A method includes identifying at least one of historical data associated with historical substrate lots processed by substrate processing tools in a substrate processing facility or simulated data for simulated substrate lots processed by simulated substrate processing tools. The method further includes generating features from the at least one of the historical data for the historical substrate lots or the simulated data for the simulated substrate lots. The method further includes training a machine learning model with data input comprising the features to generate a trained machine learning model. The trained machine learning model is capable of generating one or more outputs indicative of one or more corrective actions to be performed in the substrate processing facility.

A method for improving the yield of a lithographic process, the method including: determining a parameter fingerprint of a performance parameter across a substrate, the parameter fingerprint including information relating to uncertainty in the performance parameter; determining a process window fingerprint of the performance parameter across the substrate, the process window being associated with an allowable range of the performance parameter; and determining a probability metric associated with the probability of the performance parameter being outside an allowable range. Optionally a correction to the lithographic process is determined based on the probability metric.

A method and associated apparatuses for controlling a process of manufacturing semiconductor devices on a substrate. The method includes obtaining process data relating to the process and determining a correction for the process based on the process data and a first control objective associated with the devices on the substrate. A first probability of the first control objective being achievable is determined and the correction adjusted based on the probability and at least a second control objective having a second probability of being achievable compared to the first control objective.

A micro-lithographic projection exposure system comprises an illumination unit and a projection lens with at least one element which is penetrated at least in regions by a temperature-control fluid line provided for conducting a temperature-control fluid for controlling the temperature of the element. The temperature-control fluid line is connected to a temperature-control fluid storage container. A temperature-control element for controlling the temperature of the temperature-control fluid is provided on or in the temperature-control fluid line. At least two of the elements are independently penetrated by a respective separate at least one of temperature-control fluid lines, or at least two different regions of the at least one element are penetrated independently by a respective separate at least one of the temperature-control fluid lines, or at least two of the elements are penetrated by the temperature-control fluid line. A corresponding method is provided.

Described herein is a method for training a machine learning model to determine a source of error contribution to multiple features of a pattern printed on a substrate. The method includes obtaining training data having multiple datasets, wherein each dataset has error contribution values representative of an error contribution from one of multiple sources to the features, and wherein each dataset is associated with an actual classification that identifies a source of the error contribution of the corresponding dataset; and training, based on the training data, a machine learning model to predict a classification of a reference dataset of the datasets such that a cost function that determines a difference between the predicted classification and the actual classification of the reference dataset is reduced.

Methods and systems for photopatterning and miniaturization. In some examples, a method for patterning a substrate includes irradiating a pattern onto the substrate with ultraviolet light and heating the substrate, causing the substrate and the pattern to shrink in at least one dimension to form a miniaturized pattern on the substrate. In some examples, a system for patterning a substrate includes an ultraviolet light source, a heater, and a controller configured for irradiating a pattern onto the substrate with ultraviolet light and heating the substrate, causing the substrate and the pattern to shrink in at least one dimension to form a miniaturized pattern on the substrate.

The invention relates to a method for operating a machine for microlithography which has a multiplicity of machine components. According to one aspect, malfunctions of these machine components that occur during the operation of the machine are each describable by a symptom, wherein the method includes the following steps: creating a database in which a cause is in each case assigned to different combinations of these symptoms, automatically recording the symptoms occurring within a predetermined time interval when a problem occurs during the operation of the machine and automatically assigning a cause to the problem on the basis of the recorded symptoms and the database.

In one embodiment, a multi-charged-particle-beam writing method includes dividing a data path into a plurality of first blocks based on at least either one of each of a plurality of input/output circuits and a plurality of wiring groups, and calculating a first shift amount for multiple beams for each of the plurality of first blocks. The data path is for inputting control data to a cell array on a blanking aperture array substrate. The control data is for controlling ON/OFF of each beam of the multiple beams. Each of the plurality of wiring groups includes a plurality of pieces of wiring connected to the plurality of input/output circuits and grouped together based on inter-wiring distance. The first shift amount is due to at least one of an electric field and a magnetic field for each of the plurality of first blocks. An irradiation position or a dose of the multiple beams is corrected based on the first shift amount, and irradiation is performed.

A method of calculating process corrections for a lithographic tool, and associated apparatuses. The method comprises measuring process defect data on a substrate that has been previously exposed using the lithographic tool; fitting a process signature model to the measured process defect data, so as to obtain a model of the process signature for the lithographic tool; and using the process signature model to calculate the process corrections for the lithographic tool.

A method of determining a control setting for a lithographic apparatus. The method includes obtaining a first correction for a current layer on a current substrate based on first metrology data associated with one or more previous substrates, and obtaining a second correction for the current layer on the current substrate. The second correction is based on a residual determined based on second metrology data associated with a previous layer on the current substrate. The method further includes determining the control setting for the lithographic apparatus for patterning the current layer on the current substrate by combining the first correction and the second correction.