The sluggish kinetics of oxygen evolution reaction (OER) is the main bottleneck for the electrocatalytic water splitting to produce hydrogen (H2), and the by‐product is worthless O2. Therefore, ...designing a thermodynamically favorable oxidation reaction to replace OER and coupling with value‐added product generation on the anode is of significance for boosting H2 generation under low electrolysis voltage. Herein, cobalt hydroxide@hydroxysulfide nanosheets on carbon paper (Co(OH)2@HOS/CP) are synthesized as bifunctional electrocatalysts to facilitate H2 production and convert methanol to valuable formate simultaneously. Benefiting from the influences/changes on the composition, surface properties, electronic structure, and chemistry of Co(OH)2, the as‐obtained electrodes exhibit very high selectivity for methanol to value‐added formate oxidation (MFO) and boost electrocatalytic performance with low overpotential of 155 mV for MFO and 148 mV for hydrogen evolution reaction at a current density of 10 mA cm−2. Furthermore, the integrated two‐electrode electrolyzer drives 10 mA cm−2 at a cell voltage of 1.497 V with united 100% Faradaic efficiency for anodic and cathodic reaction and continuous 20 h of operation without obvious decay. The electrocatalytic hydrogen production with the assistance of alternative oxidation by the robust electrocatalyst can be further used to realize the upgrading of other organic molecules with less energy consumption.
New cobalt hydroxide@hydroxysulfide nanosheet electrocatalysts are developed to boost hydrogen fuel generation by coupling with selective oxidation of methanol to a value‐added formate. As a result, the electrolysis voltage is reduced to 1.497 V at a current density of 10 mA cm−2 and the Faradaic efficiencies are closed to 100% at the anode and cathode.
Electro‐oxidative organic upgrading, as an ideal alternative to sluggish oxygen evolution reaction (OER) performance, can effectively decrease energy consumption to boost hydrogen evolution reaction ...(HER) performance. However, developing highly active electrocatalysts for long‐term durable organic upgrading with high selectivity at large and steady current density remains challenging. Herein, hollow NiSe nanocrystals heterogenized with carbon nanotubes (h‐NiSe/CNTs) are fabricated via a facile one‐pot approach. The highly dispersed h‐NiSe/CNTs 3D network can efficiently facilitate rapid mass/electron diffusion, thus achieving highly active and long‐term stable electrocatalysis for catalyzing methanol to value‐added formate at high and steady current density (≈345 mA cm−2) with high Faradaic efficiency (>95%). This reaction replaces sluggish OER performance to reduce the energy consumption for boosting H2 generation by six times. The critical active species and methanol activation mechanism are systematically studied using X‐ray photoelectron spectroscopy, X‐ray absorption fine structure analysis, in situ Raman, and density functional theory calculations, indicating that the non‐ignorable SeOx collaborated with in situ formed NiOOH species can synergistically modulate the d band center to achieve an optimal adsorption for methanol selective oxidation and suppress the further oxidation to CO2, thus leading to active and stable electrolysis for producing value‐added formate with high selectivity and co‐generating H2 with less energy consumption.
Hollow NiSe nanocrystals/carbon nanotubes nanoheterostructures are synthesized as highly active and durable electrocatalysts for long‐term methanol selective upgrading conversion to value‐added formate at large and steady current density (≈345 mA cm−2) with a high Faradaic efficiency (>95%), simultaneously replacing sluggish OER performance to boost H2 generation with lower energy costs.
Machine learning (ML) is emerging as a powerful tool for identifying quantitative structure–activity relationships to accelerate electrocatalyst design by learning from historic data without explicit ...programming. The algorithms, data/database, and descriptors are usually the decisive factors for ML and the descriptors play a pivotal role for electrocatalysis as they contain the essence of catalysis from the physicochemical nature. Despite the considerable research efforts regarding electrocatalyst design with ML, the lack of universal selection tactics for descriptors bridging the gap between structures and activity impedes its wider application. A timely summary of the application of ML in electrocatalyst design helps to deepen the understanding of the nature of descriptors and improve the application scope and design efficiency. This review summarizes the geometrical, electronic, and activity descriptors used as input for ML training and predicting to reveal the general rules for their application in the design of electrocatalysts. In response to the challenges of hydrogen evolution reaction, oxygen evolution reaction, oxygen reduction reaction, CO2 reduction reaction, and nitrogen reduction reaction, the ML application in these areas is tracked for the progress and prospective changes. Additionally, the potential application of the automated design and discovery are discussed for the other well‐known electrocatalytic processes.
Descriptors play a pivotal role for machine learning (ML)‐assisted electrocatalyst design as they contain the essence of catalysis from the physicochemical nature. This article reviews the progresses and prospectives of the descriptor‐oriented ML application in the design of electrocatalysts for oxygen evolution reaction, oxygen reduction reaction, CO2 reduction reaction, and nitrogen reduction reaction.
