Edits for JOSS paper

paper/paper.bib

@@ -113,7 +113,7 @@ @article{thompson2022lammps
 }
 
 # HOOMD-Blue
-@article{anderson2010hoomd,
+@article{anderson2020hoomd,
   title = {HOOMD-blue: A Python package for high-performance molecular dynamics and hard particle Monte Carlo simulations},
   volume = {173},
   ISSN = {0927-0256},
@@ -412,3 +412,19 @@ @article{marrink2019computational
   month = jan,
   pages = {6184–6226}
 }
+
+# nanoparticle paper
+@article{craven2021examining
+  abstract = {In this work, molecular dynamics simulations are used to examine the self-assembly of anisotropically coated “patchy” nanoparticles. Specifically, we use a coarse-grained model to examine silica nanoparticles coated with alkane chains, where the poles of the grafted nanoparticle are bare, resulting in strongly attractive patches. Through a systematic screening process, the patchy nanoparticles are found to form dispersed, string-like, and aggregated phases, dependent on the combination of alkane chain length, coating chain density, and the fractional coated surface area. Correlation analysis is used to identify the ability of various particle descriptors to predict bulk phase behavior from more computationally efficient single grafted nanoparticle simulations and demonstrates that the solvent-accessible surface area of the nanoparticle core is a key predictor of bulk phase behavior. The results of this work enhance our knowledge of the phase space of patchy nanoparticles and provide a powerful approach for future screening of these materials.},
+  author = {Craven, Nicholas C and Gilmer, Justin B and Spindel, Caroline J and Summers, Andrew Z and Iacovella, Christopher R and McCabe, Clare},
+  doi = {10.1063/5.0032658},
+  issn = {0021-9606},
+  journal = {The Journal of Chemical Physics},
+  month = {jan},
+  number = {3},
+  pages = {34903},
+  title = {{Examining the self-assembly of patchy alkane-grafted silica nanoparticles using molecular simulation}},
+  url = {https://doi.org/10.1063/5.0032658},
+  volume = {154},
+  year = {2021}
+}

paper/paper.md

@@ -6,6 +6,8 @@ tags:
 - molecular-simulations
 - data-structure
 - MoSDeF
+- interoperability
+- force fields
 
 authors:
 - name: Co D. Quach
@@ -86,10 +88,11 @@ bibliography: paper.bib
 
 
 # Summary
-The General Molecular Simulation Object, or GMSO, stands as an open-source Python data structure, offering a versatile and expandable framework for handling chemical and biomolecular topologies. This library is an integral component of the Molecular Simulation Design Framework (MoSDeF), dedicated to streamlining the creation, parameterization, and representation of systems for molecule simulations. The GMSO library serves as a dynamic repository for storing chemical/biomolecular structures, encompassing metadata, coordinates, and interaction potentials. Moreover, the library includes routines for editing and exporting stored structures into various file formats, which can be used with other software for visualization (e.g., VMD[@humphrey1996vmd] and OVITO[@]) or conducting molecular simulations (e.g., GROMACS [@abraham2015gromacs], LAMMPS[@thompson2022lammps], GOMC[@nejahi2021update]).
+The General Molecular Simulation Object, or GMSO, offers an open-source Python data structure, offering a versatile and expandable framework for handling chemical and biomolecular topologies. This library is an core component of the Molecular Simulation Design Framework (MoSDeF), dedicated to streamlining the creation, parameterization, and representation of systems for molecular simulations. The GMSO library serves as a dynamic repository for storing chemical/biomolecular structures, encompassing metadata, coordinates, and interaction potentials. Moreover, the library includes routines for editing and exporting stored structures into various file formats, which can be used with other software for visualization (e.g., VMD[@humphrey1996vmd] and OVITO[@]) or conducting molecular simulations (e.g., GROMACS [@abraham2015gromacs], LAMMPS[@thompson2022lammps], GOMC[@nejahi2021update], and HOOMD-blue[@anderson2020hoomd]).
 
 
 # Statement of need
+# TODO: NCC is this statement of need to broad? Do we need something specific to GMSO? Maybe one sentence?
 
