Minor edits on JOSS paper

paper.md

@@ -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
@@ -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.
@@ -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].