{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T14:25:39Z","timestamp":1770560739220,"version":"3.49.0"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":21,"publisher":"Elsevier BV","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Per- and poly-fluoroalkyl substances (PFAS) have emerged as &amp;apos;forever-chemicals&amp;apos; due to their persistence in the environment, raising concerns about their widespread commercial and industrial use. To address this challenge, machine learning (ML) models were developed to tap into unexplored data collected from the ECOTOX database. Both linear and nonlinear ML models were set-up using unique curation tools and the Box-Jenkins moving average-based multi-target approach. Our best predictive ML models not only had an overall predictive accuracy higher than 90%, but also allowed for mechanistic insights vis-\u00e0-vis the key structural features linked to PFAS toxicity under various experimental conditions. Specifically, a proper balance between high lipophilicity, low molecular weight and fewer electronegative elements is likely to elicit high aquatic PFAS toxicity. These findings hold potential for guiding the design of new PFAS with a reduced environmental footprint, fostering a more sustainable approach to chemical development.<\/jats:p>","DOI":"10.2139\/ssrn.6192715","type":"posted-content","created":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T14:39:25Z","timestamp":1770475165000},"source":"Crossref","is-referenced-by-count":0,"title":["Mechanistic Mapping of Aquatic Toxicity of Per- and Poly-fluoroalkyl Substances: Machine Learning-Driven Approach for Environmental Risk Assessment of 'Forever-Chemicals'"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4818-9047","authenticated-orcid":true,"given":"Amit Kumar","family":"Halder","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7039-4533","authenticated-orcid":true,"given":"Ana  S.","family":"Moura","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7226-8995","authenticated-orcid":true,"given":"J.","family":"Ferraz-Caetano","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3375-8670","authenticated-orcid":true,"given":"M.  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