 The Molecular Simulation Design Framework (MoSDeF) is a suite of software tailored to facilitate the initialization of chemical and biomolecular systems for computational simulations [@cummings2021opena]. These tools were developed to specifically address a critical aspect of the (ir)reproducibility issue within the molecular simulation community — namely, the insufficient documentation of the structure preparation process and force field parameter implementation [@thompson2020towards]. The initialization step, often performed through Graphical User Interfaces (GUI) or via the use of ad-hoc, unpublished, and unreviewed code, poses the risk of introducing irreproducible and untraceable errors[@baker2016reproducibility]. By providing general-purposed and standardized tools that build and parameterize molecular systems for molecular simulations, directly support  various molecular dynamics (MD) and Monte Carlo (MC) engines, MoSDeF aims to trivialize the describing and disseminating such processes without creating extra burdens for computational simulation researchers [@cummings2021opena].
 
@@ -109,7 +112,7 @@ The parameterization step introduces additional information, requiring a more so
 Currently, existing data structures, such as ParmEd and OpenMM[@shirts2016lessons; @eastmann2017openmm], fulfill many functionalities and are widely adopted [@elenareal2023real; @kehrein2023unravel; @tesei2021accurate; @marrink2019computational]. However, their underlying structures are tailored to specific subsets of simulation workflows and ecosystems, as well as force field equation forms, sacrificing generality and broad applicability. This limitation includes hard-coding and assumptions about potential expressions and units. They lack the generality that MoSDeF and its users seek, such as the ability to define and store arbitrary potential expressions or unit systems. Integrating these new features into existing software, unfortunately, would require a major overhaul, potentially impacting existing simulation workflows and is not appealing to current project stakeholders.
 
 
-Hence, we developed the General Molecular Simulation Object (GMSO) library, which is a lightweight, extensible data structure encapsulating chemical/biomolecular systems and their associated interaction parameters, i.e., force fields, to cater to MoSDeF ecosystem. The library is designed to accommodate a wide range of chemical/biomolecular models, offering the capability to support arbitrary potential expressions and unit systems. Generalizing these potential (force field) expressions allows users to enter the force field in its native form and units, minimizing user error when setting up the force field file while providing the ability to easily auto-convert the potential form and units to the molecular engine's required form. GMSO satisfies the broader community's need for a general, extensible, and reproducible method of setting up molecular simulations. In addition to core data classes, the library includes routines for interacting/converting to and from other ecosystems, including ParmEd and OpenMM, enhancing interoperability without reinventing functionalities. GMSO supports output to multiple molecular simulation engine-specific file formats, currently including , including GROMACS, LAMMPS, HOOMD-Blue, NAMD, Cassandra, and GOMC, with plans for future expansion[@abraham2015gromacs; @thompson2022lammps; @anderson2010hoomd, @phillips2020scalable, @shah2017cassandra, @nejahi2021update]. When integrated with other MoSDeF software and workflow manager like Signac [@adorf2018simple], GMSO facilitates large-scale automated molecular screening for diverse molecules/structures and state points, which is critical for developing new materials, chemicals and drugs [@quach2022high, @thompson2019scalable].
+Hence, we developed the General Molecular Simulation Object (GMSO) library, which is a lightweight and extensible data structure encapsulating chemical/biomolecular systems and their associated interaction parameters, i.e., force fields, to cater to the general force fields. The library is designed to accommodate a wide range of chemical/biomolecular models, offering the capability to support arbitrary potential expressions and unit systems. Generalizing these potential (force field) expressions allows users to enter the force field in its native form and units, minimizing user error when setting up the force field file while providing the ability to easily auto-convert the potential form and units to the molecular engine's required form. GMSO satisfies the broader community's need for a general, extensible, and reproducible method of setting up molecular simulations. In addition to core data classes, the library includes routines for interacting/converting to and from other ecosystems, including ParmEd and OpenMM, enhancing interoperability without reinventing functionalities. GMSO supports output to multiple molecular simulation engine-specific file formats, currently including: GROMACS [@abraham2015gromacs], LAMMPS [@thompson2022lammps], HOOMD-Blue [@anderson2020hoomd], NAMD[@phillips2020scalable], Cassandra [@shah2017cassandra], and GOMC [@nejahi2021update], with plans for future expansion. When integrated with other MoSDeF software and workflow manager like Signac [@adorf2018simple], GMSO facilitates large-scale automated molecular screening for diverse molecules/structures and state points, which is critical for developing new materials, chemicals and drugs [@craven2021examining, @quach2022high, @thompson2019scalable].
 
 
 # Acknowledgements