Calcium | EPFL Graph Search

Calcium is a chemical element with the symbol Ca and atomic number 20. As an alkaline earth metal, calcium is a reactive metal that forms a dark oxide-nitride layer when exposed to air. Its physical and chemical properties are most similar to its heavier homologues strontium and barium. It is the fifth most abundant element in Earth's crust, and the third most abundant metal, after iron and aluminium. The most common calcium compound on Earth is calcium carbonate, found in limestone and the fossilised remnants of early sea life; gypsum, anhydrite, fluorite, and apatite are also sources of calcium. The name derives from Latin calx "lime", which was obtained from heating limestone. Some calcium compounds were known to the ancients, though their chemistry was unknown until the seventeenth century. Pure calcium was isolated in 1808 via electrolysis of its oxide by Humphry Davy, who named the element. Calcium compounds are widely used in many industries: in foods and pharmaceuticals for ca

Aluminium and alkali uptake in calcium silicate hydrates (C-S-H)

Calcium silicate hydrate (C-S-H) is the main hydrate phase in Portland cements. Its composition varies depending on the Ca/Si ratio and on the presence of other ions such as aluminium (called CA- S-H) or alkalis. This thesis aimed to study the composition and the structure of C-S-H. An experimental data base was realised on the effect of different Ca/Si and Al/Si ratios, alkali concentrations (potassium and sodium hydroxide) and of different temperatures on C-S-H after equilibration times up to 1 year. The composition of the solid phases was analysed by TGA, XRD/Rietveld analysis and 29Si and 27Al MAS NMR. The solutions were analysed by ionic chromatography and pH measurements. In the absence of alkali, only C-A-S-H is formed at Al/Si ≤ 0.1. At higher Al/Si ratios, katoite, stratlingite and/or AH3 precipitate in addition to C-A-S-H, such that a part of the aluminium is consumed and limits the Al/Si ratio in C-S-H to 0.15±0.05 regardless of the Ca/Si ratios. A strong correlation between the aqueous aluminium concentration and the aluminium uptake in the solid phase is observed. Aluminium in C-S-H is observed mainly as tetrahedrally, Al(IV) or octahedrally coordinated, Al(VI) aluminium. At high Ca/Si ratios, Al(VI) is favoured and the aluminium uptake in C-S-H increases with the aqueous aluminium concentration. At low Ca/Si ratio (≤ 0.8), aluminium is observed mainly as Al(IV) and the low aqueous aluminium concentrations (below detection limit) indicate a higher affinity of aluminium towards C-S-H. The uptake of aluminium increases slightly the mean basal spacing slightly at low Ca/Si ratio and up to ≈2Å at higher Ca/Si ratios due to incorporation of aluminium and calcium in the interlayer. The presence of alkali hydroxide increases the pH leading (i) to a destabilisation of stratlingite and (ii) to higher aqueous silicon and aluminium concentrations and to lower calcium concentrations. As the aluminium uptake in C-S-H is strongly related to the aqueous aluminium concentrations, the aluminium uptake in the C-S-H increases significantly in the presence of alkali hydroxides, as aluminium is more soluble at higher pH. The increase of the temperature from 7 to 80 °C increases the phase-purity and long-range order of the C-S-H. The mean chain length remains stable up to 50°C, while at 80°C chain length increases and crosslinking is observed in the presence of aluminium. At all temperatures studied, the presence of aluminium has little effect on the calculated solubility of C(-A)-S-H. The incorporation of alkali ions in C-S-H increases with the initial concentration of alkali and with the decrease of Ca/Si ratio. The aqueous calcium concentration play a dominant role in alkali uptake, as calcium competes with the alkali ions to charge balance the negatively charged silanol groups of the C-S-H. A low concentration of calcium favours the alkali uptake in C-S-H. The uptake of alkali ions shortens the silica chain length as calcium is redistributed from the interlayer to the main sheet. The alkali uptake is not significantly influenced by the presence of aluminium in C-S-H, the hydration time or the type of cation (sodium or potassium).

