The Molecule Calculator

What is MolCalc?
MolCalc is a web interface that allows anyone to build (small*) molecules and estimate** molecular properties such as molecular structure, heats of formation, vibrational frequencies and vibrational modes, and molecular orbitals and orbital energies in a matter of seconds or minutes - depending on the size.  

MolCalc is designed for teaching as opposed to research - specifically for assignments in which students build their own molecules and estimate their own molecular properties.  (**MolCalc is therefore designed to run fast and the estimated molecular properties will not match experimental values exactly, and in some cases be quite different.)  The idea is to have students develop a “chemical intuition” about how molecular structure affects molecular properties, without performing the underlying calculations by hand (which would be near impossible for all but the simplest chemical systems).

How can I use MolCalc in teaching?
Just like a pocket calculator or a symbolic math program (such as Mathematica or MAPLE), MolCalc allows one to assign “higher level” chemical problems that are not practically possible to solve otherwise.  

For example, one might now ask students to compute the effect of a substituent on a particular vibration, and then rationalize the effect using molecular orbitals.  Or one might ask more open ended questions such as “build a molecule with an unusually long C-C single bond”.

How does MolCalc work?
In the Molecule Editor page the molecular structure is build using Jmol and energy minimized using the UFF force field as implemented in Jmol.

In the Molecule Calculator page the structure is re-optimized at the PM3 level of theory for a maximum of 50 steps.  This structure is then used to compute the heat of formation or vibrational frequencies at the PM3 level of theory, or the molecular orbitals using the RHF/STO-3G level of theory.  These calculations are performed with the GAMESS program. OpenBabel is used to manage input files and coordinate files.

*MolCalc 1.0 allows calculations on (closed shell) molecules with only doubly occupied molecular orbitals and with less than 11 non-hydrogen atoms.

Can I modify and/or install MolCalc on my own server?
Yes, MolCalc is distributed through github under the GPL license (

https://github.com/jensengroup/molcalc

). You must obtain a copy of the GAMESS code separately from http://www.msg.ameslab.gov/gamess/download.html

The interface code uses PHP5, jQuery, HTML5, and CSS3 and is very modular.  It therefore quite easy to add new capabilities to MolCalc.

What if I find a bug in MolCalc?
Please report it here.
Who is involved with MolCalc?
MolCalc 1.0 is written by Jimmy Charnley Kromann based on an idea by Jan Jensen. Toke Fritzemeier wrote an early prototype.  The Molecule Editor was inspired, in part, by the Virtual Molecular Modeling Kit.

The development of MolCalc is supported by the University of Copenhagen through the Education at its Best initiative (Den gode uddannelse).


This work is licensed under a Creative Commons Attribution 3.0 Unported License.  

Perspective on Density Functional Theory by Kieron Burke

Kieron Burke has written a very readable perspective on density functional theory in Journal of Chemical Physics, who, very commendably, has made it freely accessible.

To whet your appetite here are some quotes from the paper:

If you wish to annoy and confuse a traditional quantum chemist, ask “How much correlation is there in the KS wavefunction?”

When teaching chemistry students, I explain that DFT is some algorithm meaning unreliable, while ab initio is Latin for too expensive.

Interestingly, I have recently co-authored an approximation with about 105 “empirical” parameters.111 Don Truhlar, eat your heart out!

Users should stick to the standard functionals (as most do, according to Fig. 1), or explain very carefully why not.

If you enjoyed the article you may also want to check out this presentation of Kieron's entitled "Density Functional Theory: A great physics success story"

Thanks to Sten Rettrup for alerting me this paper

Computational Chemistry Highlights: July Issue

The July issue of Computational Chemistry Highlights is out.

CCH is an overlay journal that identifies the most important papers in computational and theoretical chemistry published in the last 1-2 years. CCH is not affiliated with any publisher: it is a free resource run by scientists for scientists. You can read more about it here.

Table of content for this issue features contributions from CCH editors Steven Bachrach, Grant Hill, and Robert Paton:

Aromatic Transition States in Nonpericyclic Reactions: Anionic 5 -Endo Cyclylizations are Aborted Sigmatropic Shifts


Chemical Networks (Triple Header!)

A Paramagnetic Bonding Mechanism for Diatomics in Strong Magnetic Fields

Dynamic Origin of the Stereoselectivity of a Nucleophilic Substitution Reaction

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Computational Chemistry Highlights: June issue

The June issue of Computational Chemistry Highlights is out.

