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This process model is a conceptual process model that simulate the reactive captures of CO2 and the subsequent conversion of captured CO2 to methanol. The model was developed using Aspen Plus.
An electrocatalytic process for carbon dioxide conversion includes combining a Catalytically Active Element and Helper Catalyst in the presence of carbon dioxide, allowing a reaction to proceed to produce a reaction product, and applying electrical energy to said reaction to achieve electrochemical conversion of said reactant to said reaction product. The Catalytically Active Element can be a metal in the form of supported or unsupported particles or flakes with an average size between 0.6 nm and 100 nm. the reaction products comprise at least one of CO, HCO.sup.-, H.sub.2CO, (HCO.sub.2).sup.-, H.sub.2CO.sub.2, CH.sub.3OH, CH.sub.4, C.sub.2H.sub.4, CH.sub.3CH.sub.2OH, CH.sub.3COO.sup.-, CH.sub.3COOH, C.sub.2H.sub.6, (COOH).sub.2, (COO.sup.-).sub.2, and CF.sub.3COOH.
An electrocatalytic process for carbon dioxide conversion includes combining a Catalytically Active Element and a Helper Polymer in the presence of carbon dioxide, allowing a reaction to proceed to produce a reaction product, and applying electrical energy to said reaction to achieve electrochemical conversion of said carbon dioxide reactant to said reaction product. The Catalytically Active Element can be a metal in the form of supported or unsupported particles or flakes with an average size between 0.6 nm and 100 nm. The reaction products comprise at least one of CO, HCO.sup.-, H.sub.2CO, (HCO.sub.2).sup.-, H.sub.2CO.sub.2, CH.sub.3OH, CH.sub.4, C.sub.2H.sub.4, CH.sub.3CH.sub.2OH, CH.sub.3COO.sup.-, CH.sub.3COOH, C.sub.2H.sub.6, (COOH).sub.2, (COO.sup.-).sub.2, and CF.sub.3COOH.
The high-pressure carbon monoxide (HiPco) process, developed at Rice University, has been reported to produce single-walled carbon nanotubes from gas-phase reactions of iron carbonyl in carbon monoxide at high pressures (10-100 atm). Computational modeling is used here to develop an understanding of the HiPco process. A detailed kinetic model of the HiPco process that includes of the precursor, decomposition metal cluster formation and growth, and carbon nanotube growth was developed in the previous article (Part I). Decomposition of precursor molecules is necessary to initiate metal cluster formation. The metal clusters serve as catalysts for carbon nanotube growth. The diameter of metal clusters and number of atoms in these clusters are some of the essential information for predicting carbon nanotube formation and growth, which is then modeled by the Boudouard reaction with metal catalysts. Based on the detailed model simulations, a reduced kinetic model was also developed in Part I for use in reactor-scale flowfield calculations. Here this reduced kinetic model is integrated with a two-dimensional axisymmetric reactor flow model to predict reactor performance. Carbon nanotube growth is examined with respect to several process variables (peripheral jet temperature, reactor pressure, and Fe(CO)5 concentration) with the use of the axisymmetric model, and the computed results are compared with existing experimental data. The model yields most of the qualitative trends observed in the experiments and helps to understanding the fundamental processes in HiPco carbon nanotube production.
A chemical kinetic model is developed to help understand and optimize the production of single-walled carbon nanotubes via the high-pressure carbon monoxide (HiPco) process, which employs iron pentacarbonyl as the catalyst precursor and carbon monoxide as the carbon feedstock. The model separates the HiPco process into three steps, precursor decomposition, catalyst growth and evaporation, and carbon nanotube production resulting from the catalyst-enhanced disproportionation of carbon monoxide, known as the Boudouard reaction: 2 CO(g)-->C(s) + CO2(g). The resulting detailed model contains 971 species and 1948 chemical reactions. A second model with a reduced reaction set containing 14 species and 22 chemical reactions is developed on the basis of the detailed model and reproduces the chemistry of the major species. Results showing the parametric dependence of temperature, total pressure, and initial precursor partial pressures are presented, with comparison between the two models. The reduced model is more amenable to coupled reacting flow-field simulations, presented in the following article.
