An on-line energy dispersive X-ray diffraction (EDXRD) analyser for mineralogical analysis of material in a process stream or a sample is disclosed. The analyser includes a collimated X-ray source to produce a diverging beam of polychromatic X-rays, and an energy resolving X-ray detector, and a substantially X-ray transparent member having the form of a solid of revolution which is circularly symmetric about a central axis between the collimated X-ray source and the energy resolving X-ray detector, an outer surface of the X-ray transparent member positionable adjacent the material to be analysed. A primary beam collimator is disposed adjacent to or within the substantially X-ray transparent member to substantially prevent direct transmission of polychromatic X-rays emitted from the source to the detector. The analyser is configured such that the diverging beam of polychromatic X-rays are directed towards the substantially X-ray transparent member, and where the energy resolving X-ray detector collects a portion of the beam of X-rays diffracted by the material and outputs a signal containing energy information of the collected, diffracted X-rays.

The present invention provides a method for analysis and determination of the heavy metal occurrence key mineral phases in industrial solid waste, by performing N concentration gradients dissociation determination of the heavy metal solid waste to be tested under the same dissociation conditions, to give the dissociation degrees of the heavy metal elements to be tested at N different concentration gradients; the dissociated solid residues after dissociation being quantitatively analyzed for the mineral phase, to give the relative content of each mineral phase in the M mineral phases of the heavy metal solid waste to be tested; then calculating to give the occurrence distribution proportion of the heavy metal elements in the mineral phase, which are accumulated from high to low; the occurrence key mineral phase whose cumulative occurrence proportion exceeds the preset cumulative threshold value is determined to be the key mineral phase of the heavy metal elements.

A system of collating a spectral data of an arbitrary material with spectral data of existing materials to identify the kind of the arbitrary material comprises a one-dimensional CNN processor calculating a characteristic value vector based on a spectral data of a material by a one-dimensional convolution neural network algorithm, and a metric learning processor computing a probability that the kind of the material is each kind of the existing materials from the characteristic value vector by a deep metric learning algorithm. The processors learn with the spectral data of existing materials to compute a probability for the kind of each material such that the probabilities for the kinds of the respective materials inputted for data for learning becomes maximum. When the data of the arbitrary material is inputted, the kind giving the maximum probability is identified as the kind of the arbitrary material with high precision.

The present invention relates to a method for determining the crystal structure of a crystal (4) capable of electron diffraction. The method includes the steps of obtaining a three-dimensional electron diffraction pattern and processing data from the electron diffraction pattern. The essence of the invention is that the method of determination consists in creating virtual diffraction frames containing a list of integrated scattered electron intensities. Subsequently, the dynamical diffraction theory is used in the data processing step. In another embodiment, the invention provides an apparatus capable of performing this method.

A process for quantifying the amount of unbound metal and bound metal in solution is provided. A process for quantifying the amount of bound metal amino acid chelate and free ligand in a solid (e.g., dry mixture such as an animal feed) is also provided.

Molecular structure of a crystal may be solved based on at least two diffraction tilt series acquired from a sample. The two diffraction tilt series include multiple diffraction patterns of at least one crystal of the sample acquired at different electron doses. In some examples, the two diffraction tilt series are acquired at different magnifications.

Crystallographic information of crystalline sample can be determined from one or more three-dimensional diffraction pattern datasets generated based on diffraction patterns collected from multiple crystals. The crystals for diffraction pattern acquisition may be selected based on a sample image. At a location of each selected crystal, multiple diffraction patterns of the crystal are acquired at different angles of incidence by tilting the electron beam, wherein the sample is not rotated while the electron beam is directed at the selected crystal.

A method for correcting distortion in a coherent electron diffraction imaging (CEDI) image induced by a projection lens makes use of a known secondary material that is imaged together with a sample of interest. Reflections generated from the secondary material are located in the image, and these observed reflections are used to approximate a beam center location. Using a known lattice structure of the secondary material, Friedel pairs are located in the image and unit cell vectors are identified. Predicted positions for each of the secondary material reflections are then determined, and the position differences between the observed reflections and the predicted reflections are used to construct a relocation function applicable to the overall image. The relocation function is then used to adjust the position of image components so as to correct for the distortion.

Provided herein are diffractometer-based global diagnostic systems and uses thereof. The systems may comprise one or more diffraction apparatus operatively coupled to a computer database over a network. The one or more diffraction apparatus may be configured for transfer of data such as pathology lab image data, diffraction pattern data, subject data, or any combination thereof to the computer database over the network. The systems may further comprise one or more computer processors operatively coupled to the one or more diffraction apparatus, which computer processors may be configured to receive the data from the diffraction apparatus, transmit the data to the computer database, and process the data using a data analytics algorithm which may provide a computer-aided diagnostic indicator for the individual subject.

The system for in-situ real-time measurements of microstructure properties of 3D-printing objects during 3-D printing processes. An intensive parallel X-ray beam (with an adjustable beam size) impinges on a printing object and is diffracted on a crystal lattice of the printing material. The diffracted radiation impinges on a reflector formed with an array of reflector crystals mounted on an arcuated substrate. The diffracted beams reflected from the reflector crystals correspond to the diffraction intensity peaks produced by interaction of the crystal lattice of the printing material with the impinging X-ray beam. The intensities of the diffraction peaks are observed by detectors which produce corresponding output signals, which are processed to provide critical information on the crystal phase composition, which is closely related to the defects and performance of the printing objects. The subject in-situ technology provides an effective and efficient way to monitor, in real-time, the quality of 3D-printing parts during the 3-D printing process, with a significant potential for effective process control based on the reliable microstructure feedback.