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At least 487 records · Page 27

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DOE OSTI2025

Modeling household-level party composition behavior for multiparty activities: a random parameter nested logit modeling approach

This study presents findings of a household-level party composition model for multiparty activities. It exploits data from a comprehensive Household Travel Survey conducted by Chicago Metropolitan Agency of Planning. The study estimates a random parameter nested logit model to capture households’ unobserved preference heterogeneity and non-proportional substitution patterns in terms of activity party composition for multiparty activities. A wide variety of household demographics, activity attributes and residential neighborhood characteristics are examined in this paper. The magnitude of the impacts of the determinants are tested in this study by analyzing the elasticity of the variables, which suggests that household demographics and attributes of the multiparty activities have significant effects on the household-level activity party composition. Residential neighborhood characteristics, although somewhat less impactful, still play a meaningful role. This model will be implemented within the POLARIS transportation systems simulator to improve the activity generation modeling workflow, and the prediction accuracy of various activity-travel components.

activity party composition↗

DOE OSTI2022

Shape-driven, emergent behavior in active particle mixtures

Abstract Active particle systems can vary greatly from one-component systems of spheres to mixtures of particle shapes at different composition ratios. We investigate computationally the combined effect of anisotropy and stoichiometry on the collective behavior of two-dimensional active colloidal mixtures of polygons. We uncover three emergent phenomena not yet reported in active Brownian particle systems. First, we find that mixtures containing hexagons exhibit micro-phase separation with large grains of hexagonal symmetry. We quantify a measurable, implicit ‘steric attraction’ between the active particles as a result of shape anisotropy and activity. This calculation provides further evidence that implicit interactions in active systems, even without explicit attraction, can lead to an effective preferential attraction between particles. Next, we report stable fluid clusters in mixtures containing one triangle or square component. We attribute the fluidization of the dense cluster to the interplay of cluster destabilizing particles, which introduce grain boundaries and slip planes into the system, causing solid-like clusters to break up into fluid clusters. Third, we show that fluid clusters can coexist with solid clusters within a sparse gas of particles in a steady state of three coexisting phases. Our results highlight the potential for a wide variety of behavior to be accessible to active matter systems and establish a route to control active colloidal systems through simple parameter designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Short-term warming increased soil heterotrophic respiration due to enhanced active microbial community

Soil microbes, particularly active microbes, play a crucial role in conserving soil carbon under climate change, especially in forest ecosystems, constituting over 50% of global soil organic carbon. Nevertheless, the response mechanisms of active microbial community to climate warming and their subsequent impacts on soil heterotrophic respiration (Rh) remain insufficiently understood. To resolve this mechanistic uncertainty, we implemented a 3-year soil translocation experiment to investigate soil warming effects on active microbial community and Rh. We used 16S rRNA gene amplicon sequencing, Metatranscriptomics sequencing, coupled with correlation analyses to explore the linkages between warming-induced shifts in Rh and the active microbial community. Our results demonstrated that warming of soil induced a 55% enhancement in Rh. Concurrently, the Shannon index and Richness of active microbial community increased by 20% and 117%, respectively. Warming significantly altered active microbial community composition, inducing a compositional shift characterized by 0.5-to 2-fold increases in the abundances of Proteobacteria, Chloroflexi, and Actinobacteria. Our study also revealed 92–100% increases in the abundance of C-degradation functional genes encoding starch, cellulose, and lignin decomposition pathways within active microbial community under warming. Statistical analyses identified significant positive correlations between Rh and the abundance of Proteobacteria and Actinobacteria, as well as expression levels of functional genes associated with lignin and cellulose decomposition pathways. Furthermore, our results suggested that short-term warming increased Rh through altering diversity, species composition, and C degradation functional genes of active microbial community providing insights into the influence of microbial communities on soil C-climate feedbacks under climate warming.

