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At least 487 records · Page 27

Metal–Ligand Cooperativity via Exchange Coupling Promotes Iron- Catalyzed Electrochemical CO 2 Reduction at Low Overpotentials

Biological and heterogeneous catalysts for the electrochemical CO 2 reduction reaction (CO 2 RR) often exhibit a high degree of electronic delocalization that serves to minimize overpotential and maximize selectivity over the hydrogen evolution reaction (HER). Here, we report a molecular iron(II) system that captures this design concept in a homogeneous setting through the use of a redox non-innocent terpyridine-based pentapyridine ligand (tpyPY2Me). As a result of strong metal-ligand exchange coupling between the Fe(II) center and ligand, [Fe(tpyPY2Me)] 2+ exhibits redox behavior at potentials 640 mV more positive than the isostructural [Zn(tpyPY2Me)] 2+ analog containing the redox-inactive Zn(II) ion. This shift in redox potential is attributed to the requirement for both an open-shell metal ion and a redox non-innocent ligand. The metal-ligand cooperativity in [Fe(tpyPY2Me)] 2+ drives the electrochemical reduction of CO 2 to CO at low overpotentials with high selectivity for CO 2 RR (>90%) and turnover frequencies of 100,000 s -1 with no degradation over 20 h. The decrease in the thermodynamic barrier engendered by this coupling also enables homogeneous CO 2 reduction catalysis in water without compromising selectivity or rates. Synthesis of the two-electron reduction product, [Fe(tpyPY2Me)] o , and characterization by X-ray crystallography, Mössbauer spectroscopy, X-ray absorption spectroscopy (XAS), variable temperature NMR, and density functional theory (DFT) calculations, support assignment of an open-shell singlet electronic structure that maintains a formal Fe(II) oxidation state with a doubly reduced ligand system. Furthermore, this work provides a starting point for the design of systems that exploit metal-ligand cooperativity for electrocatalysis where the electrochemical potential of redox non-innocent ligands can be tuned through secondary metal-dependent interactions.

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Recovering carbon losses in CO 2 electrolysis using a solid electrolyte reactor

The practical implementation of electrochemical CO 2 reduction technology is greatly challenged by notable CO 2 crossover to the anode side, where the crossed-over CO 2 is mixed with O 2 , via interfacial carbonate formation in traditional CO 2 electrolysers. Here we report a porous solid electrolyte reactor strategy to efficiently recover these carbon losses. Furthermore, by creating a permeable and ion-conducting sulfonated polymer electrolyte between cathode and anode as a buffer layer, the crossover carbonate can combine with protons generated from the anode to re-form CO 2 gas for reuse without mixing with anodic O 2 . Using a silver nanowire catalyst for CO 2 reduction to CO, we demonstrated up to 90% recovery of the crossover CO 2 in an ultrahigh gas purity form (>99%), while delivering over 90% CO Faradaic efficiency under a 200 mA cm -2 current. A high continuous CO 2 conversion efficiency of over 90% was achieved by recycling the recovered CO 2 to the CO 2 input stream.

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Development of an innovative process for post-combustion CO 2 capture to produce high-value NaHCO 3 nanomaterials

An innovative post-combustion process using aqueous sodium glycinates solutions (SGS) for CO 2 capture from a split flue gas stream emitted from the 600 MWe coal power plant, used in the Wolverine Clean Energy Venture (WCEV) project, was developed in Aspen Plus v.10. The flue gas flow rate used in the process was 12.43 kg/s (at 353.15 K and 101.33 kPa) and contained 0.0023 and 13.33 mol% of SO 2 and CO 2 , respectively. The overall process includes 5 main units designed to remove all SO 2 and capture more than 90 mol% of CO 2 in the flue gas stream, while producing high-value, salable sodium bicarbonate (NaHCO 3 ) nanomaterials to offset the total process costs. The hydraulics, mass transfer characteristics, and process performance obtained using Aspen Plus were discussed. Also, the capital expenditure (CAPEX), operating expenditure (OPEX), and Levelized cost of CO 2 capture (LCOC) were calculated to assess the feasibility of this process. Further, the hydraulics in the SO 2 washing and CO 2 capture units showed a pressure drop of 12 and 1 kPa, respectively, and the behaviors of the liquid holdup and normalized packing specific wetted surface area were similar in both units. The gas-side mass transfer coefficients were orders of magnitude greater than the liquid-side mass transfer coefficients. The process was able to capture 2.352 kg/s of CO 2 and produce 4.486 kg/s of valuable NaHCO 3 nanomaterials. Also, the calculated CAPEX, OPEX, and LCOC of the process for a 30-year plant lifetime were ($\$ $4,450,552), (233.00 $\$ $/h) and (35.49 $\$ $/ton of CO 2 captured), respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic understanding of support effect on the activity and selectivity of indium oxide catalysts for CO 2 hydrogenation