EPFL2014

Nanoscale modelling of ionic transport in the porous C-S-H network

Khalil Ferjaoui

To reduce the CO2 footprint of construction materials, concrete producers blend their cement with Supplementary Cementitious Materials (SCMs). SCMs such as fly ash or blast furnace slag are mostly the byproducts of other industries. And while SCMs are chosen to match the properties of the common Ordinary Portland cement (OPC), their addition to the cement recipe may alter the chemistry of the system. These changes may lead to different mechanical and transport properties of the cement-based structure which may, in turn, affect its long-term resistance to harmful external agents. Therefore, understanding the relationship between cementâs microstructure and the degradation mechanisms is key for optimizing the design of new cementitious materialsIn this context, chloride attack is the most common reason for steel rebars to corrode especially when exposed to external chloride (seawater, deicer saltsâŠ). At low w/c ratios (typically 13) pore solution, the C-S-H surface develops a negative surface charge density. Electrostatic interactions between the surface and the ions in the pore solution result in a redistribution of the ionic species in two layers of charge at the interface of the solid i.e. the Electrical double layer (EDL). In nanoscopic pores, the EDL is dominated by atomic phenomena which are thought to interfere with the mobility of ions and chloride in particular. In order to understand and quantify the surface effects and their influence on ionic transport, we firstly propose an atomistic model of the EDL formation based on the use of the Metropolis Monte Carlo algorithm. This model is used to compute the ionic distributions and electrochemical potentials of electrolytes at equilibrium in nanoscopic pores. These quantities constitute the main driving forces of ionic transport at the pore scale. The microstructure parameters including the surface charge density of C-S-H, the ionic strength (and pH) of the pore solution, and the pore size are equally investigated and their effect on chlorideâs behavior quantified. Among the other parameters, the model also provides quantitative information on the effect of calcium ions which are thought to play a major role in the binding of chloride on C-S-H. The next step consists in using the calculated atomic-scale properties of the EDL in order to resolve the transport problem at the pore scale and compute microscopic diffusivities of chloride. This is achieved by using the molecular computations from the Monte Carlo (MC) engine in order to implement a modified version of the classical Poisson-Boltzmann system. The method is compared to the classical Finite element analysis of the Poisson-Nernst-Planck (PNP) equations and the data are discussed in the light of established experimental results in the literature.

EPFL2022

Impact and implications of mixed plaque class in automated characterization of complex atherosclerotic lesions

Yanan Niu

Atherosclerosis is a complex disease altering vasculature morphology, and subsequently flow, with progressive plaque formation, mural disruption, and lumen occlusion. Determination of clinically-relevant plaque components-particularly calcium, lipid, and fibrous tissue-has driven automated image-based tissue characterization. Atherosclerotic tissue of mixed composition type arises when these principal components interdigitate and combine during the course of progressive atherosclerosis. Nevertheless, such mixed plaque is treated non uniformly, and often neglected, as a distinct class in image analysis. We therefore quantitatively investigate frameworks to characterize mixed and other plaque tissue types, and examine their implications. Convolutional neural networks operated on labeled intravascular optical coherence tomography images using various characterization frameworks. The treatment of mixed plaque by image-based classifiers influenced the accuracy and homogeneity of the segmented classes. Excluding mixed plaque as a class on to itself necessarily assigns heterogeneous lesion subcomponents to one of the three homogeneous subtypes; when included, 61.7% of mixed tissue is labeled as calcium, reducing specificity in homogeneous calcium detection by 34.8%. Segmenting mixed plaque as distinct from homogeneous, non-mixed tissue improves lesion classification. This can be achieved either on the basis of homogeneous tissue classifier prediction uncertainty (77.8% overall accuracy) or by training classifiers to identify mixed plaque as a discrete tissue class (82.9% overall accuracy). Alternatively, mixed plaque can be grouped with one of the homogeneous classes, yielding a single histologically diverse class that helps preserve the homogeneity of the others. Ultimately, the best approach depends upon the alignment of histological and functional distinctions. While no vascular lesion characterization framework or method is universally optimal or appropriate, context should remain central in selecting tissue characterization techniques.

PERGAMON-ELSEVIER SCIENCE LTD2022