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Energy-Efficient Capacitive Deionization through Electrode Modification and Process Development
Electrochemical separation technologies, such as capacitive deionization (CDI), are promising for addressing global energy and water challenges. However, there is a need to improve the performance, better understand property-performance relationships, and evaluate the longevity of CDI electrodes. This study explores the chemical modification of electrodes and the adjustment of CDI operating parameters. Results indicate that nitric acid (HNO3) conditioning of activated carbon cloth (ACC) electrodes removes metal oxides, introduces oxygen and nitrogen functionalities, and increases the specific capacitance (16% at 1 mV/s). Moreover, these changes in electrode properties positively impact device-level CDI performance. Through HNO3-conditioning of the ACC and tuning of the operational parameters, this work demonstrates higher electrosorption capacity (4.0x), greater charge efficiency (90% vs 24%), and lower energy consumption (3.8x). Despite these enhancements, limitations of the HNO 3 -conditioned ACC include decreased desorption kinetics and a 32% loss in electrosorption capacity after 200 cycles. Overall, this work provides guidance on using oxidative pretreatment via HNO 3 to modify ACC electrodes for CDI and evaluates the trade-offs associated with varying operational parameters.
Modeling Microwave-Enhanced Chemical Vapor Infiltration Process for Preventing Premature Pore Closure
The chemical vapor infiltration (CVI) process involves infiltrating a porous preform with reacting gases that undergo chemical transformation at high temperatures to deposit the ceramic phase within the pores, ultimately leading to a dense composite. The conventional CVI process in composite manufacturing needs to follow an isothermal approach to minimize temperature differences between the external and internal surfaces of the preform, ensuring that reactive gases infiltrate internal pores before external surfaces seal. Here, this study addresses the challenge of premature pore closure in CVI processes through microwave heating. A frequency-domain microwave solver is developed in OpenFOAM to investigate volumetric heating mechanisms within the preform. Through numerical studies, we demonstrate the capability of microwave heating of creating an inside-out temperature inversion. This inversion accelerates reactions proximal to the preform center, effectively mitigating the risk of premature external pore closure and ensuring uniform densification. The results reveal a significant enhancement in temperature inversion when high-permittivity reflectors are incorporated to generate resonant waves. This microwave heating strategy is then coupled with high-fidelity direct numerical simulation (DNS) of reacting flow, enabling the analysis of resulting densification processes. The DNS includes detailed chemistry and realistic diffusion coefficients. The numerical results can be used to estimate the impact of microwave-induced temperature inversion on densification in productions.
Revisiting the Terawatt Challenge
Richard E. Smalley, in 2003, defined the Terawatt (TW) Challenge as “Adapting our energy infrastructure to simultaneously address diminishing oil resources and rising levels of atmospheric CO 2 .” Smalley, best known for the discovery of C 60 , for which he received the 1996 Nobel Prize in Chemistry, continued to address the challenges of anthropomorphic and natural global energy flows until he passed away in 2005. Smalley challenged the world to transform the energy sector. He envisioned electricity transmitted by high-voltage direct current (DC) lines from massively deployed solar plants in sunny areas and remotely sited nuclear plants. He also envisioned using advanced batteries for local storage of energy. To meet the needs of ~10 people in a world with a dwindling oil supply, Smalley asserted that the world would need to transform its fossil-fuel-driven 14-TW (average power) energy used in 2003 to a largely renewable-energy-driven 30–60 TW (average power) in 2050. This would be possible only if solar-electricity costs could be drastically reduced. The challenges associated with this transition have been called the “Terawatt Challenge.” Fifteen years later, solar-module costs have been reduced by tenfold and annual deployment of solar photovoltaic (PV) modules has grown by a factor of 100,from ~1 gigawatt (GW) in 2004 to ~100 GW in 2018, with a total of 500 GW installed worldwide, producing 2% of the planet’s electricity. As global installed solar generating capacity approaches1 TW, we revisit Smalley’s TW challenge to identify what has changed and quantify the TW Challenge for a baseline scenario and for two scenarios designed as upper and lower bounds determined by the degree we implement electrification and storage. In this paper, we show that the energy choices we make today will dramatically affect the magnitude of future global energy requirements.