Herein we present a mechanistic study on the support effect (ZrO 2 and CeO 2 ) of In 2 O 3 catalysts in CO 2 hydrogenation by a combined experimental and computational approach. Kinetic experiments and surface characterization suggested that the activity of In 2 O 3 catalysts cannot be simply correlated with the abundance of surface oxygen vacancies (O v ) formed by either H 2 -reduction or thermal treatment, which has been frequently invoked in previous studies. The support effect should originate from the electronic interactions between In 2 O 3 and the support oxide, rather than geometric factors or the difference in the particle size of In 2 O 3 . Theoretical modelling revealed that surface O v facilitate the formation and stabilization of the formate (HCOO*) intermediate. While a carbonate-like structure is favored for CO 2 adsorption on CeO 2 -supported or unsupported In 2 O 3 catalysts, CO 2 tends to bind strongly in a bent configuration on the O v site at the In 2 O 3 -ZrO 2 interface. The distinct CO 2 adsorption structures on different supported In 2 O 3 catalysts may account for the different reaction energy profiles in the subsequent hydrogenation reactions, especially the rate-limiting step, i.e., hydrogenation of HCOO* to CH 2 O* and methoxy (CH 3 O*). The relatively higher methanol selectivity of In 2 O 3 catalyst supported on ZrO 2 with respect to that on CeO 2 are suggested to stem from the greater energy difference (Δ$E_a$) between the parallel hydrogenation and C-O bond cleavage of HCOO*, which leads to the formation of methanol and CO, respectively. We report this study underlines the important role of metal-oxide-interface in determining the catalytic behavior of oxide-supported In 2 O 3 catalysts in CO 2 conversion.

30 DIRECT ENERGY CONVERSION↗

Electrodeposited Sn–Cu@Sn dendrites for selective electrochemical CO 2 reduction to formic acid

Large-scale CO 2 electrolysis can be applied to store renewable energy in chemicals. Recent developments in gas diffusion electrodes now enable a commercially relevant current density. However, the low selectivity of the CO 2 reduction reaction (CO 2 RR) still hinders practical applications. The selectivity of the CO 2 RR highly depends on the electrocatalyst. Sn catalysts are considered promising cathode materials for the production of formic acid. The selectivity of Sn catalysts can be regulated by controlling their morphology or alloying them with secondary metals. In this work, we enhanced the selectivity of CO 2 reduction to formic acid by synthesizing Sn–Cu@Sn dendrites that have a core@shell architecture. The Sn–Cu@Sn dendrites were prepared by a scalable electro-deposition method. The electronic structure was modified to suppress a reaction pathway for CO production on the Sn surface. Notably, the Sn shell inhibited the cathodic corrosion of Cu during the CO 2 RR. On a gas diffusion electrode, the Sn–Cu@Sn dendrites exhibited 84.2% faraday efficiency to formic acid for 120 h with high stability.

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Electrolyzers in focus: advances in CO 2 electrolyzer designs

Electrochemical CO 2 reduction (ECR) remains a viable method to reintegrate anthropogenic CO 2 into current energy infrastructures through its conversion into commodity chemicals. To facilitate the integration of ECR, electrochemical devices called electrolyzers must be implemented to overcome the inherent limitations that exist in current ECR experiments, namely kinetics and mass transport. In this review, we outline the current and advancing designs in ECR electrolyzers, with a focus on the following five electrochemical devices: membrane electrode assemblies (MEA), flow cell (FC), rotating disk electrode (RDE), rotating ring-disk electrode (RRDE), and rotating cylinder electrode (RCE). We highlight the tunable components of each electrolyzer with a forward outlook on the optimization and relevance of electrolyzer designs in upcoming ECR applications.

