Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
  • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
  • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
  • G01N21/27—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands using photo-electric detection ; circuits for computing concentration
  • G01N21/274—Calibration, base line adjustment, drift correction
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
  • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
  • G01J3/28—Investigating the spectrum
  • G01J3/42—Absorption spectrometry; Double beam spectrometry; Flicker spectrometry; Reflection spectrometry

Definitions

• the present invention relates generally to the field of spectral analysis and in particular to a method and apparatus useful for quantitative analysis of spectral data.
• the method and apparatus of the present invention finds particular application to the quantitative analysis of spectral data obtained from a sample comprising a plurality of components or analytes, that is, a multicomponent sample.
• Spectral analysis finds wide application in identifying and quantitating analytes in a sample.
• One particular form of spectral analysis measures the amount of ' electromagnetic radiation which is absorbed by a réelle sample.
• an infrared spectrophotometer directs a beam of infrared radiation at or through a sample and measures the amount of infrared radiation absorbed by the sample throughout some range of radiation wavelengths.
• An absorbance spectrum may then be plotted which relates sample absorbance to radiation wavelength.
• the overall shape of the absorbance spectrum including the wavelengths and relative magnitudes of peak absorbance values, is characteristic of the particular analytes in the sample and thus may be used to attempt to identify, generally or particularly, the analytes.
• the absorbance spectrum may also be used in an attempt to quantitate the concentrations of each analyte in the sample.
• the absorbance of an analyte in a sample is essentially proportional to the concentration of the analyte in the sample.
• concentration of the analyte may be easily determined by coirtij iF.i the sample absorbance at at least one wavelength to the absorbance of a sample at the same wavelength containing a known concentration of the analyte.
• the prior methods and apparatus each require that absorbance spectra for a plurality of calibration samples be obtained.
• the calibration samples each include various predetermined concentrations of analytes which are thought to be the same analytes present in unknown concentrations in an unknown sample.
• a plurality of absorbance values at predetermined identical wavelengths are determined on each of the calibration spectra providing a set of absorbance values for each spectra.
• the sets are arranged as, for example, columns in an absorbance matrix, A.
• the known concentrations of the analytes also form a set of values for each calibration sample. All of the sets of concentration values for the calibration samples are arranged as columns in a concentration matrix, C.
• the absorbance matrix A is related to the concentration matrix C by a constant matrix K in accordance with the following expression:
• An absorbance spectrum is also determined for an unknown sample. Absorbance values are selected from the unknown sample spectrum at the same wavelengths used to determine absorbance values from the calibration spectra.
• the unknown sample absorbance values are arranged into a sample matrix S, a ector, and the concentrations of the analytes in the unknown sample may then be. determined using the following relationship:
• vector and both “matrix” and “vector” may be used herein for such a matrix.
• the method just described has several inherent disadvantages which limit the accuracy of the method and similar methods.
• the number of absorbance values selected from the calibration spectra and the wavelengths at which the absorbance values are determined influence the accuracy of the method. For example, absorbance
• the number of absorbance values may be increased.
• increased numbers of absorbance values also increases the complexity and the time required to determine the P matrix and to determine the unknown sample concentration vector U.
• the resulting sets of absorbance values still pro ide only a 3 imited representation of the absorbance spectra.
• the measured absorbance spectra may include some high-frequency noise introduced by the measurement method.
• the absorbance values selected from the spectra will include the high frequency noise, further contributing to inaccurate unknown sample concentration results.
• a further difficulty in the method is that it is first necessary to determine a base line for each spectrum to account for background absorbance.
• the determination of a base line can be somewhat arbitrary and, if improperly or inaccurately accomplished, further diminishes the accuracy of prior art quantitation methods.
• concentration vector U assumes that the unknown sample includes only the analytes present in the calibration samples.
• the prior methods include no means for indicating that other analytes may be present in the sample and merely determine analyte concentrations as though only the analytes present in the calibration samples are present in the unknown sample. Consequently, the unknown sample analyte concentrations determined by prior methods and apparatus may be inaccurate and improperly indicate analyte concentrations which actually are not present.
• the present invention provides a multicompnent quantitative analytical method and apparatus which overcomes the limitations and disadvantages described above.
• a method and apparatus in accordance herewith uniquely and advantageously more accurately represents the calibration and unknown spectra which reduces the influence of high-frequency noise.
• the present method and apparatus eliminates the need for selection of base lines for the spectra and importantly provides means for
• a method in accordance herewith includes the steps of, and an apparatus includes means for, obtaining calibration spectra for calibration samples containing known concentrations of selected analytes such that the spectra represent values proportional to concentration.
• the calibration spectra are each transformed using a transform with orthogonal basis functions.
• a multivariant analysis is performed to obtain a reference or calibration matrix relating known concentrations of analytes in the calibration samples to the transformed spectra.
• an unknown spectrum is determined and the spectrum is transformed using a transform with orthogonal basis functions.
• an unknown concentration matrix is.determined, thereby completing the quantitative multicomponent analysis of analytes present in the unknown sample.