Active microbial community↗

DOE OSTI2020

Acidic Oxygen Evolution Reaction Activity–Stability Relationships in Ru-Based Pyrochlores

Ru-based oxygen evolution reaction (OER) catalysts show significant promise for efficient water electrolysis, but rapid degradation poses a major challenge for commercial applications. In this work, we explore several Ru-based pyrochlores (A 2 Ru 2 O 7 , A = Y, Nd, Gd, Bi) as OER catalysts and demonstrate improved activity and stability of catalytic Ru sites relative to RuO 2 . Furthermore, we combine complementary experimental and theoretical analysis to understand how the A-site element impacts activity and stability under acidic OER conditions. Among the A 2 Ru 2 O 7 studied herein, we find that a longer Ru–O bond and a weaker interaction of the Ru 4d and O 2p orbitals compared with RuO 2 results in enhanced initial activity. We observe that the OER activity of the catalysts changes over time and is accompanied by both A-site and Ru dissolution at different relative rates depending on the identity of the A-site. Pourbaix diagrams constructed using density functional theory (DFT) calculations reveal a driving force for this experimentally observed dissolution, indicating that all compositions studied herein are thermodynamically unstable in acidic OER conditions. Theoretical activity predictions show consistent trends between A-site cation leaching and OER activity. These trends coupled with Bader charge analysis suggest that dissolution exposes highly oxidized Ru sites that exhibit enhanced activity. Overall, using the stability number (molO2 evolved/molRu dissolved) as a comparative metric, the A 2 Ru 2 O 7 materials studied in this work show substantially greater stability than a standard RuO2 and commensurate stability to some Ir mixed metal oxides. Finally, the insights described herein provide a pathway to enhanced Ru catalyst activity and durability, ultimately improving the efficiency of water electrolyzers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Active Sites in the Dealuminated Beta Zeolite-Supported Cobalt Catalyst for Non-Oxidative Ethane Dehydrogenation

Dispersed metal species in siliceous zeolites have been actively studied for non-oxidative dehydrogenation of ethane (NDE). Fundamental insights into the dynamics of metal species in zeolites under reaction conditions have rarely been explored. Herein, we report an atomic level understanding of the dynamics and activity of cobalt (Co) sites in dealuminated Beta zeolite (DeAl-BEA) for NDE during induction and reaction conditions with extensive characterization techniques such as diffuse reflectance UV–vis, solid state nuclear magnetic resonance and X-ray photoelectron, X-ray diffraction along with in situ Fourier transform infrared and X-ray absorption spectroscopy. For a catalyst with 0.5 mass % Co loading, tetrahedral Co 2+ mononuclear sites, di-coordinated to the zeolite framework and with two silanol groups in vicinity (i.e., (≡SiO) 2 Co(HO–Si≡) 2 ), form upon exposure to hydrogen during induction and persist through the NDE reaction. Increasing the Co loading to 3.0 mass % yielded Co sites with similar electronic and coordination structures but slightly elongated Co–O bonds. Upon cooling to room temperature, the Co sites persisted in the same coordination environment, though the disappearance of a feature in the Co K-edge near-edge region revealed changes in the active site’s electronic structure coinciding with modest shifts in bond lengths. The electronic structure and activity of (≡SiO) 2 Co(HO–Si≡) 2 sites were studied comparatively to a few other hypothetical Co 2+ coordination structures, using electronic structure calculations and microkinetic simulations. The simulations showed that NDE is controlled by β-hydride elimination following C–H bond activation and that Co-sites possessing flexibility because of neighboring silanol defects are more active. Interestingly, dinuclear Co–O–Co sites (i.e., (≡SiO)Co(HO–Si≡) 2 –O–(HO–Si≡) 2 Co(≡SiO)) were more active than the mononuclear (≡SiO) 2 Co(HO–Si≡) 2 sites because of favorable hydrogen bonding with the vicinal silanol groups. In conclusion, the present study bridges the gap between the knowledge acquired by ex-situ characterizations and the active sites under the reaction conditions in alkane dehydrogenation chemistry.

