Abstract: The disclosure discloses an irreversible covalent organic framework for efficient and selective gold recovery and a preparation method thereof, and belongs to the technical field of precious metal recovery from an aqueous solution. In the disclosure, metal trifluoromethanesulfonate is used as a catalyst, and a solvothermal method is used to prepare a mother covalent organic framework, and then the corresponding structural unit is used to perform an exchange reaction to prepare an irreversible amide-linked covalent organic framework material. The disclosure solves the problem of preparation of high-stability irreversible covalent organic framework, the introduced amide bond gives the covalent organic framework the ability to quickly and selectively recover precious metal gold from an aqueous solution, and the covalent organic framework can be used repeatedly.

Abstract: The disclosure discloses an irreversible covalent organic framework for efficient and selective gold recovery and a preparation method thereof, and belongs to the technical field of precious metal recovery from an aqueous solution. In the disclosure, metal trifluoromethanesulfonate is used as a catalyst, and a solvothermal method is used to prepare a mother covalent organic framework, and then the corresponding structural unit is used to perform an exchange reaction to prepare an irreversible amide-linked covalent organic framework material. The disclosure solves the problem of preparation of high-stability irreversible covalent organic framework, the introduced amide bond gives the covalent organic framework the ability to quickly and selectively recover precious metal gold from an aqueous solution, and the covalent organic framework can be used repeatedly.

Abstract: A system may include at least one computer-readable storage medium including a set of instructions for providing an on-demand service; and at least one processor in communication with the computer-readable storage medium. When executing the set of instructions, the at least one processor may be directed to: receive a service request from a user terminal; determine at least one route for the service request; and determine an estimated price for the service request based on the at least one route and at least one price estimation model. In some embodiments, to determine the estimated price, the processor may further be directed to: extract one or more characteristics of the service request based on the route; and process the characteristics of the service request using the price estimation model.

Abstract: The present disclosure relates to systems and methods for determining an estimated time of arrival. The systems may perform the methods to operate logical circuits to obtain a departure location associated with a terminal device and information relating to the departure location. The information may include one or more service providers. The system may operate the logical circuits to obtain a trained machine learning model. The system may operate the logical circuits to determine an estimated time of arrival for one of the one or more service providers to arrive at the departure location based on the information and the machine learning model.