{"id":259,"date":"2026-02-09T15:50:00","date_gmt":"2026-02-09T06:50:00","guid":{"rendered":"https:\/\/himatchemeng.tech\/?page_id=259"},"modified":"2026-02-26T10:42:35","modified_gmt":"2026-02-26T01:42:35","slug":"page001-2","status":"publish","type":"page","link":"https:\/\/himatchemeng.tech\/en\/research\/page001-2\/","title":{"rendered":"Hybrid Physical Property Prediction Model Combining \u201cEquation of State\u201d and \u201cAI\u201d"},"content":{"rendered":"\n<p>An equation of state (EoS) is used to correlate and predict various physical properties across a wide range of temperature and pressure conditions, from pure substances to mixtures. This is because it can determine not only the pressure-volume-temperature relationship but also various thermodynamic state variables. The equation of state typically taught in high school chemistry is PV=nRT. However, this is the ideal gas equation of state and cannot be applied to real substances. Therefore, numerous types of equations have been proposed to accommodate real substances. These equations of state are incorporated and used within process simulators, such as Aspen+ and PROII, which are essential tools for process design.<\/p>\n\n\n\n<div class=\"wp-block-columns are-vertically-aligned-center is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-vertically-aligned-center is-layout-flow wp-block-column-is-layout-flow\">\n<p>Calculations using a equation of state applicable to actual substances involve obtaining substance-specific parameters from measured physical properties, applying them to the equation of state, and predicting physical properties. This creates a circular problem where predicting physical properties requires known physical properties. To address this issue, we are developing a novel model that combines AI with an integrated \u201cequation of state and AI\u201d model to predict physical properties without requiring prior knowledge of those properties.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-vertically-aligned-center is-layout-flow wp-block-column-is-layout-flow\"><div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"472\" height=\"283\" src=\"https:\/\/himatchemeng.tech\/edit\/wp-content\/uploads\/r017.jpg\" alt=\"\" class=\"wp-image-179\"\/><\/figure>\n<\/div><\/div>\n<\/div>\n\n\n\n<h3 class=\"wp-block-heading vk_block-margin-sm--margin-bottom\">Peng-Robinson equation of state-van der Waals one fluid mixing rule, interaction parameters <em>k<sub>ij<\/sub><\/em>, <em>l<sub>ij<\/sub><\/em> between CO<sub>2<\/sub> and organic solvents<\/h3>\n\n\n\n<p><strong><strong>Peng-Robinson equation of state<\/strong><\/strong><\/p>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column has-background is-layout-flow wp-block-column-is-layout-flow\" style=\"background-color:#262626\"><div class=\"wp-block-image vk_block-margin-lg--margin-top vk_block-margin-lg--margin-bottom\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" src=\"https:\/\/himatchemeng.tech\/edit\/wp-content\/uploads\/r005.jpg\" alt=\"\" class=\"wp-image-114\"\/><\/figure>\n<\/div><\/div>\n<\/div>\n\n\n\n<p><strong>van der Waals one fluid mixing rule<\/strong><\/p>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-vertically-aligned-center vk_block-margin-0--margin-top has-background is-layout-flow wp-block-column-is-layout-flow\" style=\"background-color:#262626\"><div class=\"wp-block-image vk_block-margin-lg--margin-top