Explore the vast range of titles available.

The insufficient availability and activity of interfacial water remain a major challenge for alkaline hydrogen evolution reaction (HER). Here, we propose an “on-site disruption and near-site compensation” strategy to reform the interfacial water hydrogen bonding network via deliberate cation penetration and catalyst support engineering. This concept is validated using tip-like bimetallic RuNi nanoalloys planted on super-hydrophilic and high-curvature carbon nanocages (RuNi/NC). Theoretical simulations suggest that tip-induced localized concentration of hydrated K + facilitates optimization of interfacial water dynamics and intermediate adsorption. In situ synchrotron X-ray spectroscopy endorses an H* spillover-bridged Volmer‒Tafel mechanism synergistically relayed between Ru and Ni. Consequently, RuNi/NC exhibits low overpotential of 12 mV and high durability of 1600 h at 10 mA cm ‒2 for alkaline HER, and demonstrates high performance in both water electrolysis and chlor-alkali electrolysis. This strategy offers a microscopic perspective on catalyst design for manipulation of the local interfacial water structure toward enhanced HER kinetics. A RuNi/NC catalyst with optimized interfacial water dynamics for alkaline H 2 evolution is reported. The designed strategy shows enhanced catalytic activity by achieving 12 mV overpotential at 10 mA cm ‒2 and 13.6-fold higher mass activity than Pt/C.

This paper introduces the Flexible Global Ocean‐Atmosphere‐Land System Model: Grid‐Point Version 3 (FGOALS‐g3) and evaluates its basic performance based on some of its participation in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) experiments. Our results show that many significant improvements have been achieved by FGOALS‐g3 in terms of climatological mean states, variabilities, and long‐term trends. For example, FGOALS‐g3 has a small (−0.015°C/100 yr) climate drift in 700‐yr preindustrial control (piControl) runs and smaller biases in climatological mean variables, such as the land/sea surface temperatures (SSTs) and seasonal soil moisture cycle, compared with its previous version FGOALS‐g2 during the historical period. The characteristics of climate variabilities, for example, Madden‐Julian oscillation (MJO) eastward/westward propagation ratios, spatial patterns of interannual variability of tropical SST anomalies, and relationship between the East Asian Summer Monsoon and El Niño–Southern Oscillation (ENSO), are well captured by FGOALS‐g3. In particular, the cooling trend of globally averaged surface temperature during 1940–1970, which is a challenge for most CMIP3 and CMIP5 models, is well reproduced by FGOALS‐g3 in historical runs. In addition to the external forcing factors recommended by CMIP6, anthropogenic groundwater forcing from 1965 to 2014 was incorporated into the FGOALS‐g3 historical runs. Plain Language Summary The sixth phase of the Coupled Model Intercomparison Project (CMIP6) is a crucial support for the sixth Assessment Report of Intergovernmental Panel on Climate Change (IPCC AR6) and will also provide important foundation for research in climate change in the next few years. This paper gives the description of FGOALS‐g3 model, its experiment configures, and the experiments conducted according to the experimental design of CMIP6 and evaluates the preliminary performance of model simulation. This work offers references to CMIP6 data users and provides enormous output data sets for assessing and understanding climate change. Key Points This paper describes FGOALS‐g3 and its experiment design for CMIP6 Historical, preindustrial, and scenario simulations are evaluated Climate drift is small in preindustrial simulation, and mean climate and climate variabilities at different temporal scales are realistic in historical runs

This paper describes the datasets from the Scenario Model Intercomparison Project (ScenarioMIP) simulation experiments run with the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model, GridPoint version 3 (CAS FGOALS-g3). FGOALS-g3 is driven by eight shared socioeconomic pathways (SSPs) with different sets of future emission, concentration, and land-use scenarios. All Tier 1 and 2 experiments were carried out and were initialized using historical runs. A branch run method was used for the ensemble simulations. Model outputs were three-hourly, six-hourly, daily, and/or monthly mean values for the primary variables of the four component models. An evaluation and analysis of the simulations is also presented. The present results are expected to aid research into future climate change and socio-economic development.

