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Mineral identification and quantification are key to the understanding and, hence, the capacity to predict material properties. The method of choice for mineral quantification is powder X-ray diffraction (XRD), generally using a Rietveld refinement approach. However, a successful Rietveld refinement requires preliminary identification of the phases that make up the sample. This is generally carried out manually, and this task becomes extremely long or virtually impossible in the case of very large datasets such as those from synchrotron X-ray diffraction computed tomography. To circumvent this issue, this article proposes a novel neural network (NN) method for automating phase identification and quantification. An XRD pattern calculation code was used to generate large datasets of synthetic data that are used to train the NN. This approach offers significant advantages, including the ability to construct databases with a substantial number of XRD patterns and the introduction of extensive variability into these patterns. To enhance the performance of the NN, a specifically designed loss function for proportion inference was employed during the training process, offering improved efficiency and stability compared with traditional functions. The NN, trained exclusively with synthetic data, proved its ability to identify and quantify mineral phases on synthetic and real XRD patterns. Trained NN errors were equal to 0.5% for phase quantification on the synthetic test set, and 6% on the experimental data, in a system containing four phases of contrasting crystal structures (calcite, gibbsite, dolomite and hematite). The proposed method is freely available on GitHub and allows for major advances since it can be applied to any dataset, regardless of the mineral phases present.

Abstract Nuclear power plays a pivotal role in ensuring a scalable, affordable, and reliable low-carbon electricity supply. Along with other low-carbon energy technologies, nuclear energy is essential for reducing our reliance on fossil fuels, addressing climate change and air pollution, and achieving a sustainable economy. Whilst significant progress has been made in reducing the volume of final radioactive waste, its management remains one of the most important challenges when considering the continued use and expansion of nuclear energy. This recently published collection highlights the latest technological and scientific advances aimed to improve the safe, long-term, and sustainable management of wastes produced from nuclear power generation.

Abstract Performance assessment in deep geological nuclear waste repository systems necessitates an extended knowledge of the pore water chemical conditions prevailing in host-rock formations. In the last two decades, important progress has been made in the experimental characterization and thermodynamic modeling of pore water speciation, but the influence of experimental artifacts and uncertainties of thermodynamic input parameters are seldom evaluated. In this respect, we conducted an uncertainty propagation study in a reference geochemical model describing the pore water chemistry of the Callovian-Oxfordian clay formation. Nineteen model input parameters were perturbed, including those associated to experimental characterization (leached anions, exchanged cations, cation exchange selectivity coefficients) and those associated to generic thermodynamic databases (solubilities). A set of 13 quantities of interest were studied by the use of polynomial chaos expansions built non-intrusively with a least-squares forward stepwise regression approach. Training and validation sets of simulations were carried out using the geochemical speciation code PHREEQC. The statistical results explored the marginal distribution of each quantity of interest, their bivariate correlations as well as their global sensitivity indices. The influence of the assumed distributions for input parameters uncertainties was evaluated by considering two parametric domain sizes.

To understand the main properties of cement, a ubiquitous material, a sound description of its chemistry and mineralogy, including its reactivity in aggressive environments and its mechanical properties, is vital. In particular, the porosity distribution and associated sample carbonation, both of which affect cement's properties and durability, should be quantified accurately, and their kinetics and mechanisms of formation known both in detail and in situ. However, traditional methods of cement mineralogy analysis (e.g. chemical mapping) involve sample preparation (e.g. slicing) that can be destructive and/or expose cement to the atmosphere, leading to preparation artefacts (e.g. dehydration). In addition, the kinetics of mineralogical development during hydration, and associated porosity development, cannot be examined. To circumvent these issues, X-ray diffraction computed tomography (XRD-CT) has been used. This allowed the mineralogy of ternary blended cement composed of clinker, fly ash and blast furnace slag to be deciphered. Consistent with previous results obtained for both powdered samples and dilute systems, it was possible, using a consolidated cement paste (with a water-to-solid ratio akin to that used in civil engineering), to determine that the mineralogy consists of alite (only detected in the in situ hydration experiment), calcite, calcium silicate hydrates (C-S-H), ettringite, mullite, portlandite, and an amorphous fraction of unreacted slag and fly ash. Mineralogical evolution during the first hydration steps indicated fast ferrite reactivity. Insights were also gained into how the cement porosity evolves over time and into associated spatially and time-resolved carbonation mechanisms. It was observed that macroporosity developed in less than 30 h of hydration, with pore sizes reaching about 100–150 µm in width. Carbonation was not observed for this time scale, but was found to affect the first 100 µm of cement located around macropores in a sample cured for six months. Regarding this carbonation, the only mineral detected was calcite.

The oxidation profile of a surficial clay aquitard was studied on a 35-meter borecore from the Albian Tégulines Clay near Brienne-le-Château (Paris Basin, France). Mineralogical, geochemical, and petrophysical data showed evidences of gradual oxidation taking place down to a depth of 20 m. Below 20 m, the clay material was nonplastic and nonfractured, and it inherited reduced redox conditions from bacterial sulfate reduction that occurred after sediment deposition. Above 20 m, the clay material was plastic. Up to a depth of 10-11 m, only rare yellowish aggregates of glauconite attested to limited oxidation, and pore water chemistry was unmodified. The 5–11 m depth interval was characterized by intensive pyrite oxidation, calcite dissolution, and formation of sulfate and iron hydroxide minerals. The upper 2-3 m was ochrous and entirely oxidized. These mineralogical changes were mirrored with pore water chemistry modifications such as an increase of alkalinity and sulfate concentration in the upper part of the profile. The presence of siderite at ~11 m evinced the reactivity of Fe(II) in the structure of clay minerals with dioxygen from meteoric waters that infiltrated into the Tégulines Clay through vertical fractures.