Mashed Articles

http://www.freepatentsonline.com/7419887.html

This patent teaches a new type of nanofabrication process involving the focusing of a laser beam width to nanometer dimensions and using the laser to fuse nanoparticles deposited via a nanosize pore. Claim 1 reads:

1. The process of forming a nano structure on a substrate, comprising:

suspending nano particles in a suspension fluid;

applying a pressure to the suspension fluid for forcing the nano particles through a nano size pore onto the substrate;

directing a micrometer size laser beam through a concentrator for forming a nanometer size laser beam; and

directing the nano size laser beam onto the deposited nano particles on the substrate.

http://www.freepatentsonline.com/7413633.html

Polyurethane is useful as a protective coatings and sealants in numerous applications. This patent from Albany International discloses adding nanoparticles to a urethane coating used as a belt in paper making processes to improve the crack and wear resistance of such belts. Claim 1 reads:

1. A papermaking process belt or textile belt, comprising:

a urethane-based coating comprising nanoparticles, wherein at least one of the following characteristics is improved: resistance to crack propagation, resistance to groove closure, or wear characteristics.

http://www.freepatentsonline.com/7412428.html

This patent is one in a series of patents from Alex Nugent who has come up with a variety of techniques to use nanoparticle based interconnections to simulate physical neural networks. One of the limitations of current artificial intelligence approaches is the reliance on software solutions which have an intrinsic delay required for the transfer of information between memory and a processor. On the other hand physical neural networks have the potential to integrate memory with processing. This latest patent teaches a system for applying a Hebbian learning process to a physical neutral network formed from nanoparticles, nanowires, or nanotubes.

1. A system, comprising:

a physical neural network configured utilizing nanotechnology and integrated with feedback circuitry, wherein said physical neural network comprises a plurality of nanoconductors comprising at least one of nanotubes, nanowires, or nanoparticles, suspended and free to move about in a dielectric medium and which form neural connections between pre-synaptic and post-synaptic components of said physical neural network; and

a learning mechanism for applying Hebbian learning to said physical neural network.