The three-member historical simulations by the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System model, version f3-L (CAS FGOALS-f3-L), which is contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6), are described in this study. The details of the CAS FGOALS-f3-L model, experiment settings and output datasets are briefly introduced. The datasets include monthly and daily outputs from the atmospheric, oceanic, land and sea-ice component models of CAS FGOALS-f3-L, and all these data have been published online in the Earth System Grid Federation (ESGF, https://esgf-node.llnl.gov/projects/cmip6/ ). The three ensembles are initialized from the 600th, 650th and 700th model year of the preindustrial experiment (piControl) and forced by the same historical forcing provided by CMIP6 from 1850 to 2014. The performance of the coupled model is validated in comparison with some recent observed atmospheric and oceanic datasets. It is shown that CAS FGOALS-f3-L is able to reproduce the main features of the modern climate, including the climatology of air surface temperature and precipitation, the long-term changes in global mean surface air temperature, ocean heat content and sea surface steric height, and the horizontal and vertical distribution of temperature in the ocean and atmosphere. Meanwhile, like other state-of-the-art coupled GCMs, there are still some obvious biases in the historical simulations, which are also illustrated. This paper can help users to better understand the advantages and biases of the model and the datasets.

The purpose of this study was to examine the efficacy of the algicidal bacterium Sagittula stellata on the cell lysis of Nannochloropsis oceanica, a microalga found in the marine environment, in order to extract intracellular valuables. Algicidal bacteria are capable of lysing algal cell walls while keeping lipids and proteins intact yet separated. We obtained these microbes from locations with consistent algae blooms and found that the bacterium Sagittula stellata displayed significant algicidal properties toward Nannochloropsis oceanica, achieving an algicidal rate of 80.1%. We detected a decrease of 66.2% in in vivo fluorescence intensity in algae cultures, obtained a recoverable crude lipid content of 23.3% and a polyunsaturated fatty acid (PUFA) ratio of 29.0% of bacteria-treated algae, and observed the lysis of the cell membrane and the structure of the nucleus of algae. We also identified the inhibited transcription of the ribulose-1,5-bisphosphate carboxylase/oxygenase small subunit (rbcS) gene and proliferating cell nuclear antigen (PCNA)–related genes and the upregulated heat shock protein (hsp) gene in algal cells during bacterial exposure. Our results indicate that Sagittula stellata effectively lysed microalgae cells, allowing the recovery of intracellular valuables. The algicidal method of Sagittula stellata on Nannochloropsis oceanica cells was confirmed to be a direct attack (or predation), followed by an indirect attack through the secretion of extracellular algicidal compounds. This study provides an important framework for the broad application of algicidal microorganisms in algal cell disruption and the production of intracellular valuables.

The datasets for the tier-1 Scenario Model Intercomparison Project (ScenarioMIP) experiments from the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System model, finite-volume version 3 (CAS FGOALS-f3-L) are described in this study. ScenarioMIP is one of the core MIP experiments in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Considering future CO 2 , CH 4 , N 2 O and other gases’ concentrations, as well as land use, the design of ScenarioMIP involves eight pathways, including two tiers (tier-1 and tier-2) of priority. Tier-1 includes four combined Shared Socioeconomic Pathways (SSPs) with radiative forcing, i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, in which the globally averaged radiative forcing at the top of the atmosphere around the year 2100 is approximately 2.6, 4.5, 7.0 and 8.5 W m −2 , respectively. This study provides an introduction to the ScenarioMIP datasets of this model, such as their storage location, sizes, variables, etc. Preliminary analysis indicates that surface air temperatures will increase by about 1.89°C, 3.07°C, 4.06°C and 5.17°C by around 2100 under these four scenarios, respectively. Meanwhile, some other key climate variables, such as sea-ice extension, precipitation, heat content, and sea level rise, also show significant long-term trends associated with the radiative forcing increases. These datasets will help us understand how the climate will change under different anthropogenic and radiative forcings.

With the development of integrated energy systems (IES), the traditional demand response technologies for single energy that do not take customer satisfaction into account have been unable to meet actual needs. Therefore, it is urgent to study the integrated demand response (IDR) technology for integrated energy, which considers consumers’ willingness to participate in IDR. This paper proposes an energy management optimization method for community IES based on user dominated demand side response (UDDSR). Firstly, the responsive power loads and thermal loads are modeled, and aggregated using UDDSR bidding optimization. Next, the community IES is modeled and an aggregated building thermal model is introduced to measure the temperature requirements of the entire community of users for heating. Then, a day-ahead scheduling model is proposed to realize the energy management optimization. Finally, a penalty mechanism is introduced to punish the participants causing imbalance response against the day-ahead IDR bids, and the conditional value-at-risk (CVaR) theory is introduced to enhance the robustness of the scheduling model under different prediction accuracies. The case study demonstrates that the proposed method can reduce the operating cost of the community under the premise of fully considering users’ willingness, and can complete the IDR request initiated by the power grid operator or the dispatching department.

