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This presentation touches on ENDF/B-VIII.1 Validation: Covariance. Topics include inconsistencies in the ENDF files, derived matrices, lumped reactions and process ENDF data file with PUFF. Finally correcting data with cognac and redundant covariance that are not consistent are discussed.
This dataset contains data from a manipulative field study aimed at identifying critical thresholds for acute response of plants and ecosystems to water stress (TARP) that took place at Walker Branch Watershed in Oak Ridge, Tennessee from 2002-2005 (2002-06-20 to 2005-12-16). The study used understory tents for the removal of 100% of the growing-season throughfall and stem flow, to provide data on the impact of acute drought on mechanisms responsible for growth and mortality of deciduous forest canopy trees representative of common plant functional types (Liriodendron and Quercus). Through three years of manipulation (2003, 2004 and 2005; pretreatment measurements in 2002) various measures of tree response to surface moisture deficits were recorded including root and leaf traits, plant nonstructural carbohydrates status, hourly sapflow, basal area, and periodic observations of foliar photosynthesis and conductance. Additionally, environmental data such as air and soil temperature, soil water content, and soil matric potential were recorded. This dataset contains data 16 files in comma-separate (*.csv) format. Additional metadata are provided: 16 data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.
The treatment of aqueous solution waste containing organic compounds and radionuclides has always been a great concern since the processes available are usually expensive and unfeasible for the low volume of radioactive liquid waste recovered. In view of a more efficient and low cost treatment, biosorption-based technologies for the removal of this hazardous radionuclides, heavy metals, and organic substances from contaminated matrices have been studied as an alternative process. In this context, bone meal is the material of choice, and contains calcium phosphate in the form of hydroxyapatite. Previous studies with hydroxyapatite showed that this material is efficient in removing heavy metals from polluted soils due to its adsorbing ability. In this context, uranium biosorption capacity by using bone meal was evaluated by different experimental conditions. This study aims at analyzing the capacity of bone meal to remove uranium from aqueous solution through biosorption process, considering that this nuclide is radiotoxic and may cause serious environmental problems and risks to human life if not correctly disposed. The biosorption capacity of U by bone meal was evaluated under different experimental conditions. The results suggested that adsorption with this material can be applied in the treatment of aqueous solutions as a low-cost and highly efficient alternative to remove U. Therefore, we believe that our results are useful for other investigators dealing with similar problems. Further work is required to evaluate this material as a potential adsorbent concerning the treatment of liquid organic radioactive waste containing uranium. Next studies are crucial to ascertain the biosorption efficiency, by analyzing other variables, such as adsorbent dosage, pH and temperature.
Decommissioning and dismantling of nuclear facilities are major challenges facing the nuclear industry. Robot manipulators with capabilities of restoring nuclear structures and significantly prolonging nuclear power generation in addition to their applications in decommissioning and dismantling (D and D) would immensely ease the above-mentioned challenge. Ability to remotely sense/monitor and analyze dangerous and hazardous environments such as nuclear reactors as well as performing reparatory tasks in such environments using robot manipulators require additional information from vision sensors. Structural sample collection and inspection as well as restoration require object and position information. Computer vision is used to obtain precise 3D position information. The current work uses the Sawyer robot with the integrated Cognex camera. The research presents an approach to facilitate and improve operations in a nuclear reactor using robotic vision control. The vision control system is modeled with Augmented Image Space-based visual servoing approach. Results showing accurate robot control. Object recognition is used to recognize the image and calculate it poses. To transform coordinates of the object's pose from the camera frame to the robotic frame transformation matrices are employed. Future work will employ a 3D camera (with depth information) using Denso robot. (authors)
