Students and researchers pursuing molecular modeling or computational chemistry use readily available software such as Schrodinger, Gaussian, Arguslab, Hyperchem etc. to facilitate the visualization of molecules and calculation of their energy. A variety of computational tools form the basis of working of such software. The first step in using most of these software programs is to optimize the geometry of the input molecule. During such optimization procedure, the software searches for parameters of geometry such as bond length, bond angle and dihedral angle which results in the molecule’s minimum energy and hence the most stable geometry. While it is pertinent for the student to be able to choose the right computational tool to obtain reliable results, the visualization of potential energy diagram of the molecule is equally important. It may be appropriately said that the core of all the computational tools is rooted in a deep understanding of potential energy diagrams or potential energy surfaces (PESs). Potential energy surfaces are multidimensional graphs of potential energy against the various independent variables of geometrical parameters. They can span from three-dimensional representations (with two dimensions for the independent variables and one for energy) to more complex, higher-dimensional forms. A PES is often compared to a landscape, with hills, valleys, and ridges corresponding to high and low energy configurations. It is a challenge for undergraduate students to understand the PESs of polyatomic molecules as they have always dealt with potential energy diagrams that are of two dimensions only. This article discusses a simplified approach to grasp the concept of PES for polyatomic molecules, using water—the simplest polyatomic molecule—as an example. A three-dimensional PES graph is created in MS Excel using values calculated from the free molecular modeling software, ArgusLab. Additionally, the process of reducing the 3D plot to a 2D plot through slicing is also explained.
| Published in | International Journal of Computational and Theoretical Chemistry (Volume 13, Issue 1) |
| DOI | 10.11648/j.ijctc.20251301.14 |
| Page(s) | 43-48 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Computational Chemistry, Potential Energy Surface, Water, Polyatomic Molecule, Slicing
| [1] | Clary, D. C. Chem. Phys., 1979, 41, 387. |
| [2] | Ohmine, I. & Tanaka, H., J. Chem. Phys., 1990, 93, 8138. |
| [3] | Partridge, H. & Schwenke, D. W. J. Chem. Phys., 1997, 106, 4618. |
| [4] | Rahman, A. & Stillinger, F. H., J. Chem. Phys., 1971, 55, 3336. |
| [5] | Dang, L. X. & Pettitt, B. M., J. Phys. Chem., 1987, 91, 3349. |
| [6] | Sceats, M. G. & Rice, S. A., J. Chem. Phys., 1980, 72, 3236. |
| [7] | Karmakar, A. K. & Joarder, R. N., Phys. Lett. A, 1994, 190, 480. |
| [8] | Wang, Y. & Bowman, J. M., Chem. Phys. Lett., 2010, 491, 1. |
| [9] | Efimov, Y. Ya. & Naberukhin, Y. I., Spectrochim. Acta. A. Mol. Biomol. Spectrosc., 2011, 78, 617. |
| [10] | Jorgensen, W. L. & Tirado-Rives, J., Proc. Natl. Acad. Sci., 2005, 102, 6665. |
| [11] | Starr, F. W. et al. Phys Rev E, 2001, 63, 041201. |
| [12] | Morawietz, T., Sharma, V. and Behler, J., J. Chem. Phys. 2012, 136, 064103. |
| [13] | Anderson, J. A. & Tschumper, G. S., J. Phys. Chem. A, 2006, 110, 7268. |
| [14] | Burnham, C. J. & Xantheas, S. S., J. Chem. Phys., 2002, 116, 1479. |
| [15] | Fowler, J. E. & Schaefer, H. F. I., J. Am. Chem. Soc., 1995, 117, 446. |
| [16] | Kondati Natarajan, S., Morawietz, T. and Behler, J. Phys. Chem. Chem. Phys., 2015, 17, 8356. |
| [17] | Ranea, V. A., J. Chem. Phys., 2012, 137, 204702. |
| [18] | Bratko, D., Blum, L. & Luzar, A., J. Chem. Phys., 1985, 83, 6367. |
| [19] | Behler, J., J. Phys. Condens. Matter Inst. Phys. J., 2014, 26, 183001. |
| [20] | Dahlke, E. E. & Truhlar, D. G. Improved density functionals for water. J. Phys. Chem. B, 2005, 109, 15677. |
| [21] | Guillot, B. Mol. Liq. Water New Millenium, 2002, 101, 219. |
| [22] | Castellan, G. W. Physical Chemistry 631 (Addison Wesley Publishing Co., Reading, Massachussets, 1983). |
| [23] | Lewars, E. G. The concept of Potential Energy Surface. in Computational Chemistry, Introduction to the Theory and Applications of Molecular and Quantum Mechanics 27 (Springer, 2011). |
APA Style
Bhashyam, V. (2025). Before You Click: Understanding the Potential Energy Surface of Water. International Journal of Computational and Theoretical Chemistry, 13(1), 43-48. https://doi.org/10.11648/j.ijctc.20251301.14
ACS Style
Bhashyam, V. Before You Click: Understanding the Potential Energy Surface of Water. Int. J. Comput. Theor. Chem. 2025, 13(1), 43-48. doi: 10.11648/j.ijctc.20251301.14
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.ijctc.20251301.14,
author = {Vaijayanthi Bhashyam},
title = {Before You Click: Understanding the Potential Energy Surface of Water
},
journal = {International Journal of Computational and Theoretical Chemistry},
