Abstract: Ablation of holes having diameters as small as 82 nm and having clean walls was obtained in a poly(methyl methacrylate) on a silicon substrate by focusing pulses from a Ne-like Ar, 46.9 nm wavelength, capillary-discharge laser using a freestanding Fresnel zone plate diffracting into third order is described. Spectroscopic analysis of light from the ablation has also been performed. These results demonstrate the use of focused coherent EUV/SXR light for the direct nanoscale patterning of materials.

Abstract: Ablation of holes having diameters as small as 82 nm and having clean walls was obtained in a poly(methyl methacrylate) on a silicon substrate by focusing pulses from a Ne-like Ar, 46.9 nm wavelength, capillary-discharge laser using a freestanding Fresnel zone plate diffracting into third order is described. Spectroscopic analysis of light from the ablation has also been performed. These results demonstrate the use of focused coherent EUV/SXR light for the direct nanoscale patterning of materials.

Abstract: A scanning boom microscope comprises an optical axis that can be varied into any axis or direction relative to a circular displacement about an optical boom that supports the scanning boom microscope's objective in free space. Accordingly, scanning boom microscope can be positioned to observe free standing samples away from the microscope base.

Abstract: A particle detection system uses a reflective optic comprising a curved surface to detect high angle scattered light generated by a particle in a liquid medium, when a laser beam is incident on the particle. When the particles transit the laser beam, light is scattered in all directions and is described by MIE scattering theory for particles about the size of the wavelength of light and larger or Rayleigh Scattering when the particles are smaller than the wavelength of light. By using the reflective optic, the scattered light can be detected over angles that are greater than normally obtainable.

Abstract: A particle detection system to identify and classify particles is programmed to capture digitized images of the particle generated by directing a light source through a fluid that includes the particle. The particle scatters the light and the scattered light is detected using a detector. The detector creates a digital signal corresponding to the particle, which is used by the system to generate biological optical signal. This biological optical signal can then be used to classify the event, or particle.

Abstract: A particle detection system to identify and classify particles is programmed to capture digitized images of the particle generated by directing a light source through a fluid that includes the particle. The particle scatters the light and the scattered light is detected using a detector. The detector creates a digital signal corresponding to the particle, which is used by the system to generate Bio-Optical Signature. This Bio-Optical Signature can then be used to classify the event, or particle. Count rate and trends of the classified particles are monitored to detect a change that is representative of the overall health safety of the water or by knowing the levels of bacteria in process water, such as Reverse Osmosis (RO) feed water, reject brine, and product water, the operator may better monitor the life and condition of the RO membrane.

Abstract: A particle detection system to identify and classify particles is programmed to capture digitized images of the particle generated by directing a light source through a fluid that includes the particle. The particle scatters the light and the scattered light is detected using a detector. The detector creates a digital signal corresponding to the particle, which is used by the system to generate a Bio-Optical Signature. This Bio-Optical Signature can then be used to classify the event, or particle. A count rate of the classified particles is monitored to detect a change that is representative of a toxin attack.

Abstract: A particle detection system to identify and classify particles is programmed to capture digitized images of the particle generated by directing a light source through a fluid that includes the particle. The particle scatters the light and the scattered light is detected using a detector. The detector creates a digital signal corresponding to the particle, which is used by the system to generate a Bio-Optical Signature. This Bio-Optical Signature can then be used to classify the event, or particle. A count rate of the classified particles is monitored to detect a change that is representative of a toxin attack.

Abstract: A particle detection system to identify and classify particles is programmed to capture digitized images of the particle generated by directing a light source through a fluid that includes the particle. The particle scatters the light and the scattered light is detected using a detector. The detector creates a digital signal corresponding to the particle, which is used by the system to generate Bio-Optical Signature. This Bio-Optical Signature can then be used to classify the event, or particle. Count rate and trends of the classified particles are monitored to detect a change that is representative of the overall health safety of the water or by knowing the levels of bacteria in process water, such as Reverse Osmosis (RO) feed water, reject brine, and product water, the operator may better monitor the life and condition of the RO membrane.

Abstract: A particle detection system to identify and classify particles is programmed to capture digitized images of the particle generated by directing a light source through a fluid that includes the particle. The particle scatters the light and the scattered light is detected using a detector. The detector creates a digital signal corresponding to the particle, which is used by the system to generate biological optical signal. This biological optical signal can then be used to classify the event, or particle.