[PRE REVIEW]: lattice_mc: A Python Lattice-Gas Monte Carlo Module

[whedon]

Submitting author: @bjmorgan (Benjamin J. Morgan)
Repository: https://github.com/bjmorgan/lattice_mc
Version: 1.0.0
Editor: @labarba
Reviewer: @asmit3

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[arfon]

👋 @labarba - the submitting author suggested you as an editor for this submission.

[labarba]

The code repository needs A statement of need, which means ...

The authors should clearly state what problems the software is designed to solve and who the target audience is.

I was not able to find this, @bjmorgan.

[bjmorgan]

@labarba I have amended the README.md and paper.md. Hopefully the additional information is suitable and appropriate for the JOSS requirements.

In solid electrolytes, ionic motion is typically effected by a series of discrete "jumps" where ions move between adjacent lattice sites [1]. For dilute mobile ions, ionic trajectories are random walks, and simple analytical expressions exits that relate macroscopic transport coefficients, i.e. diffusion coefficients and ionic conductivities, to the microscopic jump frequency of individual ions [2,3]. Practical solid electrolytes have high mobile ion concentrations, with significnat interparticle interactions producing deviations from the dilute limit random walk behaviour. In general, the quantitative effect of interparticle interactions cannot be determined analytically. As an alternative, numerical simulations, such as lattice-gas Monte Carlo methods, can be used to directly calculate these relationships. Lattice-gas Monte Carlo methods are particularly suited to studying how varying properties across broad classes of materials give quantitative differences in macroscopic ionic transport, and can be used to understand the different transport properties of materials with, for example, different crystal structures or mobile ion stoichiometries.

lattice_mc has been written to allow materials scientists and solid-state chemists model how the microscopic physics of solid electrolytes (crystal structure, stoichiometry, interaction models) determine macroscopic transport behaviour (diffusion and ionic conduction), with the goal of understand the factors that make different materials more or less useful for specific applications (e.g. Li-ion batteries or fuel cells).

[labarba]

The title in the paper metadata appears as "lattice_mc: A Python Lattice-Gas Monte Carlo Module". I"m not sure why this full title does not appear in the title of the pre-review issue ... it should also probably match the heading in the README.

I'm looking for a reviewer now.

[arfon]

The title in the paper metadata appears as "lattice_mc: A Python Lattice-Gas Monte Carlo Module". I"m not sure why this full title does not appear in the title of the pre-review issue ... it should also probably match the heading in the README.

I just updated this.

[labarba]

Sorry ... I was demonstrating the JOSS bot to a chief librarian and hit "Enter" in the process ... Ignore the actions just above!

[labarba]

@whedon commands

[whedon]

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[labarba]

@arfon : Does our bot have a command to unassign a reviewer? I assigned myself by mistake.

[arfon]

@arfon : Does our bot have a command to unassign a reviewer? I assigned myself by mistake.

Not right now sorry, you're on the hook for reviewing now . In all seriousness, when we find a reviewer just use the @whedon assign username as reviewer and it will clobber your assignment.

[labarba]

@whedon assign asmit3 as reviewer

[whedon]

OK, the reviewer is asmit3

[labarba]

@whedon start review

[whedon]

You didn't say the magic word! Try this:

@whedon start review magic-word=bananas

[labarba]

@whedon start review magic-word=bananas

[whedon]

OK, I've started the review over in #247. Feel free to close this issue now!