Unlocking Hydrogen Carrier Potential: Integrated Mechanistic Studies and Surrogate Modeling
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Engineering topics
Publications and source records attributed to Moore, Thomas.
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The transition from fossil fuels to renewable energy has brought about a rapid increase in the availability of clean electricity. However, electricity generated from sources such as wind and solar are limited to intermittent operation due to daily and seasonal variation. One solution is to utilize electrochemical devices in energy storage and electrochemical manufacturing applications, where they can harness surplus energy and decarbonize chemical industries traditionally reliant on petrochemical feedstocks. Managing the growing prevalence of renewable energy underscores the importance of developing and scaling up these technologies, which can in turn facilitate the achievement of carbon emission reduction commitments of companies and developed economies. Likewise, the electrification of transport creates an increasing need for energy-dense electrochemical energy storage devices such as batteries and supercapacitors. Naturally, simulation tools are required to assist in the design of efficient and industrial-scale electrochemical devices.
Numerous cutting-edge scientific technologies originate at the laboratory scale, but transitioning them to practical industry applications is a formidable challenge. Traditional pilot projects at intermediate scales are costly and time-consuming. An alternative, the pilot-scale model, relies on high-fidelity numerical simulations, but even these simulations can be computationally prohibitive at larger scales. To overcome these limitations, we propose a scalable, physics-constrained reduced order model (ROM) method. The ROM identifies critical physics modes from small-scale unit components, projecting governing equations onto these modes to create a reduced model that retains essential physics details. We also employ Discontinuous Galerkin Domain Decomposition (DG-DD) to apply ROM to unit components and interfaces, enabling the construction of large-scale global systems without data at such large scales. Here this method is demonstrated on the Poisson and Stokes flow equations, showing that it can solve equations about 15–40 times faster with only ~1% relative error. Furthermore, ROM takes one order of magnitude less memory than the full order model, enabling larger scale predictions at a given memory limitation.
This code solves for the one-dimensional concentration and temperature distribution within a carbon capture column using a homogenized absorber model. These solutions are compared to experimental data.
Bicarbonate electrolytes are used in a range of chemical processes; however, resolved simulation of these electrolytes is difficult, as disparate reaction time scales lead to numerical stiffness and the formation of fine boundary layers. Based on several physically motivated approximations, we reduce the full set of chemical reactions within a bicarbonate electrolyte to a simpler subset, eliminating the numerical stiffness. We supported this simplification via a two-variable singular perturbation expansion and demonstrated that under neutral conditions (6 < pH < 10) typically found within a fluid-fed CO 2 electrolyzer, the simplifications lead to negligible error. Here, we also discuss two alternative simplifications, one valid at high pH and another valid at arbitrary pH. These simplifications reduce the condition number of the matrices resulting from spatiotemporal discretization by up to 10 orders of magnitude and enable three-dimensional (3D) simulation of CO 2 electrolyzers containing carbonate solutions.
scaleupROM is a scalable, physics-constrained reduced order model (ROM). It aims to provide robust, accelerated physics predictions at extrapolated scales, based on the small, component-level data. This is implemented by combining projection-based ROM with discontinuous Galerkin domain decomposition, in the framework of MFEM and libROM. It currently supports the Poisson equation and Stokes flow equation, and more work is in progress toward general, nonlinear physics systems.
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In low-temperature CO 2 electrolysis, a fundamental trade-off exists between maximizing electrolyzer performance and minimizing downstream CO 2 recovery. Here, by coupling a down-the-gas-channel electrolyzer model with a techno-economic analysis, we find that the optimal single-pass CO 2 conversion for ethylene production is typically low—on the order of 5%–10%—although larger optima are found if the H 2 faradic efficiency is very low. Similarly, strategies for eliminating carbonate crossover require more energy than downstream gas separation if they increase the cell potential by ~0.2 V; however, when CAPEX are accounted for, this “break-even” voltage increases to ~ 0.4 to 0.8 V for electricity prices varying from 6c/kWh to 1.5c/kWh. These findings are a consequence of the low energy requirements of industrial gas separation relative to electrochemical CO 2 reduction. Under most circumstances, maintaining near-optimal electrolyzer performance is more important than reducing or eliminating downstream gas separations.
Advanced structured packing geometries fabricated with 3D printing were used for absorber CO 2 capture with a liquid solvent. Compared to conventional packing, they had greatly enhanced (90–140%) effective surface areas and comparable hydrodynamics.
CO 2 BOLs are promising CCS solvents, whose mass transfer rates improve upon cooling. We show this unintuitive behavior is due to slow transport of reaction products from the gas–liquid interface, caused by shifts in reaction equilibria.
Carbon utilization is a crucially important performance characteristic of CO 2 electrolyzers; however, applications of simple and accurate descriptive models to experimental data on this topic are currently lacking. Here, we apply a simple analytical reactor model to parameterize single-pass conversion as a function of feed-gas flow rate and show that it captures a wide body of experimental data in the literature exceptionally well. In doing so, we demonstrate that this simple conceptual approach can characterize progress and capture recent innovations in reactor design. To validate the extracted parameters, we employ a well-established comprehensive model to confirm that the results agree with physical expectations. Lastly, we explore the implications of the descriptive model by examining the inherent trade-off between single-pass conversion efficiency and reactor productivity. Understanding such trade-offs is crucially important for advancing this electrolyzer technology toward commercial applications.
