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At least 163 records · Page 9

Nanocomposite Materials for Radionuclide Sequestration from Groundwater Environments

The half-lives of radionuclides range from fractions of a second to billions of years. Since no practical method of altering radioactive decay exists, and since exposure to either the energy emitted from radioactive decay or chemical properties of radionuclides poses dire health risks, radioactive materials must be segregated and controlled. The capture, treatment, and disposition of radioactive materials remain an extraordinary challenge. In here, we focus our attention on the synthesis and characterization of a unique class of nanocomposite materials that have potential for removal of radionuclide contamination. Specifically, we report a simple approach to decorate the surface of iron-based (Fe/FexOy) material with various nano-catalysts. Specifically, copper (Cu), tin (Sn), and silver (Ag) nanoparticles were prepared through two different reduction approaches, namely, citrate and cetyltrimethylammonium bromide (CTAB) methods, on the iron-based material surface. All samples were characterized by a variety of analytical tools, which included scanning electron microscopy (SEM), electron-dispersive X-ray microanalysis (EDS), and EDS mapping to elucidate materials’ morphology as well as nano-catalysts’ loading and location on the iron-based structures.

Hunyadi Murph, Simona E.↗

New soil carbon sequestration with nitrogen enrichment: a meta-analysis

Background and aims: Through agriculture and industry, humans are increasing the deposition and availability of nitrogen (N) in ecosystems worldwide. Carbon (C) isotope tracers provide useful insights into soil C dynamics, as they allow to study soil C pools of different ages. In this study we evaluated to what extent N enrichment affects soil C dynamics in experiments that applied C isotope tracers. Methods: Using meta-analysis, we synthesized data from 35 published papers. We made a distinction between “new C” and “old C” stocks, i.e., soil C derived from plant C input since the start of the isotopic enrichment, or unlabeled, pre-existing soil C. Results: Averaged across studies, N addition increased new soil C stocks (+30.3%), total soil C stocks (+6.1%) and soil C input proxies (+30.7%). Although N addition had no overall, average, effect on old soil C stocks and old soil C respiration, old soil C stocks increased with the amount of N added and respiration of old soil C declined. Nitrogen-induced effects on new soil C and soil C input both decreased with the amount of extraneous N added in control treatments. Conclusion: Although our findings require additional confirmation from long-term field experiments, our analysis provides isotopic evidence that N addition stimulates soil C storage both by increasing soil C input and (at high N rates) by decreasing decomposition of old soil C. Furthermore, we demonstrate that the widely reported saturating response of plant growth to N enrichment also applies to new soil C storage.

54 ENVIRONMENTAL SCIENCES↗

NOx sequestration by calcium aluminate cementitious materials

This study quantifies NO{sub x} uptake efficiency and explores NO{sub x} binding mechanisms in calcium aluminate cementitious (CAC) materials. Comparison between unmodified and TiO{sub 2}-modified CAC separates intrinsic NO{sub x} binding mechanisms from those related to photocatalysis. Attributed to surface-related heterogeneous reactions, the NO{sub x} binding occurs in unmodified CAC at nitrite-to-nitrate ratio of 1: 1.3 and can be increased with surface area. The photocatalytic reactions in TiO{sub 2}-modified CAC increase NO{sub x} uptake, and ~50% of converted NO{sub x} resists releasing back into the environment via dissolution. Compared to previously studied ordinary portland cement (OPC) materials, CAC increases NO{sub x} uptake capacity and demonstrates a more permanent NO{sub x} binding, potentially mitigating concerns related to the release of previously bound N-species in OPC. Examination of the interaction between NO{sub x} and a synthetic pure aluminum-bearing phase shows that the permanent NO{sub x} uptake in CAC could be largely attributed to the chemical binding of converted NO{sub x} within aluminum-bearing phases.

36 MATERIALS SCIENCE↗

Corrosion integrity of oil cement modified by environment responsive microspheres for CO2 geologic sequestration wells

In order to ensure the safe and effectiveness of CO{sub 2} geological storage, an environmental responsive polymer microspheres (ERPM) was prepared to improve the corrosion resistance of cement stone. The structure and environmental response characteristics of ERPM were characterized, and then the anti-corrosion performance and anti-corrosion mechanism for ERPM were discussed. The results shown that ERPM had good environmental response characteristics and temperature resistance. ERPM could effectively suppressed the corrosion rate and the damage degree of mechanical properties of cement stone. The corrosion integrity of cement stone was improved due to the acidic response characteristic and form polymer films of ERPM, which effectively shield the direct contact between corrosion medium and hydration products.

36 MATERIALS SCIENCE↗

Sequestration and release of nitrite and nitrate in alkali-activated slag: A route toward smart corrosion control

Intercalating the corrosion inhibitive ions in hydrotalcite is a promising approach to improve the long-term efficiency of inhibitors in corrosion protection of steel in reinforced concrete. In this work, the potential of autogenously generating nitrite- and nitrate-intercalated hydrotalcite in alkali-activated slag (AAS) is investigated. The results show that the added nitrite and nitrate ions are preferably uptaken in the interlayer structure of hydrotalcite in AAS, and the sequestered nitrite and nitrate are released upon chloride exposure in seawater and NaCl solution. The incorporation of nitrite and nitrate has little detrimental effects on the chloride binding capacity of AAS but slightly enhances the chloride ingress due to the pore coarsening effect. Similar to ordinary Portland cement (OPC), AAS is more permeable to the chloride in seawater than NaCl solution. However, unlike the release of bound chloride contributed by ettringite formation in seawater-exposed OPC, the enhanced chloride ingress in seawater-exposed AAS is primarily attributed to the aggravated pH reduction at the exposure front due to brucite formation. This study contributes to the design of alkali-activated binders with a smart inhibitor releasing ability for mitigating corrosion of steel in concrete.

36 MATERIALS SCIENCE↗

Normal or abnormal? Machine learning for the leakage detection in carbon sequestration projects using pressure field data

The international commitments for atmospheric carbon reduction will require a rapid increase in carbon capture and storage (CCS) projects. The key to any successful CCS project lies in the long term storage and prevention of leakage of stored carbon dioxide (CO 2 ). In addition to being a greenhouse gas, CO 2 leaks reaching the surface can accumulate in low-lying areas resulting in a serious health risk. Among several alternatives, some of the more promising CCS storage formations are depleted oil and gas reservoirs, where the reservoirs had good geological seals prior to hydrocarbon extraction. With more CCS wells coming online, it is imperative to implement permanent, automated monitoring tools. We apply machine learning models to automate the leakage detection process in carbon storage reservoirs using rates of (CO 2 ) injection and pressure data measured by simple harmonic pulse testing (HPT). To validate the feasibility of this machine learning based workflow, we use data from HPT experiments carried out in the Cranfield oil field, Mississippi, USA. The data consist of a series of pulse tests conducted with baseline parameters and with an artificially introduced leak. Here, in this study, we pose the leakage detection task as an anomaly detection problem where deviation from the predicted behavior indicates leaks in the reservoir. Results show that different machine learning architectures such as multi-layer feed forward network, Long Short-Term Memory, and convolutional neural network are able to identify leakages and can provide early warning. These warnings can then be used to take remedial measures.

58 GEOSCIENCES↗