Fei Comapny

Tomás Vystavel

Pavel Stejskal

Pavel Potocek

Ondrej Machek

Libor Strakos

Michal Hrouzek

Marek Uncovský

Martin Cafourek

Anna Prokhodtseva

Pavel Poloucek

Bart Buijsse

Thomas Hantschel

Aurelien Philippe Jean Maclou Botman

Bohuslav Sed'a

Alan Frank De Jong

Jan Klusácek

Marek Uncovsky

Libor Novak

Martinus Petrus Maria Bierhoff

Krishna Kanth Neelisetty

Oleksii Kaplenko

Lubomir Tuma

Jaroslav Stárek

Roger Louis Alvis

Jan Neuzil

Remco Theodorus Johannes Petrus Geurts

Clement Porret

John Mitchels

Mykola Kaplenko

Jakub Kuba

Tomáš Trnkócy

Pierre Bleuet

Josef Sesták

Magda Zaoralova

Zuzana Hlavenková

John Fretwell

Frantisek Vaske

Laurens Kwakman

Jaromir Vanhara

Han Han

Petronella Catharina Maria Baken

Kristýna Bukvisová

Ondrej Klvac

Ernst Jan Ruben Vesseur

Lukás Drybcák

Aurélien Botman

Daniel BOSÁK

Ernst Jan Vesseur

Ellen Baken

Mart Bierhoff

Drybcák Lukás

Systems and methods for pre-aligning samples for more efficient processing of multiple samples with a BIB system according to the present invention comprises affixing a sample to an adjustable portion of a sample holder, nesting the sample holder with a first mask having a first mask edge, wherein the first mask is positioned outside of a BIB system, and aligning the sample such that it has a desired geometric relationship to the first mask edge. The first mask may be geometrically similar with a second mask within the BIB system that has a second mask edge such that the geometric relationship between the first mask edge and the sample when the sample holder is nested with the first mask is the same as the geometric relationship between the second mask edge and the sample when the sample holder is nested with the second mask.

Systems and methods for pre-aligning samples for more efficient processing of multiple samples with a Broad Ion Beam (BIB) system

Techniques for training an artificial neural network (ANN) using simulated specimen images are described. Simulated specimen images are generated based on data models. The data models describe characteristics of a crystalline material and characteristics of one or more defect types. The data models do not include any image data. Simulated specimen images are input as training data into a training algorithm to generate an artificial neural network (ANN) for identifying defects in crystalline materials. After the ANN is trained, the ANN analyzes captured specimen images to identify defects shown therein.

Training an artificial neural network using simulated specimen images

The invention relates to a method of, and apparatus for, examining a sample using a charged particle beam apparatus. The method as defined herein comprises the step of detecting, using a first detector, emissions of a first type from the sample in response to the charged particle beam illuminating the sample. The method further comprises the step of acquiring spectral information on emissions of a second type from the sample in response to the charged particle beam illuminating the sample. As defined herein, said step of acquiring spectral information comprises the steps of providing a spectral information prediction algorithm and using said algorithm for predicting said spectral information based on detected emissions of the first type as an input parameter of said algorithm. With this it is possible to gather EDS data using only a BSE detector.

Method of examining a sample using a charged particle beam apparatus

Methods and apparatus determine offcut angle of a crystalline sample using electron channeling patterns (ECPs), wherein backscattered electron intensity exhibits angular variation dependent on crystal orientation. A zone axis normal to a given crystal plane follows a circle as the sample is azimuthally rotated. On an ECP image presented with tilt angles as axes, the radius of the circle is the offcut angle of the sample. Large offcut angles are determined by a tilt technique that brings the zone axis into the ECP field of view. ECPs are produced with a scanning electron beam and a monolithic backscattered electron detector; or alternatively with a stationary electron beam and a pixelated electron backscatter diffraction detector. Applications include strain engineering, process monitoring, detecting spatial variations, and incoming wafer inspection. Methods are 40&#xd7; faster than X-ray diffraction. 0.01-0.1&#xb0; accuracy enables semiconductor applications.

Offcut angle determination using electron channeling patterns

Methods for locating and characterizing defects can include performing a first scan of a substrate to produce a first defect map including a first set of coordinates of one or more defects of the substrate and performing a second scan of one or more regions of the substrate associated with the defects based on the first defect map to produce one or more electron channeling contrast (ECC) images of the defects. Characterization of the defects can be based on the ECC images alone or in combination with other techniques. Such methods can include determining a second set of coordinates associated with the one or more defects based on the ECC images and directing an ion beam toward the substrate and milling the substrate based on the second set of coordinates.

Method and system for wafer defect inspection

Methods and systems for conducting tomographic imaging microscopy of a sample with a high energy charged particle beam include irradiating a first region of the sample in a first angular position with a high energy charged particle beam and detecting emissions resultant from the charged particle beam irradiating the first region. The sample is repositioned into a second angular position such that the second region to be different than the first region, and a second region of the sample is irradiated. Example repositioning may include one or more of a translation of the sample, a helical rotation of the sample, the sample being positioned in a non-eucentric position, or a combination thereof. Emissions resultant from irradiation of the second region are then detected, and a 3D model of a portion of the sample is generated based at least in part on the detected first emissions and detected second emissions.

