Facile synthesis of catalytically active CeO₂ with excellent thermal stability for soot oxidation.

Petroleum has become a strategic resource to the national economy, and forecasting its demand is a critical step to supporting energy planning and policy-making for carbon reduction. We first conducted a characteristic analysis of end consumption for petroleum products, and the key affecting factors are identified through an extended logarithmic mean Divisia index (LMDI) method. Afterwards, the long-range energy alternatives planning system (LEAP) was adopted to predict the petroleum products demand by considering the potential impacts of different policies on the identified key factors. Through comparative analysis of three scenarios including five sub-scenarios, the findings show that the dual carbon constraints are crucial to petroleum demand control. Under the enforcement of existing carbon peaking policies, the petroleum products demand will peak around 2043 at 731.5 million tons, and the impact of energy intensity-related policies is more significant than that of activity level. However, even if the existing policy efforts are continued, supporting the carbon-neutral target will not be easy. By further strengthening the constraints, the demand will peak around 2027 at 680 million tons, and the abatement contribution will come mainly from industry (manufacturing), construction, and transportation. Additional abatement technologies are necessary for the petroleum industry to achieve carbon neutrality.

Distillation is the most energy-consuming unit operation of the chemical industry, however, its decarbonization strategy necessitates laborious manual process simulation, optimization and carbon emission accounting. Here we established a reasoning agent consisting of a large language model (LLM) and an extensive tool set to automate learning material collection, process simulation, optimization and carbon emission accounting of a representative methanol and ethanol distillation case study. Then the agent automatically constructed a heat pump-assisted distillation process to save energy. The impact of three energy supply scenarios on the carbon emissions of distillation, namely, coal, natural gas and renewables, was evaluated. Combining the heat pump-assisted process and renewables could substantially reduce the carbon emission by 98% compared with the coal-based traditional distillation process. This study explored using reasoning agents to automate carbon emission and decarbonization intervention quantification, and facilitated high-resolution carbon emission models of the industry.

An improved control scheme for stand-alone DFIG-based wind energy conversion system is proposed. The intermediate DC-link of back-to-back PWM converter is supported with a battery energy storage system to smooth the fluctuation of power caused by the variation of wind speed and loads. A three-phase four-leg converter is employed as the Stator-Side Converter (SSC) to provide a path for the zero-sequence current. Based on the modified topology, the stator voltage of DFIG is directly controlled by the SSC. And the rotor speed of DFIG is regulated by the rotor-side converter for maximum power point tracking. Modified repetitive controllers incorporated with the state-feedback controllers are adopted for the SSC to ensure the desirable stator voltage even under the unbalanced loads or non-linear loads conditions. The proposal avoids the complicated operation of the harmonic extraction, and the positive- and negative-sequence current decomposition, which is verified by the simulation results.