Abstract: An improved method for integrating curve peaks as compared to techniques such as the trapezoidal rule wherein integration parameters are at fixed x-axis positions. Integration parameters are instead specified relative to a peak center, which allows the peak to shift over time due to hardware changes, temperature fluctuation, pressure changes, etc., while maintaining integration parameters at optimal locations for that peak. As such, the present disclosure finds particular utility in spectroscopy wherein, in the case of Raman spectroscopy, for example, specific wavenumber shift locations may drift over time, leading to inaccurate results based upon absolute integration parameters.

Abstract: An improved method for integrating curve peaks as compared to techniques such as the trapezoidal rule wherein integration parameters are at fixed x-axis positions. Integration parameters are instead specified relative to a peak center, which allows the peak to shift over time due to hardware changes, temperature fluctuation, pressure changes, etc., while maintaining integration parameters at optimal locations for that peak. As such, the present disclosure finds particular utility in spectroscopy wherein, in the case of Raman spectroscopy, for example, specific wavenumber shift locations may drift over time, leading to inaccurate results based upon absolute integration parameters.

Abstract: Methods and systems for spectrometer dark correction are described which achieve more stable baselines, especially towards the edges where intensity correction magnifies any non-zero results of dark subtraction, and changes in dark current due to changes in temperature of the camera window frame are typically more pronounced. The resulting induced curvature of the baseline makes quantitation difficult in these regions. Use of the invention may provide metrics for the identification of system failure states such as loss of camera vacuum seal, drift in the temperature stabilization, and light leaks. In system aspects of the invention, a processor receives signals from a light detector in the spectrometer and executes software programs to calculate spectral responses, sum or average results, and perform other operations necessary to carry out the disclosed methods. In most preferred embodiments, the light signals received from a sample are used for Raman analysis.

Abstract: Methods and systems for spectrometer dark correction are described which achieve more stable baselines, especially towards the edges where intensity correction magnifies any non-zero results of dark subtraction, and changes in dark current due to changes in temperature of the camera window frame are typically more pronounced. The resulting induced curvature of the baseline makes quantitation difficult in these regions. Use of the present disclosure may provide metrics for the identification of system failure states such as loss of camera vacuum seal, drift in the temperature stabilization, and light leaks. In system aspects of the present disclosure, a processor receives signals from a light detector in the spectrometer and executes software programs to calculate spectral responses, sum or average results, and perform other operations necessary to carry out the disclosed methods. In most preferred embodiments, the light signals received from a sample are used for Raman analysis.

Abstract: Methods and systems for spectrometer dark correction are described which achieve more stable baselines, especially towards the edges where intensity correction magnifies any non-zero results of dark subtraction, and changes in dark current due to changes in temperature of the camera window frame are typically more pronounced. The resulting induced curvature of the baseline makes quantitation difficult in these regions. Use of the invention may provide metrics for the identification of system failure states such as loss of camera vacuum seal, drift in the temperature stabilization, and light leaks. In system aspects of the invention, a processor receives signals from a light detector in the spectrometer and executes software programs to calculate spectral responses, sum or average results, and perform other operations necessary to carry out the disclosed methods. In most preferred embodiments, the light signals received from a sample are used for Raman analysis.

Abstract: Methods and systems for spectrometer dark correction are described which achieve more stable baselines, especially towards the edges where intensity correction magnifies any non-zero results of dark subtraction, and changes in dark current due to changes in temperature of the camera window frame are typically more pronounced. The resulting induced curvature of the baseline makes quantitation difficult in these regions. Use of the invention may provide metrics for the identification of system failure states such as loss of camera vacuum seal, drift in the temperature stabilization, and light leaks. In system aspects of the invention, a processor receives signals from a light detector in the spectrometer and executes software programs to calculate spectral responses, sum or average results, and perform other operations necessary to carry out the disclosed methods. In most preferred embodiments, the light signals received from a sample are used for Raman analysis.

Abstract: Methods and systems for spectrometer dark correction are described which achieve more stable baselines, especially towards the edges where intensity correction magnifies any non-zero results of dark subtraction, and changes in dark current due to changes in temperature of the camera window frame are typically more pronounced. The resulting induced curvature of the baseline makes quantitation difficult in these regions. Use of the invention may provide metrics for the identification of system failure states such as loss of camera vacuum seal, drift in the temperature stabilization, and light leaks. In system aspects of the invention, a processor receives signals from a light detector in the spectrometer and executes software programs to calculate spectral responses, sum or average results, and perform other operations necessary to carry out the disclosed methods. In most preferred embodiments, the light signals received from a sample are used for Raman analysis.

Abstract: Methods and systems for spectrometer dark correction are described which achieve more stable baselines, especially towards the edges where intensity correction magnifies any non-zero results of dark subtraction, and changes in dark current due to changes in temperature of the camera window frame are typically more pronounced. The resulting induced curvature of the baseline makes quantitation difficult in these regions. Use of the invention may provide metrics for the identification of system failure states such as loss of camera vacuum seal, drift in the temperature stabilization, and light leaks. In system aspects of the invention, a processor receives signals from a light detector in the spectrometer and executes software programs to calculate spectral responses, sum or average results, and perform other operations necessary to carry out the disclosed methods. In most preferred embodiments, the light signals received from a sample are used for Raman analysis.

Abstract: Raw data inputs are treated as independent signal sources to reduce computational lag without adversely affecting signal-to-noise ratio (SNR). Applications include spectroscopy, multiple linear regression, mass balance quantitation and the calculation of physical properties. The input-specific averaging has been applied to Raman spectroscopy, where the inputs are averaged spectra from which peak heights or areas are obtained from integration. Alternatively, peak areas or heights can be obtained from unaveraged spectra and are then averaged before use in further calculations as inputs to produce a desired output. The output(s) are linear or nonlinear combinations of the peak heights or areas, coupled with weighting factors which relate the raw inputs to a quantitative output such as concentration of a chemical species. Each specific input can use a different type of averaging. The overall goal may be optimization for best precision, and/or optimization for minimum lag time.