宋震，教授、博士生導(dǎo)師

職務(wù)：副院長(zhǎng)

電子郵箱：songz@ecust.edu.cn

地址：華東理工大學(xué)徐匯校區(qū)實(shí)驗(yàn)12樓510室

個(gè)人簡(jiǎn)介

2025.01–至今     華東理工大學(xué)，化工學(xué)院，副院長(zhǎng)（分管研究生教育）

2023.01–至今     華東理工大學(xué)，化工學(xué)院，教授

2021.07–2023.01   華東理工大學(xué)，化工學(xué)院，特聘研究員

2019.04–2021.06   德國(guó)馬格德堡大學(xué)，過程系統(tǒng)工程學(xué)院，研究員

2017.06–2019.04   德國(guó)馬普學(xué)會(huì)復(fù)雜技術(shù)系統(tǒng)動(dòng)力學(xué)研究所，過程系統(tǒng)工程研究組，博士后

2011.09–2017.05   華東理工大學(xué)，化工學(xué)院，化學(xué)工程，博士

2007.09–2011.06   山東大學(xué)，化學(xué)與化工學(xué)院，化學(xué)工程與工藝，學(xué)士

研究方向

聚焦介質(zhì)強(qiáng)化過程與產(chǎn)品創(chuàng)新，開展難分離體系、受限反應(yīng)體系、電化學(xué)體系、高端材料制備體系的應(yīng)用基礎(chǔ)研究，研究興趣包括：

1.介質(zhì)分子/體系理性設(shè)計(jì)

2.機(jī)理與數(shù)據(jù)融合驅(qū)動(dòng)建模

3.化工數(shù)據(jù)庫(kù)智能構(gòu)建與軟件平臺(tái)開發(fā)

歡迎對(duì)機(jī)器學(xué)習(xí)建模、介質(zhì)篩選設(shè)計(jì)、化工過程強(qiáng)化等相關(guān)模擬與實(shí)驗(yàn)方向感興趣的本科生、研究生、博士生、博士后聯(lián)系加入團(tuán)隊(duì)！

承擔(dān)項(xiàng)目

國(guó)家海外高層次青年人才項(xiàng)目，2022-2024，主持

國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目課題，2024-2029，主持

國(guó)家自然科學(xué)基金面上基金，2026-2029，主持

國(guó)家自然科學(xué)基金青年科學(xué)基金，2023-2025，主持

上海市海外高層次人才項(xiàng)目，2021-2024，主持

上海市教委AI賦能專項(xiàng)項(xiàng)目，2025-2026，主持

學(xué)術(shù)任職

中國(guó)系統(tǒng)工程學(xué)會(huì)過程系統(tǒng)工程專委會(huì)  委員

中國(guó)化工學(xué)會(huì)硅能源與化工專業(yè)委員會(huì)  委員

個(gè)人榮譽(yù)

 2025  全球華人化工學(xué)者學(xué)會(huì)“未來(lái)化工學(xué)者”

 2024  上海高校“雙帶頭人”教師黨支部書記“強(qiáng)國(guó)行”專項(xiàng)行動(dòng)團(tuán)隊(duì)（負(fù)責(zé)人）

 2024  全國(guó)首屆化工行業(yè)人工智能應(yīng)用創(chuàng)新大賽總決賽二等獎(jiǎng)

 2023  華東理工大學(xué)“青年五四獎(jiǎng)?wù)隆眰€(gè)人

 2023  華東理工大學(xué)-東岳藥業(yè)研究生獎(jiǎng)教金特等獎(jiǎng)

 2022  華東理工大學(xué)優(yōu)秀班導(dǎo)師

 2021  國(guó)家級(jí)高層次青年人才

 2021  上海市海外高層次人才

代表性學(xué)術(shù)成果

至今在Chem. Rev.、Angew. Chem. Int. Ed.、AIChE J.、Digit. Discov.等化學(xué)、化工及人工智能交叉領(lǐng)域主流學(xué)術(shù)期刊發(fā)表論文90余篇，被引3780余次，H-index35；參編離子液體百科全書“Encyclopedia of Ionic Liquids”、Wiley 專著“Applied AI Techniques in the Process Industry”；建立溶劑性質(zhì)智能預(yù)測(cè)平臺(tái)（ai4solvents.com）。近五年代表性論文如下：

1.Song Z^#,*, Chen JH^#, Cheng J, Chen GZ, Qi ZW*. Computer-aided molecular design of ionic liquids as advanced process media: A review from fundamentals to applications. Chemical Reviews, 2024, 124, 248-317.