CO 2 emissions can be transformed into high-added-value commodities through CO 2 electrocatalysis; however, efficient low-cost electrocatalysts are needed for global scale-up. Inspired by other emerging technologies, the authors report the development of a gas diffusion electrode containing highly dispersed Ag sites in a low-cost Zn matrix. Here, this catalyst shows unprecedented Ag mass activity for CO production: –614 mA cm –2 at 0.17 mg of Ag. Subsequent electrolyte engineering demonstrates that halide anions can further improve stability and activity of the Zn–Ag catalyst, outperforming pure Ag and Au. Membrane electrode assemblies are constructed and coupled to a microbial process that converts the CO to acetate and ethanol. Combined, these concepts present pathways to design catalysts and systems for CO 2 conversion toward sought-after products.
Gas diffusion electrodes (GDEs) have shown promising performance for the electrochemical reduction of CO 2 (CO 2 R). In this study, a resolved, pore scale model of electrochemical reduction of CO 2 within a liquid-filled catalyst layer is developed. Three CO 2 mass transport regimes are identified in which the CO 2 penetration depth is controlled by CO 2 consumption in the electrolyte, CO 2 conversion along the solid-electrolyte double-phase boundaries (DPBs), and CO 2 conversion concentrated around the gas–solid–electrolyte triple-phase boundaries (TPBs). While it is possible for CO 2 R to be localized around the TPBs, in systems with submicron pore radii operating at <1 A cm –2 CO 2 R will be distributed across the DPBs within the catalyst layer. This validates the assumption of pore-scale uniformity implicit in popular, volume-averaged GDE models. Overall, the CO 2 conversion efficiency depends strongly on the governing mass transport regime, and operational-phase diagrams are constructed to guide the catalyst layer design.
The encapsulation of highly viscous liquid-like Nanoparticle Organic Hybrid Materials (NOHMs) inside a gas permeable polymer to form SIPs (Solvent Impregnated Polymers) significantly enhanced the CO 2 capture kinetics of NOHMs, leading to a remarkable 50-fold increase in CO 2 flux compared to the neat NOHMs. To understand the mechanism for enhanced CO 2 mass transfer within these hybrid materials, kinetic modeling of CO 2 uptake into SIPs containing polyethylenimine functionalized NOHMs, denoted NPEI-SIP, was conducted. CO 2 mass transfer into NPEI-SIP films was found to conform, both qualitatively and quantitatively, with a diffusion-controlled moving front model. The diffusion-controlled model was also used to simulate CO 2 uptake within a fixed bed containing polydisperse NPEI-SIP particles, and this model accurately predicted experimentally measured breakthrough curves at 25 °C and 50 °C. The 50-fold increase in gas flux was shown to be a consequence of the very large CO 2 permeability within the polymer–solvent composite. Furthermore, the increase in gas flux is also dependent on the diffusion–reaction regime in which the chemical solvent operates, and the largest improvement will occur when immobilizing solvents, such as NOHMs, which operate in the instantaneous-reaction regime. The CO 2 capacity (~3 mol CO 2 /kg) and saturation time (~5 min) of 430 μm SIP particles were comparable to popular CO 2 chemisorption materials such as amine grafted silicates, in spite of the slow kinetics of NOHM-I-PEI in liquid form (CO 2 saturation time ~24 h for a 1 mm thin film).
Hybrid CO 2 capture materials, solvent impregnated polymers (SIPs), are developed based on a simple and scalable encapsulation technique to enhance CO 2 capture kinetics of water-lean solvents with high viscosity. Liquid-like nanoparticle organic hybrid materials functionalized with polyethylenimine (NOHM-I-PEI) are incorporated into a shell material and UV-cured to produce gas-permeable solid sorbents with uniform NOHMs loading (NPEI-SIPs). The CO 2 capture kinetics of NPEI-SIPs show a remarkable 50-fold increase compared to that of neat NOHM-I-PEI due to a large increase in the NOHMs-CO 2 interfacial surface area provided by the SIP design. The optimum NOHM-I-PEI loading and sorption temperature are found to be ≈49 wt% and 50 °C, respectively, and NPEI-SIPs exhibit great thermal stability over 20 CO 2 capture/sorbent regeneration temperature swing cycles. The pseudoequilibrium CO 2 loadings of NPEI-SIPs under humid conditions are as high as 3.1 mmol CO 2 g -1 NPEI - SIPs for 15 vol% CO 2 (postcombustion capture) and 1.7 mmol CO 2 g -1 NPEI - SIPs for 400 ppm (direct air capture). Overall, these findings suggest that NPEI-SIPs can effectively capture CO 2 from a wide range of CO 2 concentrations including direct air capture while allowing the flexible design of CO 2 capture reactors by combining the benefits of liquid solvents and solid sorbents.
A rate-based model of an absorption column was developed and used to analyze several intercooling strategies utilizing “heat exchange packings.” These packings are capable of removing heat from the column and transferring it to a cooling fluid within the packing. For absorption of CO 2 into aqueous monoethanolamine under industrial conditions, intercooling via heat exchange packings placed along 10–20% of the column could reduce the column height by ~15%. The height of these columns was close to the minimum theoretical value, calculated by numerically optimizing the temperature profile. Effective intercooling could also be achieved by using the cool, rich solvent as the cooling fluid. This reduces the cooling load and facilitates recovery of waste heat. Heat exchange packings could also be used to redistribute heat within the column, reducing the column height with no net cooling load. However, this approach requires larger heat transfer coefficients than have been experimentally observed.