From 30474f0ae82d2f2652e6e3df6361872adb447b99 Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Tue, 17 Dec 2024 08:33:21 +0000 Subject: [PATCH] Creating 10.21105.joss.07244.jats --- .../paper.jats/10.21105.joss.07244.jats | 528 ++++++++++++++++++ 1 file changed, 528 insertions(+) create mode 100644 joss.07244/paper.jats/10.21105.joss.07244.jats diff --git a/joss.07244/paper.jats/10.21105.joss.07244.jats b/joss.07244/paper.jats/10.21105.joss.07244.jats new file mode 100644 index 000000000..5110cdced --- /dev/null +++ b/joss.07244/paper.jats/10.21105.joss.07244.jats @@ -0,0 +1,528 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +7244 +10.21105/joss.07244 + +RNMC: kinetic Monte Carlo implementations for complex +reaction networks + + + +https://orcid.org/0000-0003-3897-3097 + +Zichi +Laura + + + + + +https://orcid.org/0000-0002-6408-1255 + +Barter +Daniel + + + + +https://orcid.org/0000-0002-6408-1255 + +Sivonxay +Eric + + + + +https://orcid.org/0000-0003-1554-197X + +Spotte-Smith +Evan Walter Clark + + + + + + +Mohanakrishnan +Rohith Srinivaas + + + + + + +Chan +Emory M. + + + + + +Persson +Kristin Aslaug + + + +* + + + +Blau +Samuel M. + + +* + + + +Materials Science Division, Lawrence Berkeley National +Laboratory, Berkeley, CA, United States of America 94720 + + + + +Department of Physics, University of Michigan - Ann Arbor, +Ann Arbor, MI, United States of America 48109 + + + + +Energy Storage and Distributed Resources, Lawrence Berkeley +National Laboratory, Berkeley, CA United States of America +94720 + + + + +Department of Materials Science and Engineering, University +of California - Berkeley, CA, United States of America +94720 + + + + +Molecular Foundry, Lawrence Berkeley National Laboratory, +Berkeley, CA, United States of America 94720 + + + + +* E-mail: +* E-mail: + + +14 +8 +2024 + +9 +104 +7244 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2024 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +C++ +chemical dynamics +kinetic Monte Carlo +nanoparticle +electrochemistry +Gillespie + + + + + + Summary +

Macroscopic chemical and physical phenomena are driven by + microscopic interactions at the atomic and molecular scales. In order + to capture complex processes with high fidelity, simulation methods + that bridge disparate time and length scales are needed. While + techniques like molecular dynamics and ab initio + simulations capture dynamics and reactivity at high resolution, they + cannot be used beyond relatively small length (hundreds to thousands + of atoms) and time scales (picoseconds to microseconds). Kinetic Monte + Carlo (kMC) approaches overcome these limitations to bridge length and + time scales across several orders of magnitude while retaining + relevant microscopic resolution, making it a powerful and flexible + tool.

+

Here, we present Reaction Network Monte Carlo + (RNMC), an easy-to-use, modular, + high-performance kMC simulation framework that enables modeling of + complex systems. RNMC consists of a core module + defining the common features of kMC algorithms, including an + implementation of the Gillespie algorithm + (Gillespie, + 1977), input/output operations leveraging SQLite databases, + random number sampling, threading logic for parallel execution, and + dependency graphs for efficient event propensity updates. In addition, + there are currently three modules defining kMC implementations for + different types of applications. The GMC + (Gillespie Monte Carlo) module enables simulations of reaction + networks in a homogeneous (well-mixed) environment. + GMC is a basic tool that is appropriate for + general simulations of solution-phase chemistry. The + NPMC (NanoParticle Monte Carlo) module enables + simulation of dynamics in nanoparticles with 3D statistical field + theory and supports one- and two-site interactions. Finally, the + LGMC (Lattice Gillespie Monte Carlo) module is + designed for simulations of multi-phase systems (especially at + solid-fluid interfaces) where chemical and electrochemical reactions + can occur between a lattice region and a homogeneous region. We have + designed RNMC to be easily extensible, enabling + users to add additional kMC modules for other diverse chemical and + physical systems.

+ + + Statement of need +

There are many existing kMC implementations, including several open + source examples (e.g. the Stochastic Parallel PARticle Kinetic + Simulator or SPPARKS + (Garcia + Cardona et al., 2009) and kmos + (Hoffmann + et al., 2014)). 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. All simulators leverage the small core library, + which serves as a common interface through the use of templating. As + long as they can operate through this shared core, different + simulation implementations are totally independent. This means that + new developers need only read and understand the core library to be + able to add new capabilities to RNMC, lowering + the barrier to entry, and further reduces the likelihood that new + additions will adversely affect pre-existing code.

+

The simulation modules already implemented in + RNMC provide unique capabilities that are not + widely available in other open source codes. + NPMC is specifically designed for 3D + simulations of the complex photophysical interaction networks in + nanocrystals + (Teitelboim + et al., 2019), particularly multi-domain heterostructures whose + optical properties cannot be calculated deterministically + (Skripka + et al., 2023). NPMC can be used to + simulate energy transfer interactions between dopants in + nanoparticles, their radiative transitions, and nonlinear processes + such as upconversion + (Chan, + 2015) and photon avalanching + (Skripka + et al., 2023). 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. Electrochemical reactions + can be treated using Marcus theory + (Marcus, + 1965) or Butler-Volmer kinetics + (Newman + & Balsara, 2021). 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 + (Barter + et al., 2023; + Spotte-Smith + et al., 2022, + 2023). + 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 + (Xia + et al., 2023).

+ + + Acknowledgements +

This project was intellectually led by the Laboratory Directed + Research and Development Program of Lawrence Berkeley National + Laboratory under U.S. Department of Energy Contract + No. DE-AC02-05CH11231. L.Z. was supported in part by the U.S. + Department of Energy, Office of Science, Office of Workforce + Development for Teachers and Scientists (WDTS) under the Science + Undergraduate Laboratory Internships Program (SULI). E.W.C.S.-S. was + supported by the Kavli Energy NanoScience Institute Philomathia + Graduate Student Fellowship. Work at the Molecular Foundry (E.M.C., + K.A.P) was supported by the Office of Science, Office of Basic Energy + Sciences, of the U.S. Department of Energy under Contract + No. DE-AC02-05CH11231. Additional support came from the Joint Center + for Energy Storage Research (JCESR), an Energy Innovation Hub funded + by the U.S. Department of Energy, Office of Science, Basic Energy + Sciences. This code was developed and tested using computational + resources provided by the National Energy Research Scientific + Computing Center (NERSC), a U.S. Department of Energy Office of + Science User Facility under Contract No. DE-AC02-05CH11231, the Eagle + and Swift HPC systems at the National Renewable Energy Laboratory + (NREL), and the Lawrencium HPC cluster at Lawrence Berkeley National + Laboratory.

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