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Partitioning of americium from lanthanides (Ln) present in used nuclear fuel plays a key role in the sustainable development of nuclear energy 1 – 3 . This task is extremely challenging because thermodynamically stable Am(III) and Ln(III) ions have nearly identical ionic radii and coordination chemistry. Oxidization of Am(III) to Am(VI) produces AmO 2 2+ ions distinct with Ln(III) ions, which has the potential to facilitate separations in principle. However, the rapid reduction of Am(VI) back to Am(III) by radiolysis products and organic reagents required for the traditional separation protocols including solvent and solid extractions hampers practical redox-based separations. Herein, we report a nanoscale polyoxometalate (POM) cluster with a vacancy site compatible with the selective coordination of hexavalent actinides ( 238 U, 237 Np, 242 Pu and 243 Am) over trivalent lanthanides in nitric acid media. To our knowledge, this cluster is the most stable Am(VI) species in aqueous media observed so far. Ultrafiltration-based separation of nanoscale Am(VI)-POM clusters from hydrated lanthanide ions by commercially available, fine-pored membranes enables the development of a once-through americium/lanthanide separation strategy that is highly efficient and rapid, does not involve any organic components and requires minimal energy input. A new strategy to separate radioactive americium from lanthanides based on complexation with polyoxometalates and ultrafiltration technique is highly efficient and rapid, does not involve any organic components and requires minimal energy input.

Effective capture of radioactive organic iodides from nuclear waste remains a significant challenge due to the drawbacks of current adsorbents such as low uptake capacity, high cost, and non-recyclability. We report here a general approach to overcome this challenge by creating radioactive organic iodide molecular traps through functionalization of metal-organic framework materials with tertiary amine-binding sites. The molecular trap exhibits a high CH 3 I saturation uptake capacity of 71 wt% at 150 °C, which is more than 340% higher than the industrial adsorbent Ag 0 @MOR under identical conditions. These functionalized metal-organic frameworks also serve as good adsorbents at low temperatures. Furthermore, the resulting adsorbent can be recycled multiple times without loss of capacity, making recyclability a reality. In combination with its chemical and thermal stability, high capture efficiency and low cost, the adsorbent demonstrates promise for industrial radioactive organic iodides capture from nuclear waste. The capture mechanism was investigated by experimental and theoretical methods. Capturing radioactive organic iodides from nuclear waste is important for safe nuclear energy usage, but remains a significant challenge. Here, Li and co-workers fabricate a stable metal–organic framework functionalized with tertiary amine groups that exhibits high capacities for radioactive organic iodides uptake.

Crystallization in glasses is usually considered to be a problem in the glass industry. However, controlled crystallization of glasses is an important prerequisite in the development of glass-ceramics with tailored useful properties. Similar boundary conditions apply when considering glass-ceramics for the immobilization of nuclear waste via vitrification. While uncontrolled crystallization in nuclear-waste glasses is problematic, chemically durable glass-ceramics with significantly high waste loadings can be produced with controlled crystallization of glasses. This article presents an overview of various aspects of nuclear-waste glasses where crystallization is either considered to be advantageous or problematic. The classification of glass-ceramic waste forms and strategies to design glass-ceramics for a given waste stream is discussed. Some open and relevant problems faced by researchers developing nuclear-waste glass-ceramics are also offered.

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.

Standard methods to assess the durability of vitrified radioactive waste were first developed in the 1980’s and, over the last 40 years, have evolved to yield a range of responses depending on experimental conditions and glass composition. Mechanistic understanding of glass dissolution has progressed in parallel, enhancing our interpretation of the data acquired. With the implementation of subsurface disposal for vitrified radioactive waste drawing closer, it is timely to review the available standard methodologies and reflect upon their relative advantages, limitations, and how the data obtained can be interpreted to support the post-closure safety case for radioactive waste disposal.

Portland cement-based grouts used for radioactive waste immobilisation contain a Ca- and Si-rich binder phase, known as calcium–silicate–hydrate (C–S–H). Depending on the blend of cement used, the Ca/Si ratio can vary considerably. A range of C–S–H minerals with Ca/Si ratios from 0.6 to 1.6 were synthesised and contacted with aqueous U(VI) at 0.5 mM and 10 mM concentrations. Solid-state 29 Si MAS-NMR spectroscopy was applied to probe the Si coordination environment in U(VI)-contacted C–S–H minerals and, in conjunction with U L III -edge X-ray absorption spectroscopy analysis, inferences of the fate of U(VI) in these systems were made. At moderate or high Ca/Si ratios, uranophane-type uranyl silicates or Ca-uranates dominated, while at the lowest Ca/Si ratios, the formation of a Ca-bearing uranyl silicate mineral, similar to haiweeite (Ca[(UO 2 ) 2 Si 5 O 12 (OH) 2 ]·3H 2 O) or Ca-bearing weeksite (Ca 2 (UO 2 ) 2 Si 6 O 15 ·10H 2 O) was identified. This study highlights the influence of Ca/Si ratio on uranyl sequestration, of interest in the development of post-closure safety models for U-bearing radioactive waste disposal.

