Plasma Separation Process Feasibility Study for Commercial Enrichment of Gadolinium-157
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A method for recycling lithium-ion battery materials is provided. The method includes isolating a composite electrode comprising an electrode material adhered to a current collector with a polyvinylidene difluoride (PVDF) binder. The composite electrode is combined with triethyl phosphate (TEP) as a solvent to form a mixture. The electrode material is delaminated from the current collector in the mixture to give a free electrode material and a free current collector. Each of the free electrode material and the free current collector is recovered from the mixture. The free electrode material may be reused to prepare another composite electrode, as well as a lithium-ion battery comprising the same, which are also disclosed.
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During High Temperature Gas-cooled Reactor (HTGR) operation, tristructural isotropic (TRISO) coated-particle fuel undergoes irradiation-induced changes in morphology and thermomechanical properties. Experimental results from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program show, among other things, the mechanism of gap formation between the buffer and inner pyrolytic carbon (IPyC) layers, which could be explored further via computational simulations using the Bison code. Two simulation models were developed, the debonding restricted model, where no gap formation between buffer and IPyC layers is permitted, and the debonding enabled model, where the gap between those layers is created. The inputs of the simulated models are based on the irradiation conditions from the AGR-1 experiment. The research included simulations on spherical and aspherical fuel types. Under the specific temperatures and fluences of the AGR-1 irradiation experiment, and the Bison simulations, it was concluded that the most common scenario is a gap formation along the buffer-IPyC interface, while the least possible scenario is the situation where there is no gap formation at the buffer-IPyC junction. The computational results confirmed that the sphericity of the fuel influences the thickness of the gap that occurs at the buffer-IPyC junction, in a way that with increasing aspect ratio the gap thickness increases. The results obtained for spherical and aspherical fuel are nearly identical. Finally, performed simulations match conclusions observed from the AGR-1 experiment, which as such shows that the Bison code is a good computational method for simulating the TRISO fuel. Future simulations will include the validation of performed research and comparison of the results between Bison and PARFUME codes.
Separation technologies currently used in U.S. manufacturing industries are estimated to account for more than 20% of plant energy consumption. However, accurately determining the impact of new separation technology solutions can sometimes be difficult, especially when evaluating a slate of new candidate separation technologies, each of which has its own separation performance, energy demand, and capital cost. In these cases, a typical approach is to assess each new separation technology by collecting performance and cost information and then using that information to develop a techno-economic analysis to identify overall benefits. While this approach is thorough, it can be time consuming and can hinder reaching a critical understanding of the potential of a given separation challenge, especially when there is no known solution. To address these issues, we developed an assessment methodology, using industrial screening processes, that can be used to better understand the potential impacts of addressing a given separation challenge. This paper presents an overview of our separation challenge stream assessment methodology. The methodology involves defining an “ideal” separator and deriving the associated minimum separation energy. The “ideal” separator represents the most optimistic outlook of a given opportunity so the maximum impact from existing and not-yet-developed solutions can be assessed. Using established biorefinery models, we applied the methodology to 10 different separation challenge streams from two different biomass conversion platforms to identify the type of information that can be obtained. Three of the ten challenge streams assessed had maximum possible cost savings predictions >20%, and associated reductions in process energy carbon intensity ranging from 0 to 54%. Two streams had cost and energy savings potential that were < 5%. Some of the opportunity drivers from the various assessments include higher product yields, reduction or elimination of downstream equipment, new co-products, and cost savings associated with raw materials and energy consumption. The information from these assessments can help guide the selection or development of new separation technology solutions based on the various potential factors that drive the projected benefits.
Process intensification aims to combine multiple tasks within multi-functional units to drastically improve economic, energy or sustainability metrics of a chemical process. Limited work exists to systematically identify the synergistic domains where intensification outperforms its nonintensified counterpart. In this work, we computationally derive the synergistic domains of a reactive separation system. Specifically, we first postulate general models for both intensified and nonintensified systems. We use these models to generate data to train a ReLU-type artifical neural network (ANN). Further, the trained ReLU-NN model is formulated as a multi-parametric mixed-integer linear program (mp-MILP), and the critical regions of this mp-MILP define the synergistic feasible domains of intensification. We have derived these synergistic domains of vapor–liquid equilibrium (VLE)-based reactive separation for several industrial applications. These synergistic domains enable quick screening of properties that favor intensification.