36 MATERIALS SCIENCE↗

DOE OSTI2021

In-Canal Assay of High Specific Activity 60 Co at the Advanced Test Reactor

Production of high specific activity (HSA) 60 Co has recently resumed at the Advanced Test Reactor (ATR) at the Idaho National Laboratory. The technical steps of performing in-canal assay of HSA 60 Co targets at the ATR are described herein. The HSA targets are assayed on a regular basis, between cycles at the ATR, in order to assess the progress of activation. The targets are also assayed at the conclusion of the irradiation in order to provide activity estimates for the distributor and to be used for safety and shipping evaluations. These target assay activities must take place in the ATR canal to provide sufficient radiological shielding. Furthermore, a specialized assay fixture is used in conjunction with custom 60 Co radiation standards to assess the irradiated target. The specific activity of each irradiated target was determined by first measuring the 60 Co standards to determine a sensitivity factor. Then, each irradiated target was measured, and the integrated measurement was multiplied by the sensitivity factor to determine the total activity of the irradiated target. Finally, a correction factor was determined to adjust the reported activity, accounting for differences in the physical geometries of the standards and targets. These methods were used to accurately assay the gross activity of nine irradiated 60 Co targets, two of which were delivered to the distributor where confirmatory hot-cell assays were performed verifying the accuracy of the in-canal assay method.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2021

Modelling multiple occurrences of activities during a day: An extension of the MDCEV model

The increased interest in time use among transport researchers has led to a search for flexible but tractable models of time use, such as Bhat's Multiple Discrete Continuous Extreme Value (MDCEV) model. MDCEV formulations typically model aggregate time allocation into different activity types during a given period, such as the amount of time spent working and shopping in a day. While these applications provide valuable insights into activity participation, they ignore disaggregate activity-episodes, that is the fact that people might split their total time spent working in multiple separate blocks, with breaks or other activities in between. Insights into this splitting into episodes are necessary for predicting trips and understanding time use satiation. We propose a modified MDCEV model where an activity-episode, rather than an activity type, is the basic choice alternative, using a modified utility function to capture the reduced likelihood of individuals performing a very large number of episodes of the same activity. Results from two large revealed preference datasets exhibit equivalent forecast accuracy between the traditional and proposed approach at an aggregate level, but the latter also provides insights on the number and duration of activity-episodes with significant accuracy.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Biphasic response of human iPSC-derived neural network activity following exposure to a sarin-surrogate nerve agent

Organophosphorus nerve agents (OPNA) are hazardous environmental exposures to the civilian population and have been historically weaponized as chemical warfare agents (CWA). OPNA exposure can lead to several neurological, sensory, and motor symptoms that can manifest into chronic neurological illnesses later in life. There is still a large need for technological advancement to better understand changes in brain function following OPNA exposure. The human-relevant in vitro multi-electrode array (MEA) system, which combines the MEA technology with human stem cell technology, has the potential to monitor the acute, sub-chronic, and chronic consequences of OPNA exposure on brain activity. However, the application of this system to assess OPNA hazards and risks to human brain function remains to be investigated. In a concentration-response study, we have employed a human-relevant MEA system to monitor and detect changes in the electrical activity of engineered neural networks to increasing concentrations of the sarin surrogate 4-nitrophenyl isopropyl methylphosphonate (NIMP). We report a biphasic response in the spiking (but not bursting) activity of neurons exposed to low (i.e., 0.4 and 4 μM) versus high concentrations (i.e., 40 and 100 μM) of NIMP, which was monitored during the exposure period and up to 6 days post-exposure. Regardless of the NIMP concentration, at a network level, communication or coordination of neuronal activity decreased as early as 60 min and persisted at 24 h of NIMP exposure. Once NIMP was removed, coordinated activity was no different than control (0 μM of NIMP). Interestingly, only in the high concentration of NIMP did coordination of activity at a network level begin to decrease again at 2 days post-exposure and persisted on day 6 post-exposure. Notably, cell viability was not affected during or after NIMP exposure. Also, while the catalytic activity of AChE decreased during NIMP exposure, its activity recovered once NIMP was removed. Gene expression analysis suggests that human iPSC-derived neurons and primary human astrocytes resulted in altered genes related to the cell’s interaction with the extracellular environment, its intracellular calcium signaling pathways, and inflammation, which could have contributed to how neurons communicated at a network level.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Establishing a Theoretical Landscape for Identifying Basal Plane Active 2D Metal Borides (MBenes) toward Nitrogen Electroreduction

