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At least 145 records · Page 8

Enhancing Electrochemical CO2 Conversion by Controlling Electrocatalysts' Structure

Electrochemical reduction of CO2 (CO2R) to valuable, carbon-neutral chemical feedstocks and storable fuels driven by renewable electricity has been recognized as one of the promising pathways to mitigate the greenhouse effect, reduce global demand for fossil fuels, achieve carbon neutrality, and create sustainable energy. Tremendous ongoing efforts have focused on controlling the morphology, composition, structure, size, defects, etc., of the electrocatalysts to improve product selectivity, activity, and durability to approach the feasibility of practical applications (current density higher than 200 mA/cm2 and lifetime ~1,000 hr+). This presentation will discuss how the geometry and surface composition of novel copper- and tin-based catalysts would maximize the CO2 conversion to carbon monoxide and liquid formic acid/formate in both common aqueous H-cell and electrolyzer configurations. Several spectroscopic, microscopic, and electrochemical characterization tools have been utilized to correlate the changes in the structural, physico-chemical, and electronic properties with the catalytic activity. Our work provides additional electrocatalyst design considerations for high-performance CO2 electrolysis.

Nguyen Phan, Thuy Duong↗

Anolyte Buffering and CO Coverage Effects in the Electrochemical Reduction of CO at Cu Electrocatalysts

Electrolytic CO reduction was investigated at copper electrocatalysts in zero-gap membrane electrode assemblies as a function of buffering agents and cofeeding with CO 2 or Ar. Results show an acetate Faradaic efficiency (FE) of 90% at 300 mA cm −2 using pure CO feeds and phosphate-buffered anolyte near pH 8. When using CO feeds with more alkaline anolytes, the hydrogen evolution reaction becomes the dominant reduction reaction, independent of the buffer. Product distributions of cofeeding experiments with CO and CO 2 show that increasing CO 2 cofeeding results in increased selectivity toward ethylene (42% FE) in near-neutral KHCO 3 anolytes or ethanol (40% FE) in alkaline KOH anolytes. Evaluation of several commercial anion exchange membranes shows similar selectivity trends, suggesting product selectivity is dominated by the local pH and surface coverage of CO. Based on these results, we propose pH buffering and CO coverage behaviors that facilitate high selectivities to acetate.

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Janus Nanocages of Platinum-Group Metals and Their Use as Effective Dual-Electrocatalysts

Janus nanocages with distinctive platinum-group metals on the outer and inner surfaces can naturally catalyze at least two different reactions. In this work, we report a general method based on successive deposition and then selective etching for the facile synthesis of such nanocages. Herein, we have fabricated 11 different types of Janus nanocages characterized by a uniform size and well-defined {100} facets, together with porous, ultrathin, asymmetric walls up to 1.6 nm thick. When tested as dual-electrocatalysts toward oxygen reduction and evolution reactions, the Janus nanocages based on Pt and Ir exhibited superior activities depending on the thickness and relative position of the metal layer. Density functional theory studies suggest that the alloy composition and surface structure of the nanocages both play important roles in enhancing the electrocatalytic activities by modulating the stability of key reaction intermediates.

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Atomic-scale modeling of C/N kinetic stability descriptors for PGM-free electrocatalysts at finite temperatures

The durability of platinum group metal-free (PGM-free) electrocatalysts is a major barrier to their usage in polymer electrolyte fuel cell cathodes. C and N removal from active sites may play an important role in the catalyst’s ability to maintain high activity. While C degradation mechanisms are kinetically controlled, previous studies have focused on thermodynamic descriptors. In this work, we develop a temperature-dependent kinetic descriptor of C and N stability using an electron beam-damage model. Our approach considers the electron beam energy threshold (EBET) describing the knock-on displacement of C and N atoms as a stability descriptor for atomic structures. The stability of different sites is calculated to be different showing this approach can discriminate between similar sites with varied configurations. Additionally, we provide important insight regarding TEM beam damage of proposed active sites. We calculate 60 keV electrons can damage some proposed active site structures even at room temperature.

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Tantalum oxide stabilized molybdenum-doped ruthenium oxide electrocatalysts for PEM water electrolysis

Proton exchange membrane (PEM) water electrolysis offers key advantages, including high current density, high efficiency, and compact system architecture for hydrogen production. However, its widespread implementation is limited by the scarcity and high cost of Ir-based anodic catalysts. Herein, we report an Ir-free electrocatalyst for the acidic oxygen evolution reaction (OER): tantalum oxide (TaO x )–coated molybdenum-doped RuO 2 (TaO x -MoRuO 2 ). The catalyst exhibits a low overpotential of 180 mV at 10 mA cm -2 and excellent durability, with a degradation rate of 0.034 mV h -1 over a 150-hour test at 50 mA cm -2 —surpassing other Ru-based catalysts evaluated under similar conditions. A PEM electrolyzer employing TaO x -MoRuO 2 as the anode maintained stable operation for 100 hours at 500 mA cm -2 . In conclusion, the TaO x coating layer suppresses Ru and Mo dissolution, thus enhancing their stability likely via interfacial electronic reconfiguration of Ru and Mo mediated by bridging oxygen atoms.