The safety assessments of the geological storage of spent nuclear fuel require understanding the underground radionuclide mobility in case of a leakage from multi-barrier canisters. Uranium, the most common radionuclide in non-reprocessed spent nuclear fuels, is immobile in reduced form (U(IV) and highly mobile in an oxidized state (U(VI)). The latter form is considered one of the most dangerous environmental threats in the safety assessments of spent nuclear fuel repositories. The sorption of uranium to mineral surfaces surrounding the repository limits their mobility. We quantify uranium sorption using surface complexation models (SCMs). Unfortunately, numerical SCM solvers often encounter convergence problems due to the complex nature of convoluted equations and correlations between model parameters. This study explored two machine learning surrogates for the 2-pK Triple Layer Model of uranium retention by oxide surfaces if released as U(IV) in the oxidizing conditions: random forest regressor and deep neural networks. Our surrogate models, particularly DNN, accurately reproduce SCM model predictions at a fraction of the computational cost without any convergence issues. The safety assessment of spent fuel repositories, specifically the migration of leaked radioactive waste, will benefit from having ultrafast AI/ML surrogates for the computationally expensive sorption models that can be easily incorporated into larger-scale contaminant migration models. One such model is presented here.

Development of an effective monitoring method for spent nuclear fuel (SNF) in a dry storage cask (DSC) is important to meet the increasing demand for dry storage investigations. The DSC investigation should provide information about the quantity of stored SNF, and quality assurance of materials should be possible without opening the cask. However, traditional nondestructive examination (NDE) methods such as x-rays are difficult to deploy for DSC investigation because a typical DSC is intentionally designed to shield against radiation. To address this challenge, cosmic ray muons (CRMs) are used as an alternative NDE radiation probe because they can easily penetrate an entire DSC system; however, a wide application of muons is often hindered due to the naturally low CRM flux (~10 4 muons/m 2 /min). This paper introduces a newly proposed imaging algorithm, momentum-informed muon scattering tomography (MMST) , and presents how a limitation of the current muon scattering tomography technique has been addressed by measuring muon momentum. To demonstrate its functionality, a commercial DSC with 24 pressurized light water reactor fuel assemblies (FAs) and the MMST system were designed in GEANT4. Three noticeable improvements were observed for MMST system as a DSC investigation tool: (1) a signal stabilization, (2) an enhanced capability to differentiate various materials, and (3) statistically increased precision to identify and locate missing FAs. The results show that MMST improves the investigation accuracy from 79 to 98% when one FA is missing and 51% to 88% when one-half FA is missing. The advancement of the NDE technique using CRM for DSC verification is expected to resolve long-standing problems in increasing demand for DSC inspections and nuclear security.

Detecting helium leakage is important in many applications, such as in dry cask nuclear waste storage systems. This work develops a helium detection system based on the relative permittivity (dielectric constant) difference between air and helium. This difference changes the status of an electrostatic microelectromechanical system (MEMS) switch. The switch is a capacitive-based device and requires a very negligible amount of power. Exciting the switch’s electrical resonance enhances the MEMS switch sensitivity to detect low helium concentration. This work simulates two different MEMS switch configurations: a cantilever-based MEMS modeled as a single-degree-freedom model and a clamped-clamped beam MEMS molded using the COMSOL Multiphysics finite-element software. While both configurations demonstrate the switch’s simple operation concept, the clamped-clamped beam was selected for detailed parametric characterization due to its comprehensive modeling approach. The beam detects at least 5% helium concentration levels when excited at 3.8 MHz, near electrical resonance. The switch performance decreases at lower excitation frequencies or increases the circuit resistance. The MEMS sensor detection level was relatively immune to beam thickness and parasitic capacitance changes. However, higher parasitic capacitance increases the switch’s susceptibility to errors, fluctuations, and uncertainties.

In this study we present a replication method to determine surface roughness and to identify surface features when a sample cannot be directly analyzed by conventional techniques. As a demonstration, this method was applied to an unused spent nuclear fuel dry storage canister to determine variation across different surface features. In this study, an initial material down-selection was performed to determine the best molding agent and determined that non-modified Polytek PlatSil23-75 provided the most accurate representation of the surface while providing good usability. Other materials that were considered include Polygel Brush-On 35 polyurethane rubber (with and without Pol-ease 2300 release agent), Polytek PlatSil73-25 silicone rubber (with and without PlatThix thickening agent and Pol-ease 2300 release agent), and Express STD vinylpolysiloxane impression putty. The ability of PlatSil73-25 to create an accurate surface replica was evaluated by creating surface molds of several locations on surface roughness standards representing ISO grade surfaces N 3 , N 5 , N 7 , and N 8 . Overall, the molds were able to accurately reproduce the expected roughness average (R a ) values, but systematically over-estimated the peak-valley maximum roughness (R z ) values. Using a 3D printed sample cell, several locations across the stainless steel spent nuclear fuel canister were sampled to determine the surface roughness. These measurements provided information regarding variability in normal surface roughness across the canister as well as a detailed evaluation on specific surface features (e.g., welds, grind marks, etc.). The results of these measurements can support development of dry storage canister ageing management programs, as surface roughness is an important factor for surface dust deposition and accumulation. This method can be applied more broadly to different surfaces beyond stainless steel to provide rapid, accurate surface replications for analytical evaluation by profilometry.