Radial distribution function: Difference between revisions

Content deleted Content added
m clean up, typo(s) fixed: Harper Collins → HarperCollins
Link suggestions feature: 3 links added.
Tags: Visual edit Mobile edit Mobile web edit Newcomer task Suggested: add links
 
Line 13:
The radial distribution function is usually determined by calculating the distance between all particle pairs and binning them into a histogram. The histogram is then normalized with respect to an ideal gas, where particle histograms are completely uncorrelated. For three dimensions, this normalization is the number density of the system <math>( \rho )</math> multiplied by the volume of the spherical shell, which symbolically can be expressed as <math>\rho \, 4\pi r^2 dr</math>.
 
Given a [[potential energy]] function, the radial distribution function can be computed either via computer simulation methods like the [[Monte Carlo method]], or via the [[Ornstein–Zernike equation]], using approximative closure relations like the [[Percus–Yevick approximation]] or the [[hypernetted-chain equation|hypernetted-chain theory]]. It can also be determined experimentally, by radiation scattering techniques or by direct visualization for large enough (micrometer-sized) particles via traditional or [[confocal microscopy]].
 
The radial distribution function is of fundamental importance since it can be used, using the [[Kirkwood–Buff solution theory]], to link the microscopic details to macroscopic properties. Moreover, by the reversion of the Kirkwood–Buff theory, it is possible to attain the microscopic details of the radial distribution function from the macroscopic properties. The radial distribution function may also be inverted to predict the potential energy function using the [[Ornstein–Zernike equation]] or structure-optimized potential refinement.<ref>{{cite journal |last1=Shanks |first1=B. | last2 = Potoff | first2 = J. | last3 = Hoepfner | first3 = M. |title=Transferable Force Fields from Experimental Scattering Data with Machine Learning Assisted Structure Refinement |journal=J. Phys. Chem. Lett. |date=December 5, 2022 |volume=13 |issue=49 |pages=11512–11520 |doi= 10.1021/acs.jpclett.2c03163|pmid=36469859 |s2cid=254274307 }}</ref>
 
== Definition ==
Consider a system of <math>N</math> particles in a volume <math>V</math> (for an average [[number density]] <math>\rho =N/V</math>) and at a temperature <math>T</math> (let us also define <math>\textstyle \beta = \frac{1}{kT}</math>; <math>k</math> is the [[Boltzmann constant]]). The particle coordinates are <math>\mathbf{r}_{i}</math>, with <math>\textstyle i = 1, \, \ldots, \, N</math>. The [[potential energy]] due to the interaction between particles is <math>\textstyle U_{N} (\mathbf{r}_{1}\, \ldots, \, \mathbf{r}_{N})</math> and we do not consider the case of an externally applied field.
 
The appropriate [[Ensemble average|averages]] are taken in the [[canonical ensemble]] <math>(N,V,T)</math>, with <math>\textstyle Z_{N} = \int \cdots \int \mathrm{e}^{-\beta U_{N}} \mathrm{d} \mathbf{r}_1 \cdots \mathrm{d} \mathbf{r}_N</math> the configurational integral, taken over all possible combinations of particle positions. The probability of an elementary configuration, namely finding particle 1 in <math>\textstyle \mathrm{d} \mathbf{r}_1</math>, particle 2 in <math>\textstyle \mathrm{d} \mathbf{r}_2</math>, etc. is given by
Line 90:
 
=== Energy equation ===
If the particles interact via identical pairwise potentials: <math>\textstyle U_{N} = \sum_{i > j = 1}^N u(\left | \mathbf{r}_i - \mathbf{r}_j \right |)</math>, the average [[internal energy]] per particle is:<ref name="HansenMcDonald2005">{{cite book |author=[[Jean-Pierre Hansen|Hansen, J. P.]] and McDonald, I. R. |year=2005 |title=Theory of Simple Liquids |edition= 3rd |publisher=Academic Press}}</ref>{{rp|Section 2.5}}
{{NumBlk|:| <math>\frac{\left \langle E \right \rangle}{N} = \frac{3}{2} kT + \frac{\left \langle U_{N} \right \rangle}{N} = \frac{3}{2} kT + \frac{\rho}{2}\int_V \mathrm{d} \mathbf{r} \, u(r)g(r, \rho, T) </math>.|{{EquationRef|9}}}}