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Laboratory for Chemical Computation and Modeling (Lab CCM)

The Laboratory for Chemical Computation and Modeling (Lab CCM) was established in October 2022 as one of the founding research divisions of the Institute for Computational Science and Artificial Intelligence (COSARI) of the Van Lang University. It aims to attract talented and dedicated researchers and students and pursue collaborative efforts to carry out innovative research work in the field of computational molecular and materials sciences. We endeavour to emerge as a division of excellence in the field both regionally and internationally.

Introduction

The main aims of our research work are a discovery of novel chemical phenomena and properties, a understanding of chemical reactions and catalytic processes… at the molecular level, and a prediction of new types of compounds that could be used as improved or innovative materials in various applications in molecular, biomolecular and materials sciences, by using all the available arsenal of quantum chemical computations and theoretical modeling.

We use the methods directly derived from the basic postulates of quantum mechanics ranging from high accuracy molecular orbital methods (such as coupled-cluster theory, multi-configuration perturbation techniques….) to density functional theory techniques to determine the molecular structures, thermochemical parameters, spectroscopic signatures and chemical reactivities of different classes of compounds in the gas phase, solution and solid state. Molecular dynamics simulations are also applied to explore structures and properties of compounds in solution and solid materials.

Mission & Vision

Mission

To research, develop and apply chemical computing and modeling technology to create new knowledge, predict and optimize chemical properties, and molecular design. and provides advanced computational t
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Vision

Become a leading research center for computational and chemical modeling globally, promoting advancement in the field of computational and chemical modeling. learning, opens the door to understanding
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Research Interests

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