Abstract: An embodiment fuel cell including a high temperature polymer electrolyte membrane includes an electrolyte membrane including a phosphoric acid-doped polymer of intrinsic microporosity, a cathode disposed on a first surface of the electrolyte membrane, and an anode disposed on a second surface of the electrolyte membrane, the second surface opposite the first surface.

Abstract: An adhesive film and a display member including the same are disclosed. The adhesive film is formed of an adhesive composition including: a copolymer of a monomer mixture including a hydroxyl group-containing (meth)acrylate and a comonomer; and nanoparticles. The adhesive film has a creep at ?20° C. of about 50 ?m to about 100 ?m and a gel fraction of about 50% to about 75%.

Abstract: Disclosed is an ionomer for a high-temperature polymer electrolyte membrane fuel cell, which includes a phosphorus (P)-containing functional group having proton conductivity and partially contains fluorine in the main chain thereof.

Abstract: A display device includes first and second electrodes, light-emitting elements on the first and second electrodes, data lines extending from a pad area to a display area, connection wirings spaced apart from the data lines and extending from the pad area to a non-display area on respective sides of the display area, first pads overlapping the data lines in the pad area, and second pads overlapping the connection wirings, wherein the connection wirings include a first connection wiring overlapping a second pad, a second connection wiring not overlapping the second pad and overlapping the first connection wiring in the non-display area, and a third connection wiring overlapping the first connection wiring and electrically connected to the second pad, wherein the first and third connection wirings overlap each other in the pad area, and the first, second, and third connection wirings overlap each other in the non-display area.

Abstract: Disclosed herein are a neural network model deployment method and apparatus for providing a deep learning service. The neural network model deployment method may include providing a specification wizard to a user, searching for and training a neural network based on a user requirement specification that is input through the specification wizard, generating a neural network template code based on the user requirement specification and the trained neural network, converting the trained neural network into a deployment neural network that is usable in a target device based on the user requirement specification, and deploying the deployment neural network to the target device.