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At least 307 records · Page 17

Restructuring of Benzimidazole-Based Copper Complexes during Electrochemical CO 2 Reduction

Copper-based molecular catalysts have been widely used for the electrochemical reduction of carbon dioxide (ERCO 2 ). However, establishing a correlation between structure and catalytic performance has been challenging due to the dynamic nature of these materials under ERCO 2 working conditions. Here, we report on the restructuring of the copper complexes [Cu(bzimpy)Cl 2 ] and [Cu(pyrben) 2 (NO 3 )]NO 3 during ERCO 2 in an acidic medium, evidencing its effects on the observed activity, selectivity, and stability. In situ X-ray absorption spectroscopy (XAS) suggested that, at sufficiently negative potentials, the Cu 2+ centers of both complexes are reduced to undercoordinated Cu 0 species. Pb underpotential deposition of post-ERCO 2 samples indicated that such Cu 0 species also present a dominant contribution of the (100) domain, which is in line with the high Faradaic efficiency toward C 2 products (∼45%) shown by both complexes at −1.24 V vs RHE. By combining online electrochemical mass spectrometry, in situ XAS, electron paramagnetic resonance (EPR), and quantitative product analysis, we found that [Cu(bzimpy)Cl 2 ] exhibits a partially reversible restructuring, regenerating the main complex moiety, [Cu(bzimpy)] 2+ , and its geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying Critical Electrode Metrics for Efficient, Selective CO 2 Electrochemical Conversion

Low-temperature electrochemical CO 2 reduction (CO 2 R) in zero-gap membrane electrode assembly (MEA) reactors presents a scalable route to fuels and carbon utilization. However, performance at industrially relevant current densities hinges on mesoscale catalyst layer integration, particularly at the ionomer|catalyst interface. Here, we demonstrate a generalizable in situ electrochemical impedance spectroscopy (EIS) method. We utilize this technique to decouple electrode-level parameters that are correlated to the overall MEA performance. By performing this ex situ EIS method on CO 2 -to-CO catalyst-coated membranes with systematically varied ionomer-to-catalyst (I:C) ratios, we reveal a pronounced dependence of performance, ion transport resistance, and catalyst utilization on the I:C ratio as well as the electrode conditioning. We demonstrate that an optimal I:C ratio exists at which ion transport resistance is minimized and Faradaic efficiency for CO production is maximized. Beyond the electrodes examined, here we compare ion transport resistance to MEA selectivity/Faradaic efficiency obtained in prior studies, revealing a clear correlation between the two. These results suggest that ion transport resistance within the catalyst layer may be a quantitative predictor of MEA performance which underscores the importance of mesoscale integration in achieving scalable CO 2 R technologies.

08 HYDROGEN↗

Green Methanol via an Integrated Direct Air Capture, CO 2 Electrolyzer, and Hydrogenation Reactor

This project pioneered a groundbreaking reactor design to produce green methanol by harnessing the electrochemical CO 2 reduction reaction (eCO 2 RR), a cornerstone of power-to-fuels technology. The effort integrated three innovative technologies to achieve carbon-neutral methanol production at a target cost of under $\$$800/ton: 1. Direct Air Capture (DAC): Using a cutting-edge sorbent material developed at Holocene, scalable models were developed to integrate captured atmospheric CO₂ into the reactor system. 2. Intermediate-Temperature CO 2 Electrolyzer: Developed by the University of Tennessee (UTK), this electrolyzer utilizes a cost-effective, proton-conducting solid acid electrolyte (CsH 2 PO 4 , CDP) and a mixed-metal oxide cathode. It achieves high faradaic efficiencies (>98%) by effectively suppressing hydrogen evolution at high current densities, converting CO 2 to CO with remarkable selectivity. 3. Catalysis and Reactor Engineering: Oak Ridge National Laboratory (ORNL) contributed world-class expertise in heterogeneous catalysis and reactor design. Their advanced ASPEN modeling drove systems integration and supported techno-economic and life cycle analyses. This effort was further bolstered by partnerships with industry leaders Air Company and Plug Power, who provided critical guidance on scaling, systems engineering, and the integration of water electrolyzers into large-scale operations. During Phase 1, the team focused on modeling and validating a lab-scale reactor demonstrating the feasibility of the integrated approach. Key accomplishments include a 52% increase in current density at 0.8 V while maintaining >98% CO faradaic efficiency, successful 10× scale-up of the electrolyzer with performance within 5% of coin-cell results, best-in-class durability (168-hour test at 0.6 V with 0.14 mA/cm 2 -h degradation), validated TEA confirming the $\$$800/ton methanol target, and completed preliminary LCA showing potential for net-negative GHG emissions under renewable energy scenarios.

