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Activity of Cu-Al-oxo extra-framework clusters for selective methane oxidation on Cu exchanged zeolites
Cu-zeolites are able to directly convert methane to methanol via a 3-step process using O2 as oxidant. Among the different zeolite topologies, Cu-exchanged mordenite (MOR) shows the highest methanol yields, attributed to a preferential formation of active Cu-oxo species in its 8-MR pores. The presence of extra-framework or partially detached Al species entrained in the micropores of MOR leads to the formation of nearly homotopic redox active Cu-Al-oxo nanoclusters with the ability to activate CH4. Studies of the activity of these sites together with characterization by 27Al NMR and IR spectroscopy leads to the conclusion that the active species are located in the 8-MR side pockets of MOR and it consists of two Cu ions and one Al linked by O. This Cu-Al oxo cluster shows an activity per Cu in methane oxidation significantly higher than of any previ-ously reported active Cu-oxo species. In order to determine unambiguously the structure of the active Cu-Al-oxo cluster, we combine experimental XANES of Cu K- and L- edges, Cu K-edge HERFD-XANES and Cu K-edge EXAFS with TDDFT and AIMD-assisted simulations. Our results provide evidence of a [Cu2AlO3]2+ cluster exchanged on MOR Al pairs that is able to oxidize up to two methane molecules per cluster at ambient pressure.
Mesoscale Convective Systems Represented in High Resolution E3SMv2 and Impact of New Cloud and Convection Parameterizations
Mesoscale convective systems (MCSs) play an important role in modulating the global hydrological cycle, general circulation, and radiative energy budget. In this study, we evaluate MCS simulations in the second version of U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv2). E3SMv2 atmosphere model (EAMv2) is run at the uniform 0.25? horizontal resolution. We track MCSs consistently in the model and observations using the PyFLEXTRKR algorithm, which defines MCS based on both cloud-top brightness temperature (Tb) and surface precipitation. Results from using Tb only to define MCS, commonly used in previous studies, are also discussed. Furthermore, sensitivity experiments are performed to examine the impact of new cloud and convection parameterizations developed for EAMv3 on simulated MCSs. Our results show that EAMv2 simulated MCS precipitation is largely underestimated in the tropics and contiguous United States. This is mainly attributed to the underestimated precipitation intensity in EAMv2. In contrast, the simulated MCS frequency becomes more comparable to observations if MCSs are defined only based on cloud-top Tb. The Tb-based MCS tracking method, however, includes many cloud systems with very weak precipitation which conflicts with the MCS definition. This result illustrates the importance of accounting for precipitation in evaluating simulated MCSs. We also find that the new physics parameterizations help increase the relative contribution of convective precipitation to total precipitation in the tropics, but the simulated MCS properties are generally not improved. This suggests that simulating MCSs will remain a challenge for the next version of E3SM.
Exposing Process‐Level Biases in a Global Cloud Permitting Model With ARM Observations
The emergence of global convective‐permitting models (GCPMs) represents a significant advancement in climate modeling, offering improved representation of deep convection and complex precipitation patterns. In this study, we evaluate the performance of the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) using its doubly periodic configuration (DP‐SCREAM) against large eddy simulations and modern observational data sets from the Atmospheric Radiation Measurement program. We introduce several new transitional cloud regime cases, such as the transition from shallow to deep convection and from stratocumulus to cumulus, as well as cold‐air outbreak scenarios. The results reveal both strengths and limitations of SCREAM, particularly in the accurate simulation of cloud transitions and midlevel convection, with varying degrees of sensitivity to horizontal and vertical resolution. Despite improvements at higher resolutions, key biases remain, including the abrupt transition from shallow to deep convection and the lack of congestus clouds. These findings underscore the need for further refinement in turbulence parameterizations and vertical grid resolution in GCPMs.
