Abstract: Vacuum-integrated photoresist-less methods and apparatuses for forming metal hardmasks can provide sub-30 nm patterning resolution. A metal-containing (e.g., metal salt or organometallic compound) film that is sensitive to a patterning agent is deposited on a semiconductor substrate. The metal-containing film is then patterned directly (i.e., without the use of a photoresist) by exposure to the patterning agent in a vacuum ambient to form the metal mask. For example, the metal-containing film is photosensitive and the patterning is conducted using sub-30 nm wavelength optical lithography, such as EUV lithography.

Abstract: Vacuum-integrated photoresist-less methods and apparatuses for forming metal hardmasks can provide sub-30 nm patterning resolution. A metal-containing (e.g., metal salt or organometallic compound) film that is sensitive to a patterning agent is deposited on a semiconductor substrate. The metal-containing film is then patterned directly (i.e., without the use of a photoresist) by exposure to the patterning agent in a vacuum ambient to form the metal mask. For example, the metal-containing film is photosensitive and the patterning is conducted using sub-30 nm wavelength optical lithography, such as EUV lithography.

Abstract: Etch in a thermal etch reaction is predicted using a machine learning model. Chemical characteristics of an etch process and associated energies in one or more reaction pathways of a given thermal etch reaction are identified using a quantum mechanical simulation. Labels indicative of etch characteristics may be associated with the chemical characteristics and associated energies of the given thermal etch reaction. The machine learning model can be trained using chemical characteristics and associated energies as independent variables and labels as dependent variables across many different etch reactions of different types. When chemical characteristics and associated energies for a new thermal etch reaction are provided as inputs in the machine learning model, the machine learning model can accurately predict etch characteristics of the new thermal etch reaction as outputs.

Abstract: A sorption structure defined in a plasma process chamber includes an inner layer having one or more heating elements to heat the sorption structure, a middle section having a coolant flow delivery network through which a coolant circulates to cool the sorption structure to a temperature to allow selective adsorption of by-products released in the process chamber, and a vacuum flow network that is connected to a vacuum line to create low pressure vacuum and remove the by-products released from the sorption structure. A lattice structure is defined over the middle section, the lattice structure includes network of openings defined in a plurality of layers to increase surface area for improved by-products adsorption. The inner section is disposed adjacent to the middle section. An outer layer of the lattice structure faces an interior region of the chamber.

Abstract: Defects on a substrate comprising electronic components can be classified with a computational defect analysis system that may be implemented in multiple stages. For example, a first stage classification engine may process metrology data to produce an initial classification of defects. A second stage classification engine may use the initial classification, along with manufacturing information and/or prior defect knowledge to output probabilities that the defects are caused by one or more potential sources.

Abstract: Development of resists are useful, for example, to form a patterning mask in the context of high-resolution patterning. Development can be accomplished using a halide-containing chemistry such as a hydrogen halide. A metal-containing resist film may be deposited on a semiconductor substrate using a dry or wet deposition technique. The resist film may be an EUV-sensitive organo-metal oxide or organo-metal-containing thin film resist. After exposure, the photopatterned metal-containing resist is developed using wet or dry development.

Abstract: Vacuum-integrated photoresist-less methods and apparatuses for forming metal hardmasks can provide sub-30 nm patterning resolution. A metal-containing (e.g., metal salt or organometallic compound) film that is sensitive to a patterning agent is deposited on a semiconductor substrate. The metal-containing film is then patterned directly (i.e., without the use of a photoresist) by exposure to the patterning agent in a vacuum ambient to form the metal mask. For example, the metal-containing film is photosensitive and the patterning is conducted using sub-30 nm wavelength optical lithography, such as EUV lithography.

Abstract: Defects on a substrate comprising electronic components can be classified with a computational defect analysis system that may be implemented in multiple stages. For example, a first stage classification engine may process metrology data to produce an initial classification of defects. A second stage classification engine may use the initial classification, along with manufacturing information and/or prior defect knowledge to output probabilities that the defects are caused by one or more potential sources.

Abstract: Vacuum-integrated photoresist-less methods and apparatuses for forming metal hardmasks can provide sub-30 nm patterning resolution. A metal-containing (e.g., metal salt or organometallic compound) film that is sensitive to a patterning agent is deposited on a semiconductor substrate. The metal-containing film is then patterned directly (i.e., without the use of a photoresist) by exposure to the patterning agent in a vacuum ambient to form the metal mask. For example, the metal-containing film is photosensitive and the patterning is conducted using sub-30 nm wavelength optical lithography, such as EUV lithography.

Abstract: Vacuum-integrated photoresist-less methods and apparatuses for forming metal hardmasks can provide sub-30 nm patterning resolution. A metal-containing (e.g., metal salt or organometallic compound) film that is sensitive to a patterning agent is deposited on a semiconductor substrate. The metal-containing film is then patterned directly (i.e., without the use of a photoresist) by exposure to the patterning agent in a vacuum ambient to form the metal mask. For example, the metal-containing film is photosensitive and the patterning is conducted using sub-30 nm wavelength optical lithography, such as EUV lithography.

Abstract: Defects on a substrate comprising electronic components can be classified with a computational defect analysis system that may be implemented in multiple stages. For example, a first stage classification engine may process metrology data to produce an initial classification of defects. A second stage classification engine may use the initial classification, along with manufacturing information and/or prior defect knowledge to output probabilities that the defects are caused by one or more potential sources.

