Fei Comapny

Erik Michiel Franken

Bart Jozef Janssen

Yuchen Deng

Edwin Verschueren

Lingbo Yu

Maarten Kuijper

Remco Schoenmakers

Holger Kohr

Valentina Caprara Vivoli

Maurice Peemen

Uwe Luecken

Ivan Lazic

John J Flanagan

Martin Verheijen

Andreas Voigt

Bart Van Knippenberg

A sample holder retains a sample and can continuously rotate the sample in a single direction while the sample is exposed to a charged particle beam (CPB) or other radiation source. Typically, the CPB is strobed to produce a series of CPB images at random or arbitrary angles of rotation. The sample holder can rotate more than one complete revolution of the sample. The CPB images are used in tomographic reconstruction, and in some cases, relative rotation angles are used in the reconstruction, without input of an absolute rotation angle.

Rotating sample holder for random angle sampling in tomography

A charged particle beam microscope system is operated in a transmission imaging mode. During the operation, the charged particle beam microsystem directs a charged particle beam to the sample to produce images. A time series of beam tilts is applied in a pattern to the charged particle beam directed to the sample to produce a sequence of images. At least some of the images in the sequence of images are captured while the charged particle beam is transitioning between one beam tilt in the time series of beam tilts and a sequentially adjacent beam tilt in the time series of beam tilts. The pattern is configured to induce image changes between the images in the sequence of images that are indicative of optical aberrations in the charged particle beam microscope system.

Measurement and correction of optical aberrations in charged particle beam microscopy

Computer-implemented methods for controlling a charged particle microscopy system include estimating a drift of a stage of the charged particle microscopy system based on an image sequence, and automatically adjusting a stage settling wait duration based on the drift estimate. Charged particle microscopy systems include an imaging system, a movement stage, and a processor and memory configured with computer-executable instructions that, when executed, cause the processor to estimate a stage settling duration of the movement stage based on an image sequence obtained with the imaging system, and automatically adjust a stage settling wait duration for the movement stage based on the stage settling duration.

Auto-tuning stage settling time with feedback in charged particle microscopy

Methods and systems for quantum computing based sample analysis include computing cross-correlations of two images using a quantum processing system, and computing less noisy image based of two or more images using a quantum processing system. Specifically, the disclosure includes methods and systems for utilizing a quantum computing system to compute and store cross correlation values for two sets of data, which was previously believed to be physically impossible. Additionally, the disclosure also includes methods and systems for utilizing a quantum computing system to generate less noisy data sets using a quantum expectation maximization maximum likelihood (EMML). Specifically, the disclosed systems and methods allow for the generation of less noisy data sets by utilizing the special traits of quantum computers, the systems and methods disclosed herein represent a drastic improvement in efficiency over current systems and methods that rely on traditional computing systems.

Systems and methods for quantum computing based sample analysis

Disclosed herein are methods, apparatuses, systems, and computer-readable media related to defective pixel management in charged particle microscopy. For example, in some embodiments, a charged particle microscope support apparatus may include: first logic to identify a defective pixel region of a charged particle camera, wherein the charged particle camera cannot detect charged particle events in the defective pixel region; second logic to generate a first charged particle event indicator that identifies a first time and a first location of a first charged particle event outside the defective pixel region, wherein the first charged particle event is detected by the charged particle camera; third logic to generate a second charged particle event indicator that identifies a second time and a second location in the defective pixel region; and fourth logic to output data representative of the charged particle event indicators.

Defective pixel management in charged particle microscopy

Convolutional neural networks (CNNs) of a set of CNNs are evaluated using a test set of images (electron micrographs) associated with a selected particle type. A preferred CNN is selected based on the evaluation and used for processing electron micrographs of test samples. The test set of images can be obtained by manual selection or generated using a model of the selected particle type. Upon selection of images using the preferred CNN in processing additional electron micrographs, the selected images can be added to a training set or used as an additional training set to retrain the preferred CNN. In some examples, only selected layers of the preferred CNN are retrained. In other examples, two dimensional projections of based on particles of similar structure are used for CNN training or retraining.

Using convolution neural networks for on-the-fly single particle reconstruction

The invention relates to a method of imaging a sample, said sample mounted on a sample holder in an electron microscope, the electron microscope comprising an electron source for generating a beam of energetic electrons along an optical axis and optical elements for focusing and deflecting the beam so as to irradiate the sample with a beam of electrons. The sample holder is capable of positioning and tilting the sample with respect to the electron beam. The method comprises the step of acquiring a tilt series of images by irradiating the sample with the beam of electrons, and concurrently changing a position of the sample during acquisition of the images, so that each image is acquired at an associated unique tilt angle and an associated unique position.

Method of imaging a sample using an electron microscope

A method of using a Transmission Charged Particle Microscope, comprising:

Innovative imaging technique in transmission charged particle microscopy

A method of imaging a specimen in a Scanning Transmission Charged Particle Microscope, comprising the following steps:

Intelligent pre-scan in scanning transmission charged particle microscopy

When detecting particulate radiation, such as electrons, with a pixelated detector, a cloud of electron/hole pairs is formed in the detector. Using the signal caused by this cloud of electron/hole pairs, a position of the impact is estimated. When the size of the cloud is comparable to the pixel size, or much smaller, the estimated position shows a strong bias to the center of the pixel and the corners, as well to the middle of the borders. This hinders forming an image with super-resolution. By shifting the position or by attributing the electron to several sub-pixels this bias can be countered, resulting in a more truthful representation.

Method for detecting particulate radiation

The invention relates to a method of performing tomographic imaging of a sample comprising providing a beam of charged particles; providing the sample on a sample holder that can be tilted; in an imaging step, directing the beam through the sample to image the sample; repeating this procedure at each of a series of sample tilts to acquire a set of images; in a reconstruction step, mathematically processing images from said set to construct a composite image, whereby in said imaging step, for a given sample tilt, a sequence of component images is captured at a corresponding sequence of focus settings; and in said reconstruction step, for at least one member of said series of sample tilts, multiple members of said sequence of component images are used in said mathematical image processing. This renders a 3D imaging cube rather than a 2D imaging sheet at a given sample tilt.

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Eindhoven, Netherlands

Erik Michiel Franken