Naturally occurring Li consists of two stable isotopes, 6 Li with an abundance of about 7.5%, and 7 Li making up the remainder with 92.5%. The development of a 6 Li enrichment technique, in terms of technical reliability and environmental safety to reach 6 Li future requirements, represents a key step in the roadmap for nuclear fusion energy supply worldwide. This paper uses finite element analysis-based models to simulate electrochemical Li isotope separation, which is an attractive method in terms of simplicity, safety, and scalability. In the model, we quantitatively analyze how different electrochemical factors including thermodynamics, charge-transfer kinetics, and diffusivities affect the separation process (separation factor), together with cell parameters, such as cell length and current density. The maximum separation factor of 1.128 could be obtained with the cell under the optimal thermodynamic, kinetic, and diffusive conditions, which is among the highest separation factors ever reported. Furthermore, these results will assist in designing the actual isotope separation setup with large separation factor and appropriate timing for sample collection.
Environmental pollution, water scarcity, resource shortage, and fossil fuel reliance have all represented threats to a sustainable future. Separation processes play a pivotal role in improving sustainability in fields such as industrial processes, resource recycling, wastewater treatment, and water desalination, among others. Electrochemical systems have gained increased attention as effective separation platforms, not only in performance but also as a potentially energy-efficient approach. However, the reliance on non-renewable energy sources, such as fossil fuels, for electricity generation limits the advancement toward a fully sustainable separation process. Integration of separation processes with eco-friendly renewable energy sources can increase overall sustainability and decrease carbon footprint. Here, in this review, we provide an overview of electrochemical separations and recent efforts to integrate them with renewable energy sources such as heat and solar energy. We discuss electrochemical separations, including electrosorption and electrodialysis, and research to transition these processes to thermoelectrochemical (TEC) and photoelectrochemical (PEC) platforms. Finally, we discuss current challenges and future prospects in direct integration of renewable energy sources with separation processes.
Abstract The industrial Air Separations Unit (ASU) is a complicated and tightly operated process. The use of dynamic process analytics is also a key element of safe and economic operation of these processes, with increasing focus on predictive analytics to take preemptive actions. With the availability of real‐time data from hundreds of sensors, the data analysis process should also consider the topology of the data, as seen in sensor networks. In this paper, a novel tool is presented that considers the complex connectivity patterns in the sensor network and uses local adaptive disturbance estimations to predict global network‐scale trends. The paper introduces the emerging field of Graph Signal Processing (GSP) and presents a rigorous derivation of the tool starting from the extraction of the sensor‐network (in a graph theoretical sense) from the data. This network, which is in the form of a matrix, is then used to derive a Kalman‐filter type of state‐space model driven by input disturbances. Multiple disturbance models (e.g., step, ramp, periodic) are included to allow the model to have different kinds of disturbance propagation. Each graph node (representing the sensors used) dynamically adapts to the most recent detected disturbance individually. These estimated disturbances are propagated to the global network using the graph. Modifications to ensure stability are also discussed. The fidelity of the tool is tested on certain downtime events and the paper concludes by discussing the advantages of the method and planned future improvements.
Sustainable separation process development is crucial in promoting economic and environmental sustainability. Separation processes can be energy-intensive, and early-stage or emerging separation technologies can also be costly. For instance, separations in biomass-based fuels and chemicals production can account for up to 50% of the production cost, while industrial separations can consume up to 15% of the total energy used in the United States. Separations are essential to many industrial processes and play a crucial role in helping industry achieve several United Nations sustainable development goals (SDG), such as clean energy, responsible production, and climate change mitigation. Therefore, it is imperative to have a comprehensive discussion within the scientific community to identify innovative approaches for sustainable separation processes. This editorial highlights the key insights and research findings presented in this research topic titled "Future Perspectives on Separation Technologies."
This work provides a broad overview of the separation processes used to isolate actinides and the experimentally and computationally determined chemical characteristics that define those separations. The redox chemistry of the actinides plays a pivotal role in both aqueous and pyrochemical processing separations. The near-overlapping energies of the 6d and 5f orbitals in the light actinides allow for facile adjustment of actinide oxidation states, which is used in many established separation methods. In contrast, the stable, generally 3+ oxidation states of the mid- and heavy actinides can make it difficult to separate them from the similarly lanthanides(III). In aqueous separations, the tendency of the actinides to form anionic and neutral aqueous complexes with a variety of complexants (especially soft donors) is used to achieve high separation factors between chemically similar elements in both solid–liquid separations and liquid–liquid extraction. This selectivity can be further tuned through the use of specialized organic or solid-phase ligands. Pyroprocessing separations utilize the unique redox behavior of the actinides to adjust their distribution between a molten salt electrolyte and either a solid electrode or molten metal phase. Atomic-level insights into the mechanisms underlying actinide separation processes, with the ultimate goal of predicting separation behavior, can be provided by electronic structure and statistical mechanical-based calculation methods.
