Academic Profile

Dr. Ni received his B.S. (2005) in Computational Mathematics and M.S. (2008) in Chemical Engineering from Beijing University of Chemical Technology. From 2008 to 2012, he did his Ph.D. in Physics with Prof. Marjolein Dijkstra in Utrecht University (the Netherlands) focusing on the computational study on the self-assembly of colloidal systems. From 2012 to 2014, he did his postdoc with Profs. Martien A. Cohen Stuart and Peter G. Bolhuis focusing on the self-assembly of fibril-forming polypeptides. In 2014, he was awarded the NWO VENI fellowship which is the most prestigious personal grant for young scientists in the Netherlands to start independent research. In March 2016, he joined the School of Chemical and Biomedical Engineering in Nanyang Technological University as an assistant professor.

2016: Best Research Prize by the European Cooperation in Science and Technology (COST) Action – Flowing Matter [An annual prize for European Early Stage Researchers in soft matter within eight years after the date of PhD]
2014: NWO VENI Talent Personal Grant
2011: Chinese Government Award for Outstanding Self-financed Students Abroad
2005: The First Prize in National Postgraduates Mathematical Contest in Modeling in China
2004: The Honorable Mention in International Mathematical Contest in Modeling,
2002: The Cup of Higher Education Press (Champion) in National Wide Mathematical Contest in Modeling in China
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Asst Prof Ni Ran
Assistant Professor, School of Chemical and Biomedical Engineering

The concept of "soft matter" was first introduced by Pierre-Gilles de Gennes in his Nobel lecture in 1991. Essentially, soft matter is a subfield of condensed matter comprising a variety of physical systems that are deformed or structurally altered by thermal or mechanical stress of the magnitude of thermal fluctuations. Because of their responsivity with respect to perturbations, e.g. thermal fluctuations, mechanical deformation, external fields, etc., soft matter have shown great promise as the next generation “smart materials”.

In our group, we use computer simulation as a tool to study and predict the structural properties and dynamic behaviour of soft matter systems in and out of equilibrium to direct the experimental fabrication of functional materials. In particular, we are interested in the self-assembly of colloidal and (bio) polymer systems and work synergically with experimentalists to design new functional materials with application in photonic devices, bio-sensor, bio-materials, etc. Presently, we are interested in the projects below:

1. Dynamic assembly of active matter
2. Glass transition of anisotropic colloids
3. Hierarchical self-assembly of anisotropic colloids
4. Self-assembly of fibril-forming polypeptides
  • Dynamic hyperuniform materials

  • High Throughput Prediction of Molecular Microstructures Using Deep Learning Neural Networks

  • Programmable DNA self-assembly via Machine Learning
  • X. Xia, H. Hao, M. P. Ciamarra, R. Ni. (2020). Linker-mediated self-assembly of mobile DNA coated colloids. Science Advances, 6, eaaz6921.

  • Q. Lei, R. Ni. (2019). Hydrodynamics of Random-Organizing Hyperuniform Fluids. Proc. National Academy of Sciences, USA, 116, 22983.

  • P. Sampedro Ruiz, Q. Lei, R. Ni. (2019). Melting and re-entrant melting of polydisperse hard disks. Communications Physics, 2, 70.

  • Q. Lei, M. Pica Ciamarra, R. Ni. (2019). Non-Equilibrium Strongly Hyperuniform Fluids of Circle Active Particles with Large Local Density Fluctuations. Science Advances, 5, eaau7423.

  • K Sankaewtong*, Q-l Lei*, R Ni. (2019). Self-assembled multi-layer simple cubic photonic crystals of oppositely charged colloids in confinement. Soft Matter, 15, 3104-3110.