Identifying novel chemical and processing methods for the synthesis of high performance carbon black

Identifying novel chemical and processing methods for the synthesis of high performance carbon black | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Identifying novel chemical and processing methods for the synthesis of high performance carbon black Nicola Ferralis, Asieh Ghanekarade, Michal Gulas, Simone Zürcher, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6630540/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Here we present a novel, comprehensive methodology for simulating pyrolysis of an ensemble of aromatic molecules (such as pyrene and coronene) into primary carbon black (CB) using molecular dynamics. This novel approach incorporates relevant and explicit chemical reactions expected during pyrolysis, rather than using force fields to stochastically instantiate such reactions. This allows for detailed investigation of the effects of temperature, pressure, and composition on CB formation and growth under realistic manufacturing conditions. The framework of simulated CB models successfully replicated experimentally derived CB primary structures, which were validated through X-ray diffraction (XRD), density measurements, and transmission electron microscopy (TEM). The study revealed key factors contributing to enhanced crystallinity: the effects of differential phase changes from gas to supercritical regimes and the effects of sequential, stepwise injection of feedstock during growth to the overall system crystallinity. The experimentally validated findings provide valuable insights into the complex relationships between realistic experimental process conditions, feedstock composition, and the resulting carbon black structure, offering a powerful tool for optimizing carbon black synthesis and tailoring its properties for specific applications. Physical sciences/Materials science/Materials for energy and catalysis/Batteries Physical sciences/Chemistry/Physical chemistry/Chemical physics Full Text Additional Declarations There is NO Competing Interest. Supplementary Files MDCarbonBlackMIT20250509SI.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6630540","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":458624968,"identity":"782a6642-e15e-49d5-9c2b-7b168d4f39c3","order_by":0,"name":"Nicola 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