A program of laboratory experiments, modeling and fieldwork was carried out at Yale University, University of Maryland, and University of Hawai‘i, under a DOE Award (DE-FE0004375) to study mineral carbonation as a practical method of geologic carbon sequestration. Mineral carbonation, also called carbon mineralization, is the conversion of (fluid) carbon dioxide into (solid) carbonate minerals in rocks, by way of naturally occurring chemical reactions. Mafic and ultramafic rocks, such as volcanic basalt, are natural candidates for carbonation, because the magnesium and iron silicate minerals in these rocks react with brines of dissolved carbon dioxide to form carbonate minerals. By trapping carbon dioxide (CO 2 ) underground as a constituent of solid rock, carbonation of natural basalt formations would be a secure method of sequestering CO 2 captured at power plants in efforts to mitigate climate change. Geochemical laboratory experiments at Yale, carried out in a batch reactor at 200°C and 150 bar (15 MPa), studied carbonation of the olivine mineral forsterite (Mg 2 SiO 4 ) reacting with CO 2 brines in the form of sodium bicarbonate (NaHCO 3 ) solutions. The main carbonation product in these reactions is the carbonate mineral magnesite (MgCO 3 ). A series of 32 runs varied the reaction time, the reactive surface area of olivine grains and powders, the concentration of the reacting fluid, and the starting ratio of fluid to olivine mass. These experiments were the first to study the rate of olivine carbonation under passive conditions approaching equilibrium. The results show that, in a simple batch reaction, olivine carbonation is fastest during the first 24 hours and then slows significantly and even reverses. A natural measure of the extent of carbonation is a quantity called the carbonation fraction, which compares the amount of carbon removed from solution, during a run, to the maximum amount that could have been removed if the olivine initially present had fully dissolved and the cations released had subsequently precipitated in carbonate minerals. The carbonation fractions observed in batch experiments with olivine grains and powders varied significantly, from less than 0.01 (1%) to more than 0.5 (50%). Over time, the carbonation fractions reached an upper limit after about 24 to 72 hours of reaction, then stayed constant or decreased. The peak Final Scientific/Technical Report DE-FE0004275 | Mineral Carbonation | 4 coincided with the appearance of secondary magnesium-bearing silicate minerals, whose formation competes for magnesium ions in solution and can even promote conditions that dissolve magnesite. The highest carbonation fractions resulted from experiments with low ratios of concentrated solution to olivine, during which amorphous silica spheres or meshes formed, instead of secondary silicate minerals. The highest carbonation fractions appear to result from competing effects. Precipitation of silica layers on olivine reduces the reactive surface area and, thus, the rate of olivine dissolution (which ultimately limits the carbonation rate), but these same silica layers can also inhibit the formation of secondary silicate minerals that consume magnesite formed in earlier stages of carbonation. Simulation of these experiments with simple geochemical models using the software program EQ3/6 reproduces the general trends observed—especially the results for the carbonation fraction in short-run experiments. Although further experimentation and better models are needed, this study nevertheless provides a framework for understanding the optimal conditions for sequestering carbon dioxide by reacting CO 2 -bearing fluids with rocks containing olivine minerals. A series of experiments at the Rock Physics Laboratory at the University of Maryland studied the carbonation process during deformation of thermally cracked olivine-rich rock samples (dunite) saturated with CO 2 brines of varying compositions. A goal of these geomechanical experiments was to see if flow and deformation processes, which accompany natural carbonation reactions in underground settings, work to enhance or inhibit the reactions. The experiments involved hydrostatic compaction, followed by deformation at a constant rate of strain. Sample permeability was monitored during the reactions. Comparison of the samples’ volume changes to their axial strains (shortening) during deformation indicates that samples reacted with CO 2 -saturated brines accommodate more axial compaction, before the onset of dilation (a swelling that precedes rock failure), than samples reacted with distilled water. Analyses of the reacted samples with scanning electron microscope (SEM) images indicate, first, that dissolution of olivine occurring in the initial stages of carbonation can provide pathways to fluid flow that sustain the reaction, and, second, that carbonate minerals precipitated along existing fractures in the rocks may serve as asperities, or roughness on a crack’s surface that restricts its closure. Final Scientific/Technical Report DE-FE0004275 | Mineral Carbonation | 5 In a related study undertaken by one of the principal investigators as a spin-off of the main project, a simple model of (magnesite) crystal growth in the pore space of basalts undergoing carbonation was developed. The model suggests that, under a carefully controlled program of CO 2 injection, carbonate mineral growth can harden the rock formation against earthquakes that might otherwise be induced by the injection of large fluid volumes (Yarushina and Bercovici, 2013). The overall conclusion of the research project is that mineral carbonation of underground mafic and ultramafic rock formations is a viable candidate for long-term sequestration of man-made carbon dioxide. No results obtained during the project indicate that the method is inherently intractable in its implementation; moreover, enormous volumes of basalt near Earth’s surface are candidate locations for large-scale injection programs. The geochemical experiments do indicate, however, that there will be significant engineering challenges in maintaining high rates of carbonation, by delaying the onset of chemical conditions that promote formation of secondary silicate minerals and, therefore, slow down, or even reverse, the carbonation process. It remains an open question as to whether carbonation processes can be sustained for many years in an engineered system operating on a large scale—a scale capable of accommodating millions of tons of CO 2 annually. The development of realistic theoretical models that can systematically describe the combined effects of reactive flow, precipitation and geomechanical deformation is a major barrier to further understanding of the practical viability of mineral carbonation as large-scale method of carbon sequestration.
Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity re-quires a multi-stage membrane process, where the optimal network configuration of the mem-brane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules.
Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.
Highlights: • We study the effect and its mechanism of urbanization process on carbon emissions. • We use threshold regression and mediating effect models at China's provincial-level. • Urbanization and carbon emission abatement in China can achieve a harmonious state. • Abatement effect of urbanization on carbon emissions weakens with a deepening urbanization. • The relationship between urbanization and carbon emissions is mediated by some factors. - Abstract: As the largest carbon emitter and developing country in the world, China's rapid urbanization in recent decades plays a significant role in carbon emissions. However, there is still no consensus on whether urbanization process and carbon emission abatement in China can achieve a harmonious state. Based on the panel data of China's 30 provincial-level regions during 2001–2014, this paper uses the threshold regression model and the mediating effect model to investigate the effect and its mechanism of urbanization process on carbon emissions measured by three indicators: carbon emission scale, per capita carbon emissions, and carbon intensity. The results show that urbanization can contribute to declines in carbon emission scale, per capita carbon emissions, and carbon intensity. That is to say, urbanization can present an abatement effect on carbon emissions. However, such an abatement effect is diminishing with a deepening urbanization. Moreover, the relationship between urbanization and carbon emissions is mediated by four mediating variables, i.e., technological progress, industrial structure, energy consumption structure, and foreign direct investment. Therefore, a harmonious relationship between urbanization and carbon emission abatement can be achieved if policy-makers attempt to arouse the positive mediation roles of such factors when formulating relevant policies.
Graphical abstract: The ordered mesoporous carbon–niobium oxide composites have been synthesized by a multi-component co-assembly method associated with a carbonization process. - Highlights: • Ordered mesoporous carbon–niobium oxide composites were synthesized. • The content of Nb{sub 2}O{sub 5} in the composites could be tuned from 38 to 75%. • Niobium species were highly dispersed in amorphous carbon framework walls. • The composites exhibited good catalytic performance in the dehydration of fructose. - Abstract: Ordered mesoporous carbon–niobium oxide composites have been synthesized by a multi-component co-assembly method associated with a carbonization process using phenolic resol as carbon source, niobium chloride as precursor and amphiphilic triblock copolymer Pluronic F127 as template. The resulting materials were characterized using a combination of techniques including differential scanning calorimetry–thermogravimetric analysis, N{sub 2} physical adsorption, X-ray diffraction, transmission electron microscopy, and X-ray photoelectron spectroscopy. The results show that with increasing the content of Nb{sub 2}O{sub 5} from 38 to 75% the specific surface area decreases from 306.4 to 124.5 m{sup 2} g{sup −1}, while the ordered mesoporous structure is remained. Niobium species is well dispersed in the amorphous carbon framework. The mesoporous carbon–niobium oxide composites exhibit high catalytic activity in the dehydration of fructose to 5-hydroxymethylfurfural. A 100% conversion of fructose and a 76.5% selectivity of 5-hydroxymethylfurfural were obtained over the carbon–niobium oxide composite containing 75% Nb{sub 2}O{sub 5} under the investigated reaction conditions.
Carbon, as a reductant for quartz, must be made available so as to have suitable reactivity in conjunction with high purity, especially with respect to boron and phosphorus. A detailed experimental plan was developed to do this. Different sources of carbon were selected to be subjected to various purification methods and reactivity-enhancement processes. A developmental scale arc furnace was installed to perform quartz-carbon reactivity testing.