vk_block-margin-lg--margin-bottom\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" src=\"https:\/\/himatchemeng.tech\/edit\/wp-content\/uploads\/r006.jpg\" alt=\"\" class=\"wp-image-116\"\/><\/figure>\n<\/div><\/div>\n<\/div>\n\n\n\n<ul class=\"wp-block-list is-style-vk-triangle-mark list_an\">\n<li><a href=\"\/en\/research\/page001-2\/model01\/\">Prediction model based on critical points and eccentricity factors of organic solvents<\/a><span class=\"wp-rich-text-font-awesome-icon wp-font-awesome-icon\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"up-right-from-square\" class=\"svg-inline--fa fa-up-right-from-square \" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path fill=\"currentColor\" d=\"M290.4 19.8C295.4 7.8 307.1 0 320 0L480 0c17.7 0 32 14.3 32 32l0 160c0 12.9-7.8 24.6-19.8 29.6s-25.7 2.2-34.9-6.9L400 157.3 246.6 310.6c-12.5 12.5-32.8 12.5-45.3 0s-12.5-32.8 0-45.3L354.7 112 297.4 54.6c-9.2-9.2-11.9-22.9-6.9-34.9zM0 176c0-44.2 35.8-80 80-80l80 0c17.7 0 32 14.3 32 32s-14.3 32-32 32l-80 0c-8.8 0-16 7.2-16 16l0 256c0 8.8 7.2 16 16 16l256 0c8.8 0 16-7.2 16-16l0-80c0-17.7 14.3-32 32-32s32 14.3 32 32l0 80c0 44.2-35.8 80-80 80L80 512c-44.2 0-80-35.8-80-80L0 176z\"><\/path><\/svg><\/span><\/li>\n\n\n\n<li><a href=\"\/en\/research\/page001-2\/model02\/\">Prediction model based on molecular information obtained from quantum science computing (future update)<\/a><span class=\"wp-rich-text-font-awesome-icon wp-font-awesome-icon\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"up-right-from-square\" class=\"svg-inline--fa fa-up-right-from-square \" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path fill=\"currentColor\" d=\"M290.4 19.8C295.4 7.8 307.1 0 320 0L480 0c17.7 0 32 14.3 32 32l0 160c0 12.9-7.8 24.6-19.8 29.6s-25.7 2.2-34.9-6.9L400 157.3 246.6 310.6c-12.5 12.5-32.8 12.5-45.3 0s-12.5-32.8 0-45.3L354.7 112 297.4 54.6c-9.2-9.2-11.9-22.9-6.9-34.9zM0 176c0-44.2 35.8-80 80-80l80 0c17.7 0 32 14.3 32 32s-14.3 32-32 32l-80 0c-8.8 0-16 7.2-16 16l0 256c0 8.8 7.2 16 16 16l256 0c8.8 0 16-7.2 16-16l0-80c0-17.7 14.3-32 32-32s32 14.3 32 32l0 80c0 44.2-35.8 80-80 80L80 512c-44.2 0-80-35.8-80-80L0 176z\"><\/path><\/svg><\/span><\/li>\n\n\n\n<li><a href=\"\/en\/research\/page001-2\/model03\/\">Prediction model based on molecular information of organic solvents in carbon dioxide using PCM theory (future update)<\/a><span class=\"wp-rich-text-font-awesome-icon wp-font-awesome-icon\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"up-right-from-square\" class=\"svg-inline--fa fa-up-right-from-square \" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path fill=\"currentColor\" d=\"M290.4 19.8C295.4 7.8 307.1 0 320 0L480 0c17.7 0 32 14.3 32 32l0 160c0 12.9-7.8 24.6-19.8 29.6s-25.7 2.2-34.9-6.9L400 157.3 246.6 310.6c-12.5 12.5-32.8 12.5-45.3 0s-12.5-32.8 0-45.3L354.7 112 297.4 54.6c-9.2-9.2-11.9-22.9-6.9-34.9zM0 176c0-44.2 35.8-80 80-80l80 0c17.7 0 32 14.3 32 32s-14.3 32-32 32l-80 0c-8.8 0-16 7.2-16 16l0 256c0 8.8 7.2 16 16 16l256 0c8.8 0 16-7.2 16-16l0-80c0-17.7 14.3-32 32-32s32 14.3 32 32l0 80c0 44.2-35.8 80-80 80L80 512c-44.2 0-80-35.8-80-80L0 176z\"><\/path><\/svg><\/span><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">PC-SAFT Equation of State, Pure Component Parameters<\/h3>\n\n\n\n<ul class=\"wp-block-list is-style-vk-triangle-mark list_an\">\n<li><a href=\"\/en\/research\/page001-2\/model04\/\">Prediction model based on group contribution method (molecular structure) (future update)<\/a><span class=\"wp-rich-text-font-awesome-icon