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HIGH PRECISION OPTICAL CHARACTERIZATION OF CARRIER TRANSPORT PROPERTIES IN SEMICONDUCTORS

2021
Online Patent

Titel:
HIGH PRECISION OPTICAL CHARACTERIZATION OF CARRIER TRANSPORT PROPERTIES IN SEMICONDUCTORS
Link:
Veröffentlichung: 2021
Medientyp: Patent
Sonstiges:
  • Nachgewiesen in: USPTO Patent Applications
  • Sprachen: English
  • Document Number: 20210165040
  • Publication Date: June 3, 2021
  • Appl. No: 17/149303
  • Application Filed: January 14, 2021
  • Assignees: XCALIPR CORPORATION (Dover, DE, US)
  • Claim: 1. A method of evaluating a semiconductor sample, comprising: (a) directing an amplitude modulated pump laser beam onto an area of a surface of the sample to produce a time periodic modulation of the reflectance of the sample; (b) directing a second probe laser beam onto at least a portion of the area obtaining the time periodic modulation of the reflectance, wherein the probe laser beam comprises at least one wavelength suitable for detecting the induced changes in the reflectivity of the sample; (c) collecting and directing the probe light reflected from the sample into a photoreceiver to produce an output electrical signal corresponding to changes in the reflected probe light amplitude; (d) measuring the electrical signal using a phase-locked detection circuit; (e) performing a series of photo-modulated reflectance measurements of steps (a), (b), (c), and (d), with the surface of the sample at a plurality of distances from the focal plane of the pump laser beam; and (f) performing a nonlinear regression analysis using at least the information collected in step (e) to determine at least one electronic transport property of the sample.
  • Claim: 2. The method of claim 1, wherein the nonlinear regression analysis comprises a parametric model of the form: |ΔR/R|=A/[D2+2D{ω2(Z)+ωp2(Z)}+{ω2(Z)+ωp2(Z)}2(1+ψ2)]1/4+C, where |R/R| represents photo-modulated reflectance amplitude data, Z is the longitudinal displacement of the sample surface from focus, ω(Z) is a probe beam radius at the sample surface, ωp(Z) is a pump beam radius at the sample surface, A is a function which represents an amplitude, D is a parameter which represents the square of a carrier diffusion length, ψ is a parameter which represents the product of the modulation frequency and a carrier recombination lifetime, and C is a parameter which represents a constant.
  • Claim: 3. The method of claim 1, wherein the nonlinear regression analysis comprises a parametric model of the form: ϕ=½ tan−1{Dψ/[D+{ω2(Z)+ωp2(Z)}(1+ψ2)]}+ϕo, where ϕ represents photo-modulated reflectance phase data, Z is the longitudinal displacement of the sample surface from focus, ω(Z) is a probe beam radius at the sample surface, ωp(Z) is a pump beam radius at the sample surface, D is a parameter which represents the square of a carrier diffusion length, ψ is a parameter which represents the product of the modulation frequency and a carrier recombination lifetime, and ϕo is a parameter which represents a phase.
  • Claim: 4. The method of claim 1, wherein the nonlinear regression analysis comprises a parametric model of the form: |ΔR/R|=A/[D+ω2(Z)+ωp2(Z)]1/2+C, where |ΔR/R| represents photo-modulated reflectance amplitude data, Z is the longitudinal displacement of the sample surface from focus, ω(Z) is a probe beam radius at the sample surface, ωp(Z) is a pump beam radius at the sample surface, A is a function which represents an amplitude, D is a parameter which represents the square of a carrier diffusion length, and C is a parameter which represents a constant.
  • Claim: 5. The method of claim 1, wherein the nonlinear regression analysis comprises a parametric model of the form: |ΔR/R|=A/[(D/Ω)2+{ω2(Z)+ωp2(Z)}2]1/4+C, where |ΔR/R| represents photo-modulated reflectance amplitude data, Z is the longitudinal displacement of the sample surface from focus, ω(Z) is a probe beam radius at the sample surface, ωp(Z) is a pump beam radius at the sample surface, Ω is the modulation frequency, A is a function which represents an amplitude, D is a parameter which represents a carrier diffusion coefficient, and C is a parameter which represents a constant.
  • Claim: 6. The method of claim 1, wherein the nonlinear regression analysis comprises a parametric model of the form: Re[ΔR/R]=Re[A exp{iϕo}/(ω2(Z)+ωp2(Z)+D/(1+iψ))], where Re[ΔR/R] represents photo-modulated reflectance in-phase data, Z is the longitudinal displacement of the sample surface from focus, ω(Z) is a probe beam radius at the sample surface, ωp(Z) is a pump beam radius at the sample surface, A is a parameter which represents an amplitude, ϕo is a parameter which represents a phase, D is a parameter which represents the square of a carrier diffusion length, and ψ is a parameter which represents the product of the modulation frequency and a carrier recombination lifetime.
  • Claim: 7. The method of claim 1, wherein the nonlinear regression analysis comprises a parametric model of the form: Im[ΔR/R]=Im[A exp{iϕo}/(ω2(Z)+ωp2(Z)+D/(1+iψ))], where Im[ΔR/R] represents photo-modulated reflectance quadrature data, Z is the longitudinal displacement of the sample surface from focus, ω(Z) is a probe beam radius at the sample surface, ωp(Z) is a pump beam radius at the sample surface, A is a parameter which represents an amplitude, ϕo is a parameter which represents a phase, D is a parameter which represents the square of a carrier diffusion length, and ψ is a parameter which represents the product of the modulation frequency and a carrier recombination lifetime.