CO2 reduction↗

An Electrochemical Hydrogen-Looping System for Low-Cost CO 2 Capture from Seawater

Carbon dioxide (CO 2 ) capture from seawater is a viable, long-term solution for addressing legacy carbon pollution on the planet. However, significant challenges to widespread applicability exist in terms of efficiency, cost, and scalability. In this work, we have developed an electrochemical hydrogen-looping (EHL) system that capitalizes on the generation of proton and OH – from seawater. A CO 2 capture efficiency as high as 91% is achieved for our EHL flow cell. We have demonstrated that the electrochemical hydrogen-looping flow cell can remove CO 2 from simulated seawater at a record low electric energy consumption of 660 kWh ton –1 CO 2 , which is a significant reduction of 56% compared with the currently used bipolar membrane electrodialysis technology. In conclusion, the electrochemical hydrogen-looping flow cell with its much lower energy consumption provides an economical approach for direct removal of CO 2 from seawater at practical scale.

Electrical energy↗

Morphology and chemical behavior of model CsO x /Cu 2 O/Cu(111) nanocatalysts for methanol synthesis: Reaction with CO 2 and H 2

Cs is a promoter of Cu-based catalysts for the synthesis of alcohols from CO 2 hydrogenation. Scanning tunneling microscopy and ambient-pressure x-ray photoelectron spectroscopy were used to study the morphology and chemical properties of surfaces generated by the deposition of cesium on Cu 2 O/Cu(111) and Cu(111) substrates. CsO x nanostructures were formed after Cs metal was deposited on Cu 2 O/Cu(111) at 300 K. The formed CsO x protrude over the surface of copper oxide by 2–4 Å, with the dimension at the base of the nanostructures being in the range of 1–3 nm. Heating to elevated temperature induced significant changes in the size and dispersion of the CsO x nanostructures, and there was a clear reconstruction of the copper oxide substrate, which then exhibited long range order with a hexagonally packed structure. The as-deposited and annealed surfaces of CsO x /Cu 2 O/Cu(111) were more reactive toward CO 2 than plain Cu 2 O/Cu(111) or clean Cu(111). Yet, none of them were stable in the presence of H 2 , which fully reduced the copper oxide at 400–450 K. In CsO x /Cu(111), the CsO x nanoclusters were dispersed all over the metallic copper in no particular order. The CsO x species had an average width of 2 nm and ~1 Å height. The CsO x /Cu(111) systems exhibited the highest activity for the binding and dissociation of CO 2 , indicating that the CsO x -copper interface plays a key role in alcohol synthesis.

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Cobalt‐Doped Bismuth Nanosheet Catalyst for Enhanced Electrochemical CO 2 Reduction to Electrolyte‐Free Formic Acid

Electrochemical carbon dioxide (CO 2 ) reduction reaction (CO 2 RR) to valuable liquid fuels, such as formic acid/formate (HCOOH/HCOO − ) is a promising strategy for carbon neutrality. Enhancing CO 2 RR activity while retaining high selectivity is critical for commercialization. To address this, we developed metal-doped bismuth (Bi) nanosheets via a facile hydrolysis method. These doped nanosheets efficiently generated high-purity HCOOH using a porous solid electrolyte (PSE) layer. Among the evaluated metal-doped Bi catalysts, Co-doped Bi demonstrated improved CO 2 RR performance compared to pristine Bi, achieving ~90 % HCOO − selectivity and boosted activity with a low overpotential of ~1.0 V at a current density of 200 mA cm −2 . In a solid electrolyte reactor, Co-doped Bi maintained HCOOH Faradaic efficiency of ~72 % after a 100-hour operation under a current density of 100 mA cm −2 , generating 0.1 M HCOOH at 3.2 V. Density functional theory (DFT) results revealed that Co-doped Bi required a lower applied potential for HCOOH generation from CO 2 , due to stronger binding energy to the key intermediates OCHO* compared to pure Bi. In conclusion, this study shows that metal doping in Bi nanosheets modifies the chemical composition, element distribution, and morphology, improving CO 2 RR catalytic activity performance by tuning surface adsorption affinity and reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reduction of CO 2 and CS 2 with Uranium(III) Metallocene Aryloxides