wp-font-awesome-icon\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"up-right-from-square\" class=\"svg-inline--fa fa-up-right-from-square \" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path fill=\"currentColor\" d=\"M290.4 19.8C295.4 7.8 307.1 0 320 0L480 0c17.7 0 32 14.3 32 32l0 160c0 12.9-7.8 24.6-19.8 29.6s-25.7 2.2-34.9-6.9L400 157.3 246.6 310.6c-12.5 12.5-32.8 12.5-45.3 0s-12.5-32.8 0-45.3L354.7 112 297.4 54.6c-9.2-9.2-11.9-22.9-6.9-34.9zM0 176c0-44.2 35.8-80 80-80l80 0c17.7 0 32 14.3 32 32s-14.3 32-32 32l-80 0c-8.8 0-16 7.2-16 16l0 256c0 8.8 7.2 16 16 16l256 0c8.8 0 16-7.2 16-16l0-80c0-17.7 14.3-32 32-32s32 14.3 32 32l0 80c0 44.2-35.8 80-80 80L80 512c-44.2 0-80-35.8-80-80L0 176z\"><\/path><\/svg><\/span><\/li>\n\n\n\n<li><a href=\"\/en\/research\/page001-2\/model05\/\">Prediction model based on molecular information obtained from quantum science computing (future update)<\/a><span class=\"wp-rich-text-font-awesome-icon wp-font-awesome-icon\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"up-right-from-square\" class=\"svg-inline--fa fa-up-right-from-square \" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path fill=\"currentColor\" d=\"M290.4 19.8C295.4 7.8 307.1 0 320 0L480 0c17.7 0 32 14.3 32 32l0 160c0 12.9-7.8 24.6-19.8 29.6s-25.7 2.2-34.9-6.9L400 157.3 246.6 310.6c-12.5 12.5-32.8 12.5-45.3 0s-12.5-32.8 0-45.3L354.7 112 297.4 54.6c-9.2-9.2-11.9-22.9-6.9-34.9zM0 176c0-44.2 35.8-80 80-80l80 0c17.7 0 32 14.3 32 32s-14.3 32-32 32l-80 0c-8.8 0-16 7.2-16 16l0 256c0 8.8 7.2 16 16 16l256 0c8.8 0 16-7.2 16-16l0-80c0-17.7 14.3-32 32-32s32 14.3 32 32l0 80c0 44.2-35.8 80-80 80L80 512c-44.2 0-80-35.8-80-80L0 176z\"><\/path><\/svg><\/span><\/li>\n\n\n\n<li><a href=\"\/en\/research\/page001-2\/model06\/\">Prediction model treating molecular structure as graph structural information (future update)<\/a><span class=\"wp-rich-text-font-awesome-icon wp-font-awesome-icon\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"up-right-from-square\" class=\"svg-inline--fa fa-up-right-from-square \" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path fill=\"currentColor\" d=\"M290.4 19.8C295.4 7.8 307.1 0 320 0L480 0c17.7 0 32 14.3 32 32l0 160c0 12.9-7.8 24.6-19.8 29.6s-25.7 2.2-34.9-6.9L400 157.3 246.6 310.6c-12.5 12.5-32.8 12.5-45.3 0s-12.5-32.8 0-45.3L354.7 112 297.4 54.6c-9.2-9.2-11.9-22.9-6.9-34.9zM0 176c0-44.2 35.8-80 80-80l80 0c17.7 0 32 14.3 32 32s-14.3 32-32 32l-80 0c-8.8 0-16 7.2-16 16l0 256c0 8.8 7.2 16 16 16l256 0c8.8 0 16-7.2 16-16l0-80c0-17.7 14.3-32 32-32s32 14.3 32 32l0 80c0 44.2-35.8 80-80 80L80 512c-44.2 0-80-35.8-80-80L0 176z\"><\/path><\/svg><\/span><\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>An equation of state (EoS) is used to correlate and predict various physical properties across a wide range of [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":171,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_locale":"en_US","_original_post":"https:\/\/himatchemeng.tech\/?page_id=198","footnotes":""},"class_list":["post-259","page","type-page","status-publish","hentry","en-US"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Hybrid Physical Property Prediction Model Combining \u201cEquation of State\u201d and \u201cAI\u201d - \u57fc\u7389\u5927\u5b66 \u5de5\u5b66\u90e8 \u5fdc\u7528\u5316\u5b66\u79d1 \u677e\u5ddd\u7814\u7a76\u5ba4<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/himatchemeng.tech\/en\/research\/page001-2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" 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