The massive emission of carbon dioxide (CO2), the major portion of greenhouse gases, has negatively affected our ecosystem. Developing new technologies to effectively reduce CO2 emission or convert ...CO2 to useful products has never been more imperative. In response to this challenge, we herein developed novel in situ exsolved Fe–Ni alloy nanospheres uniformly socketed on an oxygen-deficient perovskite La(Sr)Fe(Ni) as a highly stable and efficient catalyst for the effective conversion of CO2 to carbon monoxide (CO) in a high-temperature solid oxide electrolysis cell (HT-SOEC). The symmetry between the reduction and reoxidation cycles of this catalyst indicates its good redox reversibility. The cathodic reaction kinetics for CO2 electrolysis is significantly improved with a polarization resistance as low as 0.272 Ω cm2. In addition, a remarkably enhanced current density of 1.78 A cm–2, along with a high Faraday efficiency (∼98.8%), was achieved at 1.6 V and 850 °C. Moreover, the potentiostatic stability test of up to 100 h showed that the cell was stable without any noticeable coking in a CO2/CO (70:30) flow at an applied potential of 0.6 V (vs OCV) and 850 °C. The increased oxygen vacancies together with the in situ exsolved nanospheres on the perovskite backbone ensures sufficiently active sites and consequently improves the electrochemical performance for the efficient CO2 conversion. Therefore, this newly developed perovskite can be a promising cathode material for HT-SOEC. More generally, this study points to a new direction to develop highly efficient catalysts in the form of the perovskite oxides with perfectly in situ exsolved metal/bimetal nanospheres.
The occurrence of the 2017/2018 La Niña, following a weak‐to‐neutral La Niña in boreal winter 2016/2017, was surprising. Based on observational records and multiple linear regression analysis for the ...Pacific zonal wind tendency (dU/dt), this study investigates possible reasons why the La Niña condition suddenly happened in late 2017. Similar to previous four double‐peaked La Niña events (1983–1985, 1998–2000, 2007–2009, and 2010–2012), we find that the multiyearly persistent easterly anomaly in the central equatorial Pacific is a key condition to the development of the second La Niña. The occurrence of the 2017/2018 La Niña results from large warm sea surface temperature (SST) anomalies in the tropical Indian and Atlantic Oceans that act to force the persistent easterly anomaly in the Pacific via modifying the Walker Circulations. About 24% of the variance of the Pacific dU/dt can be statistically explained by the tropical Indian Ocean and Atlantic SST anomalies.
Plain Language Summary
The 2017/2018 La Niña appears to be surprising, given that an El Niño‐like condition has already developed in the first half of 2017 but actually in opposite to most models' forecasts that issued a false alarm of an El Niño. Previous studies suggested that both the tropical Indian and Atlantic Oceans have exhibited a rapid warming in recent decades, which have caused an easterly trend in the central Pacific. In this study, we examine the possible contributions of the tropical Indian Ocean and Atlantic SSTs to the occurrence of the second La Niña in 2017/2018. Our results highlight the importance of the SST warming in the tropical Indian and Atlantic Oceans for the occurrence of the second La Niña under rapid SST warming in the two basins during recent decades.
Key Points
Persistent easterly anomaly in the central equatorial Pacific is a key condition to the occurrence of the second La Niña
Rapid SST warming in the tropical Indian and Atlantic Oceans acts to strengthen the persistent easterly anomaly
About 24% of the variance of the dU/dt in the central equatorial Pacific during 1980‐2017 can be explained by the IO and AO SSTAs
Variations in the El Niño/Southern Oscillation (ENSO) are associated with a wide array of regional climate extremes and ecosystem impacts
. Robust, long-lead forecasts would therefore be valuable for ...managing policy responses. But despite decades of effort, forecasting ENSO events at lead times of more than one year remains problematic
. Here we show that a statistical forecast model employing a deep-learning approach produces skilful ENSO forecasts for lead times of up to one and a half years. To circumvent the limited amount of observation data, we use transfer learning to train a convolutional neural network (CNN) first on historical simulations
and subsequently on reanalysis from 1871 to 1973. During the validation period from 1984 to 2017, the all-season correlation skill of the Nino3.4 index of the CNN model is much higher than those of current state-of-the-art dynamical forecast systems. The CNN model is also better at predicting the detailed zonal distribution of sea surface temperatures, overcoming a weakness of dynamical forecast models. A heat map analysis indicates that the CNN model predicts ENSO events using physically reasonable precursors. The CNN model is thus a powerful tool for both the prediction of ENSO events and for the analysis of their associated complex mechanisms.
Despite the fact that antimony triselenide (Sb2Se3) thin‐film solar cells have undergone rapid development in recent years, the large open‐circuit voltage (VOC) deficit still remains as the biggest ...bottleneck, as even the world‐record device suffers from a large VOC deficit of 0.59 V. Here, an effective interface engineering approach is reported where the Sb2Se3/CdS heterojunction (HTJ) is subjected to a post‐annealing treatment using a rapid thermal process. It is found that nonradiative recombination near the Sb2Se3/CdS HTJ, including interface recombination and space charge region recombination, is greatly suppressed after the HTJ annealing treatment. Ultimately, a substrate Sb2Se3/CdS thin‐film solar cell with a competitive power conversion efficiency of 8.64% and a record VOC of 0.52 V is successfully fabricated. The device exhibits a much mitigated VOC deficit of 0.49 V, which is lower than that of any other reported efficient antimony chalcogenide solar cell.