CCH is an overlay journal that identifies the most important papers in computational and theoretical chemistry published in the last 1-2 years. CCH is not affiliated with any publisher: it is a free resource run by scientists for scientists. You can read more about it here.

Table of content for this issue features contributions from CCH editors Steven Bachrach, Grant Hill, and Jan Jensen:

Accurate Predictions of Nonpolar Solvation Free Energies Require Explicit Consideration of Binding Site Hydration

Tunnelling control of chemical reactions – the organic chemist's perspective

Accurate ab Initio Spin Densities

Jailbreaking Benzene Dimers

Interpreting Protein Structural Dynamics from NMR Chemical Shifts

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Teaching computational chemistry with the ADF program

Célia Fonseca Guerra at the Vrije Universiteit Amsterdam has made the exercises she uses in teaching a bachelor level course on computational chemistry available here. The exercises are based on the ADF program, but could be adapted to other programs without too much trouble.

Complete basis set limit extrapolation

The complete basis set (CBS) limit is not a basis set though it is often written as such, e.g. B3LYP/CBS.  Instead the CBS limit is an extrapolated estimate of a result obtained using an infinitely large (complete) basis set.  In principle this procedure removes any error due to the linear combination of atomic orbitals approximation, and any remaining disagreement with experiment is due to some other approximation such as the treatment of correlation.  For many properties the CCSD(T)/CBS value can be regarded as a numerically exact for all practical purposes, i.e. it is unlikely that any higher level of theory predict significantly better results.

The extrapolation is based on a minimum of three separate calculations with increasingly larger basis sets.  CBS limit extrapolation works only with basis sets designed specifically for the task, such as the correlation- or polarization-consistent basis sets, e.g. cc-pVxZ or pc-n.

The procedure is as follows: a given property $Y$ of interest (e.g. a relative energy, a frequency, or a bond length) is computed at a given level of theory (e.g. B3LYP) using at least three basis sets (e.g. cc-VDZ, cc-VTZ, and cc-VQZ.  These data points a then fit to an equation, the two most popular equations are given here

$Y(x)=Y_{CBS}+Ae^{-Bx}$  (1)

$Y(x)=Y_{CBS}+Ax^{-3}$    (2)

Here, $Y_{CBS}$ is the CBS limit we're after and $x$ is 2 for cc-pVDZ, 3 for cc-pVTZ, and so on. $x$ is also often written as $L_{max}$ (or $l_{max}$), which is the highest angular momentum included in the basis set.  For cc-pVDZ this means $d$ orbitals, which have an angular momentum of 2, so $x$ and $L_{max}$ are really the same.

Equation (1) contains three parameters ($Y_{CBS}$, $A$, and $B$) so a minimum of three different basis sets are needed to determine them.  While Equation (2) only has two parameters, a minimum of three data points are still needed for reliable results.

For some properties and correlation methods the use of the double-zeta basis set does not lead to a good fit, so calculations with pentuple-zeta basis sets are necessary.   There is some evidence that the pc-n basis set provides faster convergence to the CMS limit.  CBS limit extrapolation is computationally very demanding and is typically done on relatively small systems to provide benchmark values to test more efficient methods.

Acknowledgment: I thank Anders Christensen for providing me with key papers and with helpful discussion.


This work is licensed under a Creative Commons Attribution 3.0 

Computational Chemistry Highlights: May issue

The May issue of Computational Chemistry Highlights is out.

CCH is an overlay journal that identifies the most important papers in computational and theoretical chemistry published in the last 1-2 years.  CCH is not affiliated with any publisher: it is a free resource run by scientists for scientists.  You can read more about it here.

Table of content for this issue features contributions from CCH editors Steven Bachrach, Dean Tantillo, Dmitri Fedorov, and Jan Jensen:

On the aromatic stabilization of corannulene and coronene

Computational Design and Selection of Optimal Organic Photovoltaic Materials

Energy Decomposition Analysis in Solution Based on the Fragment Molecular Orbital Method

Amino acid-catalyzed aldol and Michael reactions

ROBIA and Dolabriferol

Quantitative NMR-Derived Interproton Distances Combined with Quantum Mechanical Calculations of 13C Chemical Shifts in the Stereochemical Determination of Conicasterol F, a Nuclear Receptor Ligand from Theonella swinhoei

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