Abstract: Predictive multi-stage modelling for complex semiconductor device manufacturing process control is provided. In one aspect, a method of predictive multi-stage modelling for controlling a complex semiconductor device manufacturing process includes: collecting geometrical data from metrology measurements made at select stages of the manufacturing process; and making an outcome probability prediction at each of the select stages using a multiplicative kernel Gaussian process, wherein the outcome probability prediction is a function of a current stage and all prior stages. Machine-learning models can be trained for each of the select stages of the manufacturing process using the multiplicative kernel Gaussian process. The machine-learning models can be used to provide probabilistic predictions for a final outcome in real-time for production wafers. The probabilistic predictions can then be used to select production wafers for rework, sort, scrap or disposition.

Abstract: Predictive multi-stage modelling for complex semiconductor device manufacturing process control is provided. In one aspect, a method of predictive multi-stage modelling for controlling a complex semiconductor device manufacturing process includes: collecting geometrical data from metrology measurements made at select stages of the manufacturing process; and making an outcome probability prediction at each of the select stages using a multiplicative kernel Gaussian process, wherein the outcome probability prediction is a function of a current stage and all prior stages. Machine-learning models can be trained for each of the select stages of the manufacturing process using the multiplicative kernel Gaussian process. The machine-learning models can be used to provide probabilistic predictions for a final outcome in real-time for production wafers. The probabilistic predictions can then be used to select production wafers for rework, sort, scrap or disposition.

Abstract: Techniques for semiconductor process flow disposition optimization using clamped Monte Carlo distribution are provided. In one aspect, a method for optimizing a semiconductor fabrication process includes: providing a model of the fabrication process; identifying sensitive parameters of the fabrication process using Monte Carlo simulations that sample sections of experimental parameter populations from the fabrication process as input to the model to determine parameters which impact an outcome of the Monte Carlo simulations, wherein the parameters which impact the outcome of the Monte Carlo simulations are the sensitive parameters; bounding the experimental parameter populations of the sensitive parameters to improve the outcome of the Monte Carlo simulations; and modifying the fabrication process based on the providing, identifying and bounding steps to improve an output of the fabrication process.

Abstract: A method of co-optimizing lithographic and etching processes for semiconductor fabrication. The method includes determining a first set of locations for a first complementary laser annealing to be performed on. The first complementary laser annealing is performed at the first set of locations on at least a first semiconductor wafer of a plurality of semiconductor wafers. The first complementary laser annealing is performed before or after a first post-exposure baking process for the at least first semiconductor wafer. After an etching process has been performed on at least the first semiconductor wafer, a second set of locations is determined for a second complementary laser annealing to be performed on. The second complementary laser annealing is performed at the second set of locations on at least a second semiconductor wafer of the plurality of semiconductor wafers. The second complementary laser annealing is performed before or after a second post-exposure baking process.

Abstract: A system, a computer program product, and method for physically fabricating an electronic circuit using design space exploration as part of a design process is described. The method begins with defining a plurality of design space parameters to be tuned along with parameter ranges for each of the plurality of design space parameters. Next an output target to be optimized is defined. A series of one or more test mask shapes are generated to appear on a photo mask using the plurality of design space parameters. A simulation of a post lithography or etch on the series of one or more test mask shapes is performed to produce simulation output values. Next, the simulation output values and corresponding design space parameters are fed into to a Bayesian inference algorithm for assessment and identification of a next combination of design space parameters to investigate.

Abstract: A system, a computer program product, and method for physically fabricating an electronic circuit using design space exploration as part of a design process is described. The method begins with defining a plurality of design space parameters to be tuned along with parameter ranges for each of the plurality of design space parameters. Next an output target to be optimized is defined. A series of one or more test mask shapes are generated to appear on a photo mask using the plurality of design space parameters. A simulation of a post lithography or etch on the series of one or more test mask shapes is performed to produce simulation output values. Next, the simulation output values and corresponding design space parameters are fed into to a Bayesian inference algorithm for assessment and identification of a next combination of design space parameters to investigate.

Abstract: A method of co-optimizing lithographic and etching processes for semiconductor fabrication. The method includes determining a first set of locations for a first complementary laser annealing to be performed on. The first complementary laser annealing is performed at the first set of locations on at least a first semiconductor wafer of a plurality of semiconductor wafers. The first complementary laser annealing is performed before or after a first post-exposure baking process for the at least first semiconductor wafer. After an etching process has been performed on at least the first semiconductor wafer, a second set of locations is determined for a second complementary laser annealing to be performed on. The second complementary laser annealing is performed at the second set of locations on at least a second semiconductor wafer of the plurality of semiconductor wafers. The second complementary laser annealing is performed before or after a second post-exposure baking process.

Abstract: An interconnect structure in which the adhesion between an upper level low-k dielectric material, such as a material comprising elements of Si, C, O, and H, and an underlying diffusion capping dielectric, such as a material comprising elements of C, Si, N and H, is improved by incorporating an adhesion transition layer between the two dielectric layers. The presence of the adhesion transition layer between the upper level low-k dielectric and the diffusion barrier capping dielectric can reduce the chance of delamination of the interconnect structure during the packaging process. The adhesion transition layer provided herein includes a lower SiOx- or SiON-containing region and an upper C graded region. Methods of forming such a structure, in particularly the adhesion transition layer, are also provided.

Abstract: Prevention of damage to an interlevel dielectric (ILD) is provided by forming an opening (e.g., trench) in the ILD, and sputtering a dielectric film onto a sidewall of the opening by overetching into a layer of the dielectric below or within the ILD during forming of the opening. The re-sputtered film protects the sidewall of the opening from subsequent plasma/ash processes and seals the porous dielectric surface along the sidewall and bottom without impacting overall process throughput. A semiconductor structure resulting from the above process is also disclosed.

Abstract: Fail sites in a semiconductor are isolated through a difference image of a fail area and a healthy area. The fail area comprises an image of a semiconductor with a fail. The healthy area comprises an image of a semiconductor absent the fail or, in other words, an image of a semiconductor with healthy structure. Instructions cause a variation in the intensities of the difference image to appear at the fail site.

Abstract: Methods of depositing a tantalum-nitride (TaN) diffusion barrier region on low-k materials. The methods include forming a protective layer on the low-k material substrate by performing plasma-enhanced atomic layer deposition (PE-ALD) from tantalum-based precursor and a nitrogen plasma in a chamber. The protective layer has a nitrogen content greater than its tantalum content. A substantially stoichiometric tantalum-nitride layer is then formed by performing PE-ALD from the tantalum-based precursor and a plasma including hydrogen and nitrogen. The invention also includes the tantalum-nitride diffusion barrier region so formed. In one embodiment, the metal precursor includes tantalum penta-chloride (TaCl5). The invention generates a sharp interface between low-k materials and liner materials.

Abstract: An interconnect structure in which the adhesion between an upper level low-k dielectric material, such as a material comprising elements of Si, C, O, and H, and an underlying diffusion capping dielectric, such as a material comprising elements of C, Si, N and H, is improved by incorporating an adhesion transition layer between the two dielectric layers. The presence of the adhesion transition layer between the upper level low-k dielectric and the diffusion barrier capping dielectric can reduce the chance of delamination of the interconnect structure during the packaging process. The adhesion transition layer provided herein includes a lower SiOx— or SiON-containing region and an upper C graded region. Methods of forming such a structure, in particularly the adhesion transition layer, are also provided.