[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123636-en":3,"doc-seo-123636-105":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},123636,549758146520,"Patrick","https://ap-avatar.wpscdn.com/avatar/80002397d8c0411e94?_k=1775819394049821470",8,"Research & Report","Optimization of microfluidic synthesis of silver nanoparticles - a generic approach using machine learning","Silver nanoparticle (AgNP) properties depend on multiple interacting parameters, making chemical synthesis optimization laborious, costly, and time-consuming. A concurrent T-junction microfluidic system combined with machine learning streamlines this task. AgNPs are prepared by reducing silver nitrate using tannic acid in the presence of trisodium citrate, which both reduces and stabilizes. Decision-tree-guided design of experiments determines particle size via kinetic nucleation and growth constants, capturing reaction chemistry, hydrodynamics (Reynolds and Dean/Reynolds ratio), mixing, and storage stability. The resulting model guides additional experiments that improve decision tree, random forest, and XGBoost performance.","University of Birmingham  \nOptimization of microfluidic synthesis of silver nanoparticles  \nNathanael, Konstantia; Cheng, Sibo; Kovalchuk, Nina M. ; Arcucci, Rossella; Simmons, Mark J. h.  \nDOI:  \n10.1016/j.cherd.2023.03.007  \nLicense:  \nCreative Commons: Attribution (CC BY)  \nDocument Version  \nPublisher's PDF, also known as Version of record  \nCitation for published version (Harvard):  \nNathanael, K, Cheng, S, Kovalchuk, NM, Arcucci, R & Simmons, MJH 2023, 'Optimization of microfluidic synthesis of silver nanoparticles: a generic approach using machine learning', Chemical Engineering Research  \nand Design, vol. 193, pp. 65-74. [https://doi.org/10.1016/j.cherd.2023.03.007](https://doi.org/10.1016/j.cherd.2023.03.007)  \nLink to publication on Research at Birmingham portal  \nGeneral rights  \nUnless a licence is specified above, all rights (including copyright and moral rights) in this document are retained by the authors and/or the copyright holders. The express permission of the copyright holder must be obtained for any use of this material other than for purposes permitted by law.  \n•Users may freely distribute the URL that is used to identify this publication.  \n•Users may download and/or print one copy of the publication from the University of Birmingham research portal for the purpose of private study or non-commercial research.  \n•User may use extracts from the document in line with the concept of ‘fair dealing’ under the Copyright, Designs and Patents Act 1988 (?)  \n•Users may not further distribute the material nor use it for the purposes of commercial gain.  \nWhere a licence is displayed above, please note the terms and conditions of the licence govern your use of this document.  \nWhen citing, please reference the published version.  \nTake down policy  \nWhile the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.  \nIf you believe that this is the case for this document, [please contact UBIRA@lists.bham.ac.uk](please contact UBIRA@lists.bham.ac.uk) providing details and we will remove access to the work immediately and investigate.  \nDownload date: 03. Aug. 2026  \nAvailable online [at](at www.sciencedirect.com)[ www.sciencedirect.com](at www.sciencedirect.com)[ ](at www.sciencedirect.com)Chemical Engineering Research and Design  \njournal [homepage: www . elsevier. com/locate/cherd](homepage: www . elsevier. com/locate/cherd)  \n| Optimization of microfluidic synthesis of silver nanoparticles: A generic approach using machine learning\u003Cbr>Konstantia Nathanael a,⁎, Sibo Chengb, Nina M. Kovalchuka, Rossella Arcuccib,c, Mark J.H. Simmons a\u003Cbr>a School of Chemical Engineering, University of Birmingham, UK\u003Cbr>b Data Science Institute, Imperial College London, London SW7 2AZ, UK\u003Cbr>c Earth Science & Engineering Department, Imperial College London, London SW7 2AZ, UK |  | \u003Cbr> |\n| --- | --- | --- |\n| a r t i c l e i n f o | a b s t r a c t |  |\n| Article history: | The properties of silver nanoparticles (AgNPs) are affected by various parameters, making |  |\n| Received 19 December 2022 | optimisation of their synthesis a laborious task. This optimisation is facilitated in this |  |\n| Received in revised form 20 February | work by concurrent use of a T-junction microfluidic system and machine learning ap- |  |\n| 2023 | proach. The AgNPs are synthesized by reducing silver nitrate with tannic acid in the |  |\n| Accepted 4 March 2023 | presence of trisodium citrate, which has a dual role in the reaction as reducing and sta- |  |\n| Available online 7 March 2023 | bilizing agent. The study uses a decision tree-guided design of experiment method for the |  |\n|  | size of AgNPs. The developed approach uses kinetic nucleation and growth constants derived from an independent set of experiments to account for chemistry of synthesis, the |  |\n| Keywords: |  |  |\n| Reaction kinetics | Reyn","cbCaik0z08ZRE1xG","https://ap.wps.com/l/cbCaik0z08ZRE1xG","pdf",3299193,1,11,"English","en",105,"# Article history\n## Abstract overview\n## Introduction","[{\"question\":\"How are silver nanoparticles synthesized in the study?\",\"answer\":\"AgNPs are produced by reducing silver nitrate with tannic acid, using trisodium citrate as a dual-role reducing and stabilizing agent.\"},{\"question\":\"Which machine learning and experimental design methods are used?\",\"answer\":\"A decision-tree-guided design of experiments is combined with machine learning models, including decision trees, random forests, and XGBoost, to optimize synthesis.\"},{\"question\":\"What factors does the model account for besides reaction chemistry?\",\"answer\":\"The model includes hydrodynamics and mixing effects, using Reynolds number and the Dean-to-Reynolds ratio, as well as storage temperature to capture particle stability after collection.\"}]","Optimization of microfluidic synthesis of silver nanoparticles - a generic approach using machine learning | PDF",1785817768,28,{"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},"optimization-of-microfluidic-synthesis-of-silver-nanoparticles-a-generic-approach-using-machine-learning","",{"@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/optimization-of-microfluidic-synthesis-of-silver-nanoparticles-a-generic-approach-using-machine-learning/123636/",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","2026-08-04",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},"How are silver nanoparticles synthesized in the study?","Question",{"text":75,"@type":76},"AgNPs are produced by reducing silver nitrate with tannic acid, using trisodium citrate as a dual-role reducing and stabilizing agent.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning and experimental design methods are used?",{"text":80,"@type":76},"A decision-tree-guided design of experiments is combined with machine learning models, including decision trees, random forests, and XGBoost, to optimize synthesis.",{"name":82,"@type":73,"acceptedAnswer":83},"What factors does the model account for besides reaction chemistry?",{"text":84,"@type":76},"The model includes hydrodynamics and mixing effects, using Reynolds number and the Dean-to-Reynolds ratio, as well as storage temperature to capture particle stability after collection.","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},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]