The concentration of key mercury species in the Hanford tank waste has not been previously measured. Based on process knowledge, an estimated inventory of 2,100 kg of mercury is assumed and was distributed in varied amounts across 149 single-shell tanks (SSTs) and 28 double-shell tanks (DSTs). Limited analyses of individual SSTs and DSTs for total mercury were all below detection, yielding upper limits in concentration estimates based solely on instrument detection limits, resulting in an uncertain mercury inventory for Hanford tanks. Accurate and reliable chemical speciation and quantification is desired to anticipate, predict, and abate the mass movements of various mercury species through the Hanford waste processing flowsheet. Highly sensitive separation and quantification methods for total, elemental, and monomethyl mercury species, in tank waste, have been developed at the Pacific Northwest National Laboratory's (PNNL) Radiochemical Processing Laboratory (RPL). A non-radiological environmental method to quantify mercury species has been adapted for application to Hanford tank 241-AP-107 raw supernatant feed, filtered feed, and cesium-decontaminated samples. These samples represent feed inventory and pretreatment process effluents prior to immobilization by vitrification. This method separates and preconcentrates total, elemental, and monomethyl mercury onto selective solid substrates with little-to-no radioactive background. The solid samples can then be released from strict radiological control, allowing for analytical work to be conducted in low-level radiological facilities. Separation of mercury species was demonstrated at PNNL's RPL in Richland, Washington before transport and analytical quantification using cold vapor atomic fluorescence spectrometry (CVAFS) at PNNL's Marine Science Laboratory (MSL) in Sequim, Washington. Additional studies were conducted to assess the stability of monomethyl mercury in distilled matrices and preconcentrated onto the Carbotrap{sup R} solid substrate to assess sample degradation over time during transport. (authors)
The growing global concerns about the effects to public health from human exposure to per- and polyfluoroalkyl substances (PFAS) motivates the development of strategies for reliable monitoring of PFAS in environmental streams, as well as for their rapid, effective removal if detected. For the continuous PFAS monitoring, an inexpensive, field-deployable, in situ sensor is urgently needed; yet the prevalent in situ techniques often struggle to strike a balance between the practical sensitivity and selectivity demands of the real world. Similarly, for effective PFAS removal, strategies for their fast, selective, and quantitative capture are desired, yet the present commercially available sorbents are unable to meet the requirements of rapid, quantitative capture of all PFAS components, and are notably inefficient in removing the more toxic smaller chains. To address these twin challenges, Pacific Northwest National Laboratory is developing strategies for improved detection and remediation of PFAS. For the rapid, selective, quantitative removal of PFAS from environmental streams, the strategy relies on designing capture probes with exclusively tailored electronic and spatial affinities for the PFAS that are able to selectively capture them from environmental streams. For the in situ detection and quantification of PFAS in complex, multicomponent matrices such as groundwater, the approach relies on the targeted capture of specific PFAS by these PFAS-specific capture probes immobilized on a platform. The platform acts as an electrode to directly measure PFAS concentration through a proportional change in electrical response upon their capture. A combination of optimization of platform design and incorporation of additional, sensitive detection modalities have allowed us to achieve detection limits as low as 0.5 ng/L for detection of PFAS compounds (compared to the 70 ng/L Health Advisory Limit of the U.S. Environmental Protection Agency). (authors)
A commonly applied method for the non-destructive characterization of the radioactive inventory of waste packages (e.g. 200-l drums) is segmented gamma-scanning. The gamma-emitting inventory is identified via their characteristic lines in the measured spectra. The corresponding net peak areas allow for quantification applying appropriate models. The identification and quantification of beta-emitters present in the waste package require further evaluation. While some of them emit gamma-rays, too, which can be used for identification and quantification, pure beta-emitters contribute to the gamma-spectra only by their Bremsstrahlung-spectra. {sup 32}P, {sup 90}Sr and {sup 90}Y are typical representatives of these isotopes. A method is developed for identification and quantification of these pure beta-emitters in radioactive waste packages. Origin of the procedure is the evaluation of the measured gamma-spectrum. After the identification of all lines present in the spectrum (characteristic gamma-lines, single- and double-escape-lines, X-ray-lines, annihilation peak etc.) this information is used together with calibration data of the detection system and further a-priori information like matrix composition, cross-section data from databases etc. to simulate the spectra without the Bremsstrahlung-components by an appropriate method. This may be Monte Carlo simulations or, like in our case, a computer code taking into account mathematical descriptions of the physical effects like photo effect, (multiple) Compton scattering, backscattering etc. and the attenuation effects of the waste matrix. In any case, the resulting spectrum must simulate the real spectrum without its Bremsstrahlung-component as good as possible. Subtracting the simulated from the measured spectrum then results in the Bremsstrahlung-components caused by the beta-emitters. Prior to evaluation, a set of Bremsstrahlung-spectra is calculated and stored for different beta-emitters in different matrices using the Bethe-Heitler equation. This data set can be extended for new conditions, if necessary, and is allocated in a data base for future application. Applying a non-linear optimization using the generalized reduced gradient method for comparing the calculated with the derived Bremsstrahlung-spectra results in the identification of the beta-emitter and a factor, which is proportional to its activity. The proportionality is determined by previous calibration measurements. The application of the method is demonstrated by measurements on a 200-l mock-up drum and a real waste package. (authors)