2.Liu XM, Chen JH, Qiu YX, Xie KC, Cheng J, YouXZ, Chen GZ, Song Z*, Qi, ZW*. Machine learning boosted eutectic solvent design for CO₂ capture with experimental validation. AIChE Journal, 2025, 71, e18631.

3.Xie KC, Chen JH, Cheng J, Wang RZ, Cheng HY, Qi ZW*, Zhu KK, Song Z*. Enhancing aromatics extraction by double salt ionic liquids: Rational screening‐validation and mechanistic insights. AIChE Journal, 2024, 70, e18301.

4.Chen GZ, Song Z*, Qi ZW*, Sundmacher K. A scalable and integrated machine learning framework for molecular properties prediction. AIChE Journal, 2023, 69, e18185.

5.Chen GZ, Song Z*, Qi Z*, Sundmacher K. Neural recommender system for the activity coefficient prediction and UNIFAC model extension of ionic liquid–solute systems. AIChE Journal, 2021, 67, e17171.

6.Song Z, Zhou T, Qi ZW, Sundmacher K. Extending the UNIFAC model for ionic liquid–solute systems by combining experimental and computational databases. AIChE Journal, 2020, 66, e16821.

7.Xia WC, Xie KC, Gao S, Song Z*, Chen L*, Li CZ*. 2025. Multidentate chelating ligands enable high-performance zinc-bromine flow batteries. Angewandte Chemie International Edition, 2025, 64, e202418669.

8.Fang Y, Fan Y, Xie KC, Ge WX, Zhu YH, Qi ZW, Song Z*, Jiang HL*, Li CZ*. Boosting hydrogen peroxide electrosynthesis via modulating the interfacial hydrogen‐bond environment. Angewandte Chemie International Edition, 2023, 62, e202304413.

9.Qin H, Pang MT, Cheng J, Wang JW, Song Z*. Rational design of hydrophobic type Ⅴ deep eutectic solvents as efficient CO₂ absorbents. Chemical Engineering Science, 2025, 315, 121904.

10.Qiu YX, Chen JH, Xie KC, Gu RF, Qi ZW, Song Z*. Graph transformer based transfer learning for aqueous pKa prediction of organic small molecules. Chemical Engineering Science, 2024, 300, 120559.

11.Cao PL, Chen JH, Chen GZ, Qi ZW, Song Z*. A critical methodological revisit on group-contribution based property prediction of ionic liquids with machine learning. Chemical Engineering Science, 2024, 298, 20395.

12.Cheng J, Xie K, Guo P, Qin H, Deng L, Qi Z*, Song Z*. Capturing CO₂ by ionic liquids and deep eutectic solvents: A comparative study based on multi-level absorbent screening. Chemical Engineering Science, 2023, 281, 119133.

13.Qin H, Xie KC, Li LM, Cheng J, Song Z*. Enhancing R410A blend separation by using ionic liquids: From UNIFAC model extension, solvent design to molecular dynamics simulation. Chemical Engineering Science, 2023, 274, 118709.

14.Qiu YX, Song Z*, Chen GZ, Chen WY, Chen L, Zhu KK*, Qi ZW, Duan XZ*, Chen D. Large chemical language models for property prediction and high-throughput screening of ionic liquids. Digital Discovery, 2025, 4, 1505.

15.Chen GZ, Song Z*, Qi ZW*, Sundmacher K. Generalizing property prediction of ionic liquids from limited labeled data: A one-stop framework empowered by transfer learning. Digital Discovery, 2023, 2, 591-601.