Durability↗

Machine learning-guided design, synthesis, and characterization of atomically dispersed electrocatalysts

The recent integration of machine learning into materials design has revolutionized the understanding of structure–property relationships and optimization of material properties beyond the trial-and-error paradigm. On one hand, machine learning has significantly accelerated the development of atomically dispersed metal-nitrogen-carbon (M-N-C) electrocatalysts, which traditionally heavily relied on heuristic approaches. On the other hand, the primary challenge of leveraging machine learning to expedite M-N-C materials discovery lies in the cost associated with data collection. Here, we review recent machine learning integration strategies for M-N-C catalyst development, including discussions on the typical algorithms such as symbolic regression and convolutional neural networks employed for the theoretical design, synthesis optimization via active learning, and advanced microscopy characterization. Subsequently, we provide our perspective on potential near-future directions for furthering machine learning-assisted development of new M-N-C catalysts and elucidating the complex physicochemical mechanisms governing the selectivity, activity, and durability in this class of materials.

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W-induced morphological modification of NiFe layered double hydroxides as efficient electrocatalysts for overall water splitting

Layered double hydroxides (LDHs) are one of the most efficient electrocatalysts for water splitting due to their nanosheet features and compositional flexibilities. This work explored the impact of W precursor concentration (0 ~ 10 mM) on LDH morphologies and performance in hydrogen production. Using an electrodeposition W-doping process, W-induced NiFe LDHs (NiFeW-LDHs) were in-situ grown on carbon fiber papers for water splitting. A performance peak was found at a W doping of 5 mM with well-aligned nanosheets, which not only boosted the charge transfer ability and gas evolution but also offered more than a four-fold electrochemical surface area increase compared to film-like NiFe hydroxides. The NiFeW-LDHs exhibited remarkable performance compared to NiFe hydroxides, showing decreased overpotentials of 31 mV and 114 mV for the oxygen evolution reactions (OERs) and hydrogen evolution reactions (HERs) at 10 mA/cm 2 and -10 mA/cm 2 , respectively, in alkaline media. The performance enhancement at 5 mM W-doping was linked to the well-aligned NiFeW-LDH nanosheets; smaller, less-textured nanosheets were observed with lower or higher W precursor concentrations (2.5 mM or >7.5 mM), leading to inferior OER and HER performances. Hence, an appropriate W doping is crucial to generating the morphologies that contribute to the higher performance of NiFeW-LDHs.

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Enhancing the activity of Fe-N-C oxygen reduction reaction electrocatalysts by high-throughput exploration of synthesis parameters

Here, the most active class of platinum group metal-free (PGM-free) oxygen reduction reaction (ORR) electrocatalysts in acidic electrolytes are those synthesized by heat treatment of iron, carbon, nitrogen precursors (Fe-N-C). Due to the large number of possible precursor compounds, a small fraction of the synthesis variable space has been explored. Correlation of synthesis variables with Fe speciation and ORR activity has been limited. In this work, an automation platform and a multi-port ball-milling were utilized to evaluate the effects of synthesis variables, such as identity of iron precursor, iron loading, and carbon and nitrogen sources on the ORR activity of iron -nitrogen-carbon catalysts in acidic electrolyte. The ORR activity is correlated with catalyst Fe speciation determined using Fe K-edge X-ray absorption spectroscopy (XAFS).

30 DIRECT ENERGY CONVERSION↗

Iron redox behavior and oxygen reduction activity of Fe-N-C electrocatalysts in different electrolytes

The iron redox behavior and oxygen reduction reaction (ORR) activity of Fe-N-C ORR electrocatalysts synthesized by a variety of techniques were investigated as a function of the identity of the electrolyte anion (bisulfate/sulfate or perchlorate) at a constant pH. In situ X-ray absorption spectroscopy data support the assignment of the redox peaks in the voltammograms to the Fe 3+ /Fe 2+ redox couple. It was found that for a given Fe-N-C catalyst, there is a correlation between the Fe redox couple peak potential and the ORR activity in perchloric acid electrolyte, but not in sulfuric acid electrolyte. While a higher Fe redox couple potential (≥ 110 mV higher) was observed in perchloric acid electrolyte, a higher ORR activity was obtained in sulfuric acid electrolyte. Here, the higher ORR activity observed in sulfuric acid than perchloric acid was correlated with the higher peak current and larger faradaic charge for the Fe redox couple. A study of the Fe redox behavior using a cavity microelectrode, eliminating the impact of ionomer, showed that the interaction of H 2 SO 4 with Fe-N-C is stronger than that of HClO 4 and that Fe redox in both electrolytes is a reversible surface electrochemical reaction.

