Concept: Radioactive waste
Here we show the efficacy of graphene oxide (GO) for rapid removal of some of the most toxic and radioactive long-lived human-made radionuclides from contaminated water, even from acidic solutions (pH < 2). The interaction of GO with actinides including Am(iii), Th(iv), Pu(iv), Np(v), U(vi) and typical fission products Sr(ii), Eu(iii) and Tc(vii) were studied, along with their sorption kinetics. Cation/GO coagulation occurs with the formation of nanoparticle aggregates of GO sheets, facilitating their removal. GO is far more effective in removal of transuranium elements from simulated nuclear waste solutions than other routinely used sorbents such as bentonite clays and activated carbon. These results point toward a simple methodology to mollify the severity of nuclear waste contamination, thereby leading to effective measures for environmental remediation.
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 CH3I 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.
Microbial fuel cells (MFCs) generate electricity from waste but to date the technology’s development and scale-up has been held-up by the need to incorporate expensive materials. A costly but vital component is the ion exchange membrane (IEM) which conducts protons between the anode and cathode electrodes. The current study compares natural rubber as an alternative material to two commercially available IEMs. Initially, the material proved impermeable to protons, but gradually a working voltage was generated that improved with time. After 6 months, MFCs with natural rubber membrane outperformed those with anion exchange membrane (AEM) but cation exchange membrane (CEM) produced 109 % higher power and 16 % higher current. After 11 months, polarisation experiments showed a decline in performance for both commercially available membranes while natural rubber continued to improve and generated 12 % higher power and 54 % higher current than CEM MFC. Scanning electron microscope images revealed distinct structural changes and the formation of micropores in natural latex samples that had been employed as IEM for 9 months. It is proposed that the channels and micropores formed as a result of biodegradation were providing pathways for proton transfer, reflected by the steady increase in power generation over time. These improvements may also be aided by the establishment of biofilms that, in contrast, caused declining performance in the CEM. The research demonstrates for the first time that the biodegradation of a ubiquitous waste material operating as IEM can benefit MFC performance while also improving the reactor’s lifetime compared to commercially available membranes.
There is interest in identifying novel materials for use in radioactive waste applications and studying their behavior under high pressure conditions. The mineral zirconolite (CaZrTi(2)O(7)) exists naturally in trace amounts in diamond-bearing deep-seated metamorphic/igneous environments, and it is also identified as a potential ceramic phase for radionuclide sequestration. However, it has been shown to undergo radiation-induced metamictization resulting in amorphous forms. In this study we probed the high pressure structural properties of this pyrochlore-like structure to study its phase transformations and possible amorphization behavior. Combined synchrotron X-ray diffraction and Raman spectroscopy studies reveal a series of high pressure phase transformations. Starting from the ambient pressure monoclinic structure, an intermediate phase with P2(1)/m symmetry is produced above 15.6 GPa via a first order transformation resulting in a wide coexistence range. Upon compression to above 56 GPa a disordered metastable phase III with a cotunnite-related structure appears that is recoverable to ambient conditions. We examine the similarity between the zirconolite behavior and the structural evolution of analogous pyrochlore systems under pressure.
The safe disposal of liquid wastes associated with oil and gas production in the United States is a major challenge given their large volumes and typically high levels of contaminants. In Pennsylvania, oil and gas wastewater is sometimes treated at brine treatment facilities and discharged to local streams. This study examined the water quality and isotopic compositions of discharged effluents, surface waters, and stream sediments associated with a treatment facility site in western Pennsylvania. The elevated levels of chloride and bromide, combined with the strontium, radium, oxygen, and hydrogen isotopic compositions of the effluents reflect the composition of Marcellus Shale produced waters. The discharge of the effluent from the treatment facility increased downstream concentrations of chloride and bromide above background levels. Barium and radium were substantially (>90%) reduced in the treated effluents compared to concentrations in Marcellus Shale produced waters. Nonetheless, (226)Ra levels in stream sediments (544-8759 Bq/kg) at the point of discharge were ∼200 times greater than upstream and background sediments (22-44 Bq/kg) and above radioactive waste disposal threshold regulations, posing potential environmental risks of radium bioaccumulation in localized areas of shale gas wastewater disposal.
