Lianglijun

Li Jun Liang, Ph.D., graduated from the Royal Institute of Technology in Sweden with a major in Biotechnology and Computational Science. He is currently an associate Professor at the School of Artificial Intelligence, Hangzhou Dianzi University, and serves as the Deputy Director of the Shangyu Institute of Hangzhou Dianzi University. He has been selected as a high-level talent of Zhejiang Province for overseas study. In recent years, he has published over 80 SCI papers, including in internationally renowned journals such as Science Advances, Nature Computational Science, Angewandte Chemie, and Advanced Materials, in the fields of computational materials and artificial intelligence, and has been granted several patents. He has led or participated in numerous projects funded by the Natural Science Foundation of Zhejiang Province, the National Natural Science Foundation of China, and China's Key Research and Development Plan

Ph. D, 02/01/2015, Theoretical Chemistry and Computation, Royal Institute of Technology, Sweden

Ph.D, 06/01/2014, Chemistry, Zhejiang University

Bachelor, 09/01/2009, Pharmacy, College of Pharmaceutical Sciences, Zhejiang University

From January 2022 to present: Deputy Director, Shangyu  Institute, Hangzhou Dianzi University

From January 2017 to present: Associate Researcher, School of Automation (Artificial Intelligence), Hangzhou Dianzi University

From June 2016 to December 2016: Lecturer, School of Automation (Artificial Intelligence), Hangzhou Dianzi University

From January 2015 to April 2016: Postdoctoral Researcher, Department of Chemistry and Biology, Royal Institute of Technology, Sweden

Member of the Big Data and Intelligent Design Committee, The Chemical Industry and Engineering Society of China;

Member of the Youth Council, European Chinese Association for Ecology, Environment, and Sustainable Development.

1. Materials design and construction of large database

With the advent of the era of big data and the development of data analysis technology, the construction of material databases plays an increasingly important role in medicine, chemistry and other fields. Under the leadership of Professor Luo Yi, we have built the largest material database in Asia: www.dcaiku.com. Using this daatbase, we designed efficient seawater desalination membrane (The Journal of Physical Chemistry C, 2021,125 (50): 27685-27692.). Cooperated with Professor Zhang Lin from Zhejiang University,we try to explore the polymer membrane separation mechanism in a data-driven way. By integrating artificial intelligence and genetic algorithms, we try to design a variety of new polymer material membranes. Next, we will continue to improve the accuracy of the artificial intelligence algorithm, explore the relationship between the process flow parameters and the membrane performance of the industrial membrane, and further study the mass transfer mechanism of ions in the membrane.

2.   Mass-transfer mechanism and material design

Our research is focused on computational materials modeling (current focus areas: porous and polymeric materials) for energy and environmental applications (e.g., carbon capture and conversion, water treatment, and solvent recovery). The objective is to provide microscopic and mesoscopic insights from bottom-up into important physical and chemical processes, to bridge the gap between physical sciences and engineering applications, and subsequently to assist in the rational design of new materials for engineering applications. The research is in the multidisciplinary field of materials, chemistry, physics and engineering.

C++ Programming； 

Python Programming；

Bioinformatics； 

1. Multi machine collaboration in complex industrial scenarios，2024.1-2026.12， CRD in Yangtze River Delta region, 2,400,000 Yuan.

2. Design graphene derivative seawater desalination membrane based on high-throughput computation and machine learning, 2023.1-2026.12, NSFC, 540,000Yuan.

3. Computational simulations of 2-D solid-state nanopore on DNA sequencing, 2016. 1-2018. 12, NSFC, 210,000 Yuan.

4.  Designed a MM membrane  with better CO₂ separation performance, 2020.1-2023.12, NSFC, 660,000

1. Y. Wang#, L. F. Villalobos#, L.J. Liang#, B. Zhu, J. Li, C. Chen, Y. Bai, C. Zhang, L. Dong*, Q. An, H. Meng, Y. Zhao, M. Elimelech*, Scalable weaving of resilient membranes with on- demand superwettability for high- performance nanoemulsion separations. Science Advances, 2024, 10(26): eadn3289.  

2. H. Liu^#, L.J. Liang^#, F. Tian, X. Xi, Y. Zhang, P. Zhang, X. Cao, Y. Bai, C. Zhang, L. Dong*, Scalable Preparation of Ultraselective and Highly Permeable Fully Aromatic Polyamide Nanofiltration Membranes for Antibiotic Desalination. Angew. Chem. Int. Ed. 2024, 136(23), e202402509.

3. Z. Zou, Y. Zhang, L.J. Liang, M. Wei, J. Leng, J. Jiang*, Yi Luo*, Wei Hu*, A Deep Learning Model for Predicting Selected Organic Molecular Spectra. Nature Computational Science, 2023, 3(11): 957-964

4. Y. Pan, H. Liu, Z. Huang, W. Zhang, H. Gao, L.J. Liang*, L. Dong*, Hong Meng*, Membranes based on Covalent Organic Frameworks through Green and Scalable Interfacial Polymerization using Ionic Liquids for Antibiotic Desalination. Angew. Chem. Int. Ed. 2023, 136(4), e202316315.

5. X. Ma, D. Lu, J. Lu, Y. Qian, S. Zhang, Z. Yao, L.J. Liang*, Z. Sun, L. Zhang*, Revealing key structural and operating features on water/salts selectivity of polyamide nanofiltration membranes by ensemble machine learning. Desalination, 2023, 548, 116293.

6. X. Ma, C. Lan, H. Lin, Y. Peng, Y., T. Li, J. Wang, J., J. Azamat, L. J. Liang*, Designing desalination MXene membranes by machine learning and global optimization algorithm. Journal of Membrane Science, 2024, 702, 122803.

7. T.Liu, J.Lyv, Y. Xu, C. Zheng, Y. Liu, R.Fu, L.J. Liang*, J. Y. Wu*, Z. Zhang*, Graphene-based woven filter membrane with excellent strength and efficiency for water desalination. Desalination, 2022, 533, 115775.

8. L.J. Liang, H. Zhou, J. Li, Q. Chen, L. Zhu*, H. Ren. Data-driven design of nanopore graphene for water desalination. Journal of Physical Chemistry C, 2021, 125(50): 27685-27692.

9. W. Zhao, L.J. Liang*, Z. Kong, J. W. Shen. A Review on desalination by grapheane-based biomimetic nanopore: From the computational modelling perspective. Journal of Molecular Liquids, 2021, 117582.

10. L.J. Liang, Z. Zhang, H. Wang, J. W. Shen, Z. Kong. Direct proof of soft knock-on mechanism of ion permeation in a voltage gated sodium channel. International Journal of Biological Macromolecules, 2021，188, 369-374.

1. Zhejiang Provincial Overseas High-level Overseas Talents, Zhejiang Provincial Department of Human Resources and Social Security, 2016

2. Golden Bridge Award of China Market Technology Association, Excellent Project Award, China Technology Market Association, 2022