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Adaptive learning-driven high-throughput synthesis of oxygen reduction reaction Fe–N–C electrocatalysts

Reducing human reliance on inefficient energy systems and fossil fuels has become more urgent due to the consequences of global climate change. However, traditional trial-and-error approaches have hampered our ability to accelerate the discovery and implementation of functional materials for efficient energy conversion devices, such as polymer electrolyte fuel cells (PEFCs). To address this, we develop an adaptive learning framework that integrates machine learning and state-of-the-art capabilities in high-throughput synthesis to achieve expedited optimization of iron-nitrogen-carbon PEFC oxygen reduction reaction (ORR) electrocatalysts. We use statistical inference, uncertainty quantification, and global optimization to build a computational design-of-experiment tool that identifies the optimum compositions to be investigated next to reduce the demands placed on experimental materials discovery. We benchmark the ability of the proposed strategy to discover optimum catalyst synthesis conditions in a six-dimensional search space when starting with a thirty-six-sample database. By following the adaptive learning strategy, we synthesize fourteen new catalysts from approximately ten billion unique compositions and discover four catalysts that outperform all original samples. The best machine learning-optimized catalyst is 33% more active than the highest-performing one in the initial database, showing an ORR activity seven times larger than those typically reported for the same class of materials.

36 MATERIALS SCIENCE↗

Lattice Strain Measurement of Core@Shell Electrocatalysts with 4D Scanning Transmission Electron Microscopy Nanobeam Electron Diffraction

Strain engineering enables the direct modification of atomic bonding and is currently an active area of research aimed at improving electrocatalytic activity. However, directly measuring the lattice strain of individual catalyst nanoparticles is challenging, especially at the scale of a single unit cell. In this study, we quantitatively map the strain present in rhodium@platinum (core@shell) nanocube electrocatalysts using conventional aberration-corrected scanning transmission electron microscopy (STEM) and the recently developed technique of 4D-STEM nanobeam electron diffraction. We demonstrate that 4D-STEM combined with data preconditioning allows for quantitative lattice strain mapping with subpicometer precision and without the influence of scan distortions. When combined with multivariate curve resolution, 4D-STEM allows us to distinguish the nanocube core from the shell and to quantify the unit cell size as a function of distance from the core–shell interface. Our results demonstrate that 4D-STEM has significant precision and accuracy advantages in strain metrology of catalyst materials compared to aberration-corrected STEM imaging and is beneficial for extracting information about the evolution of strain in catalyst nanoparticles.

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Sustainable Oxide Electrocatalyst for Hydrogen- and Oxygen-Evolution Reactions

In this work, an electrocatalyst for water splitting based on earth-abundant metals is reported. This perovskite-oxide catalyst, CaSrFe 0.75 Co 0.75 Mn 0.5 O 6-δ (CSFCM), is examined using both experimental and computational methods. It demonstrates a combination of properties, which include (a) very high activity for the oxygen-evolution reaction with an overpotential of eta = 0.19 V at 10 mA/cm 2 , (b) high stability over 1000 cycles of catalysis, (c) the ability to catalyze the hydrogen-evolution reaction effectively in both acidic and basic conditions, and (d) catalytic activity as a single-phase bulk material without the need for any additional processing, multicomponent composite preparation, or nanofabrication. Therefore, the catalytic activity of CSFCM is intrinsic, making it a good benchmark compound for future studies of electrocatalytic parameters. This work also highlights the impact of systematic structural design on electrocatalytic activity. Results from density functional theory calculations indicate that in addition to an optimal e g occupancy of similar to 1, an additional descriptor, i.e., maximizing the number of free e g carriers, correlates with the electrocatalytic activity.

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Synergistic Multisites Fe 2 Mo 6 S 8 Electrocatalysts for Ambient Nitrogen Conversion to Ammonia

Electrochemical hydrogenation of N 2 under ambient conditions is attractive for sustainable and distributable NH 3 production but is limited by the lack of selective electrocatalysts. In this work, we describe active site motifs based on the Chevrel phase chalcogenide Fe 2 Mo 6 S 8 that exhibit intrinsic activities for converting N 2 to NH 3 in aqueous electrolytes. Despite having a very low specific surface area of ~2 m 2 /g, this catalyst exhibited a Faradaic efficiency of 12.5% and an average rate of 70 μg h –1 mg cat –1 for NH 3 production at -0.20 V vs RHE. Such activities were attributed to the unique composition and structure of Fe 2 Mo 6 S 8 that provide synergistic multisites for activating and associating key reaction intermediates. Specifically, Fe/Mo sites assist adsorption and activation of N 2 , whereas S sites stabilize hydrogen intermediate H ad * for N 2 hydrogenation. Fe in Fe 2 Mo 6 S 8 enhances binding of S with H ad * and thus inhibits the competing hydrogen evolution reaction. The spatial geometry of Fe, Mo, and S sites in Fe 2 Mo 6 S 8 promotes conversion of N 2 –H ad * association intermediates, reaching a turnover frequency of ~0.23 s –1 for NH 3 production.

