Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides to a user a subset of digital design templates as recommendations based on a creative segment classification and template classifications. For instance, in one or more embodiments, the disclosed systems generate the creative segment classification for the user and determines geo-seasonal intent data. Furthermore, the disclosed system generates template classifications using a machine learning model based on geo-seasonality and creative intent. In doing so, the disclosed system identifies a subset of digital design templates based on the template classifications, geo-seasonal intent data, and the creative segment classification of the user.

Abstract: An electrically conductive and corrosion resistant graphene-based coating composition, including a binder, high-pressure airless-sprayed expanded graphene stacks, carbon fibers, and a dispersing agent, wherein the graphene-based coating composition has an electrical conductivity of at least 2 S/cm and a pull-off adhesion of at least 2 MPa.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides to a user a subset of digital design templates as recommendations based on a creative segment classification and template classifications. For instance, in one or more embodiments, the disclosed systems generate the creative segment classification for the user and determines geo-seasonal intent data. Furthermore, the disclosed system generates template classifications using a machine learning model based on geo-seasonality and creative intent. In doing so, the disclosed system identifies a subset of digital design templates based on the template classifications, geo-seasonal intent data, and the creative segment classification of the user.

Abstract: In implementations of systems for identifying templates based on fonts, a computing device implements an identification system to receive input data describing a selection of a font included in a collection of fonts. The identification system generates an embedding that represents the font in a latent space using a machine learning model trained on training data to generate embeddings for digital templates in the latent space based on intent phrases associated with the digital templates and embeddings for fonts in the latent space based on intent phrases associated with the fonts. A digital template included in a collection of digital templates is identified based on the embedding that represents the font and an embedding that represents the digital template in the latent space. The identification system generates an indication of the digital template for display in a user interface.

Abstract: An electrically conductive and corrosion resistant graphene-based coating composition, including a binder, high-pressure airless-sprayed expanded graphene stacks, carbon fibers, and a dispersing agent, wherein the graphene-based coating composition has an electrical conductivity of at least 2 S/cm and a pull-off adhesion of at least 2 MPa.

Abstract: An electrically conductive and corrosion resistant graphene-based coating composition, including a binder, a graphene-filler; and a dispersing agent, wherein the graphene filler comprises a plurality of graphene stacks.

Abstract: An electrically conductive and corrosion resistant graphene-based coating composition, including a binder, a graphene-filler; and a dispersing agent, wherein the graphene filler comprises a plurality of graphene stacks.