Convergence of Cloud Droplet Spectral Relative Dispersion During Entrainment‐Mixing Based on Particle‐Resolved Direct Numerical Simulations
Entrainment-mixing processes critically impact cloud microphysical properties, but their effects on the relative dispersion (d) of cloud droplet size distributions (CDSDs) remain elusive. A direct numerical simulation model is initialized with different CDSDs to fill the gap. These results show that d decreases for broad CDSDs and increases for narrow ones, ultimately converging to approximately 0.5 regardless of initial CDSDs during the evaporation-dominated mixing stage. The supersaturation fluctuation and the shape of CDSDs jointly influence the convergence behavior of d. Further sensitivity tests show that the initial microphysical/dynamical/thermodynamical conditions exert negligible effects on the final converged value of d but affect the convergence rate (k). The k generally increases with increasing droplet number concentration and dissipation rate, and increases with decreasing liquid water content, relative humidity of entrained air, and mixing fraction of cloudy air. A conceptual model with two timescales is proposed; k and the timescales are negatively correlated, meaning that slow mixing and/or evaporation process results in slow convergence of d. In conclusion, this finding provides an important reference for improving understanding and parameterization of d during the entrainment-mixing processes.
The Energy Exascale Earth System Model Version 3: 1. Overview of the Atmospheric Component
This paper describes the atmospheric component of the US Department of Energy's Energy Exascale Earth System Model (E3SM) version 3. Significant updates have been made to the atmospheric physics compared to earlier versions. Specifically, interactive gas chemistry has been implemented, along with improved representations of aerosols and dust emissions. A new stratiform cloud microphysics scheme more physically treats ice processes and aerosol‐cloud interactions. The deep convection parameterization has been largely improved with sophisticated microphysics for convective clouds, making model convection sensitive to large‐scale dynamics, and incorporating the dynamical and physical effects of organized mesoscale convection. Improvements in aerosol wet removal processes and parameter re‐tuning of key aerosol and cloud processes have improved model aerosol radiative forcing. The model's vertical resolution has increased from 72 to 80 layers with the extra eight layers added in the lower stratosphere to better simulate the Quasi‐Biennial Oscillation. These improvements have enhanced E3SM's capability to couple aerosol, chemistry, and biogeochemistry and reduced some long‐standing biases in simulating tropical variability. Compared to its predecessors, the model shows a much stronger signal for the Madden‐Julian Oscillation, Kelvin waves, mixed Rossby‐gravity waves, and eastward inertia‐gravity waves. Aerosol radiative forcing has been considerably reduced and is now better aligned with community best estimates, leading to significantly improved skill in simulating historical temperature records. Its simulated mean‐state climate is largely comparable to E3SMv2, but with some notable degradation in shortwave cloud radiative effect, precipitable water, and surface wind stress, which will be addressed in future updates.
Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing
Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.
Publisher Correction: Copper adparticle enabled selective electrosynthesis of n-propanol
An amendment to this paper has been published and can be accessed via a link at the top of the paper. The original version of this Article incorrectly omitted the received/accepted dates of Received: 05 June 2018; Accepted: 10 October 2018. This has now been corrected in the PDF and HTML versions of the Article.
A high throughput optical method for studying compositional effects in electrocatalysts for CO2 reduction
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Evidence for pressure induced unconventional quantum criticality in the coupled spin ladder antiferromagnet C 9 H 18 N 2 CuBr 4
Quantum phase transitions in quantum matter occur at zero temperature between distinct ground states by tuning a nonthermal control parameter. Often, they can be accurately described within the Landau theory of phase transitions, similarly to conventional thermal phase transitions. However, this picture can break down under certain circumstances. Here, we present a comprehensive study of the effect of hydrostatic pressure on the magnetic structure and spin dynamics of the spin-1/2 ladder compound C 9 H 18 N 2 CuBr 4 . Single-crystal heat capacity and neutron diffraction measurements reveal that the Néel-ordered phase breaks down beyond a critical pressure of Pc~1.0 GPa through a continuous quantum phase transition. Estimates of the critical exponents suggest that this transition may fall outside the traditional Landau paradigm. The inelastic neutron scattering spectra at 1.3 GPa are characterized by two well-separated gapped modes, including one continuum-like and another resolution-limited excitation in distinct scattering channels, which further indicates an exotic quantum-disordered phase above Pc.