Abstract: Vacuum-integrated photoresist-less methods and apparatuses for forming metal hardmasks can provide sub-30 nm patterning resolution. A metal-containing (e.g., metal salt or organometallic compound) film that is sensitive to a patterning agent is deposited on a semiconductor substrate. The metal-containing film is then patterned directly (i.e., without the use of a photoresist) by exposure to the patterning agent in a vacuum ambient to form the metal mask. For example, the metal-containing film is photosensitive and the patterning is conducted using sub-30 nm wavelength optical lithography, such as EUV lithography.

Abstract: Disclosed are methods of generating a proximity-corrected design layout for photoresist to be used in an etch operation. The methods may include identifying a feature in an initial design layout, and estimating one or more quantities characteristic of an in-feature plasma flux (IFPF) within the feature during the etch operation. The methods may further include estimating a quantity characteristic of an edge placement error (EPE) of the feature by comparing the one or more quantities characteristic of the IFPF to those in a look-up table (LUT, and/or through application of a multivariate model trained on the LUT, e.g., constructed through machine learning methods (MLM)) which associates values of the quantity characteristic of EPE with values of the one or more quantities characteristics of the IFPF. Thereafter, the initial design layout may be modified based on at the determined quantity characteristic of EPE.

Abstract: Vacuum-integrated photoresist-less methods and apparatuses for forming metal hardmasks can provide sub-30 nm patterning resolution. A metal-containing (e.g., metal salt or organometallic compound) film that is sensitive to a patterning agent is deposited on a semiconductor substrate. The metal-containing film is then patterned directly (i.e., without the use of a photoresist) by exposure to the patterning agent in a vacuum ambient to form the metal mask. For example, the metal-containing film is photosensitive and the patterning is conducted using sub-30 nm wavelength optical lithography, such as EUV lithography.

Abstract: Etch in a thermal etch reaction is predicted using a machine learning model. Chemical characteristics of an etch process and associated energies in one or more reaction pathways of a given thermal etch reaction are identified using a quantum mechanical simulation. Labels indicative of etch characteristics may be associated with the chemical characteristics and associated energies of the given thermal etch reaction. The machine learning model can be trained using chemical characteristics and associated energies as independent variables and labels as dependent variables across many different etch reactions of different types. When chemical characteristics and associated energies for a new thermal etch reaction are provided as inputs in the machine learning model, the machine learning model can accurately predict etch characteristics of the new thermal etch reaction as outputs.

Abstract: A plasma source includes a ring plasma chamber, a primary winding around an exterior of the ring plasma chamber, multiple ferrites, wherein the ring plasma chamber passes through each of the ferrites and multiple plasma chamber outlets coupling the plasma chamber to a process chamber. Each one of the plasma chamber outlets having a respective plasma restriction. A system and method for generating a plasma are also described.

Abstract: Disclosed are methods of optimizing a computerized model which relates etched feature profile on a semiconductor device to a set of independent input parameters via the use of a plurality of model parameters. The optimization methods may include modifying the model parameters so that an etch profile generated with the model is such that it reduces a metric indicative of the combined differences between experimental etch profiles resulting from experimental etch processes performed using different sets of values for sets of independent input parameters and computed etch profiles generated from the model and corresponding to the experimental etch profiles. Said metric may be calculated by projecting computed and corresponding experimental etch profiles onto a reduced-dimensional subspace used to calculate a difference between the profiles. Also disclosed herein are systems employing such optimized models, as well as methods of using such models to approximately determine the profile of an etched feature.

Abstract: Disclosed are methods of generating a proximity-corrected design layout for photoresist to be used in an etch operation. The methods may include identifying a feature in an initial design layout, and estimating one or more quantities characteristic of an in-feature plasma flux (IFPF) within the feature during the etch operation. The methods may further include estimating a quantity characteristic of an edge placement error (EPE) of the feature by comparing the one or more quantities characteristic of the IFPF to those in a look-up table (LUT, and/or through application of a multivariate model trained on the LUT, e.g., constructed through machine learning methods (MLM)) which associates values of the quantity characteristic of EPE with values of the one or more quantities characteristics of the IFPF. Thereafter, the initial design layout may be modified based on at the determined quantity characteristic of EPE.

Abstract: A plasma processing method is provided. The method includes receiving a substrate in a substrate support that is configured to be movable along a linear path. The method includes providing at least one process gas into a plasma microchamber. The plasma microchamber is disposed in a processing head having a length that is at least longer than a diameter of the substrate, and said length is perpendicular to said linear path. The method includes generating a plasma in the plasma microchamber by applying power to the plasma microchamber and applying a bias power to the substrate support. The plasma microchamber has an open side process area that is oriented and directed over a surface to be processed, and the open side process area is less than an area of the surface to be processed. The method includes translating said substrate support along said linear path while said microchamber generates the plasma in the plasma microchamber for exposing said plasma over the substrate.

Abstract: Disclosed are methods of optimizing a computer model which relates the etch profile of a feature on a semiconductor substrate to a set of independent input parameters (A), via the use of a plurality of model parameters (B). In some embodiments, the methods may include modifying one or more values of B so as to reduce a metric indicative of the differences between computed reflectance spectra generated from the model and corresponding experimental reflectance spectra with respect to one or more sets of values of A. In some embodiments, calculating the metric may include an operation of projecting the computed and corresponding experimental reflectance spectra onto a reduced-dimensional subspace and calculating the difference between the reflectance spectra as projected onto the subspace. Also disclosed are etch systems implementing such optimized computer models.