Abstract To achieve efficient ammonia synthesis via electrochemical nitrogen reduction reaction (NRR), a qualified catalyst should have both high specific activity and large active surface area. However, integrating these two merits into one single material remains a big challenge due to the difficulty in balancing multiple reaction intermediates. Here, it is demonstrated that the boron‐analogues of MXenes, namely “MBenes”, could cope with the challenge and achieve the high activity and large reaction region simultaneously toward NRR. Using extensive density functional theory computations and taking 16 MBenes as representatives, it is identified that seven MBenes (CrB, MoB, WB, Mo 2 B, V 3 B 4 , CrMnB 2 , and CrFeB 2 ) not only have intrinsic basal plane activity for NRR with limiting potentials ranging from −0.22 to −0.82 V, but also possess superior capability of suppressing the competitive hydrogen evolution reaction. Particularly, different from the MXenes whose surface oxidation may block the active sites, once oxidized, these MBenes can catalyze NRR via the self‐activating process, reducing O*/OH* into H 2 O* under reaction conditions, and favoring the N 2 electroreduction. As a result, the exceptional activity and selectivity, high active area (≈10 19 m −2 ), and antioxidation nature render these MBenes as pH‐universal catalysts for NH 3 production without introducing any dopants and defects.

Guo, Xiangyu↗

DOE OSTI2024

Propane Dehydrogenation on Pt x Zn y Active Sites in Silicalite‐1

Abstract The improvement of Pt‐based catalysts for propane dehydrogenation (PDH) has progressed by recent investigations that have identified Zn as a promising promoter for Pt subnanometer catalysts. It is desirable to gain insights into the structure, stability, and activity of such active sites and the factors that influence them, such as Zn : Pt ratio, Pt coordination and nuclearity. Here, we employ density functional theory and microkinetic simulations to investigate the stability of Pt x Zn y ( x =1–3, y=0–3) active sites grafted on silanols of Silicalite‐1 and the PDH activity of Pt. We find that the coordination of a Pt atom to a nest of grafted Zn(II) atoms increases the stability of the Pt 1 Zn y sites, whose activity is similar for y=0–2 and drops dramatically for y>2. We further demonstrate, via linear scaling relations and microkinetic simulations, that the turnover frequency obeys a volcano law as a function of propylene binding strength. The Pt 2 Zn 1 and Pt 3 Zn 1 sites are stable and exhibit activity similar to Pt 1 Zn 2 , but only Pt 1 Zn 2 manifests reaction kinetics consistent with experimental data, strongly suggesting the active site composition in the synthesized catalyst samples. The methodology presented here suggests a general strategy for deducing active site information such as composition through simple kinetic experiments.

Liu, Yilang↗

DOE OSTI2024

Propane Dehydrogenation on Pt x Zn y Active Sites in Silicalite‐1

Liu, Yilang↗

DOE OSTI2021

Single‐Atomic Site Catalyst with Heme Enzymes‐Like Active Sites for Electrochemical Sensing of Hydrogen Peroxide

Abstract Heme enzymes, with the pentacoordinate heme iron active sites, possess high catalytic activity and selectivity in biosensing applications. However, they are still subject to limited catalytic stability in the complex environment and high cost for broad applications in electrochemical sensing. It is meaningful to develop a novel substitute that has a similar structure to some heme enzymes and mimics their enzyme activities. One emerging strategy is to design the Fe‐N‐C based single‐atomic site catalysts (SASCs). The obtained atomically dispersed Fe‐N x active sites can mimic the active sites of heme enzymes effectively. In this work, a SASC (Fe‐SASC/NW) is synthesized by doping single iron atoms in polypyrrole (PPy) derived carbon nanowire via a zinc‐atom‐assisted method. The proposed Fe‐SASC/NW shows high heme enzyme‐like catalytic performance for hydrogen peroxide (H 2 O 2 ) with a specific activity of 42.8 U mg −1 . An electrochemical sensor based on Fe‐SASC/NW is developed for the detection of H 2 O 2 . This sensor exhibits a wide detection concentration range from 5.0 × 10 −10 m to 0.5 m and an excellent limit of detection (LOD) of 46.35 × 10 −9 m . Such excellent catalytic activity and electrochemical sensing sensitivity are attributed to the isolated Fe‐N x active sites and their structural similarity with natural metalloproteases.