Method and system for processing light signals received by the eye of a human or other animal, where the eye may be compromised or non-functioning. Incident light is received at first and second pixels in a photodetector array and provides a pixel electrical signal representing the received light. Each of an array of carbon nanotube (CNT) towers is connected to a pixel, has a first tower end penetrating a retinal active layer of the animal and has a second tower end positioned to receive to receive and transport the pixel electrical signal to the retinal active layer. The CNT tower may be coated with a biologically active substance or chemically modified to promote neurite connections with the tower. The photoreceptor array can be provide with a signal altering mechanism that alters at least one of light intensity and wavelength intensity sensed by a first pixel relative to a second pixel, to correct for one or more selected eye problems.
Investigate the effects of disturbance and climate variables on processes controlling carbon and water processes at AmeriFlux cluster sites in semi-arid and mesic forests in Oregon. The observations were made at three existing and productive AmeriFlux research sites that represent climate and disturbance gradients as a natural experiment of the influence of climatic and hydrologic variability on carbon sequestration and resulting atmospheric CO 2 feedback that includes anomalies during the warm/ dry phase of the Pacific Decadal Oscillation.
Understanding carbon (C) dynamics from ecosystem to global scales remains a challenge. Although expansion of global carbon dioxide (CO2) observatories makes it possible to estimate C-cycle processes from ecosystem to global scales, these estimates do not necessarily agree. At the continental US scale, only 5% of C fixed through photosynthesis remains as net ecosystem exchange (NEE), but ecosystem measurements indicate that only 2% of fixed C remains in grasslands, whereas as much as 30% remains in needleleaf forests. The wet and warm Southeast has the highest gross primary productivity and the relatively wet and cool Midwest has the highest NEE, indicating important spatial mismatches. Newly available satellite and atmospheric data can be combined in innovative ways to identify potential C loss pathways to reconcile these spatial mismatches. Independent datasets compiled from terrestrial and aquatic environments can now be combined to advance C-cycle science across the land–water interface.
The main goal of the project was to create a continuous manufacturing process for carbon foam that operates at atmospheric pressure and can generate well-formed carbon foam panels and lightweight aggregates. This objective was accomplished and has enabled a platform where carbon foam products can be manufactured at significantly reduced cost and cycle time relative to the conventional high-pressure batch process, which in turn can enable the manufacture of much larger volumes of carbon foam. All these features should enable carbon foam to enter much larger markets and create meaningful demand for U.S. coal. Carbon foam panels and aggregate both consisted of at least 70 weight percent carbon per program requirements (typical was over 90-wt%), and at least 51 weight percent of the carbon was to be coal derived (typical was over 90-wt% carbon was from coal). Analyses regarding life cycle, technoeconomics, and final technological gaps have been documented in separate reports. This final report documents the methods used to attain the main goal and describes the technical results.
Focal Area(s): This white paper addresses how explainable machine learning (ML) algorithms can improve insights gained from complex data (Focal Area 3). We will also address how ML approaches related to sensor compression and low energy AI hardware can be used for efficient data acquisition (Focal Area 1). Science Challenge: We will focus on the coupled water cycle and carbon cycle processes in terrestrial ecosystems and terrestrial-aquatic interfaces. Thus, our approaches will be centered around several data-model integration challenges indicated in EESD strategic plans for two science focus areas: Terrestrial Ecosystem Science and Hydrobiogeochemistry. We can use AI to correct systematic model errors due to biases in either data or model structure/processes. Error patterns in model predictions usually vary by region, model, season etc. But there are systematic patterns in them. e.g., soil moisture tends to be overestimated in the arid western continental United States underestimated in wetter eastern USA; some land surface models tend to underestimate moisture in wet seasons and overestimate in dry seasons. Moreover, the consequences of extreme events (e.g., drought, extreme flooding, storm surges associated with tropical storms, hurricanes) on carbon cycle processes are not well represented in ecosystem and Earth system models. Redox-sensitive processes (e.g., rapid oxidation/reduction of iron and other redox-sensitive elements in soil microsites subjected to fluctuated hydrology) in terrestrial-aquatic interfaces further challenge model predictions of hot-spots (and hot-moments) due to poor understanding of underlying mechanisms. Thus, AI/ML approaches can be used to learn patterns in the data and model errors and use them to build model equations and correct process-based model errors.