• Figure 1 is a simplified block diagram of a apparatus in accordance with the present invention
• Figure 2 is a block diagram of a method in accordance with the present invention and performed by the apparatus of Figure 1.
• Figure 3 is an example of an absorbance spectrum obtained by the apparatus of Figure 1;
• Figure 4 is a representation of a transformed absorbance spectrum in accordance with the present invention.
• Figure 6 is a block diagram illustrating * detailed substeps step 68 of the block diagram of Figure 2?
• Figure 6A is a block diagram illustrating substeps for step 68a of the block diagram of Figure 6;
• Figure 7 is a block diagram showing detailed steps of another form of multivariant analysis which may be used to implement step 62 of Figure 2;
• Figure 8 is a block diagram illustrating detailed substeps for step 68 of the method of Figure 2 utilizing the alternative mul ivariant analysis technique illustrated in Figure 7.
• the detector electronics 22 amplifies and further processes the output of the detector 21 and in turn applies an output proportional to absorbance- to an analog-to-digital converter (ADC) 24.
• ADC analog-to-digital converter
• the ADC 24 converts the analog output of the detector electronics 2__ into a multi-bit digital representation which is in turn applied to a computer system 26.
• the computer system 26 further includes a conventi ⁇ rta ⁇ i memory subsystem comprising read-only-memory (ROM) 32 s ⁇ random-access-memory (RAM) 34 both in communicafciLcen with the bus 28.
• ROM read-only-memory
• RAM random-access-memory
• a hardware interface 40 of conventional design and in communication with the bus 28 provides an interface between the computer system 26 and the remaining hardware elements of the apparatus 10, such as the source 12, the monochromator 14, the detector electronics 22 and the ADC 24.
• the microprocessor 30 controls the operation of the apparatus 10. I- turn, the operation controlled by the microprocessor 30 may be specified by a user through the terminal 36, thus providing an automated apparatus 10.
• the apparatus 10 may be formed from a conventional spectrophoto eter modified in accordance with the present invention as is described hereinbelow with respect to the operation of the apparatus 10.
• the apparatus 10 may comprise, for example, a DU-7 spectrophotometer, a DU-8 spectrophotometer, or a
• Microlab spectrophotometer all available from Beckman Instruments, Inc., and all modified to perform as disclosed herein.
• modification may include variations in software stored in the ROM 32, and RAM 34.
• Such variations cause the microprocessor 30 to, in eff c , reconfigure an otherwise conventional spectrophotometer to form the apparatus 10 in accordance with the present invention.
• the execution of such modifications will be readily apparent to those skilled in the art using the description included herewith, and may include well known and otherwise conventional
• the computer system 26, including the microprocessor 30, provides structure which corresponds to means for performing various functions.
• a first step includes determining calibration absorbance spectra for N number of calibration samples, each of the samples having varying concentrations of M components.
• Each such calibration absorbance spectra may be obtained by operating the apparatus 10 in a well known fashion. For example, each calibration sample is placed within the sample compa»rtment 16 as the sample 18.
• the monochromator 14 is then controlled so as to provide a beam of infrared radiation from the monochromator 14 having wavelengths varying over a predetermined range of wavelen g ths desired for the absorbance spectra being measured, such as about 400 to 4000 wavenumbers.
• the radiation passing through the sample 18 is detected by the detector 21, processed by the detector electronics 22 and converted to a digital signal by means of ADC 24.
• the output of the detector 21, which is a signal proportional to transmittance of the sample 18, may be converted, for example, in the detector electronics 22 to a signal proportional to absorbance.
• the ADC 24 is commanded to periodically convert the analog output of the detector electronics 22 to the digital representation which is applied to the bus 28.
• the microprocessor 30 may then
• SUBSTITUTE SHEET store each digital absorbance value into the RAM 34. Successively stored digital absorbance values together define an absorbance spectrum for the sample 18. As seen in Figure 3, a typical absorbance spectrum for one - > calibration sample may appear as shown by curve 52 representing a smoothed version of the individual digital absorbance values stored in the RAM 34.
• a portion 0 52a of the spectrum 52 may be selected as a characteristic or "fingerprint" region of the spectrum as, for example, the region between and including wavenumbers 2000 and 1000. Accordingly, the remainder of the spectrum 52 will not be used in the remainder of the 5 steps shown in Figure 2.
• a next step 54 includes transforming the calibration absorbance spectra for each of the calibration samples.
• the 0 transform selected is one with orthogonal basis functions, that is, the transform selected transforms each absorbance spectrum into vectors in a function space whose coordinate axes may represent a complete set of orthonormal functions. Examples of such function spaces 5 are those constructed from Legendre polynomials, Fourier series and transforms, and Chebyshev polynomials.
• the Fourier transform is used to transform each of the calibration absorbance spectra into corresponding vectors. 0
• step 68d Figure 6A
• step 68e the correlation coefficient k
• step 68g the vector difference between such vector sum and the 0 unknown sample vector V
• step 68g the vector difference may then be adjusted to concentration units (step 68g) by multiplying tne euclidean length of the vector O and dividing by the euclidean length of the sample vector V. The result indicates the residual 5 concentration.
• a J matrix (step 62p, Figure 7) is formed using the calibration vectors obtained from step 54 of Figure 2.
• the J matrix has N columns and a number o rows equal to the number of values obtained from the transformation performed in step 54 of Figure 2.
• the matrix J may be related to the n concentration matrix C by the following relationship:
• step 62q a method of least squares is used to solve for the elements in the matrix K.

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• 1983
  • 1983-09-19 US US06/533,833 patent/US4660151A/en not_active Expired - Lifetime
• 1984
  • 1984-09-19 EP EP84903600A patent/EP0156877B1/en not_active Expired
  • 1984-09-19 JP JP59503544A patent/JPS60502269A/ja active Granted
  • 1984-09-19 DE DE8484903600T patent/DE3478502D1/de not_active Expired
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