Ding, Shichao↗

DOE OSTI2023

Tailoring activity of iron phthalocyanine by edge-nitrogen sites induced electronic delocalization

Fe-N-C catalysts have been recognized as the most satisfactory candidates alternatively to Pt-based catalysts for oxygen reduction reaction (ORR). However, fine-tailoring of their intrinsic ORR catalytic activity still remains a great challenge due to the inferior accessibility and intrinsic activity of FeN x moieties. Herein, one order of magnitude activity enhancement of pristine Fe-N-C through cooperating with nitrogen-doped carbon micro-flower is achieved. The axial coordination effect between Fe active center and nitrogen atoms in support can break the electronic distribution symmetry of FeN x moieties and induce the electron delocalization on Fe active center and the electron localization on N, respectively, which favor the adsorption behavior of *OH intermediate. As a result, the catalyst exhibits a remarkable half-wave potential of 0.9 V and a high kinetic current density of 74.04 mA cm -2 at 0.85 V. In addition, when utilized as a cathode catalyst of liquid Zn-air batteries (ZABs), it possesses excellent electrochemical performance, for example, a high open circuit voltage (OCV) and peak power density of 1.59 V and 170.09 mW cm -2 , respectively. In conclusion, this work provides a new understanding into the activity enhancement mechanism of Fe-N-C catalysts, and inspires electronic delocalization of active sites for adjusting catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Hierarchical semi-Markov models with duration-aware dynamics for activity sequences

Residential electricity demand at granular scales is driven by what people do and for how long. Accurately forecasting this demand for applications like microgrid management and demand response therefore requires generative models for activities that can produce realistic daily activity sequences, capturing both the timing and duration of human behavior. This paper develops a generative model of human activity sequences using nationally representative time-use diaries at a 10-min resolution. We use this model to quantify which demographic factors are most critical for improving predictive performance. We propose a hierarchical semi-Markov framework that addresses two key modeling challenges. First, a time-inhomogeneous Markov router learns the patterns of “which activity comes next.” Second, a semi-Markov hazard component explicitly models activity durations, capturing “how long” activities realistically last. To ensure statistical stability when data are sparse, the model pools information across related demographic groups and time blocks. The entire framework is trained and evaluated using survey design weights to ensure our findings are representative of the U.S. population. On a held-out test set, we demonstrate that explicitly modeling durations with the hazard component provides a substantial and statistically significant improvement over purely Markovian models. Furthermore, our analysis reveals a clear hierarchy of demographic factors: Sex, Day-Type, and Household Size provide the largest predictive gains, while Region and Season, though important for energy calculations, contribute little to predicting the activity sequence itself. The result is an interpretable and robust generator of synthetic activity traces, providing a high-fidelity foundation for downstream energy systems modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Indole-3-carbinol ameliorates necroptosis and inflammation of intestinal epithelial cells in mice with ulcerative colitis by activating aryl hydrocarbon receptor

Highlights: • AHR activated by I3C plays an important role in protecting IECs from necroptosis and inflammation, in vivo and in vitro. • AHR could ubiquitinate RIPK1, promote IAPs expression and inhibit NF-κB activation in NCM460 cells. • I3C is a good candidate as a natural product to prevent and treat UC. Ulcerative colitis (UC) is a disease characterized by inflammation and disruption of the intestinal epithelial barrier. Necroptosis plays a critical role in disease progression. Indole-3-carbinol (I3C), a natural dietary agonist of aryl hydrocarbon receptor (AHR), has shown alleviating effects on UC. However, its mechanisms of action have not been comprehensively elucidated. Therefore, we aimed at investigating the protective role of I3C in DSS-induced colitis mice models. I3C significantly ameliorated body weight loss, colon length shortening and colonic pathological damage in colitis mice, reduced disease activity index (DAI) and histological (HI) scores, as well as alleviated colonic necroptosis and inflammation. In vitro, I3C attenuated necroptosis and inflammation of colonoids and NCM460 cells. AHR, activated by I3C, inhibits activation of receptor-interacting protein kinase 1 (RIPK1) and the subsequent assembly of necrosome in a time-dependent manner, as well as suppressing NF-κB activation and decreasing TNF-α, IL-1β, IL-6 and IL-8 expression. Silencing of AHR aggravated necroptosis and inflammation of NCM460 cells, and did not be ameliorated by I3C. Furthermore, AHR activation induces the expression of inhibitor of apoptosis proteins (IAPs) and the ubiquitination of RIPK1. In conclusion, I3C exerts a protective effect in DSS-induced colitis mice models by alleviating the necroptosis and inflammation of IECs through activating AHR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Ligand-Based Compound Activity Prediction via Few-Shot Learning

