A computer simulation analysis method suitable for describing the mechanical behavior of multiphase composites based on the real microstructure of materials relates to a multidisciplinary field such as computational material science, simulation and high throughput calculation. Through the first-principles calculation under nano scale, the molecular dynamics simulation under micro scale, and the thermodynamic calculation under mesoscopic scale, various physical parameters needed for the finite element simulation under macro scale can be obtained, including the elastic and plastic physical parameters of each phase in the composite at different temperature and different grain sizes. Focused ion beam experiment and image processing are adopted to obtain real material microstructure. Through the parameter coupling and parameter transfer among the calculated results of various scales, combining the microstructure of the material, stress-strain relationship, stress distribution and its evolution law, plastic deformation and other mechanical behaviors of the multiphase composites under complex stress and different temperature can be simulated.

Various embodiments of the present technology provide for the ultra-high density heterogenous integration, enabled by nano-precise pick-and-place assembly. For example, some embodiments provide for the integration of modular assembly techniques with the use of prefabricated blocks (PFBs). These PFBs can be created on one or more sources wafers. Then using pick-and-place technologies, the PFBs can be selectively arranged on a destination wafer thereby allowing Nanoscale-aligned 3D Stacked Integrated Circuit (N3-SI) and the Microscale Modular Assembled ASIC (M2A2) to be efficiently created. Some embodiments include systems and techniques for the construction of construct semiconductor devices which are arbitrarily larger than the standard photolithography field size of 26×33 mm, using pick-and-place assembly.

A method for characterizing a fluctuation induced by single particle irradiation in a device. A plurality of devices varying in size are tested respectively before and after irradiation to obtain threshold voltage distribution, such that a threshold voltage fluctuation induced by irradiation is obtained and used to correct a process fluctuation model, so as to correct a design margin of the devices working under the irradiation.

One aspect of this description relates to a method for operating an integrated circuit (IC) manufacturing system. The method includes placing a first nano-sheet structure within a IC layout diagram. The first nano-sheet structure has a first width. The method includes abutting a second nano-sheet structure with the first nano-sheet structure. The second nano-sheet structure has a second width. The second width is less than the first width. The method includes generating and storing the IC layout diagram in a storage device.

Within a layout of a first surface in a flip chip configuration, a bump restriction area is mapped according to a set of bump placement restrictions, wherein a first bump placement restriction specifies an allowed distance range between a bump and a qubit chip element in a layout of the first surface in the flip chip configuration. An electrically conductive material is deposited outside the bump restriction area, to form the bump, wherein the bump comprises an electrically conductive structure that electrically couples a signal from the first surface and is positioned according to the set of bump placement restrictions.

A method of determining a device behavior, wherein the method includes using a first procedure. The first procedure includes discretizing a user specified nano-device structure for at least one quantum method. Additionally, the first procedure includes solving the at least one quantum method, thereby having a solution of the at least one quantum method. Moreover, the first procedure includes extracting a parameter out of the solution of the at least one quantum method. Next, the first procedure includes applying at least one approximate method to the user-specified nano-device structure using the parameter. The first procedure additionally includes solving the at least one approximate method to the user-specified nano-device structure using the parameter. The first procedure also includes extracting the device behavior of the user-specified nano-device structure. Next, the method of determining the device behavior includes iterating the first procedure until a condition is satisfied.

A computer simulation analysis method suitable for describing the mechanical behavior of multiphase composites based on the real microstructure of materials relates to a multidisciplinary field such as computational material science, simulation and high throughput calculation. Through the first-principles calculation under nano scale, the molecular dynamics simulation under micro scale, and the thermodynamic calculation under mesoscopic scale, various physical parameters needed for the finite element simulation under macro scale can be obtained, including the elastic and plastic physical parameters of each phase in the composite at different temperature and different grain sizes. Focused ion beam experiment and image processing are adopted to obtain real material microstructure. Through the parameter coupling and parameter transfer among the calculated results of various scales, combining the microstructure of the material, stress-strain relationship, stress distribution and its evolution law, plastic deformation and other mechanical behaviors of the multiphase composites under complex stress and different temperature can be simulated.

A machine learning system receives a witness function that is determined based on an initial sample of a dataset comprising multiple pairs of stimuli and responses. Each stimulus includes multiple features. The system receives a holdout sample of the dataset comprising one or more pairs of stimuli and responses that are not used to determine the witness function. The system generates a simulated sample based on the holdout sample. Values of a particular feature of the stimuli of the simulated sample are predicted based on values of features other than the particular feature of the stimuli of the simulated sample. The system applies the holdout sample to the witness function to obtain a first result. The system applies the simulated sample to the witness function to obtain a second result. The system determines whether to select the particular feature based on a comparison between the first result and the second result.

A method of simulating a non-equilibrium electronic structure of a nanodevice including receiving region information and applied voltage information of each of a channel, first and second electrodes based on information on first principle and upper approximation method and information on an atomic structure, classifying wave functions generated through the first principle and upper approximation method into each region of the channel, first and second electrodes based on spatial distribution, defining Fermi-Dirac distribution function depending on an electrochemical potential of each of the channel, first and second electrodes based on the classified region information and the applied voltage information, calculating a non-equilibrium electron density using the Fermi-Dirac distribution function corresponding to the region information of each of the channel, first and second electrodes and the wave functions of the classified regions, and acquiring non-equilibrium electronic structure information based on the calculated non-equilibrium electron density, and an apparatus thereof are provided.

Various embodiments of the present technology provide for the ultra-high density heterogenous integration, enabled by nano-precise pick-and-place assembly. For example, some embodiments provide for the integration of modular assembly techniques with the use of prefabricated blocks (PFBs). These PFBs can be created on one or more sources wafers. Then using pick-and-place technologies, the PFBs can be selectively arranged on a destination wafer thereby allowing Nanoscale-aligned 3D Stacked Integrated Circuit (N3-SI) and the Microscale Modular Assembled ASIC (M2A2) to be efficiently created. Some embodiments include systems and techniques for the construction of construct semiconductor devices which are arbitrarily larger than the standard photolithography field size of 2633 mm, using pick-and-place assembly.