Rare-earth element separation processes often rely on a small decrease in ionic radii along the series of elements. Separation processes based on the distinct optical properties of REs remain less explored, although photochemical methods may offer a viable alternative. Accurate selection of the synthetic precursors of a photoswitchable acylhydrazonic ligand led to a system that could quantitatively isomerize (E−to−Z) upon irradiation with commercial LED lights. Coordination of the photoswitch with RE III nitrates (RE = La−Lu except Pm and Y) resulted in the retention of the photoswitching properties observed in solution. The lower binding affinity of the generated Z−isomer with RE III ions yielded the dissociation of the complexes upon irradiation (photodissociation) with the release of RE−nitrates in solution. The rate of the reaction was found to be dependent on the optical properties of the RE III ions, with nonemissive complexes (no 4f excited states) dissociating faster than emissive ones (having accessible 4f excited states). A thorough solid-state characterization of the complexes was performed by using crystallographic and photochemical methods. Ultimately, the accessibility of the 4f excited states of the metals following light irradiation and excitation of the ligand led to a decrease in the rate of the reaction due to quenching of the ligand excited state. These results demonstrate that the direct modulation of the metal coordination environment, combined with the metal-dependent reaction rate, could provide a strategy for the development of RE−separation processes based on differences in their optical properties.
Electrochemical separation processes are undergoing a renaissance as the range of applications continue to expand because they offer opportunities for increased energy efficiency and sustainability in comparison to conventional separation technology.
A novel sorbent-based separation process has been developed to selectively remove target molecules from the real fast pyrolysis (FP) pine bio-oils. Specifically, zeolitic molecular sieves and functionalized polymeric resins were found to effectively reduce carbonyl content and carboxylic acid number of a real pine fast pyrolysis bio-oils, therefore enhance bio-oil stability and preserve down-stream catalyst. Our results provide the first-time evidence on the potential effectiveness of sorption technology strategy for dealing with real FP bio-oils, reducing the carbonyl-rich FP oils from 7.5 mmolg-1 down to 4 mmolg-1 at 40 ?, which has potential to enable bio-oil stabilization and enhance operation stability for down-stream upgrading/hydrotreating processes.
Carbon capture has been an important topic of the twenty-first century because of the elevating carbon dioxide (CO2) levels in the atmosphere. CO2 in the atmosphere is above 420 parts per million (ppm) as of 2022, 70 ppm higher than 50 years ago. Carbon capture research and development has mostly been centered around higher concentration flue gas streams. For example, flue gas streams from steel and cement industries have been largely ignored due to lower associated CO2 concentrations and higher capture and processing costs. Capture technologies such as solvent-based, adsorption-based, cryogenic distillation, and pressure-swing adsorption are under research, but many suffer from higher costs and life cycle impacts. Membrane-based capture processes are considered cost-effective and environmentally friendly alternatives. Over the past three decades, our research group at Idaho National Laboratory has led the development of several polyphosphazene polymer chemistries and has demonstrated their selectivity for CO2 over nitrogen (N2). Poly[bis((2-methoxyethoxy)ethoxy)phosphazene] (MEEP) has shown the highest selectivity. A comprehensive life cycle assessment (LCA) was performed to determine the life cycle feasibility of the MEEP polymer material compared to other CO2-selective membranes and separation processes. The MEEP-based membrane processes emit at least 42% less equivalent CO2 than Pebax-based membrane processes. Similarly, MEEP-based membrane processes produce 34–72% less CO2 than conventional separation processes. In all studied categories, MEEP-based membranes report lower emissions than Pebax-based membranes and conventional separation processes.
Data reconciliation methods for separation processes typically rely on classical statistical approaches to generate estimates of true mass flow rates from measurements. Knowledge regarding the uncertainty of these estimates has value in decision making, but is often not acquired. Bayesian approaches intrinsically quantify uncertainty; however, literature for Bayesian data reconciliation of separation processes is scarce. This publication outlines two Bayesian data reconciliation models and provides details for how the models were implemented for the BayesMassBal (V 1.0.0) software package written in R. To demonstrate the advantages of this approach for data reconciliation, the models were first applied to simulated data and then compared to a classical model through a Monte Carlo experiment. In this example, the Bayesian models were found to provide more accurate estimates of the simulated data, while also providing quantitative information on the estimate uncertainty. To demonstrate the use of the technique in a practical problem, the models were also applied to real data collected from a pilot-scale rare earth solvent extraction process. Here, this publication provides a small window into how Bayesian methods can be used for data reconciliation, but findings suggest Bayesian data reconciliation models for separation processes have distinct advantages over classical alternatives.