Herein, the reactivity of two metallocene aryloxide U(III) complexes, [(C 5 Me 5 ) 2 U(O-Ar)], Ar = 4- t BuC 6 H 4 , 1; Ar = 2,6- t Bu 2 -4-CH 3 C 6 H 2 (BHT), 3, with CO 2 and CS 2 has been investigated. The reaction of 1 with CO 2 produces a bridging oxo complex, [{(C 5 Me 5 ) 2 (4- t BuC 6 H 4 -O)U} 2 (μ 2 -O)], 4, while 3 with CO 2 results in reductive disproportionation to form the bridging carbonate species, [{(C 5 Me 5 ) 2 (BHT)U} 2 (μ 2 -κ 2 :η 1 -CO 3 )], 5. The difference in reactivity can be attributed to the steric properties of the ligand because the reaction of 3 with an oxo-delivering agent yields a U(V) terminal oxo complex, [(C 5 Me 5 ) 2 (BHT)U=O], 6. Reduction of CS 2 to form a bridging (CS 2 ) 2- ligand, [{(C 5 Me 5 ) 2 (tBuC 6 H 4 -O)U}2(μ 2 -CS 2 )], 7, is observed with 1, while the reaction of 3 with CS 2 also produces a bridging (CS 2 ) 2- reduced ligand complex, followed by C-H bond activation of a methyl group from one (C5Me 5 ) 1- ring, [(C5Me 5 ) 2 (BHT)U{μ 2 -C(H)S 2 }U(C 5 Me 4 CH 2 )(C 5 Me 5 )(BHT)], 8. All compounds are characterized by NMR and IR spectroscopy, and their solid-state structures are determined by X-ray crystallography.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory

Renewably driven, electrochemical conversion of carbon dioxide into value-added products is expected to be a critical tool in global decarbonization. However, theoretical studies based on the computational hydrogen electrode largely ignore the nonlinear effects of the applied potential on the calculated results, leading to inaccurate predictions of catalytic behavior or mechanistic pathways. Here, we use grand canonical density functional theory (GC-DFT) to model electrochemical CO2 reduction (CO2R) over metal- and nitrogen-doped graphene catalysts (MNCs) and explicitly include the effects of the applied potential. We used GC-DFT to compute the CO2 to CO reaction intermediate energies at -0.3, -0.7, and -1.2 VSHE catalyzed by MNCs each doped with 1 of the 10 3d block metals coordinated by four pyridinic nitrogen atoms. Our results predict that Sc-, Ti-, Co-, Cu-, and Zn-N4Cs effectively catalyze CO2R at moderate to large reducing potentials (-0.7 to -1.2 VSHE). ZnN4C is a particularly promising electrocatalyst for CO2R to CO both at low and moderate applied potentials based on our thermodynamic analysis. Our findings also explain the observed pH independence of CO production over FeN4C and predict that the rate-determining step of CO2R over FeN4C is not *CO2- formation but rather *CO desorption. Additionally, the GC-DFT-computed density of states analysis illustrates how the electronic states of MNCs and adsorbates change non-uniformly with applied potential, resulting in a significantly increased *CO2- stability relative to other intermediates and demonstrating that the formation of the adsorbed *CO2- anion is critical to CO2R activation. This work demonstrates how GC-DFT paves the way for physically realistic and accurate theoretical simulations of reacting electrochemical systems.

CO2 reduction↗

Membrane‐electrode assembly design parameters for optimal CO 2 reduction

Commercial-scale generation of carbon-containing chemicals and fuels by means of electrochemical CO 2 reduction (CO 2 R) requires electrolyzers operating at high current densities and product selectivities. Membrane-electrode assemblies (MEAs) have been shown to be suitable for this purpose. In such devices, the cathode catalyst layer controls both the rate of CO 2 R and the distribution of products. In this study, we investigate how the ionomer-to-catalyst ratio (I:Cat), catalyst loading, and catalyst-layer thickness influence the performance of a cathode catalyst layer containing Ag nanoparticles supported on carbon. In this paper, we explore how these parameters affect the cell performance and establish the role of the exchange solution (water vs. CsHCO 3 ) behind the anode catalyst layer in cell performance. We show that a high total current density is best achieved using an I:Cat ratio of 3 at a Ag loading of 0.01–0.1 mg Ag /cm 2 and with a 1.0 M solution of CsHCO 3 circulated behind the anode catalyst layer. For these conditions, the optimal CO partial current density depends on the voltage applied to the MEA. The work also reveals that the performance of the cathode catalyst layer is limited by a combination of the electrochemically active surface area and the degree to which mass transfer of CO 2 to the surface of the Ag nanoparticles and the transport of OH – anions away from it limit the overall catalyst activity. Hydration of the ionomer in the cathode catalyst layer is found not to be an issue when using an exchange solution. The insights gained allowed for a Ag CO 2 R MEA that operates between 200 mA/cm 2 and 1 A/cm 2 with CO faradaic efficiencies of 78–91%, and the findings and understanding gained herein should be applicable to a broad range of CO 2 R MEA-based devices.