10 SYNTHETIC FUELS↗

Electrocatalytic Reduction of CO 2 to CO over Ag(110) and Cu(211) Modeled by Grand-Canonical Density Functional Theory

We report the results of modeling CO 2 reduction (CO 2 R) to CO over Ag(110) and Cu(211) surfaces at different applied potentials using grand-canonical density functional theory (GC-DFT), a method specifically designed to accurately model electrochemical systems. In addition to demonstrating GC-DFT’s ability to accurately model electrochemical processes, we also compare it with the computational hydrogen electrode (CHE) approach. GC-DFT predicts that the geometries of these reacting systems strongly depend on the applied potential and the Helmholtz free energies vary nonlinearly with the applied potential, which contradicts a central assumption of the CHE approach. The CHE approach neglects the change in the number of electrons on the electrode surface at different applied potentials, which reduces its accuracy as the potential changes from the potential of zero charge. Our results further demonstrate that the grand free energies of the reaction intermediates not only depend on the value of the applied potential but also on the metal surface type, adsorption site, and adsorbate. GC-DFT’s ability to predict the effect of the applied potential on adsorbate geometry enables it to evaluate different possible reaction mechanisms at different applied potentials. For instance, GC-DFT predicts that the first step of CO2R likely switches from proton-coupled electron transfer to sequential electron transfer and then proton transfer at more reducing potentials, a result that cannot be determined by the CHE because it assumes that all electron transfers are coupled to proton transfers and neglects the effect of the applied potential on the adsorbate geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Syngas Production at Si Hybrid Photoelectrodes Modified with Re(I) and Mn(I) Tricarbonyl Phenanthroline Complexes Containing Reactive Aryl Azide Groups

We installed molecular CO 2 reduction (CO 2 R) catalysts directly onto Si (photo)electrodes. The highly reactive M(5-azido-1,10-phenanthroline)(CO) 3 X (where M = Mn or Re, X = Br or Cl) complexes readily bubbled when dissolved in polar organic solvents, in both the presence and absence of an ultraviolet light source. When placed on hydrogen-terminated Si (H-Si) and native silicon oxide (SiOx), similar amounts of the complex were attached to the surface under illumination (367 nm, 50–200 mW/cm 2 ) or in the dark. Surprisingly, these films revealed submonolayer coverages instead of the multilayered structures we expected. DFT analyses support monolayer formation, showing that the triplet-state nitrene of the complex is more energetically favorable than the singlet state. Using controlled-potential electrolysis experiments, we showed that Re- and Mn-containing films on pSi photoelectrodes generated small amounts of CO when exposed to 1 atm of CO 2 and 1 sun illumination. These amounts of CO were an order of magnitude greater than control surfaces, producing 5.59 × 10 –7 mol CO/h for Re(az-phen) and 7.83 × 10 –7 mol CO/h for Mn(az-phen) films. Much of the charge passed at the pSi electrodes was consumed by the competing hydrogen evolution reaction, which we attribute to the low molecular coverage and the presence of native oxide on the electrode surface after attachment. Finally, this work demonstrates the feasibility of reacting azide-containing ligands with Si surfaces. Still, it highlights the need for alternative ligand structures and reaction conditions to form multilayer films.

azides↗

Sulfur Conversion to Donor‐Acceptor Ladder Polymer Networks through Mechanochemical Nucleophilic Aromatic Substitution for Efficient CO 2 Photoreduction

The development of synthetic methods capable of converting elemental sulfur into conjugated porous sulfur‐rich polymers remains a great challenge, although direct utilization of this readily available feedstock can significantly enrich its uses and circumvent environmental problems during sulfur storage. Here, we report herein mechanochemical (MC) nucleophilic aromatic substitution (S N Ar) that enables sulfur conversion into thianthrene‐bridged porous ladder polymer networks with dense donor‐acceptor (D−A) molecular junctions. We demonstrate that the key lies in the generation of bent thianthrene units through a solid‐state ball‐milling condensation reaction between 1,2‐dihaloarenes and elemental sulfur. We also show that the assembling of D−A structural motifs into porous networks affords efficient visible‐light‐driven photocatalytic reduction of carbon dioxide (CO 2 ) with water (H 2 O) vapor, in the absence of any additional photosensitizer, sacrificial agents or cocatalysts. Exceptional photoinduced charge separation along with boosted exciton dissociation results in a high‐performance of carbon monoxide (CO) production rate of 306.1 μmol g −1 h −1 with near 100 % CO selectivity, which is accompanied by H 2 O oxidation to O 2 , as confirmed by both experimental and theoretical results. We anticipate this novel MC S N Ar approach will advance processing techniques for direct sulfur utilization and facilitate new possibilities for the synthesis of D−A ladder polymer networks with promising potential in photocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High‐Concentration Alcohol Generation in Bipolar Membrane CO Electrolyzer