Predicting the activities of new compounds against biophysical or phenotypic assays based on the known activities of one or a few existing compounds is a common goal in early stage drug discovery. This problem can be cast as a “few-shot learning” challenge, and prior studies have developed few-shot learning methods to classify compounds as active versus inactive. However, the ability to go beyond classification and rank compounds by expected affinity is more valuable. We describe Few-Shot Compound Activity Prediction (FS-CAP), a novel neural architecture trained on a large bioactivity data set to predict compound activities against an assay outside the training set, based on only the activities of a few known compounds against the same assay. Our model aggregates encodings generated from the known compounds and their activities to capture assay information and uses a separate encoder for the new compound whose activity is to be predicted. The new method provides encouraging results relative to traditional chemical-similarity-based techniques as well as other state-of-the-art few-shot learning methods in tests on a variety of ligand-based drug discovery settings and data sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

CASSCF with Extremely Large Active Spaces Using the Adaptive Sampling Configuration Interaction Method

The complete active space self-consistent field (CASSCF) method is the principal approach employed for studying strongly correlated systems. However, exact CASSCF can only be performed on small active spaces of ~20 electrons in ~20 orbitals due to exponential growth in the computational cost. Here, we show that employing the Adaptive Sampling Configuration Interaction (ASCI) method as an approximate Full CI solver in the active space allows CASSCF-like calculations within chemical accuracy (<1 kcal/mol for relative energies) in active spaces with more than ~50 active electrons in ~50 active orbitals, significantly increasing the sizes of systems amenable to accurate multiconfigurational treatment. The main challenge with using any selected CI-based approximate CASSCF is the orbital optimization problem; they tend to exhibit large numbers of local minima in orbital space due to their lack of invariance to active–active rotations (in addition to the local minima that exist in exact CASSCF). We highlight methods that can avoid spurious local extrema as a practical solution to the orbital optimization problem. We employ ASCI-SCF to demonstrate a lack of polyradical character in moderately sized periacenes with up to 52 correlated electrons and compare against heat-bath CI on an iron porphyrin system with more than 40 correlated electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Correlating Oxidation State and Surface Area to Activity from Operando Studies of Copper CO Electroreduction Catalysts in a Gas-Fed Device

Copyright © 2020 American Chemical Society. The rational design of high-performance electrocatalysts requires a detailed understanding of dynamic changes in catalyst properties, including oxidation states, surface area, and morphology under realistic working conditions. Oxide-derived Cu catalysts exhibit a remarkable selectivity toward multicarbon products for the electrochemical CO reduction reaction (CORR), but the exact role of the oxide remains elusive for explaining the performance enhancements. Here, we used operando X-ray absorption spectroscopy (XAS) coupled with simultaneous measurements of the catalyst activity and selectivity by gas chromatography (GC) to study the relationship between oxidation states of Cu-based catalysts and the activity for ethylene (C2H4) production in a CO gas-fed cell. By utilizing a custom-built XAS cell, oxidation states of Cu catalysts can be probed in device-relevant settings and under high current densities (>80 mA cm-2) for the CORR. By employing an electrochemical oxidation process, we found that the Cu oxidation states and specific ion species do not correlate with C2H4 production. The difference in the CORR activity is also investigated in relation to electrochemical surface area (ECSA) changes. While the hydrogen evolution reaction (HER) activity is positively correlated to the ECSA changes, the increased C2H4 activity is not proportional to the ECSA. Ex situ characterization from microscopic techniques suggests that the changes in the C2H4 activity and selectivity may arise from a morphological transformation that evolves into a more active structure. These comprehensive results give rise to the development of a cell regeneration method that can restore the performance of the Cu catalyst without cell disassembly. Our study establishes a basis for the rational design of highly active electrocatalysts for broad-range reactions in a gas-fed device.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