This disclosure relates to an apparatus and methods for applying X-ray reflectometry (XRR) in characterizing three dimensional nanostructures supported on a flat substrate with a miniscule sampling area and a thickness in nanometers. In particular, this disclosure is targeted for addressing the difficulties encountered when XRR is applied to samples with intricate nanostructures along all three directions, e.g. arrays of nanostructured poles or shafts. Convergent X-ray with long wavelength, greater than that from a copper anode of 0.154 nm and less than twice of the characteristic dimensions along the film thickness direction, is preferably used with appropriate collimations on both incident and detection arms to enable the XRR for measurements of samples with limited sample area and scattering volumes.

This disclosure relates to an apparatus and methods for applying X-ray reflectometry (XRR) in characterizing three dimensional nanostructures supported on a flat substrate with a miniscule sampling area and a thickness in nanometers. In particular, this disclosure is targeted for addressing the difficulties encountered when XRR is applied to samples with intricate nanostructures along all three directions, e.g. arrays of nanostructured poles or shafts. Convergent X-ray with long wavelength, greater than that from a copper anode of 0.154 nm and less than twice of the characteristic dimensions along the film thickness direction, is preferably used with appropriate collimations on both incident and detection arms to enable the XRR for measurements of samples with limited sample area and scattering volumes.

Estimating wear on bottom hole assembly (BHA) components utilizes a rock hardness index using analysis of drill cutting. Estimating the amount of wear on borehole assembly components comprises measuring the rock properties in drilled cuttings from a borehole. A hardness value is assigned to each mineral present in the drilled cuttings. A hardness index is calculated for a drilled borehole interval. A wear resistance factor is assigned to each BHA component of the BHA. The wear resistance factor depends on the wear resistance of each BHA component. A wear value for each BHA component is calculated based on the hardness index for the drilled borehole interval, the wear resistance of the BHA component, and drilling parameters.

Estimating wear on bottom hole assembly (BHA) components utilizes a rock hardness index using analysis of drill cutting. Estimating the amount of wear on borehole assembly components comprises measuring the rock properties in drilled cuttings from a borehole. A hardness value is assigned to each mineral present in the drilled cuttings. A hardness index is calculated for a drilled borehole interval. A wear resistance factor is assigned to each BHA component of the BHA. The wear resistance factor depends on the wear resistance of each BHA component. A wear value for each BHA component is calculated based on the hardness index for the drilled borehole interval, the wear resistance of the BHA component, and drilling parameters.

An x-ray spectrum collected from a sample via excitation of the sample by an electron beam includes artifacts due to interaction volume, surface effects, contamination, or other interferences with the desired collection of representative x-rays from the sample. Inline spectral correlation, summation, averaging, other aggregation, or combinations thereof provides more precise collection of x-ray spectrum from multi-phase, unprepared, particle, or complex samples.

A phosphor contains a crystal phase having a chemical composition Ce.sub.xM.sub.3-x-yβ.sub.6γ.sub.11-z. M is one or more elements selected from the group consisting of Sc, Y, La, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu. β contains Si in an amount of 50 mol % or more of a total mol of β. γcontains N in an amount of 80 mol % or more N of a total mol of γ. x satisfies 0<x≦0.6. y satisfies 0≦y≦1.0. z satisfies 0≦z≦1.0. The phosphor shows a maximum peak of an emission spectrum in a wavelength range of 600 nm or more and 800 nm or less and a first peak of an excitation spectrum in a wavelength range of 500 nm or more and 600 nm or less.

A phosphor contains a crystal phase having a chemical composition Ce.sub.xM.sub.3-x-yβ.sub.6γ.sub.11-z. M is one or more elements selected from the group consisting of Sc, Y, La, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu. β contains Si in an amount of 50 mol % or more of a total mol of β. γcontains N in an amount of 80 mol % or more N of a total mol of γ. x satisfies 0<x≦0.6. y satisfies 0≦y≦1.0. z satisfies 0≦z≦1.0. The phosphor shows a maximum peak of an emission spectrum in a wavelength range of 600 nm or more and 800 nm or less and a first peak of an excitation spectrum in a wavelength range of 500 nm or more and 600 nm or less.

This application addresses an integrated smart system to control the variables involved in the process for melting mineral concentrates. Specifically, it addresses an integrated smart system that allows the whole melting process operation to be controlled, measuring the mineralogical quality and quantity of the concentrate that is injected into the melting furnace, as well as variables such as the temperature, the level of the liquid phases and the percentage of copper within the furnace. In this manner, by reading said variables, it acts autonomously on manipulated variables, considering uncertainties, allowing a stable temperature to be maintained in the reactor, allowing products to be obtained at the required quality and controlling the liquid phases therein, among other controlled variables, to achieve efficient melting.

This application addresses an integrated smart system to control the variables involved in the process for melting mineral concentrates. Specifically, it addresses an integrated smart system that allows the whole melting process operation to be controlled, measuring the mineralogical quality and quantity of the concentrate that is injected into the melting furnace, as well as variables such as the temperature, the level of the liquid phases and the percentage of copper within the furnace. In this manner, by reading said variables, it acts autonomously on manipulated variables, considering uncertainties, allowing a stable temperature to be maintained in the reactor, allowing products to be obtained at the required quality and controlling the liquid phases therein, among other controlled variables, to achieve efficient melting.

Method and system are disclosed for determining sample composition from spectral data acquired by a charged particle microscopy system. Chemical elements in a sample are identified by processing the spectral data with a trained neural network (NN). If the identified chemical elements not matching with a known elemental composition of the sample, the trained NN is retrained with the spectral data and the known elemental composition of the sample. The retrained NN can then be used to identify chemical elements within other samples.