Disclosed herein are embodiments of gold nanoparticles and methods of making and using the gold nanoparticles. The disclosed gold nanoparticles have core sizes and polydispersities controlled by the methods of making the gold nanoparticles. In some embodiments, the methods of making the gold nanoparticles can concern using flow reactors and reaction conditions controlled to make gold nanoparticles having a desired core size. The gold nanoparticles disclosed herein also comprise various ligands that can be used to facilitate the use of the gold nanoparticles in a variety of applications.

Disclosed herein are embodiments of gold nanoparticles and methods of making and using the gold nanoparticles. The disclosed gold nanoparticles have core sizes and polydispersities controlled by the methods of making the gold nanoparticles. In some embodiments, the methods of making the gold nanoparticles can concern using flow reactors and reaction conditions controlled to make gold nanoparticles having a desired core size. The gold nanoparticles disclosed herein also comprise various ligands that can be used to facilitate the use of the gold nanoparticles in a variety of applications.

This disclosure relates to the field of renewable oil compositions and to the use of renewable oil compositions for production of hydrocarbon compositions, which can be used for traffic fuels and other solutions. An exemplary composition contains free fatty acids and triglycerides, in a concentration of free fatty acids from 15 wt-% to 80 wt-% and a remainder being predominantly triglycerides. A method for producing hydrocarbons from a renewable oil feedstock, in which the feedstock which contains free fatty acids from 15 wt-% to 80 wt-%, and a remainder being predominantly triglycerides, is subjected to a pretreatment process followed by a hydrotreatment process for obtaining hydrocarbons.

A measurement device includes an analyzer configured to analyze a diffraction image of X-rays scattered from a subject; estimate a surface contour shape of a measurement area of the subject; extract feature data from shape information, and determine shape parameters for representing the surface contour shape; calculate a theoretical scattering intensity of each of the scattered X-rays when values of the shape parameters are changed; calculate a difference between a measured scattering intensity of each scattered X-ray and the corresponding theoretical scattering intensity, and generate a regression model of a relationship between a corresponding value of the shape parameter and the difference for each shape parameter; extract one shape parameter candidate value reducing the difference from the regression model, and calculate a theoretical scattering intensity of the shape parameter candidate value; and estimate the value of the shape parameter minimizing the difference while repeatedly changing the shape parameter candidate value.

An in vitro method for detecting presence of cancer includes obtaining a single hair sample. An x-ray beam is emitted from a source towards the hair sample. A small angle X-ray scattering (SAXS) intensity profile is generated after the x-ray beam hits the hair sample. The SAXS profile is received on a detector to obtain SAXS data, which is desmeared and Kratky Analysis is performed. A relative estimation of peak area under 1.38 nm.sup.−1 to 0.89 nm.sup.−1 from keratin and lipid content in the hair sample is performed to obtain R and is corrected by dividing by D, thickness of the hair. R′ is computed using formula: 10×R.sup.2/(D−R). The value of R′ is compared with clinically validated samples. If R′ value is below 0.7, it indicates the presence of cancer and if it is above 0.8, it indicates absence of cancer.

An in vitro method for detecting presence of cancer includes obtaining a single hair sample. An x-ray beam is emitted from a source towards the hair sample. A small angle X-ray scattering (SAXS) intensity profile is generated after the x-ray beam hits the hair sample. The SAXS profile is received on a detector to obtain SAXS data, which is desmeared and Kratky Analysis is performed. A relative estimation of peak area under 1.38 nm.sup.−1 to 0.89 nm.sup.−1 from keratin and lipid content in the hair sample is performed to obtain R and is corrected by dividing by D, thickness of the hair. R′ is computed using formula: 10×R.sup.2/(D−R). The value of R′ is compared with clinically validated samples. If R′ value is below 0.7, it indicates the presence of cancer and if it is above 0.8, it indicates absence of cancer.

A metrology system is disclosed. In one embodiment, the metrology system includes a controller communicatively coupled to a reference metrology tool and an optical metrology tool, the controller including one or more processors configured to: generate a geometric model for determining a profile of a test HAR structure from metrology data from a reference metrology tool; generate a material model for determining one or more material parameters of a test HAR structure from metrology data from the optical metrology tool; form a composite model from the geometric model and the material model; measure at least one additional test HAR structure with the optical metrology tool; and determine a profile of the at least one additional test HAR structure based on the composite model and metrology data from the optical metrology tool associated with the at least one HAR test structure.

A metrology system is disclosed. In one embodiment, the metrology system includes a controller communicatively coupled to a reference metrology tool and an optical metrology tool, the controller including one or more processors configured to: generate a geometric model for determining a profile of a test HAR structure from metrology data from a reference metrology tool; generate a material model for determining one or more material parameters of a test HAR structure from metrology data from the optical metrology tool; form a composite model from the geometric model and the material model; measure at least one additional test HAR structure with the optical metrology tool; and determine a profile of the at least one additional test HAR structure based on the composite model and metrology data from the optical metrology tool associated with the at least one HAR test structure.

A method for evaluating an array of high aspect ratio (HAR) structures on a sample includes illuminating the sample with an x-ray beam along a first axis parallel to within two degrees to the HAR structures in the array and sensing a first pattern of small angle x-ray scattering (SAXS) scattered from the sample while illuminating the sample along the first axis. The sample is illuminated with the x-ray beam along a second axis that is oblique to the HAR structures in the array, and a second pattern of the SAXS scattered from the sample is sensed while illuminating the sample along the second axis. Information is extracted with respect to the HAR structures based on the first and second patterns.

A method for evaluating an array of high aspect ratio (HAR) structures on a sample includes illuminating the sample with an x-ray beam along a first axis parallel to within two degrees to the HAR structures in the array and sensing a first pattern of small angle x-ray scattering (SAXS) scattered from the sample while illuminating the sample along the first axis. The sample is illuminated with the x-ray beam along a second axis that is oblique to the HAR structures in the array, and a second pattern of the SAXS scattered from the sample is sensed while illuminating the sample along the second axis. Information is extracted with respect to the HAR structures based on the first and second patterns.