A heterojunction post‐annealing treatment is utilized to suppress the nonradiative recombination for a highly competitive power conversion efficiency of 8.64% and a record open‐circuit voltage (VOC) of 520 mV in Sb2Se3 thin‐film solar cells. The VOC deficit of the device is lower than that of any other reported efficient antimony chalcogenide solar cells.
Currently, the Arctic is undergoing a significant warming, which has exerted widespread impacts on global climate. Although many mechanisms responsible for the Arctic warming have been proposed, the ...impacts of the multi‐decadal change of tropical sea surface temperature receive little attention. Here we use numerical experiments to elucidate that the Indian Ocean (IO) warming may contribute to the Arctic warming. Through enhancing the Atlantic Meridional Overturning Circulation, the IO warming remotely induces more ocean heat transport from the North Atlantic to the Arctic. The resulted upper ocean warming dominates the surface warming in the Arctic. Additionally, despite the net negative contribution of the atmospheric heat transport, more warm air is conveyed into the Kara Seas, North Eurasia, and North America sectors, contributing to the local warming. The results propose a new mechanism to interpret the Arctic warming and indicate the important remote impacts of the tropical IO warming.
Plain Language Summary
The Arctic warming is a significant phenomenon in the context of global warming, which not only impacts the local ecosystem but also influences global climate. Improved understanding of its causes is important to the protection of the Arctic ecosystem and the forecast of global climate. Although many previous studies have proposed various mechanisms to interpret the Arctic warming, its causes are still not fully understood. In this study, we find that the Indian Ocean (IO) warming is also a possible contributor to the Arctic warming. Through enhancing the Atlantic Meridional Overturning Circulation, the IO warming remotely induces more ocean heat transport from the North Atlantic to the Arctic and then contributes to the Arctic warming. Additionally, the southerly winds in the high latitudes in response to the IO warming, transport more warm air into the Kara Seas, North Eurasia and North America and contributes to the local warming. The present study indicates the IO warming may also contribute to the Arctic warming. A better understanding of the remote impacts of tropical oceans may foster the comprehensive understanding of the complicated reasons for the Arctic warming.
Key Points
Rapid warming in the Indian Ocean (IO) may contribute to the Arctic warming through both oceanic and atmospheric pathways
More ocean heat is transported from the North Atlantic to the Arctic due to enhanced Atlantic Meridional Overturning Circulation in response to the IO warming
Southerly winds in the high latitudes in response to the IO warming convey more warm air into parts of the Arctic
The renewable-energy-powered electrochemical CO2 reduction reaction (CO2RR) provides an attractive strategy to simultaneously address the energy storage and environmental issues through the synthesis ...of carbon-neutral fuels. This study unravels structure sensitivity of ultrasmall Ag nanocubes with lengths below 25 and 70 nm (L25- and L70-Ag-NCs) enclosed completely by the (100) facet toward an efficient CO2RR to CO. The ultrasmall L25-Ag-NCs deliver a remarkably larger current density, a significantly higher Faraday efficiency (FE) of near-unity, and a comparably higher energy efficiency of 64.0% as well as a better stability of ∼18 h as compared to L70-Ag-NCs, Ag nanoparticles, and bulk Ag. More importantly, CO generation initiates at an ultralow overpotential of 146 mV, accompanied with a remarkably high onset CO FE of 59.6%, further demonstrating the excellence of L25-Ag-NCs for highly active and selective CO2RR. Density functional theory calculations, the percentages of various catalytically active sites, and how the architecture of NCs affecting the active sites as well as the partial density of states were analyzed; the results reveal that the essential origins credited for the enhanced catalytic activity and near-unity CO selectivity over L25-Ag-NCs at lowered η originate from the particular nanostructure, where energetically favorable active sites toward CO2RR are maximally introduced through accurately synthesizing the specific nanostructure enclosed by a certain facet.
Electrochemical reduction of CO2 (CO2RR) provides great potential for intermittent renewable energy storage. This study demonstrates a predominant shape-dependent electrocatalytic reduction of CO2 to ...CO on triangular silver nanoplates (Tri-Ag-NPs) in 0.1 M KHCO3. Compared with similarly sized Ag nanoparticles (SS-Ag-NPs) and bulk Ag, Tri-Ag-NPs exhibited an enhanced current density and significantly improved Faradaic efficiency (96.8%) and energy efficiency (61.7%), together with a considerable durability (7 days). Additionally, CO starts to be observed at an ultralow overpotential of 96 mV, further confirming the superiority of Tri-Ag-NPs as a catalyst for CO2RR toward CO formation. Density functional theory calculations reveal that the significantly enhanced electrocatalytic activity and selectivity at lowered overpotential originate from the shape-controlled structure. This not only provides the optimum edge-to-corner ratio but also dominates at the facet of Ag(100) where it requires lower energy to initiate the rate-determining step. This study demonstrates a promising approach to tune electrocatalytic activity and selectivity of metal catalysts for CO2RR by creating optimal facet and edge site through shape-control synthesis.
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