124511088 @default.
• W3017367712 cites W2128126619 @default.
• W3017367712 cites W2130437470 @default.
• W3017367712 cites W2134319176 @default.
• W3017367712 cites W2137046086 @default.
• W3017367712 cites W2139062161 @default.
• W3017367712 cites W2144044408 @default.
• W3017367712 cites W2163339655 @default.
• W3017367712 cites W2168349010 @default.
• W3017367712 cites W2271786311 @default.
• W3017367712 cites W2313966941 @default.
• W3017367712 cites W2343462019 @default.
• W3017367712 cites W2464725281 @default.
• W3017367712 cites W2481594651 @default.
• W3017367712 cites W2490901606 @default.
• W3017367712 cites W2526943155 @default.
• W3017367712 cites W2527749992 @default.
• W3017367712 cites W2565212977 @default.
• W3017367712 cites W2594340878 @default.
• W3017367712 cites W2611413954 @default.
• W3017367712 cites W2734520197 @default.
• W3017367712 cites W2735246657 @default.
• W3017367712 cites W2741292700 @default.
• W3017367712 cites W2765459427 @default.
• W3017367712 cites W2779222234 @default.
• W3017367712 cites W2788484525 @default.
• W3017367712 cites W2912929541 @default.
• W3017367712 cites W2922815878 @default.
• W3017367712 cites W2929447428 @default.
• W3017367712 cites W2955826197 @default.
• W3017367712 cites W2963485997 @default.
• W3017367712 cites W2963883198 @default.
• W3017367712 cites W3003677181 @default.
• W3017367712 cites W3099030566 @default.
• W3017367712 cites W3105621768 @default.
• W3017367712 doi "https://doi.org/10.1021/acs.jpclett.0c00974" @default.
• W3017367712 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7351018" @default.
• W3017367712 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32320253" @default.
• W3017367712 hasPublicationYear "2020" @default.
• W3017367712 type Work @default.
• W3017367712 sameAs 3017367712 @default.
• W3017367712 citedByCount "25" @default.
• W3017367712 countsByYear W30173677122020 @default.
• W3017367712 countsByYear W30173677122021 @default.
• W3017367712 countsByYear W30173677122022 @default.
• W3017367712 countsByYear W30173677122023 @default.
• W3017367712 crossrefType "journal-article" @default.
• W3017367712 hasAuthorship W3017367712A5034454937 @default.
• W3017367712 hasAuthorship W3017367712A5038778212 @default.

• next