The global carbon cycle describes the exchange of carbon between the atmosphere, terrestrial vegetation, oceans, and soil. Mechanisms involving carbon in sub-terrestrial ecosystems and their impact on climate are not well understood. This lack of understanding limits current climate models and prevents accurate soil-carbon storage predications for future climate conditions. To address the lack of instrumentation for conducting high fidelity measurements of appropriate parameters in the field, a multi-sensory probe using a mix of optical, fiber optic, and electronic technologies to measure CO2, temperature, dissolved oxygen, redox potential, and water level in subsurface environments has been developed. Details of the design, fabrication and laboratory performance verification are presented. Use cases and the anticipated impacts of such measurements on climate models are discussed.
This project describes the work carried out to prepare a highly reactive and mechanically strong MgO based sorbents and to develop a Population Balance Equations (PBE) approach to describe the evolution of the particle porosity distribution that is linked with Computational Fluid Dynamics (CFD) to perform simulations of the CO2 capture and sorbent regeneration. A large number of MgO-based regenerable sorbents were prepared using low cost and abundant dolomite as the base material. Among various preparation parameters investigated the potassium/magnesium (K/Mg) ratio was identified as the key variable affecting the reactivity and CO2 capacity of the sorbent. The optimum K/Mg ratio is about 0.15. The sorbent formulation HD52-P2 was identified as the “best” sorbent formulation and a large batch (one kg) of the sorbent was prepared for the detailed study. The results of parametric study indicate the optimum carbonation and regeneration temperatures are 360° and 500°C, respectively. The results also indicate that steam has a beneficial effect on the rate of carbonation and regeneration of the sorbent and that the reactivity and capacity of the sorbent decreases in the cycling process (sorbent deactivation). The results indicate that to achieve a high CO2 removal efficiency, the bed of sorbent should be operated at a temperature range of 370-410°C which also favors production of hydrogen through the WGS reaction. To describe the carbonation reaction kinetics of the MgO, the Variable Diffusivity shrinking core Model (VDM) was developed in this project, which was shown to accurately fit the experimental data. An important advantage of this model is that the changes in the sorbent conversion with time can be expressed in an explicit manner, which will significantly reduce the CFD computation time. A Computational Fluid Dynamic/Population Balance Equations (CFD/PBE) model was developed that accounts for the particle (sorbent) porosity distribution and a new version of the method of moments, called Finite size domain Complete set of trial functions Method Of Moments (FCMOM) was used to solve the population balance equations. The PBE model was implemented in a commercial CFD code, Ansys Fluent 13.0. The code was used to test the model in some simple cases and the results were verified against available analytical solution in the literature. Furthermore, the code was used to simulate CO2 capture in a packed-bed and the results were in excellent agreement with the experimental data obtained in the packed bed. The National Energy Laboratory (NETL) Carbon Capture Unit (C2U) design was used in simulate of the hydrodynamics of the cold flow gas/solid system (Clark et al.58). The results indicate that the pressure drop predicted by the model is in good agreement with the experimental data. Furthermore, the model was shown to be able to predict chugging behavior, which was observed during the experiment. The model was used as a base-case for simulations of reactive flow at elevated pressure and temperatures. The results indicate that by controlling the solid circulation rate, up to 70% CO2 removal can be achieved and that the solid hold up in the riser is one of the main factors controlling the extent of CO2 removal. The CFD/PBE simulation model indicates that by using a simulated syngas with a composition of 20% CO2, 20% H2O, 30% CO, and 30% H2, the composition (wet basis) in the reactor outlet corresponded to about 60% CO2 capture with and exit gas containing 65% H2. A preliminary base-case-design was developed for a regenerative MgO-based pre-combustion carbon capture process for a 500 MW IGCC power plant. To minimize the external energy requirement, an extensive heat integration network was developed in Aspen/HYSYS® to produce the steam required in the regenerator and heat integration. In this process, liquid CO2 produced at 50 atm can easily be pumped and sequestered or stored. The preliminary economic analyses indicate that the estimated cost of carbon v capture is in the range of $31-$44/ton, suggesting that a regenerative MgO-Based process can be a viable option for pre-combustion carbon dioxide capture in advanced gasification based power systems.