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Minor edits on JOSS paper
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espottesmith authored Nov 25, 2024
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Expand Up @@ -41,15 +41,15 @@ authors:
corresponding: true
affiliation: 3
affiliations:
- name: Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA 94720
- name: Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America 94720
index: 1
- name: Department of Physics, University of Michigan - Ann Arbor, Ann Arbor, MI, USA 48109
- name: Department of Physics, University of Michigan - Ann Arbor, Ann Arbor, MI, United States of America 48109
index: 2
- name: Energy Storage and Distributed Resources, Lawrence Berkeley National Laboratory, Berkeley, CA USA 94720
- name: Energy Storage and Distributed Resources, Lawrence Berkeley National Laboratory, Berkeley, CA United States of America 94720
index: 3
- name: Department of Materials Science and Engineering, University of California - Berkeley, CA, USA 94720
- name: Department of Materials Science and Engineering, University of California - Berkeley, CA, United States of America 94720
index: 4
- name: Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, USA 94720
- name: Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America 94720
index: 5
date: 14 August 2024
bibliography: paper.bib
Expand All @@ -72,7 +72,7 @@ We have designed `RNMC` to be easily extensible, enabling users to add additiona

# Statement of need

Three are many existing kMC implementations, including several open source examples (e.g. the Stochastic Parallel PARticle Kinetic Simulator or `SPPARKS` [@garcia2009crossing] and `kmos` [@hoffmann2014kmos]).
There are many existing kMC implementations, including several open source examples (e.g. the Stochastic Parallel PARticle Kinetic Simulator or `SPPARKS` [@garcia2009crossing] and `kmos` [@hoffmann2014kmos]).
`RNMC` began as a fork of SPPARKS but differs in several important ways.
First, because `RNMC` uses the widely supported SQLite database engine for simulation inputs and outputs, it facilitates the automation of simulations.
Second, `RNMC` has a focus on modularity.
Expand All @@ -85,7 +85,7 @@ The simulation modules already implemented in `RNMC` provide unique capabilities
`NPMC` can be used to simulate energy transfer interactions between dopants in nanoparticles, their radiative transitions, and nonlinear processes such as upconversion [@chan2015combinatorial] and photon avalanching [@skripka2023NL].
`LGMC` is also somewhat unique in that it can simulate multi-phase systems and electrochemical processes.
Simulations using `LGMC` can include a lattice region and a homogeneous solution region which can interact *via* interfacial reactions.
Electrochemcial reactions can be treated using Marcus theory [@marcus1965theory] or Butler-Volmer kinetics [@newman2021electrochemical].
Electrochemical reactions can be treated using Marcus theory [@marcus1965theory] or Butler-Volmer kinetics [@newman2021electrochemical].
Because it allows for a dynamic lattice region, `LGMC` is also appropriate for simulations of nucleation and growth, dissolution, precipitation, and related phenomena.

We have already used the `GMC` module in a number of prior works in applications related to Li-ion and Mg-ion batteries [@spotte2022toward; @barter2023predictive; @spotte2023chemical]. We note that these simulations included tens of millions of reactions, demonstrating that `RNMC` is able to scale to large and complex reaction networks. In addition, we have used `NPMC` to perform Bayesian optimization of upconverting nanoparticles [@xia2023accelerating].
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