The dependence of rock behavior on the deformation rate is still not well understood. In salt rock, the fundamental mechanisms that drive the accumulation of irreversible deformation, the reduction of stiffness, and the development of hysteresis during cyclic loading are usually attributed to intracrystalline plasticity and diffusion. We hypothesize that at low pressure and low temperature, the rate‐dependent behavior of salt rock is governed by water‐assisted diffusion along grain boundaries. Accordingly, a chemo‐mechanical homogenization framework is proposed in which the representative elementary volume (REV) is viewed as a homogeneous polycrystalline matrix that contains sliding grain‐boundary cracks. The slip is related to the mass of salt ions that diffuse along the crack surface. The relationship between fluid inclusion‐scale and REV‐scale stresses and strains is established by using the Mori–Tanaka homogenization scheme. It is noted from the model that a lower strain rate and a larger number of sliding cracks enhance stiffness reduction and hysteresis. Thinner sliding cracks (i.e., thinner brine films) promote stiffness reduction and accelerate stress redistributions. The larger the volume fraction of the crack inclusions, the larger the REV deformation and the larger the hysteresis. Results presented in this study shed light on the mechanical behavior of salt rock that is pertinent to the design of geological storage facilities that undergo cyclic unloading, which could help optimize the energy production cycle with low carbon emissions.
- Award ID(s):
- 1634540
- NSF-PAR ID:
- 10092833
- Date Published:
- Journal Name:
- Soft Matter
- Volume:
- 14
- Issue:
- 36
- ISSN:
- 1744-683X
- Page Range / eLocation ID:
- 7526 to 7533
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Summary -
more » « less
Abstract Additive manufacturing, no longer reserved exclusively for prototyping components, can create parts with complex geometries and locally tailored properties. For example, multiple homogenous material sources can be used in different regions of a print or be mixed during printing to define properties locally. Additionally, heterogeneous composites provide an opportunity for another level of tuning properties through processing. For example, within particulate-filled polymer matrix composites before curing, the presence of an applied electric and/or magnetic fields can reorient filler particles and form hierarchical structures depending on the fields applied. Control of particle organization is important because effective material properties are highly dependent on the distribution of filler material within composites once cured. While previous work in homogenization and effective medium theories have determined properties based upon ideal analytic distributions of particle orientations and spatial location, this work expands upon these methods generating discrete distributions from quasi-Monte Carlo simulations of the electromagnetic processing event. Results of simulations provide predicted microarchitectures from which effective properties are determined via computational homogenization.
These particle dynamics simulations account for dielectric and magnetic forces and torques in addition to hydrodynamic forces and hard particle separation. As such, the distributions generated are processing field dependent. The effective properties for a composite represented by this distribution are determined via computational homogenization using finite element analysis (FEA). This provides a path from constituents, through processing parameters to effective material properties. In this work, we use these simulations in conjunction with a multi-objective optimization scheme to resolve the relationships between processing conditions and effective properties, to inform field-assisted additive manufacturing processes.
The constituent set providing the largest range of properties can be found using optimization techniques applied to the aforementioned simulation framework. This key information provides a recipe for tailoring properties for additive manufacturing design and production. For example, our simulation results show that stiffness for a 10% filler volume fraction can increase by 34% when aligned by an electric field as compared to a randomly distributed composite. The stiffness of this aligned sample is also 29% higher in the direction of the alignment than perpendicular to it, which only differs by 5% from the random case [1]. Understanding this behavior and accurately predicting composite properties is key to producing field processed composites and prints. Material property predictions compare favorably to effective medium theory and experimentation with trends in elastic and magnetic effective properties demonstrating the same anisotropic behavior as a result of applied field processing. This work will address the high computational expense of physics simulation based objective functions by using efficient algorithms and data structures. We will present an optimization framework using nested gradient searches for micro barium hexaferrite particles in a PDMS matrix, optimizing on composite magnetization to determine the volume fraction of filler that will provide the largest range of properties by varying the applied electric and magnetic fields.
