Abstract: A method in one embodiment creates a model of an authentic IC for use in comparisons with counterfeit ICs. The model can be created by determining a first or initial set of points of interest (POIs) on the simulated physical (e.g., gate level) layout and simulating side channel leakage from each POI and then expanding the size of the POI and repeating the simulation and comparing successive simulation results (between successive sizes of POIs for a given POI) to determine if a solution for the size of the POI has converged. The final POIs are then processed in a simulation that can use multiple payloads (e.g., cryptographic data) over the entire set of final POIs, and the resulting data set can be used to create the model.

Abstract: Machine assisted systems and methods for enhancing the resolution of an IC thermal profile from a system analysis are described. These systems and methods can use a neural network based predictor, that has been trained to determine a temperature rise across an entire IC. The training of the predictor can include generating a representation of two or more templates identifying different portions of an integrated circuit (IC), each template associated with location parameters to position the template in the IC; performing thermal simulations for each respective template of the IC, each thermal simulation determining an output based on a power pattern of tiles of the respective template, the output indicating a change in temperature of a center tile of the respective template relative to a base temperature of the integrated circuit; and training a neural network.

Abstract: Machine assisted systems and methods for enhancing the resolution of an IC thermal profile from a system analysis are described. The methods can include generating a representation of two or more templates identifying different portions of an integrated circuit (IC); performing a thermal simulation for each respective template of the IC based on a sequence of power patterns of tiles of the respective template; and training a neural network with a plurality of training data collected via thermal simulations performed for the templates of the IC. These systems and methods can use a machine learning predictor, that has been trained to determine a transient temperature rise across an entire IC, and then append the determined transient temperature rise to a system level thermal profile of the IC.

Abstract: A method for automatically collecting semiconductor manufacturing parameters of a manufacturing equipment is provided. The method includes reporting semiconductor manufacturing parameters obtained by self-monitoring of the manufacturing equipment and obtaining storage locations in an electronic data capture corresponding to reported semiconductor manufacturing parameters and transporting the reported semiconductor manufacturing parameters and corresponding storage locations. The method further includes receiving the reported semiconductor manufacturing parameters and the corresponding storage location and storing each reported semiconductor manufacturing parameters automatically into the electronic data capture of a manufacturing execution system according to the corresponding storage location.

Abstract: A method for automatically collecting semiconductor manufacturing parameters of a manufacturing equipment is provided. The method includes reporting semiconductor manufacturing parameters obtained by self-monitoring of the manufacturing equipment and obtaining storage locations in an electronic data capture corresponding to reported semiconductor manufacturing parameters and transporting the reported semiconductor manufacturing parameters and corresponding storage locations. The method further includes receiving the reported semiconductor manufacturing parameters and the corresponding storage location and storing each reported semiconductor manufacturing parameters automatically into the electronic data capture of a manufacturing execution system according to the corresponding storage location.

Abstract: In accordance with at least some embodiments of the present disclosure, a lateral flow immunoassay strip may include a first conjugate pad containing streptavidin-gold nanoparticle (streptavidin-AuNP) conjugates, a second conjugate pad containing anti-cardiac troponin I monoclonal antibody (anti-cTnI mAb)-AuNP-biotinylated single stranded DNA (ssDNA) conjugate complexes, and a nitrocellulose membrane coupled with the first conjugate pad and the second conjugate pad, wherein the nitrocellulose membrane contains a first test line prepared with capturing anti-cTnI mAb.