A thermal interface material under a high vacuum condition includes a graphite sheet having a thickness of from 9.6 m to 50 nm and a thermal conductivity in an a-b surface direction at 25 C. of not less than 1000 W/mK.

Biomass (e.g., plant biomass, animal biomass, and municipal waste biomass) is processed to produce useful products, such as fuels. For example, systems can use feedstock materials, such as cellulosic and/or lignocellulosic materials and/or starchy or sugary materials, to produce ethanol and/or butanol, e.g., by fermentation.

Biomass (e.g., plant biomass, animal biomass, and municipal waste biomass) is processed to produce useful products, such as fuels. For example, systems can use feedstock materials, such as cellulosic and/or lignocellulosic materials and/or starchy or sugary materials, to produce ethanol and/or butanol, e.g., by fermentation.

Transition radiation from nanotubes, nanosheets, and nanoparticles and in particular, boron nitride nanomaterials, can be utilized for the generation of light. Wavelengths of light of interest for microchip lithography, including 13.5 nm (91.8 eV) and 6.7 nm (185 eV), can be generated at useful intensities, by transition radiation light sources. Light useful for monitoring relativistic charged particle beam characteristics such as spatial distribution and intensity can be generated.

Transition radiation from nanotubes, nanosheets, and nanoparticles and in particular, boron nitride nanomaterials, can be utilized for the generation of light. Wavelengths of light of interest for microchip lithography, including 13.5 nm (91.8 eV) and 6.7 nm (185 eV), can be generated at useful intensities, by transition radiation light sources. Light useful for monitoring relativistic charged particle beam characteristics such as spatial distribution and intensity can be generated.

Disclosed herein a liquid level detection device capable of appropriately detecting a liquid level of a high temperature plasma raw material in a reservoir for storing the high temperature plasma raw material. The liquid level detection device includes: an upper limit level sensor configured to detect that the liquid level of the tin is elevated from downward to reach an upper limit level; and a refilling level sensor configured to detect that the liquid level of the tin is lowered from upward to reach a refilling level or a lower limit level. A detection responsiveness of the liquid level of the upper limit level sensor is higher than the refilling level sensor or the lower limit level sensor, and a detectability of the liquid level of the refilling level sensor or the lower limit level sensor is higher than the upper limit level sensor.

Disclosed herein a liquid level detection device capable of appropriately detecting a liquid level of a high temperature plasma raw material in a reservoir for storing the high temperature plasma raw material. The liquid level detection device includes: an upper limit level sensor configured to detect that the liquid level of the tin is elevated from downward to reach an upper limit level; and a refilling level sensor configured to detect that the liquid level of the tin is lowered from upward to reach a refilling level or a lower limit level. A detection responsiveness of the liquid level of the upper limit level sensor is higher than the refilling level sensor or the lower limit level sensor, and a detectability of the liquid level of the refilling level sensor or the lower limit level sensor is higher than the upper limit level sensor.

A method for optimizing a binary mask pattern includes determining, by a processor, an evaluation value based on a comparison between a design pattern and a substrate pattern simulated based on the binary mask pattern. The method also includes, based on the evaluation value, using, by the processor, a gradient-based optimization method to generate a first adjusted binary mask pattern. The method also includes determining, by the processor, a first updated evaluation value based on a comparison between the design pattern and a first updated substrate pattern simulated based on the first adjusted binary mask pattern. The method also includes, based on the first updated evaluation value, using, by the processor, a product of a Hessian matrix and an arbitrary vector to generate a second adjusted binary mask pattern. The method also includes simulating, by the processor, a second updated substrate pattern based on the second adjusted binary mask pattern.

A method for optimizing a binary mask pattern includes determining, by a processor, an evaluation value based on a comparison between a design pattern and a substrate pattern simulated based on the binary mask pattern. The method also includes, based on the evaluation value, using, by the processor, a gradient-based optimization method to generate a first adjusted binary mask pattern. The method also includes determining, by the processor, a first updated evaluation value based on a comparison between the design pattern and a first updated substrate pattern simulated based on the first adjusted binary mask pattern. The method also includes, based on the first updated evaluation value, using, by the processor, a product of a Hessian matrix and an arbitrary vector to generate a second adjusted binary mask pattern. The method also includes simulating, by the processor, a second updated substrate pattern based on the second adjusted binary mask pattern.

A method for optimizing a binary mask pattern includes determining, by a processor, an evaluation value based on a comparison between a design pattern and a substrate pattern simulated based on the binary mask pattern. The method also includes, based on the evaluation value, using, by the processor, a gradient-based optimization method to generate a first adjusted binary mask pattern. The method also includes determining, by the processor, a first updated evaluation value based on a comparison between the design pattern and a first updated substrate pattern simulated based on the first adjusted binary mask pattern. The method also includes, based on the first updated evaluation value, using, by the processor, a product of a Hessian matrix and an arbitrary vector to generate a second adjusted binary mask pattern. The method also includes simulating, by the processor, a second updated substrate pattern based on the second adjusted binary mask pattern.