Industrial development, energy production and mining have led to dramatically increased levels of environmental pollutants such as heavy metal ions, metal cyanides and nuclear waste. Current technologies for purifying contaminated waters are typically expensive and ion specific, and there is therefore a significant need for new approaches. Here, we report inexpensive hybrid membranes made from protein amyloid fibrils and activated porous carbon that can be used to remove heavy metal ions and radioactive waste from water. During filtration, the concentration of heavy metal ions drops by three to five orders of magnitude per passage and the process can be repeated numerous times. Notably, their efficiency remains unaltered when filtering several ions simultaneously. The performance of the membrane is enabled by the ability of the amyloids to selectively absorb heavy metal pollutants from solutions. We also show that our membranes can be used to recycle valuable heavy metal contaminants by thermally reducing ions trapped in saturated membranes, leading to the creation of elemental metal nanoparticles and films.
Nuclear energy is among the most viable alternatives to our current fossil fuel-based energy economy. The mass deployment of nuclear energy as a low-emissions source requires the reprocessing of used nuclear fuel to recover fissile materials and mitigate radioactive waste. A major concern with reprocessing used nuclear fuel is the release of volatile radionuclides such as xenon and krypton that evolve into reprocessing facility off-gas in parts per million concentrations. The existing technology to remove these radioactive noble gases is a costly cryogenic distillation; alternatively, porous materials such as metal-organic frameworks have demonstrated the ability to selectively adsorb xenon and krypton at ambient conditions. Here we carry out a high-throughput computational screening of large databases of metal-organic frameworks and identify SBMOF-1 as the most selective for xenon. We affirm this prediction and report that SBMOF-1 exhibits by far the highest reported xenon adsorption capacity and a remarkable Xe/Kr selectivity under conditions pertinent to nuclear fuel reprocessing.
There has been leakage of radioactive materials from the Fukushima Daiichi Nuclear Power Plant. A heavily contaminated area (≥ ¹³⁴,¹³⁷Cs 1000 kBq m⁻²) has been identified in the area northwest of the plant. The majority of the land in the contaminated area is forest. Here we report the amounts of biomass, litter (small organic matter on the surface of the soil), coarse woody litter, and soil in the contaminated forest area. The estimated overall volume and weight were 33 Mm³ (branches, leaves, litter, and coarse woody litter are not included) and 21 Tg (dry matter), respectively. Our results suggest that removing litter is an efficient method of decontamination. However, litter is being continuously decomposed, and contaminated leaves will continue to fall on the soil surface for several years; hence, the litter should be removed promptly but continuously before more radioactive elements are transferred into the soil.
The ecological effects of accidental or malicious radioactive contamination are insufficiently understood because of the hazards and difficulties associated with conducting studies in radioactively-polluted areas. Data sets from severely contaminated locations can therefore be small. Moreover, many potentially important factors, such as soil concentrations of toxic chemicals, pH, and temperature, can be correlated with radiation levels and with each other. In such situations, commonly-used statistical techniques like generalized linear models (GLMs) may not be able to provide useful information about how radiation and/or these other variables affect the outcome (e.g. abundance of the studied organisms). Ensemble machine learning methods such as random forests offer powerful alternatives. We propose that analysis of small radioecological data sets by GLMs and/or machine learning can be made more informative by using the following techniques: (1) adding synthetic noise variables to provide benchmarks for distinguishing the performances of valuable predictors from irrelevant ones; (2) adding noise directly to the predictors and/or to the outcome to test the robustness of analysis results against random data fluctuations; (3) adding artificial effects to selected predictors to test the sensitivity of the analysis methods in detecting predictor effects; (4) running a selected machine learning method multiple times (with different random-number seeds) to test the robustness of the detected “signal”; (5) using several machine learning methods to test the “signal’s” sensitivity to differences in analysis techniques. Here, we applied these approaches to simulated data, and to two published examples of small radioecological data sets: (I) counts of fungal taxa in samples of soil contaminated by the Chernobyl nuclear power plan accident (Ukraine), and (II) bacterial abundance in soil samples under a ruptured nuclear waste storage tank (USA). We show that the proposed techniques were advantageous compared with the methodology used in the original publications where the data sets were presented. Specifically, our approach identified a negative effect of radioactive contamination in data set I, and suggested that in data set II stable chromium could have been a stronger limiting factor for bacterial abundance than the radionuclides 137Cs and 99Tc. This new information, which was extracted from these data sets using the proposed techniques, can potentially enhance the design of radioactive waste bioremediation.
Nuclear waste cleanup is challenged by the handling of feed stocks that are both unknown and complex. Plasma filtering, operating on dissociated elements, offers advantages over chemical methods in processing such wastes. The costs incurred by plasma mass filtering for nuclear waste pretreatment, before ultimate disposal, are similar to those for chemical pretreatment. However, significant savings might be achieved in minimizing the waste mass. This advantage may be realized over a large range of chemical waste compositions, thereby addressing the heterogeneity of legacy nuclear waste.