High-level radioactive waste (HLW) consists of fission products and minor actinides. Borosilicate glass is the host material of choice in most countries to safely immobilize HLW, followed by eventual geological disposal. HLW glasses will experience both self-heating and self-irradiation effects due to the decay of fission products and minor actinides present therein. During the first 500 years of geological disposal, beta-gamma decay will be the main source of radiation due to short half-lives of fission products, as compared to very long-lived actinides which will be responsible for irradiation over much longer timescales. High-energy alpha particles and alpha recoil nuclei can potentially have significant impact (stored energy, volume change, accumulated dose, chemical durability) on the performance of the wasteform over longer timescales. Thus, to ensure safe and economic disposal over geological periods (10{sup 4} - 10{sup 6} years), the assessment of performance and properties in terms of radiation effects becomes indispensable. This work aims to simulate the effects of alpha decay in radioactive waste glasses. Two international glasses, namely UK 'MW' lithium-sodium borosilicate and Indian sodium-barium borosilicate, which are being used as HLW immobilization matrices by the UK and India respectively, were prepared by a melt-quench method and annealed below their glass transition temperatures. Both glasses were irradiated with 650 KeV He{sup 2+} ions with doses ranging from 10{sup 15} to 10{sup 17} ions/cm{sup 2}. Structural analysis was carried out using electron paramagnetic resonance (EPR) and Raman spectroscopies. First derivative continuous wave EPR spectra were recorded for all pristine and irradiated glass monoliths at room temperature using an X-band (frequency 9.6 GHz) EPR Bruker spectrometer. Results from EPR analyses showed the formation of irradiation induced paramagnetic centers at g ∼ 2.00 in all irradiated glasses. Raman spectra of pristine and irradiated samples were acquired, and showed notable changes in glass structure post-irradiation, with the emergence of a broad Raman band at 1560 cm{sup -1} upon irradiation with high fluences. (authors)
Abstract Shape‐persistent, conductive ionogels where both mechanical strength and ionic conductivity are enhanced are developed using multiphase materials composed of cellulose nanocrystals and hyperbranched polymeric ionic liquids (PILs) as a mechanically strong supporting network matrix for ionic liquids with an interrupted ion‐conducting pathway. The integration of needlelike nanocrystals and PIL promotes the formation of multiple hydrogen bonding and electrostatic ionic interaction capacitance, resulting in the formation of interconnected networks capable of confining a high amount of ionic liquid (≈95 wt%) without losing its self‐sustained shape. The resulting nanoporous and robust ionogels possess outstanding mechanical strength with a high compressive elastic modulus (≈5.6 MPa), comparable to that of tough, rubbery materials. Surprisingly, these rigid materials preserve the high ionic conductivity of original ionic liquids (≈7.8 mS cm −1 ), which are distributed within and supported by the nanocrystal network‐like rigid frame. On the one hand, such stable materials possess superior ionic conductivities in comparison to traditional solid electrolytes; on the other hand, the high compression resistance and shape‐persistence allow for easy handling in comparison to traditional fluidic electrolytes. The synergistic enhancement in ion transport and solid‐like mechanical properties afforded by these ionogel materials make them intriguing candidates for sustainable electrodeless energy storage and harvesting matrices.
Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.
Hydrophobic active pharmaceutical ingredients (APIs) are ubiquitous in the drug development pipeline, but their poor bioavailability often prevents their translation into drug products. Industrial processes to formulate hydrophobic APIs are expensive, difficult to optimize, and not flexible enough to incorporate customizable drug release profiles into drug products. Here, a novel, dual-responsive gelation process that exploits orthogonal thermo-responsive and ion-responsive gelations is introduced. This one-step “dual gelation” synthesizes core–shell (methylcellulose-alginate) hydrogel particles and encapsulates drug-laden nanoemulsions in the hydrogel matrices. In situ crystallization templates drug nanocrystals inside the polymeric core, while a kinetically stable amorphous solid dispersion is templated in the shell. Drug release is explored as a function of particle geometry, and programmable release is demonstrated for various therapeutic applications including delayed pulsatile release and sequential release of a model fixed-dose combination drug product of ibuprofen and fenofibrate. Independent control over drug loading between the shell and the core is demonstrated. This formulation approach is shown to be a flexible process to develop drug products with biocompatible materials, facile synthesis, and precise drug release performance. This work suggests and applies a novel method to leverage orthogonal gel chemistries to generate functional core–shell hydrogel particles.