volume = {13},
number = {1},
pages = {43-48},
doi = {10.11648/j.ijctc.20251301.14},
url = {https://doi.org/10.11648/j.ijctc.20251301.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijctc.20251301.14},
abstract = {Students and researchers pursuing molecular modeling or computational chemistry use readily available software such as Schrodinger, Gaussian, Arguslab, Hyperchem etc. to facilitate the visualization of molecules and calculation of their energy. A variety of computational tools form the basis of working of such software. The first step in using most of these software programs is to optimize the geometry of the input molecule. During such optimization procedure, the software searches for parameters of geometry such as bond length, bond angle and dihedral angle which results in the molecule’s minimum energy and hence the most stable geometry. While it is pertinent for the student to be able to choose the right computational tool to obtain reliable results, the visualization of potential energy diagram of the molecule is equally important. It may be appropriately said that the core of all the computational tools is rooted in a deep understanding of potential energy diagrams or potential energy surfaces (PESs). Potential energy surfaces are multidimensional graphs of potential energy against the various independent variables of geometrical parameters. They can span from three-dimensional representations (with two dimensions for the independent variables and one for energy) to more complex, higher-dimensional forms. A PES is often compared to a landscape, with hills, valleys, and ridges corresponding to high and low energy configurations. It is a challenge for undergraduate students to understand the PESs of polyatomic molecules as they have always dealt with potential energy diagrams that are of two dimensions only. This article discusses a simplified approach to grasp the concept of PES for polyatomic molecules, using water—the simplest polyatomic molecule—as an example. A three-dimensional PES graph is created in MS Excel using values calculated from the free molecular modeling software, ArgusLab. Additionally, the process of reducing the 3D plot to a 2D plot through slicing is also explained.
},
year = {2025}
}
TY - JOUR T1 - Before You Click: Understanding the Potential Energy Surface of Water AU - Vaijayanthi Bhashyam Y1 - 2025/05/29 PY - 2025 N1 - https://doi.org/10.11648/j.ijctc.20251301.14 DO - 10.11648/j.ijctc.20251301.14 T2 - International Journal of Computational and Theoretical Chemistry JF - International Journal of Computational and Theoretical Chemistry JO - International Journal of Computational and Theoretical Chemistry SP - 43 EP - 48 PB - Science Publishing Group SN - 2376-7308 UR - https://doi.org/10.11648/j.ijctc.20251301.14 AB - Students and researchers pursuing molecular modeling or computational chemistry use readily available software such as Schrodinger, Gaussian, Arguslab, Hyperchem etc. to facilitate the visualization of molecules and calculation of their energy. A variety of computational tools form the basis of working of such software. The first step in using most of these software programs is to optimize the geometry of the input molecule. During such optimization procedure, the software searches for parameters of geometry such as bond length, bond angle and dihedral angle which results in the molecule’s minimum energy and hence the most stable geometry. While it is pertinent for the student to be able to choose the right computational tool to obtain reliable results, the visualization of potential energy diagram of the molecule is equally important. It may be appropriately said that the core of all the computational tools is rooted in a deep understanding of potential energy diagrams or potential energy surfaces (PESs). Potential energy surfaces are multidimensional graphs of potential energy against the various independent variables of geometrical parameters. They can span from three-dimensional representations (with two dimensions for the independent variables and one for energy) to more complex, higher-dimensional forms. A PES is often compared to a landscape, with hills, valleys, and ridges corresponding to high and low energy configurations. It is a challenge for undergraduate students to understand the PESs of polyatomic molecules as they have always dealt with potential energy diagrams that are of two dimensions only. This article discusses a simplified approach to grasp the concept of PES for polyatomic molecules, using water—the simplest polyatomic molecule—as an example. A three-dimensional PES graph is created in MS Excel using values calculated from the free molecular modeling software, ArgusLab. Additionally, the process of reducing the 3D plot to a 2D plot through slicing is also explained. VL - 13 IS - 1 ER -
Department of Chemistry, Gargi College, University of Delhi, Delhi, India
Information