%0 Journal Article %1 smiljanic2019developing %A Smiljanic, Milena %A Weeber, Rudolf %A Pflüger, Dirk %A Holm, Christian %A Kronenburg, Andreas %D 2019 %J The European Physical Journal Special Topics %K %N 14 %P 1515--1527 %R 10.1140/epjst/e2018-800177-y %T Developing coarse-grained models for agglomerate growth %U https://doi.org/10.1140/epjst/e2018-800177-y %V 227 %X In this paper we present a coarse-graining (CG) approachfor the agglomeration of nano-particles and clusters. In the currentcontext, coarse-graining involves the replacement of fractal-like clustersby "representative" spherical particles. This simplification reducessignificantly the number of degrees of freedom and allows for the computationof much larger systems and for better collision statistics oflarger clusters. However, detailed information on the cluster shape islost, but it is exactly this detailed shape that determines collision frequenciesbetween fractal clusters and thus the agglomerates' growth.Therefore, additional properties need to be "inherited" by the coarsegrainedparticle that ensure similar collision frequencies. We generatecollision probabilities as functions of the minimum passing distance betweenthe clusters and provide these as additional function to the CGparticle. This allows for partial overlap between CG particles, and thecollision/sticking event is triggered with a specific probability only.We compare collision frequencies of CG simulations with equivalentLangevin dynamics simulations where all primary particles are tracked,and we observe decent agreement between cluster growth predicted byCG and the detailed Langevin dynamics simulations. Remaining differencesmay stem from differences in cluster transport.

@article{smiljanic2019developing, abstract = {In this paper we present a coarse-graining (CG) approachfor the agglomeration of nano-particles and clusters. In the currentcontext, coarse-graining involves the replacement of fractal-like clustersby "representative" spherical particles. This simplification reducessignificantly the number of degrees of freedom and allows for the computationof much larger systems and for better collision statistics oflarger clusters. However, detailed information on the cluster shape islost, but it is exactly this detailed shape that determines collision frequenciesbetween fractal clusters and thus the agglomerates' growth.Therefore, additional properties need to be "inherited" by the coarsegrainedparticle that ensure similar collision frequencies. We generatecollision probabilities as functions of the minimum passing distance betweenthe clusters and provide these as additional function to the CGparticle. This allows for partial overlap between CG particles, and thecollision/sticking event is triggered with a specific probability only.We compare collision frequencies of CG simulations with equivalentLangevin dynamics simulations where all primary particles are tracked,and we observe decent agreement between cluster growth predicted byCG and the detailed Langevin dynamics simulations. Remaining differencesmay stem from differences in cluster transport.}, added-at = {2023-09-04T01:49:09.000+0200}, author = {Smiljanic, Milena and Weeber, Rudolf and Pflüger, Dirk and Holm, Christian and Kronenburg, Andreas}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/22fbb5cc7b6267aec7ef83ba513ead680/icp_bib}, doi = {10.1140/epjst/e2018-800177-y}, interhash = {ce0282d851e415278e874a2da7d45c18}, intrahash = {2fbb5cc7b6267aec7ef83ba513ead680}, issn = {19516401}, journal = {The European Physical Journal Special Topics}, keywords = {}, number = 14, pages = {1515--1527}, refid = {Smiljanic2019}, timestamp = {2023-09-04T01:49:09.000+0200}, title = {Developing coarse-grained models for agglomerate growth}, url = {https://doi.org/10.1140/epjst/e2018-800177-y}, volume = 227, year = 2019 }