Dynamic Simulation Technoeconomic Model for Power Generation
Sandia National Laboratories has built and successfully tested a dynamic simulation technoeconomic model of the Palo Verde Generating Station that is now being updated to help other US power plants improve operations. Palo Verde, located west of Phoenix, Arizona, is the largest electricity generator in the US at 4 GW. Palo Verde uses — 60 million gallons per day of treated wastewater from Phoenix to cool reactors, and disposes of blowdown in evaporation ponds. The model built for Palo Verde numerically evaluates the economic impact of changing, for example, alternative cooling technologies, water usage and treatment, and influent water chemistry, and is based on detailed accounting of mass, energy, and cash flows.
Lignin-First Biorefinery Development
Cost-effective biomass fractionation is an enabling, grand challenge for biorefining, especially when both carbohydrates and lignin are targeted for valorization. The advent of Reductive Catalytic Fractionation (RCF) - an active stabilization approach that solubilizes lignin from biomass and catalytically depolymerizes it into a narrow slate of monomers and oligomers - represents a potential step forward for this important goal. In the Lignin-First Biorefinery Development project, we are employing techno-economic analysis (TEA) and life cycle assessment (LCA) to guide bench-scale R&D efforts towards cost-effective RCF-based biorefining. This project is critical to lignin valorization efforts and could enable the use of woody feedstocks in a traditional biochemical conversion context. To date, we have conducted the first rigorous TEA and LCA study of the RCF process, developed a flow-through system to separate biomass and the chemical catalyst in RCF chemistry, developed models for solvolysis chemistry and transport phenomena for poplar, and co-led an international, authoritative perspective on guidelines for the research community on how to best practice lignin-first biorefining. The primary challenges for the lignin-first RCF process going forward are catalyst stability, the need to utilize, recover, and recycle high boiling point solvents to lower RCF reactor pressure, and the challenge of operating RCF continuously - all of which are being directly tackled by this project.
Engineering scale molten salt corrosion and chemistry code development
A new engineering scale transport code Mole is described. Mole was developed using the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework for solving species transport problems in flowing liquid. It is applied to leaching of Cr from alloys into molten salts part a of a multi-physics, multi-scale approach for coupling chemistry with mechanical behavior modeling. Demonstrations of the leaching phenomenon were benchmarked to experimental data provided by the Molten Salt Reactor campaign and the results are presented.
Advancing a Watershed Hydro-Biogeochemical Theory: Linking Water Travel Time and Reaction Rates Under Changing Climate
The major goal of the project is to answer the question how and to what degree does a warming climate alter hydrological functioning and (biogeochemical and chemical weathering) reaction rates at the watershed scale? In particular, how does hydrological functioning (water storage, flow paths, and travel time) change responding to a warming climate? What are the corresponding alterations in biogeochemical and chemical weathering rates at the watershed scale? What is the general watershed-scale reaction rate law that causally links reaction rates to metrics of hydrological functioning that are determined by external hydroclimatic conditions and internal watershed structure characteristics? To answer these questions, we have used field measurements and reactive transport modeling. We have found that: 1) stream chemistry has altered tremendously in warmer years; 2) In this water-limited environment, hydrology is the dominant driver for soil respiration and carbon lateral export at the watershed scale; 3) deeper carbon respiration plays an essential role in regulating the patterns of stream carbon in low and high flow conditions, and deeper groundwater will become increasingly important as warming intensifies. This indicates in mountain streams, a warming climate will modify not only the timing and magnitude of streamflow as expected, but also the chemistry and quality of stream water.
Monitoring the long-term performance of organic redox flow battery by a distribution of relaxation time analysis
Organic redox flow batteries hold great promise as an energy storage technology, but their intricate chemistry makes them vulnerable to various degradation mechanisms. Monitoring this degradation is essential for identifying the limiting processes within the cells. Electrochemical impedance spectroscopy (EIS) offers a straightforward, in-situ method for measuring the total resistance of an operating cell. However, to pinpoint the limiting processes during long-term cycling, EIS data must be complemented by other techniques. Distribution of relaxation time (DRT) analysis is particularly effective for differentiating resistance components. Here, in this study, we perform a comprehensive analysis of resistance evolution and the separation of anode and cathode contributions during long-term cycling of a full cell employing 7,8-dihydroxyphenazine-2-sulfonic acid (DHPS) as the anolyte. Separate analyses of the DHPS anolyte and ferri-/ferrocyanide catholyte were conducted using a symmetric cell setup. The relaxation times derived from symmetric cells facilitate the identification of peaks in the DRT profiles from the full cell. Importantly, the DRT profiles indicate a correlation between the evolution of charge transfer resistance and the chemical degradation of DHPS. The methodologies and results outlined in this study offer significant insights for developing diagnostic tools applicable to other types of redox flow batteries.
