Cement hydration from hours to centuries controlled by diffusion through barrier shells of C-S-H

Rahimi-Aghdam, Saeed; Bažant, Zdeněk P.; Qomi, Mohammad Javad Abdolhosseini

doi:10.1016/j.jmps.2016.10.010

Cited by 81 publications

(53 citation statements)

References 35 publications

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“…Similarly, time‐resolved SANS and nitrogen adsorption isotherms separately capture the formation of two morphologies with different surface areas. The observed duality is routinely explained by the free volume theory, that is, interparticle vs intraparticle space available for C–S–H's nucleation and growth . It is intriguing to note that a more detailed analysis of SANS, nanoindentation, and adsorption experiments independently suggest a unique nanogranular origins for the C–S–H's seemingly two different morphologies.…”

Section: Introductionmentioning

confidence: 98%

“…The observed duality is routinely explained by the free volume theory, that is, interparticle vs intraparticle space available for C-S-H's nucleation and growth. 23,24 It is intriguing to note that a more detailed analysis of SANS, 15 nanoindentation, 9 and adsorption 25 experiments independently suggest a unique nanogranular origins for the C-S-H's seemingly two different morphologies. In particular, SANS data are interpreted using a self-similar fractal structure as produced by the diffusion-controlled single-particle aggregation of polydisperse nonspherical C-S-H nanoparticles with the average size of 5 nm.…”

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confidence: 99%

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Nanolayered attributes of calcium‐silicate‐hydrate gels

et al. 2019

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Calcium‐silicate‐hydrates (C–S–H) gel, the main binding phase in cementitious materials, has a complex multiscale texture. Despite decades of intensive research, the relation between C–S–H's chemical composition and mesoscale texture remains experimentally limited to probe and theoretically elusive to comprehend. While the nanogranular texture explains a wide range of experimental observations, understanding the fundamental processes that control particles’ size and shape are still obscure. This paper strives to establish a link between the chemistry of C–S–H nanolayers at the molecular level and formation of C–S–H globules at the mesoscale via the potential‐of‐mean‐force (PMF) coarse‐graining approach. We propose a new thermomechanical load‐cycling scheme that effectively packs polydisperse coarse‐grained nanolayers and creates representative C–S–H gel structures at various packing densities. We find that the C–S–H nanolayers percolate at ~10% packing fraction, significantly below the percolation of ideal hard contact oblate particles and rather close to that of overlapping ellipsoids. The agglomeration of C–S–H nanolayers leads to the formation of globular clusters with the effective thickness of ~5 nm, in striking agreement with small angle neutron and X‐ray scattering measurements as well as nanoscale imaging observations. The study of pore structure and local packing distribution in the course of densification shows a transition from a connected pore network to isolated nanoporosity. Furthermore, the calculated mechanical properties are in excellent agreement with statistical nanoindentation experiments, positioning nanolayered morphology as a finer description of C–S–H globule models. Such high‐resolution description becomes indispensable when investigating phenomena that involve internal building blocks of globules such as shrinkage and creep.

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Section: Introductionmentioning

confidence: 98%

mentioning

confidence: 99%

Nanolayered attributes of calcium‐silicate‐hydrate gels

et al. 2019

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“…Because the gel pores are much smaller than the capillary pores, in the literature they have always been considered as saturated. However, Rahimi-Aghdam et al (2017b) showed that this cannot be true and that at least some of the gel pores must be considered as unsaturated. Because gel pores are smaller than capillary pores, their average saturation degree should be higher than that of normal capillary pores.…”

Section: Self-desiccationmentioning

confidence: 99%

Moisture Diffusion in Unsaturated Self-Desiccating Concrete with Humidity-Dependent Permeability and Nonlinear Sorption Isotherm

2019

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A nonlinear diffusion model for the drying of concrete, previously developed at Northwestern University and embedded in some design codes, was improved and calibrated on the basis of recent more extensive experimental data from the literature as well as theoretical considerations. The improvements include a new equation for the dependence of the self-desiccation rate on pore humidity and hydration degree; an updated equation for the decrease of moisture permeability at decreasing pore humidity; new equations to predict the permeability and diffusivity parameters from the water-cement and aggregate-cement ratios, hydration degree, the type of concrete; and new equations to capture the nonlinearity of the sorption isotherm as a function of pore humidity and water-cement ratio. Furthermore, the recent idea that the pore humidity drop is the driving force, rather than a side effect, of the autogenous shrinkage is verified.

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“…As highlighted by the Materials Genome Initiative, material design and synthesis is one of the fastest growing disciplines with the current grand challenge of designing materials with targeted properties. [52][53][54][55][56][57] One such area of interest is to predict the properties of new materials computationally to expedite the discovery of superior materials. Here, we examine the case of learning the constitutive law of a 2D hyperelastic composite representative volume element, for which no closed-form constitutive law exists.…”

Section: Gpm Engineering Applicationmentioning

confidence: 99%

Leveraging the nugget parameter for efficient Gaussian process modeling

Bostanabad

Kearney

Tao

et al. 2018

Numerical Meth Engineering

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Summary Gaussian process (GP) metamodels have been widely used as surrogates for computer simulations or physical experiments. The heart of GP modeling lies in optimizing the log‐likelihood function with respect to the hyperparameters to fit the model to a set of observations. The complexity of the log‐likelihood function, computational expense, and numerical instabilities challenge this process. These issues limit the applicability of GP models more when the size of the training data set and/or problem dimensionality increase. To address these issues, we develop a novel approach for fitting GP models that significantly improves computational expense and prediction accuracy. Our approach leverages the smoothing effect of the nugget parameter on the log‐likelihood profile to track the evolution of the optimal hyperparameter estimates as the nugget parameter is adaptively varied. The new approach is implemented in the R package GPM and compared to a popular GP modeling R package (GPfit) for a set of benchmark problems. The effectiveness of the approach is also demonstrated using an engineering problem to learn the constitutive law of a hyperelastic composite where the required level of accuracy in estimating the response gradient necessitates a large training data set.

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Cement hydration from hours to centuries controlled by diffusion through barrier shells of C-S-H

Cited by 81 publications

References 35 publications

Nanolayered attributes of calcium‐silicate‐hydrate gels

Nanolayered attributes of calcium‐silicate‐hydrate gels

Moisture Diffusion in Unsaturated Self-Desiccating Concrete with Humidity-Dependent Permeability and Nonlinear Sorption Isotherm

Leveraging the nugget parameter for efficient Gaussian process modeling

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