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@@ -45,15 +45,9 @@ The first category contains models which seek to resolve all relevant physics wi
 
 - FLOW-3D [@FLOW-3D] is a commercial CFD software known for its capabilities in simulating complex free-surface problems, and has several specialized models for AM. However, the Flow-3D is proprietary, meaning its source code is not available for public inspection or modification and users must purchase a license to use the software. 
 
-The second category contains models that simplify melt pool physics to rapidly simulate heat transport, residual stress, and distortion across an entire part. Commercial finite element thermomechanics software solutions built on Abaqus [@abaqus] and Ansys [@ansys] are available; however, these software packages are not open and free to use and develop upon.   
+The second category contains models that simplify melt pool physics to rapidly simulate heat transport, residual stress, and distortion across an entire part. Commercial finite element thermomechanics software solutions built on Abaqus [@abaqus] and Ansys [@ansys] are available; however, these software packages are not open and free to use and develop upon. Adamantine [@adamantine] is a thermomechanics simulation tool built on an open-source software stack designed for high performance computing across computing architectures, including the deal.II finite element software package [@deal.ii], providing an alternative to the proprietary software solutions.
 
-There is an established need for intermediate frameworks that are capable of accurately predict melt pool shape, thermal gradients, and other meso-scale quantities across an entire part. Some open-source mesoscale heat transfer software tools have recently emerged to address these challenges: 
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-- Adamantine [@adamantine] is a thermomechanics simulation tool built on an open-source software stack designed for high performance computing across computing architectures, including the deal.II finite element software package [@deal.ii].
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-- GO-MELT [@go-melt] is a gpu-optimized multidomain thermal simulation tool implemented as a finite element solver using jax [@jax].  
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-These software tools are promising platforms for further development of GPU-capable mesoscale simulations of AM processes, however at present, they remain limited to single gaussian heat sources and do not consider fluid flow or general thermodynamic pathways which may be important for accurate predictions of the conditions that lead to anomalous features and microstructure evolution during printing. 
+There is an established need for intermediate frameworks that are capable of accurately predicting melt pool shape, thermal gradients, and other meso-scale quantities across an entire part. Such models can be used to inform process design decisions through heuristic estimations of anomalous printing features (e.g., keyhole formation and lack-of-fusion), as well as the prediction of the final microstructure and material properties of AM components. AdditiveFOAM was created to address these challenges and is written in an extensible manner that is capable of considering a large number of physical representations of the target problem. This includes volumetric source terms in the energy equation that support any number of independently moving sources with distinct energy profiles, optional Marangoni-driven fluid flow, and a generalized scheme for implementing tabulated thermodynamic pathways for metal alloys.
 
 # Software Features
 AdditiveFOAM features a volumetric heat source library that supports any number of independently moving sources with distinct energy profiles that have been validated for a number of AM processes. The volumetric source term is used in the solution of the unsteady, nonlinear heat equation which considers three distinct phases (solid, liquid, and powder) as a continuum. A novel thermodynamic algorithm enables variable-order time integration for any thermodynamic pathway supported through tabulated solid fraction-temperature lookup tables. The available time integration schemes are explicit forward Euler, implicit backward Euler, Backward differentiation formula (BDF-2), and Crank-Nicolson. An adaptive time integration and time stepping method automatically switches between implicit and explicit schemes to balances the computational cost and solution accuracy depending on the problem state and user defined tolerances. Additionally, AdditiveFOAM features boundary conditions for Marangoni driven fluid flow in the melt pool as well as convective and radiative heat transfer. Finally, AdditiveFOAM leverages existing OpenFOAM libraries to sample thermal data needed for microstructure predictions with a specific library for coupling to the grain structure prediction software ExaCA [@exaca]. Future releases of AdditiveFOAM will focus on resource-optimized adaptive mesh refinement (AMR) as well as dynamic load-balancing using the Zoltan [@zoltan] library.