A physics-constrained neural ordinary differential equations approach for robust learning of stiff chemical kinetics
The high computational cost associated with solving for detailed chemistry poses a significant challenge for predictive computational fluid dynamics (CFD) simulations of turbulent reacting flows. While deep learning techniques have been explored to develop faster surrogate models, they often fail to integrate reliably with CFD solvers. This instability arises because traditional deep learning approaches optimize for training error without ensuring compatibility with ordinary differential equation (ODE) solvers, resulting in accumulation of errors over time. Recently, neuralODE (NODE) based approaches have been shown to be a promising technique to emulate and accelerate detailed chemistry computations. Here, in the present work, we extend this NODE framework for stiff chemical kinetics by incorporating mass conservation constraints directly into the loss function during training. This ensures that the total mass as well as the individual elemental species masses are conserved in an a-posteriori manner. Proof-of-concept studies are performed with the novel physics-constrained NODE (PC-NODE) approach for homogeneous autoignition of hydrogen-air mixture over a range of composition and thermodynamic conditions. It is demonstrated that the PC-NODE framework not only improves the physical consistency of the resulting data-driven model with respect to mass conservation criteria, but also improves training efficiency. PC-NODE is shown to achieve 2–100× speedup relative to the hydrogen-air detailed chemical mechanism depending on the type of the ODE solver (implicit or explicit) used during autoregressive inference tests. Lastly, a-posteriori studies are performed wherein the trained PC-NODE model is coupled with a CFD solver. It is shown that higher accuracy is achieved with PC-NODE relative to the purely data-driven NODE approach. Moreover, PC-NODE also exhibits robustness and generalizability to unseen initial conditions from within (interpolative capability) as well as outside (extrapolative capability) the training regime.
Evaluation of hydrograph separation techniques with uncertain end-member composition
Hydrograph separation is one of many approaches used to analyse shifts in source water contributions to stream flow resulting from climate change in remote watersheds. Understanding these shifts is vital, as shifts in source water contributions to a stream can shape water management decisions. Because remote watersheds are often inaccessible and have poorly characterized contributing water sources, or end-members, it is critical to understand the implications of using different hydrograph separation techniques in these data-limited environments. To explore the uncertainty associated with different techniques, results from two hydrograph separation techniques, mass balance and principle component analysis, were compared using 3 years of aqueous geochemical data from the East River watershed located in the Elk Mountains of Central Colorado. Solute concentrations of the end-members were characterized by both a limited set of direct chemical measurements of different sources and detailed seasonal instream chemistry to examine the influences of uncertain end-member compositions in a data-limited environment. Annual volumetric end-member contributions to stream flow had relatively good agreement across separation techniques. Large variations in time were observed in the hydrograph separations, depending on the end-member type, and estimated flow contributions varied between the selected solutes. End-member concentrations characterized by stream chemistry showed several limitations including a reduced number of distinguishable end-members and differences in timing of flow contributions. Here the results highlight the benefits of using multiple hydrograph separation techniques by providing a ‘weight-of-evidence’ approach to environments with limited end-member concentration data.
Atomistic insight into the effects of electrostatic fields on hydrocarbon reaction kinetics
Reactive Molecular Dynamics (MD) and Density Functional Theory (DFT) computations are performed to provide insight into the effects of external electrostatic fields on hydrocarbon reaction kinetics. By comparing the results from MD and DFT, the suitability of the MD method in modeling electrodynamics is first assessed. Results show that the electric field-induced polarization predicted by the MD charge equilibration method is in good agreement with various DFT charge partitioning schemes. Then, the effects of oriented external electric fields on the transition pathways of non-redox reactions are investigated. Results on the minimum energy path suggest that electric fields can cause catalysis or inhibition of oxidation reactions, whereas pyrolysis reactions are not affected due to the weaker electronegativity of the hydrogen and carbon atoms. MD simulations of isolated reactions show that the reaction kinetics is also affected by applied external Lorentz forces and interatomic Coulomb forces since they can increase or decrease the energy of collision depending on the molecular conformation. In addition, electric fields can affect the kinetics of polar species and force them to align in the direction of field lines. These effects are attributed to energy transfer via intermolecular collisions and stabilization under the external Lorentz force. The kinetics of apolar species is not significantly affected mainly due to the weak induced dipole moment even under strong electric fields. The dynamics and reaction rates of species are studied by means of large-scale combustion simulations of n-dodecane and oxygen mixtures. Results show that under strong electric fields, the fuel, oxidizer, and most product molecules experience translational and rotational acceleration mainly due to close charge transfer along with a reduction in their vibrational energy due to stabilization. This study will serve as a basis to improve the current methods used in MD and to develop novel methodologies for the modeling of macroscale reacting flows under external electrostatic fields.