Method for diffraction pattern acquisition

Methods include providing a multi-pillar sample including at least a first pillar and a second pillar parallel with the first pillar, directing a charged particle beam to the first pillar, imaging the first pillar at a plurality of rotational positions by rotating the multi-pillar sample about a first pillar axis of the first pillar, directing the charged particle beam to the second pillar, and imaging the second pillar at a plurality of rotational positions by rotating the multi-pillar sample about a second pillar axis of the second pillar. Related apparatus for performing disclosed methods are disclosed. Multi-pillar samples are also disclosed.

Method and system for imaging a multi-pillar sample

Dynamic band contrast image (DBCI) is constructed with scattering patterns acquired at multiple scanning locations of a sample using a charged particle beam. Each pixel of the DBCI is generated by integrating the corresponding scattering pattern along a diffraction band. The DBCI includes charged particle channeling condition and can be used for detecting sample defects.

Method and system for dynamic band contrast imaging

The invention relates to a method of manipulating a sample in an evacuated chamber of a charged particle apparatus, the method performed in said evacuated chamber, the method including: providing a sample on a first substrate; bringing an extremal end of a manipulator in contact with the sample; attaching the sample to said extremal end, the attaching being a removable attaching; lifting the sample attached to the extremal end of the manipulator from the first substrate and transport the sample to a second substrate; attaching the sample to the second substrate; and detaching the sample from the extremal end of the manipulator. At least one of the steps of attaching the sample being performed solely by bringing the sample into contact with a bundle of carbon nanotubes.

Method of manipulating a sample in an evacuated chamber of a charged particle apparatus

The invention relates to a method of determining the thickness of a sample. According to this method, a diffraction pattern image of a sample of a first material is obtained. Said diffraction pattern image comprises at least image values representative for the diffraction pattern obtained for said sample. A slope of said image values is then determined. The slope is compared to a relation between the thickness of said first material and the slope of image value of a corresponding diffraction pattern image of said first material. The determined slope and said relation are used to determine the thickness of said sample.

Measurement and endpointing of sample thickness

The invention relates to a method 3D defect characterization of crystalline samples in a scanning type electron microscope. The method comprises Irradiating a sample provided on a stage, selecting one set of crystal lattice planes of the sample and orienting said set to a first Bragg condition with respect to a primary electron beam impinging on said sample, and obtaining Electron Channeling Contrast Image for an area of interest on the sample. The method is characterized by performing, at least once, the steps of orienting said selected set of crystal lattice planes to a further Bragg condition by at least tilting the sample stage with the sample by a user-selected angle about a first tilt axis, and obtaining by Electron Channeling Contrast Image for a further area of interest.

3D defect characterization of crystalline samples in a scanning type electron microscope

A substrate is alignable for ion beam milling or other inspection or processing by obtaining an electron channeling pattern (ECP) or other electron beam backscatter pattern from the substrate based on electron beam backscatter from the substrate. The ECP is a function of substrate crystal orientation and tilt angles associated with ECP pattern values at or near a maximum, minimum, or midpoint are used to determine substrate tilt. Such tilt is then compensated or eliminated using a tilt stage coupled the substrate, or by adjusting an ion beam axis. In typical examples, circuit substrate 'chunks' are aligned for ion beam milling to reveal circuit features for evaluation of circuit processing.

Method for sample orientation for TEM lamella preparation

Surface modification of a cryogenic specimen can be obtained using a charged particle microscope. A specimen is situated in a vacuum chamber on a specimen holder and maintained at a cryogenic temperature. The vacuum chamber is evacuated and a charged-particle beam is directed to a portion of the specimen so as to modify a surface thereof. A thin film monitor is situated in the vacuum chamber and has at least a detection surface maintained at a cryogenic temperature. A precipitation rate of frozen condensate in the vacuum chamber is measured using the thin film monitor, and based on the measured precipitation rate, the surface modification is initiated when the precipitation rate is less than a first pre-defined threshold, or interrupted if the precipitation rate rises above a second pre-defined threshold.

Cryogenic specimen processing in a charged particle microscope

A method of modifying a sample surface layer in the vacuum chamber of a particle-optical apparatus, the method performed in vacuum, the method comprising: This enables the wet processing of a sample in-situ, thereby enhancing speed and/or avoiding subsequent alteration/contamination of the sample, such as oxidation, etc. The method is particularly useful for etching a lamella after machining the lamella with a (gallium) FIB to remove the surface layer where gallium implantation occurred, or where the crystal lattice is disturbed.

Method of modifying a sample surface layer from a microscopic sample

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Brno, Czechia

Tomás Vystavel