Abstract: Graphene nanoribbons and methods for fabricating graphene nanoribbons, particularly those with long lengths, are provided. In one embodiment, a method (400) for fabricating a graphene nanoribbon (100) includes preparing (410) a mask for application on a substrate (102). The mask may include a continuous line of masking material spiraling outward from a first end (104) of the line to a second end (106). The method (400) also includes depositing (420) a graphene layer (108) over a top surface (102A) of the substrate (102), applying (430) the mask to the substrate (102) over the graphene layer (108), removing (440) an unmasked portion of the graphene layer (108), and removing (450) the masking material from a remaining portion of the graphene layer (108) to leave a continuous line of graphene on the surface (102A) of the substrate (100) corresponding with the mask.

Abstract: Graphene nanoribbons and methods for fabricating graphene nanoribbons, particularly those with long lengths, are provided. In one embodiment, a method (400) for fabricating a graphene nanoribbon (100) includes preparing (410) a mask for application on a substrate (102). The mask may include a continuous line of masking material spiraling outward from a first end (104) of the line to a second end (106). The method (400) also includes depositing (420) a graphene layer (108) over a top surface (102A) of the substrate (102), applying (430) the mask to the substrate (102) over the graphene layer (108), removing (440) an unmasked portion of the graphene layer (108), and removing (450) the masking material from a remaining portion of the graphene layer (108) to leave a continuous line of graphene on the surface (102A) of the substrate (100) corresponding with the mask.

Abstract: An apparatus for determining a condition parameter of a battery, receives measurement signals related to the battery, determines input data such as electrical impedance from the measurement signals, and provides the input data to a plurality of different prediction algorithms, wherein each prediction algorithm provides a condition parameter estimate. A plurality of condition parameter estimates are then provided to a decision fusion algorithm, allowing a more accurate prediction of the condition parameter.