Abstract: Methods and systems are disclosed using an execution pipeline on a multi-processor platform for deep learning network execution. In one example, a network workload analyzer receives a workload, analyzes a computation distribution of the workload, and groups the network nodes into groups. A network executor assigns each group to a processing core of the multi-core platform so that the respective processing core handle computation tasks of the received workload for the respective group.

Abstract: Batteries include a current collector, a cathode, an interlayer disposed on the cathode, a solid-state electrolyte disposed on the interlayer, and a lithium anode disposed on the solid-state electrolyte. In aspects, the interlayer includes a lithium salt and a sulfone compound within a polymeric matrix. In aspects, the interlayer includes a lithium salt and a sulfone compound. In aspects, methods of forming a battery comprise disposing a precursor solution comprising a lithium salt, a sulfone compound, and a monomer on a first major surface of a cathode. Methods can further include curing the precursor solution to form an interlayer including the lithium salt and the sulfone compound within a polymeric matrix. In aspects, methods can include disposing a lithium salt and a sulfone compound on a first major surface of a cathode. Methods further include disposing a solid-state electrolyte over the first major surface of the cathode.

Abstract: A composition includes a first portion including Ni-rich LiNixCoyMnzO2, where 0.5<x<1, 0<y<1, 0<z<1; a second portion including Li3PO4 such that the second portion is coated on the first portion, and the first portion is doped with an elemental metal selected from at least one of Zr, Sn, Nb, Ta, Al, and Fe. The molar ratio between Li3PO4 and Ni-rich LiNixCoyMnzO2 ranges from 0.76:100 to 3.8:100. A method of forming a composition includes mixing a metal precursor with nickel-cobalt-manganese (NCM) precursor to form a first mixture; adding a lithium-based compound to the first mixture to form a second mixture; and calcining the second mixture at a predetermined temperature for a predetermined time to form the composition.

Abstract: A battery includes a substrate; a cathode disposed on the substrate; at least one interlayer disposed on the cathode; a solid-state electrolyte (SSE) disposed on the interlayer; and a lithium anode disposed on the solid-state electrolyte, such that the at least one interlayer is a deep-eutectic-solvent-based (DES) electrolyte.

Abstract: A battery includes a substrate; a composite cathode disposed on the substrate; a solid-state electrolyte disposed on the composite cathode; and a lithium anode disposed on the solid-state electrolyte, such that the composite cathode comprises a gel polymer electrolyte layer and a porous cathode active material layer. A method of forming a cathode for a solid-state battery includes mixing an active cathode material, at least one of a conductive carbon component and an electronic conductive component, and a polymer binder to form a slurry; immersing the slurry in an alcohol reagent to form a porous disc structure by phase conversion; and immersing the porous disc structure in a liquid electrolyte to form the cathode.

Abstract: A computer retrieves data from a database. The computer retrieves a Machine Learning (ML) model trained to generate database queries. The computer applies the ML model to generate a primary database query based, at least in part, on a user inquiry available to the computer. The computer retrieves the primary database query, an initial set of data from a database available to the computer. The computer, in response to retrieving the initial set of data, receives feedback assessing the initial set of data. The computer, in response to receiving the feedback, applies a Natural Language Processing (NLP) model to identify query adjustment content within the feedback. The computer revises the primary database query based, at least in part, on the model adjustment content, to generate a secondary database query. The computer retrieves using the secondary database query, a secondary set of data from the database.

Abstract: A composition includes a first portion including Ni-rich LiNixCo?MnzO2, where 0.5<x<1, 0<y<1, 0<z<1; a second portion including Li?Zr?O?, where 0<?<9, 0<?<3, and 1<?<10 such that the second portion is coated on the first portion, and the first portion is doped with an elemental metal selected from at least one of Zr, Si, Sn, Nb, Ta, Al, and Fe. A method of forming a composition includes mixing a metal precursor with nickel-cobalt-manganese (NCM) precursor to form a first mixture; adding a lithium-based compound to the first mixture to form a second mixture; and calcining the second mixture at a predetermined temperature for a predetermined time to form the composition.

Abstract: Methods, systems, and computer-readable media for analysis of code coverage differences across environments are disclosed. A code coverage profiling system determines a first code coverage profile associated with execution of program code in a first environment. The first code coverage profile indicates one or more portions of the program code that were executed in the first environment. The code coverage profiling system determines a second code coverage profile associated with execution of the program code in a second environment. The second code coverage profile indicates one or more portions of the program code that were executed in the second environment. The code coverage profiling system performs a comparison of the first code coverage profile and the second code coverage profile. The comparison determines a difference between the portions of the program code that were executed in the first and second environments.

Abstract: A computer retrieves data from a database. The computer retrieves a Machine Learning (ML) model trained to generate database queries. The computer applies the ML model to generate a primary database query based, at least in part, on a user inquiry available to the computer. The computer retrieves the primary database query, an initial set of data from a database available to the computer. The computer, in response to retrieving the initial set of data, receives feedback assessing the initial set of data. The computer, in response to receiving the feedback, applies a Natural Language Processing (NLP) model to identify query adjustment content within the feedback. The computer revises the primary database query based, at least in part, on the model adjustment content, to generate a secondary database query. The computer retrieves using the secondary database query, a secondary set of data from the database.

Abstract: Methods, systems, and computer-readable media for analysis of code coverage differences across environments are disclosed. A code coverage profiling system determines a first code coverage profile associated with execution of program code in a first environment. The first code coverage profile indicates one or more portions of the program code that were executed in the first environment. The code coverage profiling system determines a second code coverage profile associated with execution of the program code in a second environment. The second code coverage profile indicates one or more portions of the program code that were executed in the second environment. The code coverage profiling system performs a comparison of the first code coverage profile and the second code coverage profile. The comparison determines a difference between the portions of the program code that were executed in the first and second environments.

Abstract: The present invention may include a computer receives raw data. The computer converts the raw data into a dataset, where the dataset comprises independent variables and dependent variables. Then, the computer clusters the dataset to determine a corresponding target value to each of a plurality of clusters. The computer constructs a nonlinear programming problem based on a prior experience and generates an enlarged dataset by solving the nonlinear programming problem.

Abstract: A battery includes a substrate; a composite cathode disposed on the substrate; a solid-state electrolyte disposed on the composite cathode; and a lithium anode disposed on the solid-state electrolyte, such that the composite cathode comprises a gel polymer electrolyte layer and a porous cathode active material layer. A method of forming a cathode for a solid-state battery includes mixing an active cathode material, at least one of a conductive carbon component and an electronic conductive component, and a polymer binder to form a slurry; immersing the slurry in an alcohol reagent to form a porous disc structure by phase conversion; and immersing the porous disc structure in a liquid electrolyte to form the cathode.