Efficient electrically powered CO2-to-ethanol via suppression of deoxygenation
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Highly selective electrocatalytic CO 2 reduction to ethanol by metallic clusters dynamically formed from atomically dispersed copper
Direct electrochemical conversion of CO 2 to ethanol offers a promising strategy of lowering CO 2 emission while storing energy from renewable electricity. However, current electrocatalysts offer only limited selectivity toward ethanol. Here we report a copper catalyst synthesized by a unique Cu-Li amalgm method over a commercial carbon support that achieved Faradaic efficiency (FE) higher than 91% at -0.7 V (RHE) and the active potential as low as -0.4 V (RHE) during direct electrocatalytic CO 2 -to-ethanol conversion. The catalyst also demonstrated stability over an extended period of operation. A strong correlation between the catalytic selectivity and the initial Cu atoms dispersion was found and Operando X-ray absorption spectroscopy identified a dynamic and reversible transformation from atomically dispersed copper atoms to Cu n (n = 3 and 4) under the electrochemical reaction. Frist-principles calculations further elucidate the possible catalytic mechanism of CO 2 reduction over Cu n .
Hydrophilic microporous membranes for selective ion separation and flow-battery energy storage
Abstract not provided
Ammonia-oxidizing bacteria and archaea exhibit differential nitrogen source preferences
Ammonia-oxidizing microorganisms (AOM) contribute to one of the largest nitrogen fluxes in the global nitrogen budget. Four distinct lineages of AOM: ammonia-oxidizing archaea (AOA), beta- and gamma-proteobacterial ammonia-oxidizing bacteria (β-AOB and γ-AOB) and complete ammonia oxidizers (comammox), are thought to compete for ammonia as their primary nitrogen substrate. In addition, many AOM species can utilize urea as an alternative energy and nitrogen source through hydrolysis to ammonia. How the coordination of ammonia and urea metabolism in AOM influences their ecology remains poorly understood. Here we use stable isotope tracing, kinetics and transcriptomics experiments to show that representatives of the AOM lineages employ distinct regulatory strategies for ammonia or urea utilization, thereby minimizing direct substrate competition. The tested AOA and comammox species preferentially used ammonia over urea, while β-AOB favoured urea utilization, repressed ammonia transport in the presence of urea and showed higher affinity for urea than for ammonia. Characterized γ-AOB co-utilized both substrates. Furthermore, these results reveal contrasting niche adaptation and coexistence patterns among the major AOM lineages.
Tuning OH binding energy enables selective electrochemical oxidation of ethylene to ethylene glycol
Abstract not provided
Catalyst synthesis under CO 2 electroreduction favours faceting and promotes renewable fuels electrosynthesis
The electrosynthesis of C 2+ hydrocarbons from CO 2 has garnered recent attention in light of the relatively high market price per unit energy input. Today’s low selectivities and stabilities towards C 2+ products at high current densities curtail system energy efficiency, which limits their prospects for economic competitiveness. Here we present a materials processing strategy based on in situ electrodeposition of copper under CO 2 reduction conditions that preferentially expose and maintain Cu(100) facets, which favour the formation of C 2+ products. We observe capping of facets during catalyst synthesis and achieve control over faceting to obtain a 70% increase in the ratio of Cu(100) facets to total facet area. We report a 90% Faradaic efficiency for C 2+ products at a partial current density of 520 mA cm –2 and a full-cell C 2+ power conversion efficiency of 37%. We achieve nearly constant C2H4 selectivity over 65 h operation at 350 mA cm –2 in a membrane electrode assembly electrolyser.
Direct methane activation by atomically thin platinum nanolayers on two-dimensional metal carbides
We report efficient and direct conversion of methane to value-added products has been a long-term challenge in shale gas applications. Here, we show that atomically thin nanolayers of Pt with a single or double atomic layer thickness, supported on a two-dimensional molybdenum titanium carbide (MXene), catalyse non-oxidative coupling of methane to ethane/ethylene (C 2 ). Kinetic and theoretical studies, combined with in-situ spectroscopic and microscopic characterizations, demonstrate that Pt nanolayers anchored at the hexagonal close-packed sites of the MXene support can activate the first C–H bond of methane to form methyl radicals that favour desorption over further dehydrogenation and thus suppress coke deposition. At 750 °C and 7% methane conversion, the catalyst runs for 72 hours of continuous operation without deactivation and exhibits >98% selectivity towards C 2 products, with a turnover frequency of 0.2–0.6 s -1 . Our findings provide insights into the design of highly active and stable catalysts for methane activation and create a platform for developing atomically thin supported metal catalysts.
The economic outlook for converting CO 2 and electrons to molecules
Comprehensive techno-economic analysis across a wide set of technologies and products provides insight into the economic feasibility of electron-mediated CO 2 reduction.