Material flow behavior and microstructural refinement of AA6061 alloy during friction extrusion
In this work we used friction extrusion (FE), a solid phase processing technique, to produce dense, fully consolidated 5?mm rods of aluminum alloy 6061 (AA6061). The combination of large shear stresses and high temperatures at the tool-billet interface during extrusion produced equiaxed, dynamically recrystallized grains and finely distributed precipitates. Texture and microstructure evolution during extrusion was investigated in detail using scanning electron microscopy, electron backscatter diffraction, and transmission electron microscopy. Smoothed particle hydrodynamics simulation was performed to study complex material flow during extrusion. Simulation results suggest spiral material flow during extrusion which corroborated experimental results. Advantages of friction extruded microstructure over conventionally extruded counterparts are also explored using flash annealing for solution treatment followed by artificial aging. Mechanical properties of the as-friction extruded, and the artificially aged specimens were evaluated using tensile testing and compared with conventional extruded material properties.
Inertially enhanced mass transport using 3D-printed porous flow-through electrodes with periodic lattice structures
Significance The efficient utilization of electrical energy is an increasingly important challenge, especially as renewable energy sources become cheaper and demand increases. Electrochemical reactors utilizing flow-through electrodes (FTEs) provide an attractive path toward the efficient utilization of electrical energy. Their commercial viability and ultimate adoption hinge on attaining high current densities to drive cost competitiveness. There are limited opportunities for engineering FTE materials, as these are often random, disordered media. Alternatively, three-dimensional (3D)–printed FTEs provide the opportunity to quickly explore the impact of engineered electrode architectures on device performance. We demonstrate that 3D-printed FTEs have the potential to exceed the performance of conventional materials by using the expanded design freedom to engineer the internal flow.
Sorbmatech{sup R}Cs, an Innovative Highly Selective Cs Sorbent for Wastewater Decontamination - 20065
The treatment of radioactive wastewater from the operating nuclear industry (energy production, reprocessing of spent fuel, decommissioning of shut-down facilities, etc.) or in case of incidental or accidental situation (such as Fukushima Daichii NPP accident) is an important issue requiring constant improvement of the technologies and techniques used to prevent radioactive releases into the environment and/or to reduce the production of secondary waste. CEA, Orano and CTI are collaborating since 2014, with the support of the French government's program 'investments for the future', to develop Sorbmatech{sup R}Cs, an innovative and patented selective sorbent (Grandjean and Barre 2014) to deal with the removal of radioactive {sup 137}Cs, one of the most hazardous isotope to be managed in nuclear waste, highly efficient either in agitated reactor or in column process. Sorbmatech{sup R}Cs sorbent consists of mesoporous silica particles loaded with potassium-copper hexacyanoferrate nanoparticles (KCu-HCF). This peculiar structure enables much faster sorption kinetics compared to denser crystalline structures, such as Silicotitanate or Zeolite sorbents, whose drawback consists in hindering the diffusion process through the material, and whose larger sorbent particles slow down the ion exchange process. The equilibrium of Sorbmatech{sup R}Cs is reached in few minutes, even at high flow rates in a fixed-bed column process (up to 10 m.h{sup -1} Darcy velocity) with low drop pressure. Moreover, Sorbmatech{sup R}Cs can be used over a wide pH range from 2 to 10 and has a very high selectivity towards {sup 137}Cs even in brine solution (saline, mineral or sea water). This new sorbent also has a K{sub d} higher than 10{sup 5} mL.g{sup -1} depending on the salinity of the wastewater, enabling a highly efficient removal of Cs trace in radioactive wastewater compared to Cs selective sorbent such as Zeolites and Silicotitanates. Its radiological resistance enables the treatment of high, medium and low activity wastewater. The CEA-Orano-CTI/ALSYS partnership leads to the development of a simple and low-cost synthetic route, which demonstrated large-scale manufacturing of the product on a batch of 100 kg. Two products have been developed and are ready for short run market introduction so far with grain size well adapted either for column processes or agitated reactors.. Finally, the industrial implementation has been studied and largely benefits from the properties of the sorbent. Indeed, its high sorption kinetics enable high flow rates resulting in a decrease of operation times, unit sizes, and volumes of secondary waste produced. Moreover, Sorbmatech{sup R}Cs is designed to be combined into a full and integrated solution, ranging from preliminary optimization of operating conditions through numerical dimensioning model, industrial implementation and treatment of the wastewater (through cartridge or preconditioned columns systems developed thanks to Orano's extensive expertise), to long-term stabilization of generated waste (under progress). (authors)