Abstract Ionogel electrolytes based on ionic liquids and gelling matrices offer several advantages for solid‐state lithium‐ion batteries, including nonflammability, wide processing compatibility, and favorable electrochemical and thermal properties. However, the absence of ionic liquids that are concurrently stable at low and high potentials constrains the electrochemical windows of ionogel electrolytes and thus their high‐energy‐density applications. Here, ionogel electrolytes with a layered heterostructure are introduced, combining high‐potential (anodic stability: >5 V vs Li/Li + ) and low‐potential (cathodic stability: <0 V vs Li/Li + ) imidazolium ionic liquids in a hexagonal boron nitride nanoplatelet matrix. These layered heterostructure ionogel electrolytes lead to extended electrochemical windows, while preserving high ionic conductivity (>1 mS cm −1 at room temperature). Using the layered heterostructure ionogel electrolytes, full‐cell solid‐state lithium‐ion batteries with a nickel manganese cobalt oxide cathode and a graphite anode are demonstrated, exhibiting voltages that are unachievable with either the high‐potential or low‐potential ionic liquid alone. Compared to ionogel electrolytes based on mixed ionic liquids, the layered heterostructure ionogel electrolytes enable higher stability operation of full‐cell lithium‐ion batteries, resulting in significantly enhanced cycling performance.
Industrial separation processes account for 10-15% of global energy consumption. Membrane-based processes are less energy-intensive than traditional gas separation technologies; however, enhanced material separation performance and stability for numerous gas mixtures are needed for widespread industrial adoption. This work presents a generalizable strategy for preparing mixed-matrix gas separation membranes exceeding the performance upper bounds of existing polymer membranes for a wide variety of industrial gases. By incorporating robust porous aromatic framework (PAF) particles into various dense commercial polymer matrices, gas diffusivity and solubility can be enhanced. For diverse gas mixtures (e.g., CO2/N2, O2/N2, He/CH4, H2/N2, and C2H4/C2H6), the resulting composite membranes exhibit enhanced gas permeabilities-by as much as 520%-and largely unchanged selectivities even after 6 years of aging under simulated flue gas conditions. These improvements arise from the ultrahigh porosity, excellent chemical compatibility, and unique physicochemical properties of the embedded PAF particles. Functionalizing the PAFs with polyamines also enables composite membranes that achieve among the highest reported performances against plasticization, a common obstacle in commercializing gas separation membranes. Significantly, the PAF-1 particles are readily dispersible in various common membrane casting solvents, suggesting their broader utility as a filler for designing high-performance membranes for many industrial gas separations.
In this study, a robust biocatalytic yarn with controllable liquid transport properties is created by coating thin layers of chitosan containing catalase onto a cellulosic yarn. The resulting material integrates enzyme catalytic functionality with protective coating properties of chitosan and structural functionality of the textile. Mild immobilization conditions and good affinity between the two polysaccharides minimize enzyme inactivation during the preparation steps and prevent enzyme from leaching during peroxide decomposition testing and washing, providing a novel and versatile enzyme immobilization strategy. The catalytic efficiency of enzymes in a reaction containing solid, liquid, and gas phases is facilitated when dissolved enzyme substrate is transported by liquid flowing through the coated textile structure. The flow-through configuration decomposes at least two times more peroxide in a twenty-times smaller reaction zone volume compared to a stirred tank configuration. Liquid transport through the yarn and liquid spatial distribution within the yarn are investigated by in situ neutron radiography and neutron computed tomography, revealing a constrained wicking mechanism that benefits biocatalytic yarn performance. This new class of sustainable and flexible biocatalytic textile matrices has beneficial multifunctional properties, not previously described, that are applicable for numerous small- and large-scale applications including controlled flow reactors and reactive filtration.
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Multi-principal-element alloys like high-entropy alloys (HEAs) have potential applications in many engineering fields due to their unique mechanical/functional properties. While HEAs are generally considered random solid solutions, recent studies revealed that they are prone to short-range-ordering (SRO) due to the complex multi-pair-wise interactions among the constituent elements. Meanwhile, SROs' evolution can sometimes be deleterious, and it is necessary to have control over their evolution. Examining the AlCoCrFe-Zr model alloy, long-range ordering occurs following the expectation of enthalpic predictions. Advanced characterization techniques—transmission electron microscopy, high-energy synchrotron X-ray diffraction/pair distribution function, and atom probe tomography, reveal that SRO is suppressed in as-milled and GB-decorated NC-(AlCoCrFe)100-xZrx (x = 0–1.5 atomic %). Warren-Cowley coefficient calculations are further used to validate the suppression of SRO. Besides the low segregation enthalpies of Cr, Fe, and Zr, and the high-mixing enthalpy of Cr and Fe, the short diffusion path to GBs due to high-GB density in the NC-HEAs and the higher energy state of the GBs than the matrix promotes GB-segregation that further alters the matrix chemistry and consequently disfavors SRO formation within the matrix. Despite the GB-segregation of Cr, Fe, and Zr, the matrices and GBs remain in a random solid solution.