Electrochemical reduction of carbon dioxide and carbon monoxide offers an electricity‐powered route to make multicarbon liquid products. However, in conventional systems employing anion exchange membranes (AEMs), significant liquid product crossover leads to dilute product streams, increasing separation costs; and also produces unwanted anodic oxidation, further decreasing overall efficiency. Here, we report a forward‐biased bipolar membrane (FB‐BPM) system that achieves <10% liquid product crossover while sustaining a highly alkaline environment near the cathode, suppressing ethylene and hydrogen and favoring liquid products. By tuning catalyst composition to modulate the adsorption of *H and *OH, we steer selectivity toward acetate and alcohols. Using the FB‐BPM system, we achieve >25 wt% acetate on CuZn and >15 wt% alcohols on CuSn directly from the cathode outlet stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large scale energy analysis and renovation strategies for social housing in the historic city of Venice

Social houses built after the Second World War to accommodate workers and low-income families represent one of the major energy consumers and greenhouse gas emitters in the residential sector. Plans for their renovation are underway in all European countries, and the process is more complicated for Italian cities due to the lack of space and the large number of historical buildings. This study addresses this challenge by proposing a methodology to renovate a low-income district in the city of Venice using CityBES to model and evaluate energy conservation measures. CityBES is a web-based tool that allows users to employ urban building energy modeling for large-scale energy and retrofit analyses of building stocks. In the case study conducted for Venice's Santa Marta district, due to the particular context, four common energy conservation measures covering both the building envelope and heat generation boilers have been applied. The evaluation of energy-saving performances at the district level showed that the four measures together achieved 67% energy savings, an abatement in energy cost equal to 67%, and annual carbon dioxide emissions reduction of 1.1 MtCO 2 . Furthermore, the case study demonstrates a method and workflow replicable for energy retrofit analysis of building stocks in other historical districts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Engineering Catalyst–Electrolyte Microenvironments to Optimize the Activity and Selectivity for the Electrochemical Reduction of CO 2 on Cu and Ag

We report the electrochemical reduction of carbon dioxide (CO 2 R) driven by renewably generated electricity (e.g., solar and wind) offers a promising means for reusing the CO 2 released during the production of cement, steel, and aluminum as well as the production of ammonia and methanol. If CO 2 could be removed from the atmosphere at acceptable costs (i.e., <$100/t of CO 2 ), then CO 2 R could be used to produce carbon-containing chemicals and fuels in a fully sustainable manner. Economic considerations dictate that CO 2 R current densities must be in the range of 0.1 to 1 A/cm 2 and selectivity toward the targeted product must be high in order to minimize separation costs. Industrially relevant operating conditions can be achieved by using gas diffusion electrodes (GDEs) to maximize the transport of species to and from the cathode and combining such electrodes with a solid-electrolyte membrane by eliminating the ohmic losses associated with liquid electrolytes. Additionally, high product selectivity can be attained by careful tuning of the microenvironment near the catalyst surface (e.g., the pH, the concentrations of CO 2 and H 2 O, and the identities of the cations in the double layer adjacent to the catalyst surface).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantitative Imaging of Cobalt Phthalocyanine Distribution on Carbon Nanotubes: A Deep Learning Approach to Catalyst Characterization

Electrochemical reduction of carbon dioxide (CO 2 ) offers a pathway to valuable products, with catalysts playing a crucial role. This study investigates the distribution of cobalt tetraaminophthalocyanine (CoPc-NH 2 ) immobilized on carbon nanotubes (CNTs), utilizing high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to characterize CoPc-NH 2 distribution. A challenge in the quantitative HAADF-STEM analysis is the introduction of bias from manual Co atom identification. To address this, we developed and trained a convolutional neural network (CNN) using a data set generated from images of CoPc-NH 2 /CNT samples with varying Co loadings. The CNN, implemented in TensorFlow and Keras, facilitated Co atom detections. Analysis of the CNN-generated data confirmed a correlation between Co loading and surface density, consistent with findings from UV–vis spectroscopy. Furthermore, the application of Ripley’s L(d) function highlighted the presence of slight Co atom clustering. Furthermore, this work demonstrates the utility of the combined HAADF-STEM and CNN approach for providing spatially resolved information about catalyst distribution on nonplanar supports, revealing structural details that are typically lost through other characterization methods.