-
To achieve polymer–graphene nanocomposites with high thermal conductivity ( k ), it is critically important to achieve efficient thermal coupling between graphene and the surrounding polymer matrix through effective functionalization schemes. In this work, we demonstrate that edge-functionalization of graphene nanoplatelets (GnPs) can enable a larger enhancement of effective thermal conductivity in polymer–graphene nanocomposites relative to basal plane functionalization. Effective thermal conductivity for the edge case is predicted, through molecular dynamics simulations, to be up to 48% higher relative to basal plane bonding for 35 wt% graphene loading with 10 layer thick nanoplatelets. The beneficial effect of edge bonding is related to the anisotropy of thermal transport in graphene, involving very high in-plane thermal conductivity (∼2000 W m −1 K −1 ) compared to the low out-of-plane thermal conductivity (∼10 W m −1 K −1 ). Likewise, in multilayer graphene nanoplatelets (GnPs), the thermal conductivity across the layers is even lower due to the weak van der Waals bonding between each pair of layers. Edge functionalization couples the polymer chains to the high in-plane thermal conduction pathway of graphene, thus leading to overall high thermal conductivity of the composite. Basal-plane functionalization, however, lowers the thermal resistance between the polymer and the surface graphene sheets of the nanoplatelet only, causing the heat conduction through inner layers to be less efficient, thus resulting in the basal plane scheme to be outperformed by the edge scheme. The present study enables fundamentally novel pathways for achieving high thermal conductivity polymer nanocomposites.more » « less
-
more » « less
Abstract Magnetoactive soft materials, typically composed of magnetic particles dispersed in a soft polymer matrix, are finding many applications in soft robotics due to their reversible and remote shape transformations under magnetic fields. To achieve complex shape transformations, anisotropic, and heterogeneous magnetization profiles must be programmed in the material. However, once programmed and assembled, magnetic soft actuators cannot be easily reconfigured, repurposed, or repaired, which limits their application, their durability, and versatility in their design. Here, magnetoactive soft composites are developed from squid‐derived biopolymers and NdFeB microparticles with tunable ferromagnetic and thermomechanical properties. By leveraging reversible crosslinking nanostructures in the biopolymer matrix, a healing‐assisted assembly process is developed that allows for on‐demand reconfiguration and magnetic reprogramming of magnetoactive composites. This concept in multi‐material modular actuators is demonstrated with programmable deformation modes, self‐healing properties to recover their function after mechanical damage, and shape‐memory behavior to lock in their preferred configuration and un‐actuated catch states. These dynamic magnetic soft composites can enable the modular design and assembly of new types of magnetic actuators, not only eliminating device vulnerabilities through healing and repair but also by providing adaptive mechanisms to reconfigure their function on demand.
-
Next generation displays and lighting applications are increasingly using inorganic quantum dots (QDs) embedded in polymer matrices to impart bright and tunable emission properties. The toxicity of some heavy metals present in commercial QDs ( e.g. cadmium) has, however, raised concerns about the potential for QDs embedded in polymer matrices to be released during the manufacture, use, and end-of-life phases of the material. One important potential release scenario that polymer composites can experience in the environment is photochemically induced matrix degradation. This process is not well understood at the molecular level. To study this process, the effect of an artificially accelerated weathering process on QD–polymer nanocomposites has been explored by subjecting CdSe and CdSe/ZnS QDs embedded in poly(methyl methacrylate) (PMMA) to UVC irradiation in aqueous media. Significant matrix degradation of QD–PMMA was observed along with measurable mass loss, yellowing of the nanocomposites, and a loss of QD fluorescence. While ICP-MS identified the release of ions, confocal laser scanning microscopy and dark-field hyperspectral imaging were shown to be effective analytical techniques for revealing that QD-containing polymer fragments were also released into aqueous media due to matrix degradation. Viability experiments, which were conducted with Shewanella oneidensis MR-1, showed a statistically significant decrease in bacterial viability when the bacteria were exposed to highly degraded QD-containing polymer fragments. Results from this study highlight the need to quantify not only the extent of nanoparticle release from a polymer nanocomposite but also to determine the form of the released nanoparticles ( e.g. ions or polymer fragments).more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/c8sm01454j
