Ph.D., Assistant Professor Department of Materials Science and Engineering

Prof. Luo's Computational Materials Design (CMD) group currently interests in two complementary fields: (1) first-principles calculations of advanced functional materials, focusing on their failure mechanisms and proposing novel countermeasures, and (2) development of more accurate and faster computational methods. The CMD group is in close collaboration with experimental groups in and outside China.

Personal Profile

Academic Positions

Oct. 2018 – Now            SUSTech, Department of Materials Science and Engineering, Assistant Professor

Oct. 2017 – Sep. 2018   Washington University in St. Louis, Department of Mechanical Engineering and Materials Science, Research Scientist

Apr. 2012 – Jul. 2017     University of Wisconsin-Madison, Department of Materials Science and Engineering, Research Associate

Oct. 2010 – Mar. 2012   Institute for Molecular Science (Japan), Postdoctoral Researcher



Sep. 2005 – Jul. 2010   Peking University, Condensed Matter Physics, Ph.D.

Sep. 2001 – Jul. 2005   Tianjin University, Applied Physics, B.Sc.


Awards and Honors

◆ Shenzhen Peacock Plan Award, Level B (2019)

◆ Seed Project Award, Materials Research Science and Engineering Center, USA (2016, 2017)

Fellow of Institute for Molecular Science, Japan (2011)


Research in this group involves two aspects: (1) first-principles study of advanced functional materials, e.g. electronic materials and clean-energy materials, focusing on their failure mechanisms and proposing novel countermeasures; and (2) development of more accurate and faster computational methods.


Computational Materials Science (Spring)

Finite Element Analysis for Materials Science (Fall)

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Major achievements:

1. Discovered a “dynamic swapping mechanism”, which is critical to achieve atomic-scale control of the interface structure [Nature Materials 13, 879 (2014)]. It was found that during the epitaxial growth of metastable materials, the molecular components of a later deposited atomic layer can dynamically switch position with a previously deposited atomic layer during the growth and thus induce an unexpected growth of a later-deposited atomic layer below a previously-deposited atomic layer. We identified the underlying thermodynamic driving force and dynamic mechanism, proposed a revised growth strategy, and revealed the generality of the phenomenon in other materials. The predictions were perfectly confirmed by our experimental collaborators, and later by other groups with different growth techniques and in different materials.

2. Discovered a general phenomenon during the dynamic processes in semiconductors and insulators: a rate-limiting transition state is usually located on the energy surface of an excited initial state rather than the typically assumed ground initial state [NPG Asia Materials 10, 45 (2018)]. The activation barrier calculation based on the traditional assumption can sometimes induce significant errors, e.g. hopping of carbon vacancy in silicon carbide. A straightforward method to estimate the error bars by the traditional assumption was proposed and new computational procedures of activation barriers were provided. Predictions based on the findings in this work are in excellent agreement with highly-accurate experimental results.

3. Provided in-depth understanding on the point defects and grain boundaries in several functional materials: identified their atomic structures, stabilities, electronic properties, relationship with experimental conditions, and methods to tune the defects [Advanced Materials 31, 1805047 (2019); NPG Asia Materials 9, e345 (2017)].

4. “Li dendrites” issue imposes the most critical challenge of commercializing the Li-metal rechargeable batteries. Our computational study revealed the underlying mechanism of using “nanosieve” materials, e.g. graphdiyne, to effectively suppress the Li dendrites: “nanosieve” materials can induce a “hydraulic-jump” effect, which efficiently homogenizes the Li ions above anode under an even highly nonuniform electric field and consequently induces a uniform Li deposition. Because the “hydraulic-jump” effect increases with the amplitude of electric effect, it effectively breaks the causality of Li dendrite growth (the stronger electric field, the faster growth of Li dendrites). We further found that metallization is one major failure mechanism of the “nanosieve” materials and proper passivation can increase their long-term stability of suppressing the Li dendrites [Nano Letters 21, 7284 (2021)].

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Open positions of Postdoctoral Researcher
Professor Guangfu Luo's Computational Materials Design group at the Southern University of Science and Technology (SUSTech), Shenzhen, China has been working on computational modeling of functional materials using first-principles methods, including density functional theory and many-body quantum theory. Currently, one postdoctoral positions are available, with projects involving computational modeling of the electronic properties, optical properties, defects, and growth dynamics of semiconductors and clean-energy materials.
A PhD degree in a relevant field (e.g. condensed matter physics) and familiarity with typical DFT codes (e.g. VASP or Quantum Espresso) are required. The research will broadly develop computational modeling skills and have opportunities to work closely with superior experimental groups. The appointment is initially for one year and can be extended based on mutual agreement. Depending on performance, the salary varies between 300,000 and 330,000 RMB/yr.
Interested applicants should send a cover letter and CV to luogf[at] Review will begin immediately and continue until the positions are filled.
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Department of Materials Science and Engineering, School of Engineering, 1088 Xueyuan Ave., Shenzhen 518055, China

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