HAADF-STEM↗

Controlling Mass Transport in Direct Carbon Dioxide Zero-Gap Electrolyzers via Cell Compression

The development of high-performance CO 2 electrolyzers is crucial for accelerating the sustainable production of fuels and chemicals integrated with renewable energy sources. Here, we introduce a methodology to actively control mass transport inside a realistic zero-gap membrane electrode assembly of a CO 2 electrolyzer by varying the gasket thickness, which consequently changes the cell compression. This allows control over the thickness and porosity of the gas diffusion electrodes, influencing the overall electrolyzer performance, as demonstrated using Ag-deposited electrodes. At low operating voltages (<2.9 V), both high- and low-compression electrolyzers exhibit similar faradaic efficiencies and partial current densities for CO formation. However, at high voltages, the low-compression electrolyzer with high electrode porosity demonstrates superior CO selectivity and activity with suppressed H 2 formation. These experimental results are validated by the computational membrane electrode assembly (MEA) model developed by using the measured in situ electrode thicknesses and electrode porosities. Additionally, liquid electrolyte saturation at the catalyst layer is found to play a dominant role in determining the mass transport, resulting in a decreased electrolyzer performance with low electrode porosity. Finally, the systematic investigation in this study improves the understanding of the transport dynamics in MEA-based devices and provides insights into optimizing device design parameters for industry-relevant CO 2 electrolysis.

30 DIRECT ENERGY CONVERSION↗

Modulating CO 2 Electrocatalytic Conversion to the Organics Pathway by the Catalytic Site Dimension

Electrochemical reduction of carbon dioxide to organic chemicals provides a value-added route for mitigating greenhouse gas emissions. Here, we report a family of carbon-supported Sn electrocatalysts with the tin size varying from single atom, ultrasmall clusters to nanocrystallites. High single-product Faradaic efficiency (FE) and low onset potential of CO 2 conversion to acetate (FE = 90% @ –0.6 V), ethanol (FE = 92% @ –0.4 V), and formate (FE = 91% @ –0.6 V) were achieved over the catalysts of different active site dimensions. The CO 2 conversion mechanism behind these highly selective, size-modulated p-block element catalysts was elucidated by structural characterization and computational modeling, together with kinetic isotope effect investigation.

10 SYNTHETIC FUELS↗

Ligand removal energetics control CO 2 electroreduction selectivity on atomically precise, ligated alloy nanoclusters

Atomically precise, thiolate-protected gold nanoclusters (TPNCs) exhibit remarkable catalytic performance for the electrochemical reduction of carbon dioxide (CO 2 R) to CO. The origin of their high CO 2 R activity and selectivity has been attributed to partial ligand removal from the thiolate-covered surfaces of TPNCs to expose catalytically active sulfur atoms. Recently, heterometal doped (alloy) TPNCs have been shown to exhibit enhanced CO 2 R activity and selectivity compared to their monometallic counterparts. However, systematic studies on the effect of doping (metal type and location on TPNC) on active site exposure and CO 2 R activity are missing in literature. Herein, we apply Density Functional Theory calculations to investigate the effect of heterometal (Pt, Pd, Hg and Cd) doping of Au 25 (SR) 18 TPNC on the active site exposure and CO 2 R activity and selectivity. In this study, we reveal that doping significantly modifies relevant TPNC electronic properties, such as electron affinity, while also altering partial ligand removal and carboxyl (*COOH) intermediate formation energies. Furthermore, we demonstrate that changing the dopant (e.g. Hg) position can change the selectivity of the TPNC towards CO (g) or H 2(g) formation, highlighting the importance of dopant locations in TPNC-based CO 2 R. Most notably, we report a universal (i.e. capturing different dopant types and positions) linear trend between the ligand removal energy and i) the *COOH formation energy, as well as, ii) the hydrogen (*H) formation energy on the different alloy TPNCs. Thus, utilizing the ligand removal energy as a descriptor for CO 2 RR activity and selectivity, our work opens new avenues for accelerated computational screening of different alloy TPNCs for electrocatalytic CO 2 R applications.

54 ENVIRONMENTAL SCIENCES↗