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Pure-Water-Fed Forward-Bias Bipolar Membrane CO 2 Electrolyzer

Coupling renewable electricity to reduce carbon dioxide (CO 2 ) electrochemically into carbon feedstocks offers a promising pathway to produce chemical fuels sustainably. While there has been success in developing materials and theory for CO 2 reduction, the widespread deployment of CO 2 electrolyzers has been hindered by challenges in the reactor design and operational stability due to CO 2 crossover and (bi)carbonate salt precipitation. Herein, we design asymmetrical bipolar membranes assembled into a zero-gap CO 2 electrolyzer fed with pure water, solving both challenges. By investigating and optimizing the anion-exchangelayer thickness, cathode differential pressure, and cell temperature, the forward-bias bipolar membrane CO 2 electrolyzer achieves a CO faradic efficiency over 80% with a partial current density over 200 mA cm –2 at less than 3.0 V with negligible CO 2 crossover. In addition, this electrolyzer achieves 0.61 and 2.1 mV h –1 decay rates at 150 and 300 mA cm –2 for 200 and 100 h, respectively. Postmortem analysis indicates that the deterioration of catalyst/polymer– electrolyte interfaces resulted from catalyst structural change, and ionomer degradation at reductive potential shows the decay mechanism. Furthermore, all these results point to the future research direction and show a promising pathway to deploy CO 2 electrolyzers at scale for industrial applications.

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Plasmonic Energetic Electrons Drive CO 2 Reduction on Defective Cu 2 O

Plasmonic photoreduction of CO 2 is valuable for decarbonization and producing value-added chemicals. However, insights into the mechanisms of this reaction remain elusive, particularly regarding the roles of structural defects and their interplay with the nonequilibrium charge carriers. Here, we report density functional theory calculations on Cu 2 O, a prototype photocatalyst, through which we investigate CO 2 reduction over three defected facets to reveal the interfacial charge transfer and bond dynamics under plasmonic excitation. We find that the activation barrier of C–O bond cleavage decreases from 3.2 to about 1 eV, assisted by oxygen vacancies, and that the remaining barrier can be further reduced or eliminated at the plasmon-excited states when Cu 2 O is integrated with plasmonic metals. The regeneration of oxygen vacancies (by H 2 to form water) on Cu 2 O to complete the catalysis cycle is feasible and not affected by the energetic electrons. Furthermore, our calculations thus show the important synergistic effect of energetic electrons and point defects to promote CO 2 reduction.

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Insight into Acetic Acid Synthesis from the Reaction of CH 4 and CO 2

The reaction of CH 4 and CO 2 to produce acetic acid is an atom-efficient way for using carbon resources and for mitigating CO 2 emissions. This article provides a critical assessment of the progress in this catalytic reaction from the perspective of identifying and constructing the active sites. We elucidate how Cu- and Zn-based catalysts with different structures are used for the activation of CH 4 and CO 2 . The differences in the metal oxidation state may affect the adsorption of CH 4 and CO 2 and consequently change the activation barriers for the dissociation of the C–H bond of CH 4 and the C–C coupling reaction. We discuss how the active sites and transition states can be modified by the location of metal sites, the framework environment, and the promotion effect of different acid sites. Additionally, we also compare different technologies, including catalyst pretreatment, preactivation with CO 2 , tandem reaction, and plasma-driven catalysis for the CH 4 and CO 2 conversion. We conclude by identifying opportunities for improving the efficiency of heterogeneous catalysts for this important reaction.

54 ENVIRONMENTAL SCIENCES↗

Oxidation State and Surface Reconstruction of Cu under CO 2 Reduction Conditions from In Situ X-ray Characterization

The electrochemical CO 2 reduction reaction (CO 2 RR) using Cu-based catalysts holds great potential for producing valuable multi-carbon products from renewable energy. However, the chemical and structural state of Cu catalyst surfaces during the CO 2 RR remains a matter of debate. In this paper, we show the structural evolution of the near-surface region of polycrystalline Cu electrodes under in situ conditions through a combination of grazing incidence X-ray absorption spectroscopy (GIXAS) and X-ray diffraction (GIXRD). The in situ GIXAS reveals that the surface oxide layer is fully reduced to metallic Cu before the onset potential for CO 2 RR, and the catalyst maintains the metallic state across the potentials relevant to the CO 2 RR. We also find a preferential surface reconstruction of the polycrystalline Cu surface toward (100) facets in the presence of CO 2 . Quantitative analysis of the reconstruction profiles reveals that the degree of reconstruction increases with increasingly negative applied potentials, and it persists when the applied potential returns to more positive values. These findings show that the surface of Cu electrocatalysts is dynamic during the CO 2 RR, and emphasize the importance of in situ characterization to understand the surface structure and its role in electrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