  • Claim: 8. The method of claim 1, wherein the nonlinear regression analysis comprises a parametric model of the form: Re[ΔR/R]=Re[A exp{iϕo}/(ω2(Z)+ωp2(Z)+D/(1+iψ))1/2], where Re[ΔR/R] represents photo-modulated reflectance in-phase data, Z is the longitudinal displacement of the sample surface from focus, ω(Z) is a probe beam radius at the sample surface, ωp(Z) is a pump beam radius at the sample surface, A is a function which represents an amplitude, ϕo is a parameter which represents a phase, D is a parameter which represents the square of a carrier diffusion length, and ψ is a parameter which represents the product of the modulation frequency and a carrier recombination lifetime.
  • Claim: 9. The method of claim 1, wherein the nonlinear regression analysis comprises a parametric model of the form: Im[ΔR/R]=Im[A exp{iϕo}/(ω2(Z)+ωp2(Z)+D/(1+iψ))1/2], where Im[ΔR/R] represents photo-modulated reflectance quadrature data, Z is the longitudinal displacement of the sample surface from focus, ω(Z) is a probe beam radius at the sample surface, ωp(Z) is a pump beam radius at the sample surface, A is a function which represents an amplitude, ϕo is a parameter which represents a phase, D is a parameter which represents the square of a carrier diffusion length, and ψ is a parameter which represents the product of the modulation frequency and a carrier recombination lifetime.
  • Claim: 10. The method of claim 1, wherein the nonlinear regression analysis comprises complex nonlinear least squares data fitting.
  • Claim: 11. A method of evaluating a semiconductor sample, comprising: (a) directing an amplitude modulated pump laser beam onto an area of a surface of the sample to produce a time periodic modulation of the reflectance of the sample; (b) directing a second probe laser beam onto at least a portion of the area obtaining the time periodic modulation of the reflectance, wherein the probe laser beam comprises at least one wavelength suitable for detecting the induced changes in the reflectivity of the sample; (c) collecting and directing the probe light reflected from the sample into a photoreceiver to produce an output electrical signal corresponding to changes in the reflected probe light amplitude; (d) measuring the electrical signal using a phase-locked detection circuit; (e) performing a series of photo-modulated reflectance measurements of steps (a), (b), (c), and (d), with the surface of the sample at a plurality of distances from the focal plane of the pump laser beam; and (f) using a trained neural network and at least the information collected in step (e) to predict at least one electronic transport property of the sample.
  • Claim: 12. An apparatus for evaluating a semiconductor sample, comprising: (a) a first laser source producing an amplitude modulated pump laser beam suitable for inducing changes in the reflectance of the sample; (b) a second laser source producing a continuous wave probe laser beam suitable for detecting induced changes in the reflectivity of the sample; (c) an optical system effective to direct the pump laser beam and the probe laser beam onto at least a portion of a common area of a surface of the sample, to translate a focal plane of the pump laser beam with respect to the sample surface, and to collect and direct probe light reflected from the sample into a photoreceiver; (d) a photoreceiver effective to generate an electrical signal in response to changes in the reflected probe light amplitude; (e) a phase-locked detection circuit effective to measure the electrical signal; (f) a computer/controller effective to record a series of photo-modulated reflectance measurements as a function of the distance between the sample surface and the focal plane of the pump laser beam; and (g) a computer program, embodied on a non-transitory computer readable medium, comprising executable code to perform an analysis using at least a recorded information to determine at least one electronic transport property of the sample.
  • Claim: 13. The apparatus of claim 12, wherein the wavelength of the probe beam is in the range of 365 to 395 nm.
  • Claim: 14. The apparatus of claim 12, wherein the wavelength of the pump beam is in the range of 395 to 410 nm.
  • Claim: 15. The apparatus of claim 12, wherein the wavelength of the probe beam is in the range of 465 to 495 nm.
  • Claim: 16. The apparatus of claim 12, wherein the wavelength of the pump beam is in the range of 630 to 680 nm.
  • Claim: 17. The apparatus of claim 12, wherein the wavelength of the probe beam is in the range of 630 to 680 nm.
  • Claim: 18. The apparatus of claim 12, wherein the optical system comprises an electrically tunable liquid lens.
  • Claim: 19. The apparatus of claim 12, wherein the computer program comprises a complex nonlinear least squares fitting program.
  • Claim: 20. The apparatus of claim 12, wherein the computer program comprises a trained neural network.
  • Current International Class: 01; 01

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