Abstract: Methods and systems for compensating for uncertainty in illumination angle of incidence to enable accurate measurements of semiconductor structures are described herein. In one aspect, measurements are performed at one or more nominal angles of incidence, an actual angle of incidence corresponding to each measurement is estimated, and a value of a parameter of interest characterizing a measured structure is estimated based at least in part on the collected measurement data and the actual angle of incidence. In some examples, an actual angle of incidence is directly measured. In some other examples, an actual angle of incidence is estimated from measurement data collected over a range of nominal illumination angles of incidence. In some other examples, an actual angle of incidence with respect to a tilted structure is estimated from measurement data collected over a range of nominal illumination angles of incidence.

Abstract: Methods and systems for determining random variation in one or more structures on a specimen are provided. One method includes determining characteristic(s) of output generated by an output acquisition subsystem for structure(s) formed on a specimen and simulating the characteristic(s) of the output with initial parameter values for the structure(s). The method also includes determining parameter values of the structure(s) formed on the specimen as the initial parameter values that resulted in the simulated characteristic(s) that best match the determined characteristic(s). The determined parameter values are responsive to random variation in parameter(s) of the structure(s) on the specimen.

Abstract: Methods and systems for determining random variation in one or more structures on a specimen are provided. One method includes determining characteristic(s) of output generated by an output acquisition subsystem for structure(s) formed on a specimen and simulating the characteristic(s) of the output with initial parameter values for the structure(s). The method also includes determining parameter values of the structure(s) formed on the specimen as the initial parameter values that resulted in the simulated characteristic(s) that best match the determined characteristic(s). The determined parameter values are responsive to random variation in parameter(s) of the structure(s) on the specimen.

Abstract: Methods and systems for determining random variation in one or more structures on a specimen are provided. One method includes determining characteristic(s) of output generated by an output acquisition subsystem for structure(s) formed on a specimen and simulating the characteristic(s) of the output with initial parameter values for the structure(s). The method also includes determining parameter values of the structure(s) formed on the specimen as the initial parameter values that resulted in the simulated characteristic(s) that best match the determined characteristic(s). The determined parameter values are responsive to random variation in parameter(s) of the structure(s) on the specimen.

Abstract: Methods and systems for monitoring the quality of a semiconductor measurement in a targeted manner are presented herein. Rather than relying on one or more general indices to determine overall measurement quality, one or more targeted measurement quality indicators are determined. Each targeted measurement quality indicator provides insight into whether a specific operational issue is adversely affecting measurement quality. In this manner, the one or more targeted measurement quality indicators not only highlight deficient measurements, but also provide insight into specific operational issues contributing to measurement deficiency. In some embodiments, values of one or more targeted measurement quality indicators are determined based on features extracted from measurement data.

Abstract: Methods and systems for measuring a complex semiconductor structure based on measurement data before and after a critical process step are presented. In some embodiments, the measurement is based on x-ray scatterometry measurement data. In one aspect, a measurement is based on fitting combined measurement data to a simplified geometric model of the measured structure. In some embodiments, the combined measurement data is determined by subtraction of a measured diffraction pattern before the critical process step from a measured diffraction pattern after the critical process step. In some embodiments, the simplified geometric model includes only the features affected by the critical process step. In another aspect, a measurement is based on a combined data set and a trained signal response metrology (SRM) model. In another aspect, a measurement is based on actual measurement data after the critical process step and simulated measurement data before the critical process step.

Abstract: Methods and systems for performing model-less measurements of semiconductor structures based on scatterometry measurement data are described herein. Scatterometry measurement data is processed directly, without the use of a traditional measurement model. Measurement sensitivity is defined by the changes in detected diffraction images at one or more non-zero diffraction orders over at least two different illumination incidence angles. Discrete values of a scalar function are determined directly from measured images at each incidence angle. A continuous mathematical function is fit to the set of discrete values of the scalar function determined at each incidence angle. A value of a parameter of interest is determined based on analysis of the mathematical function. In some embodiments, the scalar function includes a weighting function, and the weighting values associated with weighting function are optimized to yield an accurate fit of the mathematical function to the scalar values.

Abstract: Methods and systems for monitoring the quality of a semiconductor measurement in a targeted manner are presented herein. Rather than relying on one or more general indices to determine overall measurement quality, one or more targeted measurement quality indicators are determined. Each targeted measurement quality indicator provides insight into whether a specific operational issue is adversely affecting measurement quality. In this manner, the one or more targeted measurement quality indicators not only highlight deficient measurements, but also provide insight into specific operational issues contributing to measurement deficiency. In some embodiments, values of one or more targeted measurement quality indicators are determined based on features extracted from measurement data.

Abstract: Methods and systems for measuring a complex semiconductor structure based on measurement data before and after a critical process step are presented. In some embodiments, the measurement is based on x-ray scatterometry measurement data. In one aspect, a measurement is based on fitting combined measurement data to a simplified geometric model of the measured structure. In some embodiments, the combined measurement data is determined by subtraction of a measured diffraction pattern before the critical process step from a measured diffraction pattern after the critical process step. In some embodiments, the simplified geometric model includes only the features affected by the critical process step. In another aspect, a measurement is based on a combined data set and a trained signal response metrology (SRM) model. In another aspect, a measurement is based on actual measurement data after the critical process step and simulated measurement data before the critical process step.

Abstract: An optoelectronic device comprising an active layer sandwiched between a first electrode and a second electrode. The active layer comprises a material of the formula AaBbMmXx, wherein A represents a monovalent inorganic cation, a monovalent organic cation, or mixture of different monovalent organic or inorganic cations; B represents a divalent inorganic cation, a divalent organic cation, or mixture of different divalent organic or inorganic cations; M represents Bi3+ or Sb3+; X represents a monovalent halide anion, or mixture of different monovalent halide anions; and a, b represent 0 or any positive numbers, m, x represent any positive numbers, and a+2b+3m=x.

Abstract: A method of fabricating an organic device is provided comprising providing a first solution comprising an organic semiconductor or a precursor thereof; a solvent and a decomposable polymer additive, where the polymer additive is heated so that it decomposes into gas. The method is applicable to large scale fabrication of OLEDs, OPVs and OFET devices.

Abstract: A method of fabricating an organic device is provided comprising providing a first solution comprising an organic semiconductor or a precursor thereof; a solvent and a decomposable polymer additive, where the polymer additive is heated so that it decomposes into gas. The method is applicable to large scale fabrication of OLEDs, OPVs and OFET devices.