Abstract: Provided are a fast-charging anode sheet, a lithium-ion battery, and an electric device. The anode active material in the anode material layer of the fast-charging anode sheet includes a silicon-based material and a carbon-based material; based on the mass of the anode active material as 100%, a mass fraction of the silicon-based material in the anode active material is 70 wt %-99.5 wt %, and a mass fraction of the carbon-based material is 0.5 wt %-30 wt %.

Abstract: A top cover assembly, a battery cell, and a battery pack are provided in this disclosure. The top cover assembly includes a cover plate, a terminal plate, and a sealant. A through hole is formed through the cover plate. The through hole is configured to be in communication with an interior of the battery cell. The terminal plate is installed on the cover plate and covers the through hole. A first overflow groove is formed in the terminal plate at a position corresponding to the through hole, and a groove opening of the first overflow groove faces the through hole. The sealant is interposed between the cover plate and the terminal plate, and the sealant is partially filled into the first overflow groove.

Abstract: The present disclosure relates to a device control method, apparatus, electronic device, and storage medium.

Abstract: The present disclosure relates to a target detection method, a device control method, and a computer device. Specifically, the target detection method includes: displaying a target detection page; acquiring position information of a target object in a target space, wherein the position information is determined by motion trajectory data of the target object in the target space; and, in the target detection page, displaying in real time a position marker corresponding to the target object, wherein a page position of the position marker is determined based on the position information of the target object in the target space.

Abstract: Disclosed in the present disclosure is a method of formation and capacity grading for lithium-ion batteries, including the following steps: Formation: charging the SOC of the lithium-ion battery to be greater than or equal to 100%, wherein a charging process comprises at least a first stage, a second stage, a third stage, a fourth stage, and a fifth stage; and applying pressure to two opposite surfaces of the lithium-ion battery at each stage, wherein the pressure applied at the first stage is 0.1-0.3 Mpa, the pressure applied at the second stage is 0.3-0.5 Mpa, the pressure applied at the third stage is 0.8-1.2 Mpa, the pressure applied at the fourth stage is 0.3-0.5 Mpa, and the pressure applied at the fifth stage is 0.8-1.2 Mpa. Capacity Grading: fixing the lithium-ion battery after formation; applying pressure to 50-100 kg on the two opposite surfaces of the lithium-ion battery; and performing a capacity grading cycle.

Abstract: A high-rhythm and high-precision 90-degree turnover method including: changing materials; turning a prong over and waiting; driving a first drum conveyor line to move leftward to a turnover station; adjusting front and rear positions of the first drum conveyor line as a whole to make a stacked assembly aligned with a center line of the wooden pallet; driving a first drum conveyor line to move leftward to make a left surface of the stacked assembly abut against a surface of the wooden pallet; driving a prong group to move upward to a second height position to support the stacked assembly; and driving a third support to turn over by 90 degrees reversely to make a second drum conveyor line turned over to a horizontal state.

Abstract: System model is established to characterize mobile devices, edge servers, tasks and nodes. Node unloading rule is established, and the mobile device can be selected to unload the nodes to the edge server or leave the nodes to be executed locally. Timeline model is established to record arrival events of all tasks and execution completion events of the nodes. Online multi-workflow scheduling policy based on reinforcement learning is established, state space and action space of scheduling problem are defined, and reward function of the scheduling problem is designed. Algorithm based on policy gradient is designed to solve online multi-workflow scheduling problem for implementing the scheduling policy. Unloading decision and resource allocation are performed based on features extracted by graph convolution neural network. Current workflow and state of the server can be analyzed in real time, thereby reducing complexity and average completion time of all workflows.

Abstract: A positive electrode for a lithium-ion battery is provided. Opposite cleaning regions are provided respectively on opposite sides of the positive electrode in a thickness direction thereof for welding with a welding end of a tab. A notch is formed on a side of the cleaning regions close to an edge of the positive electrode in a width direction thereof. The notch penetrates the positive electrode in the thickness direction and a part of the tab which is corresponding to the notch in a width direction of the positive electrode is a matching part, the matching part is enabled to be provided in the notch. D1 is greater than D2, where D1 represents a dimension of a part of the cleaning regions intersecting an edge of the notch in a length direction of the positive electrode, and D2 represents a maximum dimension of the notch in the length direction.

Abstract: System model is established to characterize mobile devices, edge servers, tasks and nodes. Node unloading rule is established, and the mobile device can be selected to unload the nodes to the edge server or leave the nodes to be executed locally. Timeline model is established to record arrival events of all tasks and execution completion events of the nodes. Online multi-workflow scheduling policy based on reinforcement learning is established, state space and action space of scheduling problem are defined, and reward function of the scheduling problem is designed. Algorithm based on policy gradient is designed to solve online multi-workflow scheduling problem for implementing the scheduling policy. Unloading decision and resource allocation are performed based on features extracted by graph convolution neural network. Current workflow and state of the server can be analyzed in real time, thereby reducing complexity and average completion time of all workflows.

Abstract: The present disclosure provides a method for generating ethylene by electrochemical selective hydrogenation of acetylene, including the following steps: continuously feeding acetylene gas into an organic solvent at a flow rate of 1 sccm to 50 sccm to obtain a solution; adding an electrolyte in the form of a solution or a solid such that the solution has an electrolyte concentration of 0.1 M to 3 M, a conductivity of 100 ?s·cm?1 to 500 ?s·cm?1, and a current density of 10 mA·cm?2 to 300 mA·cm?2; adding a hydrogen source such that the solution has a proton concentration of 0.1 M to 28 M; turning on an electrochemical treatment unit, and conducting constant-current or constant-potential electrolysis such that the acetylene gas is continuously and efficiently converted into ethylene gas after the electrolysis is stably conducted. The method has simple operations, low energy consumption, and quick response.

Abstract: The present disclosure provides a method for generating ethylene by electrochemical selective hydrogenation of acetylene, including the following steps: continuously feeding acetylene gas into an organic solvent at a flow rate of 1 sccm to 50 sccm to obtain a solution; adding an electrolyte in the form of a solution or a solid such that the solution has an electrolyte concentration of 0.1 M to 3 M, a conductivity of 100 µs·cm-1 to 500 µs·cm-1, and a current density of 10 mA·cm-2 to 300 mA·cm-2; adding a hydrogen source such that the solution has a proton concentration of 0.1 M to 28 M; turning on an electrochemical treatment unit, and conducting constant-current or constant-potential electrolysis such that the acetylene gas is continuously and efficiently converted into ethylene gas after the electrolysis is stably conducted.