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Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure–Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. Here, we present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

36 MATERIALS SCIENCE↗

Stable Metal–Organic Electrocatalysts for Anion-Exchange Membrane Water Electrolyzers by Defect Engineering

Developing efficient and durable catalysts for the alkaline oxygen evolution reaction (OER) is vital to achieving practical anion-exchange membrane water electrolyzers (AEMWE) for green hydrogen production. In this work, we break the activity-stability trade-off of electrocatalysis by defect engineering of Ni-based metal-organic electrocatalysts (Ni-benzene dicarboxylate; Ni-BDC) through coordinating ferrocenecarboxylates (Fc) to the metal sites. Experimental results collectively reveal that the defect MOF (Ni-BDC:Fc_5:1) exhibits a high OER turnover frequency of 0.75 O 2 s -1 at 300 mV overpotential. Operando Raman spectroscopy and isotope-labelling electrochemical mass spectrometry measurements indicate the structure of Ni-BDC:Fc_5:1 is also more stable in service than that of pure Ni-BDC. The high activity and stability could be attributed to the moderate defects (i.e., unsaturated Ni sites) in the structure that not only increase the intrinsic activity and stability of the local active environment by inhibiting lattice oxygen exchange, but also electrochemically activates the bulk of the catalysts by creating a porous network that facilitates internal H 2 O/OH - conduction with enhanced electronic conduction. Accordingly, an AEMWE employing Ni-BDC:Fc_5:1 as the OER catalyst delivers an industrial-level current density of 1 A cm -2 at 1.73 V cell and can be steadily operated for more than 120 hours.

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Compositional Phase Control in High-Entropy Alloy Electrocatalysts

High-entropy alloys (HEAs) provide uniquely tunable structural and electronic properties that enable robust electrocatalysis. While compositional manipulation of HEAs is well-known, systematically controlling the crystalline phase and morphology remains a challenge that could provide new avenues for controlling reactive sites and physical properties. Here, we show the preferential stabilization of mixed fcc/bcc to fcc phases by controlling the Au content in quinary AuPdFeCoNi HEA nanoparticles. This systematic structural and compositional control, when investigated with an ensemble of electronic, X-ray synchrotron, and surface techniques, allows us to identify the critical short- (few-Å) and medium- (6–10 Å) range structural motifs that deliver exceptional hydrogen evolution reaction (HER) catalysis. Specifically, these HEAs exhibit both outstanding durability (240 h) and high mass activity (50 A/mg PGM ) normalized to noble metal content, outperforming commercial Pt/C (3.18 A/mg PGM ). This structural control over HEA morphology, and its direct association with changes in specific metallic oxidation states and pair–pair atomic structural features, provides new means and strategies for finely designing robust and sustainable electrocatalysts with a majority nonprecious metal composition.

36 MATERIALS SCIENCE↗

A highly efficient atomically thin curved PdIr bimetallene electrocatalyst

Abstract The multi-metallene with an ultrahigh surface area has great potential in precise tuning of surface heterogeneous d-electronic correlation by surface strain effect for the distinctive surface electronic structure, which is a brand new class of promising 2D electrocatalyst for sustainable energy device application. However, achieving such an atomically thin multi-metallene still presents a great challenge. Herein, we present a new synthetic method for an atomic-level palladium-iridium (PdIr) bimetallene with an average thickness of only ∼1.0 nm for achieving superior catalysis in the hydrogen evolution reaction (HER) and the formic acid oxidation reaction (FAOR). The curved PdIr bimetallene presents a top-ranked high electrochemical active area of 127.5 ± 10.8 m2 gPd+Ir−1 in the reported noble alloy materials, and exhibits a very low overpotential, ultrahigh activity and improved stability for HER and FAOR. DFT calculation reveals that the PdIr bimetallene herein has a unique lattice tangential strain, which can induce surface distortion while concurrently creating a variety of concave-convex featured micro-active regions formed by variously coordinated Pd sites agglomeration. Such a strong strain effect correlates the abnormal on-site active 4d10-t2g-orbital Coulomb correlation potential and directly elevates orbital-electronegativity exposure within these active regions, resulting in a preeminent barrier-free energetic path for significant enhancement of FAOR and HER catalytic performance.

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