LU YUNPENG

Lecturer, Division of Chemistry and Biological Chemistry

 

Education:	Ph.D., National University of Singapore M.Sc., National University of Singapore
Phone:	(+65) 6513 2747
Email:	yplu@ntu.edu.sg
Office:	SPMS-CBC-06-23

Research Interests

Machine Learning in Chemistry

Recently, artificial intelligence (AI), particularly in the form of machine learning (ML), has been largely integrated into research works in cheminformatics and bioinformatics. ML is a branch of AI which utilizes algorithms and mathematical models to train machines to enhance their performance in assigned taskings. My research in this field is to develop quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) based on machine learning models and chemical data from database.

Figure 1. a) Histogram of band gap (top left) and b) dielectric constant (top center) of newly generated polymers; c) Plot of band gap against dielectric constant of the newly generated polymers together with the polymers (bottom); d) the top 10 candidates with adequate band gap in the combined dataset, ranked by dielectric constant value, where BG = Band Gap (in eV) and DC = Dielectric Constant (right).

DFT Calculations to Study Reaction Mechanisms

Understanding reaction mechanism for a catalyzed chemical process is valuable to interpret reaction yields and helps to optimize reaction conditions for future improvement. Density Functional Theory (DFT) is the current “state-of-the-art” method to study reaction mechanisms because of its balanced accuracy and computation efficiency. Over years, we have collaborated with different synthetic chemistry research groups in CBC to study reaction mechanism by DFT calculations.

Figure 2. DFT calculations of the reaction profile for the Ni(II)-mediated hydroarsination reaction at 298.15 K in MeOH

Molecular Reaction Dynamics

Reactions are at the center of chemistry both in chemistry laboratory experiments and theoretical studies. Molecular reaction dynamics unfolds the history of chemical change on the molecular level. It asks questions on what happens on the atomic length and time scales as the chemical change occurs. Molecular reaction dynamics has become an integral part of modern chemistry and is set to become a cornerstone for much of the natural sciences. Theoretical work on polyatomic reactions dynamics includes new potential energy surface calculations, direct dynamics studies, calculation of isotope effects, and new approximated quantum scattering methods. From 2011, we have published 9 peer-reviewed journal papers in this field in the main stream journals, such as the Journal of Chemical Physics and Physical Chemistry Chemical Physics.

 

 

Figure 3. Calculated thermal rate coefficients for the reaction OH + H2O → H2O + HO and its isotopologues in comparison to available experimental values at T = 300 K.

 

Selected Publications

 

1.     Tay, WS; Lu, YP; Yang, XY; Li, YX; Pullarkat, SA; Leung, PH; “Catalytic and Mechanistic Developments of the Nickel(II) Pincer Complex-Catalyzed Hydroarsination Reaction”, CHEMISTRY-A EUROPEAN JOURNAL, 25, 11308, (2019) 

2.     Ho, XL; Shao, HY; Ng, YY; Ganguly, R; Lu, YP; Soo, HS, Visible Light Driven Hydrogen Evolution by Molecular Nickel Catalysts with Time-Resolved Spectroscopic and DFT Insights, INORGANIC CHEMISTRY, 58, 1469, (2019)

3.     Zhu, YF; Lu, YP*; Song, HW; “Thermal rate coefficients and kinetic isotope effects of the reaction HO + H₂O → H₂O + OH”, THEORETICAL CHEMISTRY ACCOUNTS, 138, 111, (2019)

4.     Song, HW; Lee, SY; Yang, MH; Lu, YP*, Six-dimensional and seven-dimensional quantum dynamics study of the OH + CH₄ → H₂O + CH₃ reaction, JOURNAL OF CHEMICAL PHYSICS, 139, 154310, (2013)

5.     Song, HW; Lee, SY; Yang, MH; Lu, YP*, Full-dimensional quantum calculations of the vibrational states of H5+, JOURNAL OF CHEMICAL PHYSICS, 138, 124309, (2013)