[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127832-en":3,"doc-seo-127832-105":31,"detail-sidebar-cat-0-en-105":92},{"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":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},127832,1099523885336,"Violet","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Physics-Enhanced Machine Learning for Chemical Kinetics - Accepted doctoral thesis","Accepted doctoral thesis on using physics-enhanced machine learning to model chemical kinetics with a focus on reliable, efficient surrogate representations. It compiles related research outputs including peer-reviewed journal articles, preprints, and conference talks, emphasizing neural-network approaches for surface kinetics, rate-determining steps, and mechanisms discovery. The work includes dates for submission and defense, institutional affiliation with TU Darmstadt, and publication references on TUprints with prior conference dissemination.","| Physics-Enhanced Machine Learning for Chemical Kinetics |\n| --- |\n| Physikalische Maschinenlernverfahren für die Modellierung chemischer Kinetik\u003Cbr>Zur Erlangung des akademischen Grades Doktor-Ingenieur (Dr.-Ing.) Genehmigte Dissertation von Felix Antonidas Döppel aus Bensheim Tag der Einreichung: 26 . März 2024, Tag der Prüfung: 13 . Mai 2024\u003Cbr>1. Gutachten: Prof. Dr. Martin Votsmeier\u003Cbr>2. Gutachten: Prof. Dr. Oliver Weeger\u003Cbr>3. Gutachten: Prof. Dr. Olaf Deutschmann Darmstadt, Technische Universität Darmstadt |\n| \u003Cbr>Chemistry Department Ernst-Berl-Institute\u003Cbr>Votsmeier Group |\n\nPhysics-Enhanced Machine Learning for Chemical Kinetics  \nPhysikalische Maschinenlernverfahren für die Modellierung chemischer Kinetik  \nAccepted doctoral thesis by Felix Antonidas Döppel  \nDate of submission: 26 . März 2024  \nDate of thesis defense: 13 . Mai 2024  \nDarmstadt, Technische Universität Darmstadt  \nBitte zitieren Sie dieses Dokument als: URN: urn:nbn:de:tuda-tuprints-273848  \nURL: [http://tuprints.ulb.tu-darmstadt.de/id/eprint/27384](http://tuprints.ulb.tu-darmstadt.de/id/eprint/27384)  \n[Jahr der Ver](Jahr der Ver)ö[ffentlichung auf TUprints: 2024](ffentlichung auf TUprints: 2024)  \nDieses Dokument wird bereitgestellt von tuprints, E-Publishing-Service der TU Darmstadt [http://tuprints.ulb.tu-darmstadt.de](http://tuprints.ulb.tu-darmstadt.de)[ ](http://tuprints.ulb.tu-darmstadt.de)[tuprints@ulb.tu-darmstadt.de](tuprints@ulb.tu-darmstadt.de)  \nThis work is protected by copyright  \n[https://rightsstatements.org/page/InC/1.0/](https://rightsstatements.org/page/InC/1.0/)  \nPublications  \nParts of this work have been previously published or presented at international conferences:  \nResearch articles contained within this work  \n1. F. A. Döppel and M. Votsmeier  \nEfficient machine learning based surrogate models for surface kinetics by approximating the rates of the rate-determining steps.  \nChemical Engineering Science, 2022, 262, 117964 .  \nDOI: 10.1016/j.ces.2022.117964  \n2. F. A. Döppel and M. Votsmeier  \nEfficient Neural Network Models of Chemical Kinetics Using a Latent asinh Rate Transformation. Reaction Chemistry & Engineering, 2023, 8, 2620-2631 .  \nDOI: 10.1039/D3RE00212H  \n3. F. A. Döppel, T. Wenzel, R. Herkert, B. Haasdonk and M. Votsmeier  \nGoal-Oriented Two-Layered Kernel Models as Automated Surrogates for Surface Kinetics in Reactor Simulations.  \nChemie Ingenieur Technik, 2024, 96, No. 5, 1-11 .  \nDOI: 10.1002/cite.202300178  \n4. F. A. Döppel and M. Votsmeier  \nRobust Mechanism Discovery with Atom Conserving Chemical Reaction Neural Networks.  \nChemRxiv, 2023.  \nDOI: 10.26434/chemrxiv-2023-1r389  \nResearch articles not contained within this work  \n5. T. Kircher, F. A. Döppel and M. Votsmeier  \nGlobal reaction neural networks with embedded stoichiometry and thermodynamics for learning kinetics from reactor data.  \nChemical Engineering Journal, 2024, 485, 149863 .  \nDOI: 10.1016/j.cej.2024.149863  \n6. T. Kircher, F. A. Döppel and M. Votsmeier  \nEmbedding Physics into Neural ODEs to learn Kinetics from Integral Reactors.  \nComputer Aided Chemical Engineering, 2024, accepted.  \nDOI: 10.26434/chemrxiv-2024-10xzj-v2  \nTalks  \n1. F. A. Döppel and M. Votsmeier  \nRepresenting detailed surface kinetics by neural networks  \n26th International Symposium on Chemical Reaction Engineering and the 9th Asia-Pacific Chemical Reaction Engineering Symposium. 05. -08. December 2021; New Delhi, India-Online event  \n2. K. Wilhelm, F. A. Döppel and M. Votsmeier  \nPhysics-Informed Neural Networks for Reactor Simulations  \nAnnual Meeting on Reaction Engineering 2023 . 15. - 17. May 2023; Frankfurt am Main, Germany  \n3. F. A. Döppel and M. Votsmeier  \nEfficient Implementation of Detailed Surface Kinetics by Neural Network Representations of the Rate determining Step  \n27th International Symposium for Chemical Reaction Engineering. 11. - 14. June 2023; Quebec City, Canada  \n4. F. A. Döppel, T. Kircher and M. Votsmeier  \nPhysics-Embedded Neural Netwo","cbCaioX4mH4XlMfY","https://ap.wps.com/l/cbCaioX4mH4XlMfY","pdf",7312325,2,1,122,"English","en",105,"# Research articles\n## Journal articles and related publications\n## Talks and posters","[{\"question\":\"What is the thesis about?\",\"answer\":\"The thesis investigates physics-enhanced machine learning methods for modeling chemical kinetics, including efficient surrogate models and physics-aware neural approaches.\"},{\"question\":\"What types of related research outputs are included?\",\"answer\":\"It lists journal research articles, additional pre-publication work such as ChemRxiv entries, and summaries of talks and posters presented at international events.\"},{\"question\":\"Where was the doctoral thesis submitted and defended?\",\"answer\":\"The document states Darmstadt at the Technische Universität Darmstadt (TU Darmstadt), with an identified submission date and thesis defense date.\"}]","Physics-Enhanced Machine Learning for Chemical Kinetics - Accepted doctoral thesis | PDF",1785942239,307,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"physics-enhanced-machine-learning-for-chemical-kinetics-accepted-doctoral-thesis","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/physics-enhanced-machine-learning-for-chemical-kinetics-accepted-doctoral-thesis/127832/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the thesis about?","Question",{"text":76,"@type":77},"The thesis investigates physics-enhanced machine learning methods for modeling chemical kinetics, including efficient surrogate models and physics-aware neural approaches.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What types of related research outputs are included?",{"text":81,"@type":77},"It lists journal research articles, additional pre-publication work such as ChemRxiv entries, and summaries of talks and posters presented at international events.",{"name":83,"@type":74,"acceptedAnswer":84},"Where was the doctoral thesis submitted and defended?",{"text":85,"@type":77},"The document states Darmstadt at the Technische Universität Darmstadt (TU Darmstadt), with an identified submission date and thesis defense date.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]