Dlca and Langevin Dynamics Approaches of Sol Gel Transition: A Comparison via the Fractal Dimension During Aggregation

Hsieh, Kai‐Sheng; Lallet, François; Olivi-Tran, Nathalie

doi:10.1142/s0218348x08004071

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Hsieh et al. [13] reported a similar phenomenon for the 3D DLCA model at a relative density greater than 0.05, concluding that the Langevin dynamics approach is more realistic for a constant size of the unit cell. However, since the fractal dimension decreases with decreasing probability

p_s

, the DLCA model should also be able to reproduce the fractal dimensions observed in aerogels with higher densities.…”

Section: Resultsmentioning

confidence: 73%

“…Although this mesoscale atomistic model is able to capture the structural and mechanical properties, the atomistic nature does not allow for modeling of the sol-gel process, which involves condensation reactions. Currently, the following approaches for sol-gel representation are gaining more attention [1,6]: (i) algorithm based on the Smoluchowski equation [7,8], (ii) Langevin dynamics [9,10], (iii) percolation theory and cluster aggregation models [11][12][13]. Among these, percolation theory and cluster aggregation have provided significant insights into the internal gel structure [6,8], correlating synthesis parameters with microstructure [13].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the microstructural connectivity and compressive behavior of particle aggregated silica aerogels

Xiong,

Abdusalamov,

Itskov

et al. 2024

Proc Appl Math and Mech

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Porous media such as aerogels can exhibit unique properties including low thermal conductivity, low bulk density, and low sound velocity. However, the limited mechanical properties of aerogels restrict their widespread application. This study focuses on understanding the mechanical behavior of aggregated silica aerogels by investigating their microstructural connectivity and densification mechanisms under uniaxial compression. The interparticle connectivity is generated using the diffusion‐limited cluster–cluster aggregation (DLCA) algorithm, and the particle connections are modeled by beam elements that account for contact interaction. The mechanical response of representative volume elements (RVEs) is analyzed in both linear and nonlinear regimes while applying periodic boundary conditions. The model is correlated with experimental compression test data to validate the simulation results. With increasing compressive strain, load transitions between multiple backbone paths appear in the network structure. Thus, the simulation model provides insight into the compression process. Moreover, the simulation model enables the examination of the influence of various model parameters and facilitates the evaluation of the power–law relationship between the elasticity modulus and porosity of aerogels.

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p_s

, the DLCA model should also be able to reproduce the fractal dimensions observed in aerogels with higher densities.…”

Section: Resultsmentioning

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Analysis of the microstructural connectivity and compressive behavior of particle aggregated silica aerogels

Xiong,

Abdusalamov,

Itskov

et al. 2024

Proc Appl Math and Mech

View full text Add to dashboard Cite

show abstract

Cellular Automata Coupled with Two‐Phase Lattice Boltzmann Model for Modeling of Kinetics of Formation and Structure of Silica‐Based Sol–Gel Materials

Gac,

Nowak,

Borzęcka

2024

Adv Eng Mater

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A numerical model describing the sol–gel process on a mesoscopic scale is presented. The model is implemented as a cellular automaton‐based system, specifically reaction‐limited aggregation merged with two‐phase lattice Boltzmann method, which allows to describe the sol–gel process together with microscopic phase separation occurring during this process. The influence of model parameters on the structural properties of the resulting gel porosity, mesoporosity, and specific surface area, as well as on the kinetics of the gelation process: the shape of the kinetics curve and the structure formation time, is examined. It is proposed to combine the model parameters with the composition of the reaction mixture (the content of individual reagents and catalysts) and the process conditions.

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Mesoscopic structure modeling of silica aerogels using cluster‐cluster aggregation

Xiong,

Abdusalamov,

Itskov

2024

Proc Appl Math and Mech

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Silica aerogels are nanostructured materials known for their low density, high porosity, and excellent thermal insulation properties. Among silica aerogels, organosilane‐derived aerogels have received considerable interest for their additional chemical functionalities such as hydrophobicity and flexibility. This work investigates the mesoscopic modeling of such aerogels, extending an aggregation based model developed for conventional silica aerogels. The pH of sol–gel polymerizations is one of the most critical reaction and processing parameters in determining the porosity, density, strength, and transparency of the resulting gels. Achieving optical transparency in aerogels depends on the presence of homogeneous mesoporous network structures. To account for the effect of pH, a relationship between pH and adhesion probability was incorporated into a three‐dimensional cluster‐cluster aggregation (CCA) model, providing insight into the gelation process. In addition, size‐dependent diffusivities are considered in this study. By incorporating different factors into the CCA model, the gelation kinetics are evaluated. The obtained mesoscopic structure is compared with experimental characterizations, together with preliminary mechanical simulations.

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Dlca and Langevin Dynamics Approaches of Sol Gel Transition: A Comparison via the Fractal Dimension During Aggregation

Cited by 4 publications

References 16 publications

Analysis of the microstructural connectivity and compressive behavior of particle aggregated silica aerogels

Analysis of the microstructural connectivity and compressive behavior of particle aggregated silica aerogels

Cellular Automata Coupled with Two‐Phase Lattice Boltzmann Model for Modeling of Kinetics of Formation and Structure of Silica‐Based Sol–Gel Materials

Mesoscopic structure modeling of silica aerogels using cluster‐cluster aggregation

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