Effects of Particle Mixing and Gravitational Settling on Charge Transport in Carbon Flow-Electrode Cells
Flowable carbon slurries are actively studied and under development for charge transport in various electrochemical systems including flow capacitors, capacitive deionization cells, semi-solid flow batteries, and lithium extraction. However, much less is known about in operando slurry flow dynamics and their corresponding effect on charge transport. We performed an experimental study of mixing and settling dynamics of slurry electrodes within an electrochemical flow cell during continuous operations. The electrochemical cell consisted of two horizontal co-flowing channels, separated by a cation-exchange membrane (CEM). Here we used high-speed optical imaging of planes parallel to gravity and simultaneous electrochemical measurements. At low flow rates, dense yet dynamic particle beds formed on the bottom electrode in each channel, which unexpectedly yielded the highest currents. This approach enables the operation of the flow cell at low system-average particle concentrations while leveraging gravity-driven particle settling to locally enhance carbon concentrations precisely at the current collector sites. Conversely, high flow rates were characterized by thin particle beds and well-mixed particle flows. In the latter case, the electrodes in closest proximity (located on either side of the CEM) achieved a current higher than the other electrode pairs. The observations have implications for slurry control and electrode designs in electrochemical systems.
The Pele Simulation Suite for Reacting Flows at Exascale
In this work, we present the Pele suite of software tools for compressible and incompressible reacting flows. The Pele suite leverages several different libraries, notably AMReX and SUNDIALS, to achieve performance portability on heterogeneous computing architectures across the supercomputing landscape. The Pele suite is comprised of PeleC, a compressible reacting flow block-structured adaptive mesh refinement solver, PeleLMeX, a low-Mach number reacting flow block-structured adaptive mesh refinement solver, Pele-Physics, a library for transport, thermodynamics, finite rate chemistry, soot, spray and radiation physics. The objective of this paper is (i) to present the code development efforts necessary to achieve highly effective and scalable applications for exascale machines and (ii) to detail the performance results of the Combustion-Pele project applications on Oak Ridge National Laboratory's Frontier. We show good weak and strong scaling results for both PeleC and PeleLMeX up to more than 50 billion cells on more than 4096 Frontier graphics processing unit nodes. We also present a capability demonstration simulation of a dual-fuel pulse compression ignition engine (six adaptive mesh refinement levels, and 60 billion cells or 2.1 trillion degrees of freedom) on Frontier, to date one of the largest simulations performed on the first exascale-class supercomputer.
Modeling Microwave-Enhanced Chemical Vapor Infiltration Process for Preventing Premature Pore Closure
The chemical vapor infiltration (CVI) process involves infiltrating a porous preform with reacting gases that undergo chemical transformation at high temperatures to deposit the ceramic phase within the pores, ultimately leading to a dense composite. The conventional CVI process in composite manufacturing needs to follow an isothermal approach to minimize temperature differences between the external and internal surfaces of the preform, ensuring that reactive gases infiltrate internal pores before external surfaces seal. This study addresses the challenge of premature pore closure in CVI processes through microwave heating. A frequency-domain microwave solver is developed in Open-FOAM to investigate volumetric heating mechanisms within the preform. Through numerical studies, we demonstrate the capability of microwave heating of creating an inside-out temperature inversion. This inversion accelerates reactions proximal to the preform center, effectively mitigating the risk of premature external pore closure and ensuring uniform densification. The results reveal a significant enhancement in temperature inversion when high-permittivity reflectors are incorporated to generate resonant waves. This microwave heating strategy is then coupled with high-fidelity direct numerical simulation (DNS) of reacting flow, enabling the analysis of resulting densification processes. The DNS simulation includes detailed chemistry and realistic diffusion coefficients. The numerical results can be used to estimate the impact of microwave-induced temperature inversion on densification in productions.