{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T16:25:03Z","timestamp":1786465503315,"version":"build-2736575974"},"reference-count":24,"publisher":"American Chemical Society (ACS)","issue":"31","license":[{"start":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T00:00:00Z","timestamp":1784851200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LY20E090004"],"award-info":[{"award-number":["LY20E090004"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Stirring equipment is widely used in core fields such as energy and the chemical industry. Stirring operation is one of the important links in the process of industrial production. Its efficient mixing and green-energy-saving design have always been the focus of researchers. In this study, an optimization framework that integrates class\/shape function transformation (CST) parametric design with a deep neural network was developed. The CST method was used to characterize the low-dimensional parametrization of the blade camber line, and the small sample blade space was generated by Latin hypercube sampling. A deep neural network surrogate model based on a multilayer perceptron (MLP) was established for the rapid prediction of impeller torque, particle dispersion uniformity, and other parameters, and the optimization design was carried out with a multiobjective genetic algorithm. The results show that the optimized blade can effectively reduce the energy dissipation in the wake region and strengthen the local turbulence near the tip region, thereby enhancing the off-bottom starting and axial transport capacities of the particles. Compared with the original blade, the solid cloud height in the stirred tank increases by 16.05%, reaching the criterion for complete suspension defined in previous studies, while the impeller power consumption decreases by 10.34%.This demonstrates the feasibility of this method for the energy-efficient design of stirring impellers and provides methodological support for the intelligent optimization and energy-efficiency enhancement of similar complex multiphase flow equipment.<\/jats:p>","DOI":"10.1021\/acsomega.6c04403","type":"journal-article","created":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T05:05:12Z","timestamp":1785128712000},"page":"46612-46629","source":"Crossref","is-referenced-by-count":0,"title":["Performance Optimization\nDesign of Stirred Tanks Based\non Deep Neural Networks"],"prefix":"10.1021","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4736-4171","authenticated-orcid":true,"given":"Laifa","family":"Lu","sequence":"first","affiliation":[{"name":"Zhejiang University of Technology , , ,","place":["Hangzhou, China, 310023"]},{"name":"Zhejiang University of Technology , , ,","place":["Shengzhou, China, 312400"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiali","family":"Wang","sequence":"additional","affiliation":[{"name":"Zhejiang University of Technology , , ,","place":["Hangzhou, China, 310023"]},{"name":"Zhejiang University of Technology , , ,","place":["Shengzhou, China, 312400"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuiqing","family":"Zhou","sequence":"additional","affiliation":[{"name":"Zhejiang University of Technology , , ,","place":["Hangzhou, China, 310023"]},{"name":"Zhejiang University of Technology , , ,","place":["Shengzhou, China, 312400"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zengliang","family":"Gao","sequence":"additional","affiliation":[{"name":"Zhejiang University of Technology , , ,","place":["Hangzhou, China, 310023"]},{"name":"Zhejiang University of Technology , , ,","place":["Shengzhou, China, 312400"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,7,24]]},"reference":[{"issue":"04","key":"2026081110200903900_cit1","doi-asserted-by":"publisher","first-page":"e382","DOI":"10.1055\/s-0044-1792036","article-title":"Continuously\nstirred tank reactor for pharmaceutical and chemical applications","volume":"06","author":"Li","year":"2024","journal-title":"Pharm. 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Eng."},{"key":"2026081110200903900_cit4","volume-title":"Energy Technology Perspectives\n2020","author":"International Energy Agency.","year":"2020"},{"issue":"4","key":"2026081110200903900_cit5","first-page":"546","article-title":"Study on the mixing performance of\ngas-liquid two-phase flow in a\ndouble-impeller stirred tank","volume":"51","author":"Gao","year":"2024","journal-title":"Chem. Mach,"},{"key":"2026081110200903900_cit6","doi-asserted-by":"publisher","first-page":"1980","DOI":"10.1016\/j.energy.2015.10.084","article-title":"Energy efficiency\nof different impellers in stirred tank reactors","volume":"93","author":"Ameur","year":"2015","journal-title":"Energy"},{"issue":"1","key":"2026081110200903900_cit7","first-page":"32","article-title":"Comparison\nof macro-mixing characteristics in stirred tanks with several single-layer\nimpellers","volume":"70","author":"Li","year":"2019","journal-title":"CIESC J."