Fei Comapny

Michael James Owen

Michael Buhot

Garth Howell

Ashley Donaldson

Leonardo Salazar

David Haberlah

Eric Goergen

Paul Gottlieb

Darius Koĉár

Daniel Roy Corbett

Phillip John Christopher Parker

Andrew Harley Menzies

Van Hung Phan

Philip JC Parker

The invention relates to method and system configured for material analysis and mineralogy. At least one image based on first emission from a sample is provided. First spectra of the sample based on second emissions from the second scan locations of the image are provided. A confidence score is calculated for every first spectrum, and second scan location(s) with confidence score(s) below a threshold value are selected. Second emissions from the selected second scan location(s) are acquired to provide new image and determine new second scan locations within the respective new image.

Multiple image segmentation and/or multiple dynamic spectral acquisition for material and mineral classification

A method of operating a charged particle microscope comprising:

X-ray spectroscopy in a charged-particle microscope

The present invention discloses a combination of two existing approaches for mineral analysis and makes use of the Similarity Metric Invention, that allows mineral definitions to be described in theoretical compositional terms, meaning that users are not required to find examples of each mineral, or adjust rules. This system allows untrained operators to use it, as opposed to previous systems, which required extensive training and expertise.

Automated mineral classification

Mineral definitions each include a list of elements, each of the elements having a corresponding standard spectrum. To determine the composition of an unknown mineral sample, the acquired spectrum of the sample is sequentially decomposed into the standard spectra of the elements from the element list of each of the mineral definitions, and a similarity metric computed for each mineral definition. The unknown mineral is identified as the mineral having the best similarity metric.

Mineral identification using sequential decomposition into elements from mineral definitions

A method and apparatus are provided for identifying a material with a sample-specific reference spectral list or library. A sequential approach to SEM-EDS automated mineralogy classification is carried out by performing two or more material classification analyses. A pre-classification step restricts the processing of spectra deconvolution algorithms to a subset of spectra that pass a dominant mineral criteria resulting in a significantly reduced subset of reference spectra that occur within the measured sample in pure enough form at a given minimum quantity. The following complex classification stages involving deconvolution of multiple constituents within measured spectra is based on this sample relevant subset.

Sample-specific reference spectra library

Method and apparatus for analysis and display of fine grained mineral samples. A portion of the sample is illuminated with a charged particle beam. Emitted radiation is detected, and a sample emission spectrum is generated and fit with a plurality of standard emission spectra of minerals in a candidate mineral composition. A mineral composition whose emission spectrum best fits the sample emission spectrum is selected from a plurality of candidate mineral compositions. An assigned color is received for each mineral in the selected mineral composition, and the assigned colors are blended according to the proportion of each mineral in the selected mineral composition. An image pixel corresponding to the portion of the sample is rendered for display.

Sub-pixel analysis and display of fine grained mineral samples

Optimized blending mode for mineralogy images. A luminosity value is determined for a pixel in a base layer or top layer mineralogy image. An image weighting value is determined from the luminosity value and an optional mixing parameter. A multiply value is determined by multiplying the base and top layer pixel values. An overlay value is determined from twice the multiply value if the value of one of the base layer or top layer pixel values is over a threshold, otherwise it is determined by inverting twice the product of the inverted top layer pixel value with the inverted base layer pixel value. A blended image pixel value is determined by adding the multiply value weighted with the image weighting value and the overlay value weighted with the inverted image weighting value.

Blend modes for mineralogy images

This invention relates to a method and system for determining the composition of an unknown sample. The present invention is directed to a method of calibrating an x-ray spectrometer that does not require measuring all possible elements under the operating conditions used to measure the unknown sample to be analyzed. According to a preferred embodiment, the local instrument can be calibrated from an x-ray spectrum of a single elemental standard. The instrument will have a stored library containing high quality spectra for all elements being analyzed. The analysis of the single element is compared to the library spectra for that element to define a transformation that is used to create a calibrated spectra library that includes a calibrated spectrum for each spectrum in the original library. The spectra generated by the local instrument can be compared to the calibrated library spectra to determine the elements in an unknown mineral.

Automated EDS standards calibration

Determining the composition of a mineral sample entails comparing measurements of a sample to mineral definitions and determining a similarity metric. The mineral definition includes a subspace of compositional values defined by end members. The similarity metric is related to a projection of the measured data point onto the subspace or onto an extension of the subspace.

Mineral identification using mineral definitions having compositional ranges

An improved mineral analysis system includes mineral definitions that include not only characteristics of the minerals, but also variability in those characteristics. The variabilities allow the calculation of ranges of expected values for different quality of measurements, for example, for different numbers of x-ray counts. Match probabilities can therefore be calculated to more accurately determine the composition of a mineral sample.

Mineral identification using mineral definitions including variability

A method and system for spectrum data analysis. The method comprises the steps of collecting a spectrum of an unknown material; providing a set of data templates; calculating weighting factors for the element data templates to minimize error in approximating the spectrum; removing one or more of the templates having negative weights in approximating the spectrum; and re-calculating an approximation of the spectrum with said one or more templates removed. Embodiments of the invention are suitable for analyzing noisy spectra having relatively few data points.

Method and system for spectrum data analysis

The present invention discloses a method for determining the mineral content represented by the entire SEM-EDS dataset, including initially unknown data points. SEM-EDS data points are taken and compared to a set of known data points. Any data point that is not sufficiently similar to the known data point is classified as unknown and clustered with like unknown data points. After all data points are analyzed, any clusters of unknown data points with a sufficient number of data points are further analyzed to determine their characteristics. All clusters of unknown data points with an insufficient number of data points to allow further analysis are considered outliers and discarded.

Growing community of inventors

Geebung, Australia

Michael James Owen