Phase-field modeling of constrained interactive fungal networks

Ghanbari, Farshad; Costanzo, Francesco; Hughes, David; Peco, Christian

doi:10.1016/j.jmps.2020.104160

Cited by 15 publications

(9 citation statements)

References 51 publications

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“…Likewise, both Liesegang stripes and dendritic patterns also co‐exist in other disciplines, in both living systems, like fungal organisms (Ghanbari et al., 2020), and non‐living systems, such as in Li‐ion batteries where their growth could spell the end of battery life. Our approach hence provides a generic modeling framework that may also be useful outside the geoscience application and shed light on relevant processes.…”

Section: Discussionmentioning

confidence: 98%

Dendritic Growth Patterns in Rocks: Inverting the Driving and Triggering Mechanisms

Liu,

Calo,

Regenauer‐Lieb

et al. 2023

JGR Solid Earth

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Mineral precipitation can form complex patterns under non‐equilibrium conditions, in which two representative patterns are rhythmic Liesegang stripes and fractal dendrites. Interestingly, both patterns occur in the same rock formations, including various dendritic morphologies found in different rocks, such as limestone and sandstone. However, the underlying mechanism for selecting the vastly different mineral precipitation patterns remains unclear. We use a phase‐field model to reveal the mechanisms driving pattern selection in mineral precipitation. Simulations allow us to explore the effects of diffusion parameters on determining the dendritic morphologies. We also propose a general criterion to distinguish the resulting dendrites in simulations and field observations based on a qualitative visual distinction into three categories and a quantitative fractal dimension (FD) phase diagram. Using this model, we reproduce the classified dendrites in the field and invert for the key parameters that reflect the intrinsic material properties and geological environments. This study provides a quantitative tool for identifying the morphology selection mechanism with potential applications to geological field studies, exploration for resource evaluation, and other potential industrial applications.

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Section: Discussionmentioning

confidence: 98%

Dendritic Growth Patterns in Rocks: Inverting the Driving and Triggering Mechanisms

Liu,

Calo,

Regenauer‐Lieb

et al. 2023

JGR Solid Earth

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show abstract

“…Therefore, in this section, we develop a phase-field model based on the expansion of the growth dynamics model presented in. 41 To this extent, we include the physical phenomena unique to fungus-ant interactions in the growth dynamics model, such as extraction and redistribution of chemicals inside the fungal network and fungal-host biomass interactions.…”

Section: Modeling Parasite-host Interactions In Zombie Antsmentioning

confidence: 99%

“…( 1), D c is the constant nutrient diffusivity, and the terms r can include the replenishment and the consumption of the nutrients. We encourage the readers to refer to 41 for the discussion on the importance of the r and its effect on the behavior of the model. Furthermore, D η in Eq.…”

Section: Governing Equationsmentioning

confidence: 99%

“…Typical of phase-field models, and following our previous work, 41 we define the evolution of the phase-field variable ϕ as:…”

Section: Governing Equationsmentioning

confidence: 99%

“…Phase-field methodologies are suitable for problems with complex geometries and have enabled and accelerated the modeling of systems such as biomembranes, 27,28 soft matter fracture mechanics, [29][30][31][32] or constrained fungal network development. 33 We solve our equations with the finite element method and advanced discretization techniques that we developed for large-scale fluid-structure interaction. 34,35…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Coding soft matter with bionetworks-inspired emergent principles

Ghanbari

Sgarrella

Peco

2023

Bioinspiration, Biomimetics, and Bioreplication XIII

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Soft materials are attractive to engineers due to their low density, ability to sustain large deformations and customization of properties. These custom properties are realized by tailoring the microstructural architecture and optimizing the constituent materials. However, achieving complex behavior at the macroscale is difficult through conventional engineering top-down approaches. Instead, we draw inspiration from a more biological bottom-up approach based on the concept of emergence. Slime molds and fungi are fascinating models for emergence; formed by aggregation of almost identical cells, their internal networks optimize transport better than engineers, solve mazes, detect masses at a distance, or memorize periodic events. We establish here a theoretical and computational framework to explain, quantify and reproduce how this feedback between macroscopic features and local tuning of mechanical properties determines an emergent coordinated response of the network morphology. These networks have the ability to grow, survive, or die in the presence of different concentrations of nutrients and to redistribute them, thus optimizing their proliferation. We propose a phase-field scalar variable to represent the network matrix evolution and a diffusive-advective process for nutrient distribution. This framework enables high-fidelity simulations of slime molds in three-dimensional space, which are challenging due to the coupled physics involved, high-order partial differential equations, and the existence of a highly complex evolving geometry. The emergent properties of these organisms are similar in nature to tissues with transport networks, and we can exploit them to design self-healing materials, fungal sustainable building elements, or even coordinate drone swarms. This investigation is a road to the microstructural design of active soft matter, an object of interest in many fields of engineering and science.

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Dynamic shear modulus and damping of lightweight sand-mycelium soil

Gou

2023

Acta Geotech.

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Phase-field modeling of constrained interactive fungal networks

Cited by 15 publications

References 51 publications

Dendritic Growth Patterns in Rocks: Inverting the Driving and Triggering Mechanisms

Dendritic Growth Patterns in Rocks: Inverting the Driving and Triggering Mechanisms

Coding soft matter with bionetworks-inspired emergent principles

Dynamic shear modulus and damping of lightweight sand-mycelium soil

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