@@ -62,7 +62,7 @@ different languages to change from one type of atomistic potential or atomic
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structure to another. This leads to poor reproducibility and inefficient
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transfer of code from one researcher to the next. In addition, there exists a
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zoo of tools and packages for atomic simulation with more being developed every
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- day ` [@walsh_open_2024] ` . There is however no unifying framework that can
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+ day [ @walsh_open_2024] . There is however no unifying framework that can
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encompass all these tools without significant software development effort.
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Significant effort should not be necessary because while the source of the
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fundamental outputs of atomistic potentials such as energy, forces etc. may
@@ -81,15 +81,15 @@ can be easily added to the library of provided asimmodules and iterated on.
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This will allow the community to develop a robust set of shareable simulation
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protocols. The flexibility of ASIMTools allows integration of any kind of
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simulation tools such as the heavily used Atomic Simulation Environment
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- ` [@larsen_atomic_2017] ` pymatgen ` [@ong_python_2013] ` , LAMMPS
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- ` [@thompson_lammps_2022] ` etc. with examples provided. With the asimmodules
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+ [ @larsen_atomic_2017] pymatgen [ @ong_python_2013] , LAMMPS
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+ [ @thompson_lammps_2022] etc. with examples provided. With the asimmodules
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defined, users only need to provide a set of inputs in the form of yaml files
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that define the parameters used for each simulation and are therefore a
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concrete record of used parameters.
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# State of the Field
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There exist a number of popular workflow tools for atomistic simulations such
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- as Aiida ` [@huber_aiida_2020] ` , Fireworks ` [@jain_fireworks_2015] ` and many
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+ as Aiida [ @huber_aiida_2020] , Fireworks [ @jain_fireworks_2015] and many
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more. These tools provide frameworks for constructing complex workflows with
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different underlying principles. Some managers enforce strict rules that ensure
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that data obeys FAIR principles and emphasizes data provenance and
@@ -101,7 +101,7 @@ work in ASIMTools and with a few extra steps, the protocol can be made to
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support an arbitrary calculator and input structure.
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In some workflow managers, such as Atomic Simulation Recipes
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- ` [@gjerding_atomic_2021] ` , once workflows are built, it can often be difficult
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+ [ @gjerding_atomic_2021] , once workflows are built, it can often be difficult
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to quickly change and iterate over key parameters such as the choice of
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atomistic calculator or structure as they are intrinsically built into the
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code. This is particularly challenging in an age where machine learning models
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