[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121038-en":3,"doc-seo-121038-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121038,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",8,"Research & Report","Machine Learning for Structure Search of Ligand-protected Nanoclusters","Understanding the atomic structures of ligand-protected nanoclusters is essential for their application across multiple fields, since these structures govern physical and chemical properties, stability, and reactivity. Precise structures enable tailoring nanoclusters for specific functions, yet quantum mechanical searches are challenged by an extremely high-dimensional configuration space. This dissertation develops machine learning workflows to efficiently and accurately identify low-energy structures.","Department of Applied Physics  \nMachine Learning for Structure Search of Ligand-protected Nanoclusters  \nLincan Fang  \nDOCTORAL THESES  \nAalto University publication series DOCTORAL THESES 45/2024  \nMachine Learning for Structure Search of Ligand-protected Nanoclusters  \nLincan Fang  \nA doctoral thesis completed for the degree of Doctor of Science (Technology) to be defended, with the permission of the Aalto University School of Science, at a public examination held at the lecture hall U3 (Otakaari 1) of the school on 23 February 2024 at 13 0: 0 .  \nAalto University  \nSchool of Science  \nDepartment of Applied Physics  \nSupervising professor  \nProfessor Patrick Rinke, Aalto University, Finland  \nThesis advisor  \nProfessor Chen Xi , Lanzhou University, China  \nPreliminary examiners  \nAcademy Professor Hannu Häkkinen, University of Jyväskylä , Finland Full Professor Jaakko Eemeli Akola, Norwegian University, Norway  \nOpponent  \nAssociate Professor Olga López Acevedo, Institute of Physics Universidad de Antioquia, Colombia  \nAalto University publication series DOCTORAL THESES 45/2024  \n© 2024 L ni can Fang  \nISBN 978-952-64-1 698-4 p( r ni et d)  \nISBN 978-952-64-1 699-1 p( d )f  \nISSN 1799-4934 p( r ni et d)  \nISSN 1799-4942 p( d )f  \n[http://urn.fi/URN:ISBN:978-952-64-1699-1](http://urn.fi/URN:ISBN:978-952-64-1699-1)  \nUn gi ra aif Oy He sl ni ki 2024  \nF ni al nd  \nPrinted matter  \nAbstract  \nAalto University, P.O. Box 11000, FI-00076 Aalto www.aa tl o. if  \nAuthor  \nL ni can Fang  \nName of the doctoral thesis  \nMachine Learning for Structure Search of Ligand-protected Nanoclusters  \nPub sil her School of Science  \nUn ti Department of Applied Physics  \nSer ei s Aalto University publication series DOCTORAL THESES 45/2024  \nField of research Engineering Physics  \nManuscript submitted 18 October 2023 Date of the defence 23 February 2024  \nPermission for public defence granted (date) 30 January 2024 Language Eng sil h  \n Monograph  Article thesis  Essay thesis  \n\n| Abstract\u003Cbr>Understanding the atomic structures of ligand-protected nanoclusters is essential for their application in various fields. These structures not only determine the physical and chemical properties of ligand-protected nanoclusters but also play a crucial role in their stability and reactivity. Knowing the precise atomic structures allows us to tailor nanoclusters for specific functions. However, because of the extraordinarily high dimensionality of the search space which encompasses an exceptionally large number of all potential structures, it is difficult to use quantum mechanical methods, such as the density functional theory, to find the low-energy structures of ligand-protected nanoclusters. On this point, the structure search of ligand-protected nanoclusters could be more efficient and accurate by utilizing machine learning methods.\u003Cbr>In this dissertation, I developed machine learning methods to search the atomic structures of ligand-protected nanoclusters by decomposing the problem into three steps. For the first step, I developed a molecular conformer search procedure based on Bayesian optimization to search the structures of isolated molecules. Using four amino acids as examples, I showed that the procedure is both efficient and accurate. For the second step, I modified the procedure to search the structures of a single ligand on a nanocluster. I also developed and tested strategies to avoid steric clashes between a ligand and cluster parts. Moreover, I tested and demonstrated our modified procedure by searching structures for a cysteine molecule on a well-studied gold-thiolate cluster. As a result, I found that cysteine conformers in a cluster inherit the hydrogen bond types from isolated conformers, while the energy rankings and spacings between the conformers are reordered. In the final step, I applied a machine learning method based on kernel rigid regression (KRR) models to relax the structures of ligand-protected nanoclusters. Moreover, I used an active le","cbCaibQeChAPhGVl","https://ap.wps.com/l/cbCaibQeChAPhGVl","pdf",20900045,1,90,"English","en",105,"# Abstract\n# Preface\n# Contents\n# List of Symbols and Abbreviations\n# Thesis Contributions and Structure","[{\"question\":\"Why is structure search for ligand-protected nanoclusters difficult?\",\"answer\":\"The search space is extraordinarily high-dimensional, containing an exceptionally large number of possible structures. This makes low-energy structure discovery by quantum mechanical methods such as density functional theory difficult.\"},{\"question\":\"What is the dissertation’s overall approach to structure search?\",\"answer\":\"The work decomposes the problem into three steps: Bayesian-optimization-based conformer search for isolated molecules, an extended procedure for a single ligand on a nanocluster with clash-avoidance strategies, and kernel rigid regression with an active learning workflow to relax nanocluster structures.\"},{\"question\":\"What did the study find for cysteine-containing clusters?\",\"answer\":\"Cysteine conformers in a cluster inherit hydrogen bond types from isolated conformers, while energy rankings and spacings between conformers are reordered. Low-energy structures with II-type hydrogen bonds become dominant, and different ligand-layer configurations influence cluster properties.\"}]","Machine Learning for Structure Search of Ligand-protected Nanoclusters | PDF",1785733431,227,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-for-structure-search-of-ligand-protected-nanoclusters","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-for-structure-search-of-ligand-protected-nanoclusters/121038/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is structure search for ligand-protected nanoclusters difficult?","Question",{"text":75,"@type":76},"The search space is extraordinarily high-dimensional, containing an exceptionally large number of possible structures. This makes low-energy structure discovery by quantum mechanical methods such as density functional theory difficult.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the dissertation’s overall approach to structure search?",{"text":80,"@type":76},"The work decomposes the problem into three steps: Bayesian-optimization-based conformer search for isolated molecules, an extended procedure for a single ligand on a nanocluster with clash-avoidance strategies, and kernel rigid regression with an active learning workflow to relax nanocluster structures.",{"name":82,"@type":73,"acceptedAnswer":83},"What did the study find for cysteine-containing clusters?",{"text":84,"@type":76},"Cysteine conformers in a cluster inherit hydrogen bond types from isolated conformers, while energy rankings and spacings between conformers are reordered. Low-energy structures with II-type hydrogen bonds become dominant, and different ligand-layer configurations influence cluster properties.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,96,100,104,109,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":21,"slug":95},"Story & Novel","story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":105,"slug":137},19,"General","general"]