Two versions of the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System model (CAS-FGOALS), version f3-L and g3, are used to simulate the two interglacial epochs of the mid-Holocene and the Last Interglacial in phase 4 of the Paleoclimate Modelling Intercomparison Project (PMIP4), which aims to study the impact of changes in orbital parameters on the Earth’s climate. Following the PMIP4 experimental protocols, four simulations for the mid-Holocene and two simulations for the Last Interglacial have been completed, and all the data, including monthly and daily outputs for the atmospheric, oceanic, land and sea-ice components, have been released on the Earth System Grid Federation (ESGF) node. These datasets contribute to PMIP4 and CMIP6 (phase 6 of the Coupled Model Intercomparison Project) by providing the variables necessary for the two interglacial periods. In this paper, the basic information of the CAS-FGOALS models and the protocols for the two interglacials are briefly described, and the datasets are validated using proxy records. Results suggest that the CAS-FGOALS models capture the large-scale changes in the climate system in response to changes in solar insolation during the interglacial epochs, including warming in mid-to-high latitudes, changes in the hydrological cycle, the seasonal variation in the extent of sea ice, and the damping of interannual variabilities in the tropical Pacific. Meanwhile, disagreements within and between the models and the proxy data are also presented. These datasets will help the modeling and the proxy data communities with a better understanding of model performance and biases in paleoclimate simulations.

Despite the widespread deployment of quadrotor unmanned aerial vehicles (UAVs), ensuring their flight stability under asymmetric environmental disturbances, such as concurrent wind and rain, remains a significant challenge. To address the trajectory tracking problem under these severe conditions, this paper proposes a Composite Continuous Rapid Nonsingular Adaptive Terminal Sliding Mode (CCRNATSM) control strategy. First, a composite dynamic model is developed, integrating wind aerodynamics with rain impact characteristics to accurately simulate realistic flight environments. A High-Order Sliding Mode Observer (HOSMO) is then employed for the real-time, accurate estimation of these lumped disturbances. Subsequently, this observer is integrated with an adaptive control law to ensure rapid and precise system stabilization. Comparative simulations conducted under strong disturbance conditions demonstrate that the proposed method exhibits superior performance over existing strategies, reducing roll angle deviation by 75% and shortening the recovery time to 1.5 s. Ultimately, this control strategy significantly enhances the robustness and safety of quadrotor UAVs operating in harsh, asymmetric environments.

The datasets of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L) model for the baseline experiment of the fully coupled runs in the Diagnostic, Evaluation and Characterization of Klima (DECK) common experiments of phase 6 of the Coupled Model Intercomparison Project (CMIP6) are described in this study. The CAS FGOALS-f3-L model team submitted the piControl run with a near equilibrium ocean state for 561 model years, and 160-year integrations for three ensemble members of abrupt-4× CO2 and 1pctCO2, respectively. The ensemble members restart from the 600, 650 and 700 model years in the piControl run, respectively. The baseline performances of the model are validated in this article. The preliminary evaluation suggests that the CAS FGOALS-f3-L model can preserve the long-term stability well for a mean net radiation flux of 0.31 W m −2 at the top of the atmosphere, and a limited decreasing trend of −0.03 W m −2 /100 yr. The global annual mean SST is 16.45°C for the 561-year mean, with an increase of 0.03°C/100 yr. The model captures the basic spatial patterns of climate-mean SST and precipitation, but still underestimates the SST over the warm pool. The coupled model mitigates the precipitation bias in the ITCZ compared with the results from CMIP5. Moreover, the model's climate sensitivity represented by the equilibrium climate sensitivity has been reduced from 4.5°C in CMIP5 to 3.0°C in CMIP6. All these datasets contribute to the benchmark of model behaviors for the desired continuity of CMIP.