},{"issue":"11","key":"2026081110200903900_cit8","doi-asserted-by":"publisher","first-page":"1962","DOI":"10.3390\/pr9111962","article-title":"Comparative study\non the power consumption\nand flow field characteristics of a three-blade combined agitator","volume":"9","author":"Zhang","year":"2021","journal-title":"Processes"},{"key":"2026081110200903900_cit9","doi-asserted-by":"publisher","first-page":"127497","DOI":"10.1016\/j.cej.2020.127497","article-title":"Impeller\nshape optimization of stirred-tank reactor: CFD and fluid-structure\ninteraction analyses","volume":"413","author":"Hoseini","year":"2021","journal-title":"Chem. Eng. J."},{"issue":"2","key":"2026081110200903900_cit10","first-page":"91","article-title":"PIV-based\nstudy on the flow field of a bionic whale-tail stirring reactor","volume":"47","author":"Han","year":"2022","journal-title":"Journal of Southwest China Normal University"},{"issue":"12","key":"2026081110200903900_cit11","doi-asserted-by":"publisher","first-page":"1715","DOI":"10.1007\/s10409-021-01154-3","article-title":"Artificial intelligence\nin fluid mechanics","volume":"37","author":"Zhang","year":"2021","journal-title":"Acta Mech. Sin."},{"issue":"9","key":"2026081110200903900_cit12","doi-asserted-by":"publisher","first-page":"723","DOI":"10.3390\/aerospace11090723","article-title":"Data-driven\nAI model for turbomachinery\ncompressor aerodynamics enabling rapid approximation of 3D flow solutions","volume":"11","author":"Aulich","year":"2024","journal-title":"Aerospace"},{"issue":"1","key":"2026081110200903900_cit13","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1146\/annurev-fluid-010719-060214","article-title":"Machine learning\nfor fluid mechanics","volume":"52","author":"Brunton","year":"2020","journal-title":"Annu. Rev. Fluid Mech."},{"issue":"3","key":"2026081110200903900_cit14","doi-asserted-by":"publisher","DOI":"10.1002\/aic.18324","article-title":"Multi-objective optimization\nof radially stirred tank based on CFD\nand machine learning","volume":"70","author":"Zhao","year":"2024","journal-title":"AIChE J."},{"issue":"1","key":"2026081110200903900_cit15","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1021\/acs.iecr.3c03561","article-title":"Optimization of a gas-liquid dual-impeller\nstirred tank based on deep learning with a small dataset from CFD\nsimulation","volume":"63","author":"Kang","year":"2024","journal-title":"Ind. Eng. Chem. Res."},{"issue":"6","key":"2026081110200903900_cit16","first-page":"801","article-title":"Study on the stirring\nprocess based on artificial neural\nnetworks and multiphase flow simulation technology","volume":"15","author":"Wu","year":"2024","journal-title":"Nonferrous Met. Sci. Eng."},{"key":"2026081110200903900_cit17","doi-asserted-by":"publisher","first-page":"120840","DOI":"10.1016\/j.ces.2024.120840","article-title":"ANN-CFD research on key parameters\nof stirred tank based on multi-objective optimization and decision\nmakers\u2019 preferences","volume":"302","author":"Wu","year":"2025","journal-title":"Chem. Eng. Sci."},{"key":"2026081110200903900_cit18","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1007\/s12525-021-00475-2","article-title":"Machine learning and\ndeep learning","volume":"31","author":"Janiesch","year":"2021","journal-title":"Electron. Mark."},{"key":"2026081110200903900_cit19","doi-asserted-by":"publisher","first-page":"13521","DOI":"10.1007\/s10462-023-10466-8","article-title":"Deep learning modelling techniques:\nCurrent progress,\napplications, advantages, and challenges","volume":"56","author":"Ahmed","year":"2023","journal-title":"Artif.\nIntell. 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Eng."},{"key":"2026081110200903900_cit23","doi-asserted-by":"publisher","first-page":"104878","DOI":"10.1016\/j.jtice.2023.104878","article-title":"CFD simulation\nand experimental analysis of solid-liquid mixing characteristics in\na stirred tank with a self-similarity impeller","volume":"146","author":"Gu","year":"2023","journal-title":"J. Taiwan Inst. Chem. Eng."},{"issue":"5","key":"2026081110200903900_cit24","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1002\/ceat.270150505","article-title":"Mixing times\nin stirred suspensions","volume":"15","author":"Kraume","year":"1992","journal-title":"Chem. Eng. Technol."}],"container-title":["ACS Omega"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acsomega.6c04403","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/acsodf\/article-pdf\/11\/31\/46612\/66251791\/acsomega.6c04403.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/acsodf\/article-pdf\/11\/31\/46612\/66251791\/acsomega.6c04403.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T15:01:35Z","timestamp":1786460495000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/acsodf\/article\/11\/31\/46612\/5232130\/Performance-Optimization-Design-of-Stirred-Tanks"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,24]]},"references-count":24,"journal-issue":{"issue":"31","published-online":{"date-parts":[[2026,7,24]]},"published-print":{"date-parts":[[2026,8,11]]}},"URL":"https:\/\/doi.org\/10.1021\/acsomega.6c04403","relation":{},"ISSN":["2470-1343"],"issn-type":[{"value":"2470-1343","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,24]]}}}