Processing mass spectral data may include performing one or more experiments using one or more samples, each experiment including mass analysis using a mass spectrometer; acquiring one or more raw mass spectral data sets as a result of performing the one or more experiments; receiving selection criteria; filtering the one or more raw mass spectral data sets in accordance with the selection criteria; and generating a chromatogram as a result of said filtering, wherein the chromatogram displays signal intensity as a function of scan time for a plurality of scan times and includes a non-zero signal intensity at each scan time only if, at the scan time, the selection criteria is met and otherwise the chromatogram includes a zero signal intensity at the scan time. The mass spectrometer may alternate between low and elevated energy modes and acquire two of the raw mass spectral data sets concurrently.

The operation efficiency and accuracy of the simultaneous analysis of phospholipids, including fatty acid compositions are increased. After a first-time LC/MS/MS analysis for determining the phospholipid classes of the phospholipid contained in a sample is performed (S2-S3), a second-time LC/MS/MS analysis for determining fatty acid compositions is performed only for the detected phospholipids (S4-S8). By associating a method list in which an MRM transition for phospholipid class determination is recorded for each compound of phospholipid classes with a method list in which an MRM transition for fatty acid composition determination is recorded for each phospholipid compound, it is possible to promptly select MRM transitions for fatty acid composition determination that correspond to compounds of the detected phospholipid classes, and to easily create an analysis method for the second-time analysis.

A method is provided for analyzing a sample and identifying species using chromatography and spectrometry. Possible candidate species to be used in a regression analysis are selected for consideration based on their retention indices in a chromatography column and peak locations in an infrared spectrum. By using such a selection process, the number of combinations of species to be used in the regression analysis can be significantly reduced. The species and respective concentrations in the sample are identified by using an iterative process with regression analysis and minimizing least squares errors between a sample spectrum and a computed spectrum associated with selected candidate species.

A method of performing tandem mass spectrometry includes supplying a sample to a chromatography column, directing components included in the sample and eluting from the chromatography column to a mass spectrometer, acquiring a series of mass spectra including intensity values of ions produced from the components as a function of m/z of the ions, extracting, from the series of mass spectra, a plurality of detection points representing intensity as a function of time for a selected m/z, estimating, based on the plurality of detection points extracted from the series of mass spectra, a relative position of a selected detection point included in the plurality of detection points, and performing, at the mass spectrometer and based on the estimated relative position, a dependent acquisition for the selected m/z. The relative position of the selected detection point represents a position of the selected detection point relative to an expected reference point.

A method of mass spectrometry is disclosed comprising: a) separating first ions or components of an analyte sample according to a physicochemical property other than ion mobility; b) separating said first ions or second ions formed from said components according to ion mobility; c) detecting the intensities of said first ions, or detecting the intensities of second ions formed from said components, or detecting the intensities of ions derived from said first or second ions; wherein the intensity of the ions detected at any given time is recorded together with an associated value of said physicochemical property and an associated value of said ion mobility so as to obtain spectral data; d) examining the intensities of the spectral data as a function of said ion mobility so as to detect an intensity peak in said spectral data, determining a discrete value of ion mobility for said peak, and defining a window of values of ion mobility that encompasses said discrete value; and e) filtering said spectral data so as to include only spectral data that has been associated with values of ion mobility that are within said window of ion mobility values.

A peak extraction method for extracting a true peak from a measured waveform, including acquiring a second derivative waveform; extracting a provisional peak on the basis of a maximum value and/or a minimum value of the second derivative waveform; determining the peak width of the provisional peak on the basis of a model peak function; computing, on the basis of the model peak function, a theoretical value for the height of the provisional peak using two points corresponding to the two ends of the peak width; computing, based on the second derivative waveform, an index value for a variation in the noise on the measured waveform; and computing an S/N ratio, which is a ratio of the peak height theoretical value and the index value, and extracting the provisional peak that is equal to or greater than a preset value as the true peak.

An exemplary chromatographic alignment system accesses a target file including data representative of a plurality of chromatographic features detected from a first sample and a reference file including data representative of a plurality of chromatographic features detected from a second sample. The system identifies, based on the target and reference files, a distinct retention time offset value for each chromatographic feature included in a first subset of the plurality of chromatographic features detected from the first sample. The system determines, based on the identified distinct retention time offset values for the chromatographic features included in the first subset and on a machine learning model, a distinct predicted retention time offset value for each chromatographic feature included in a second subset of the plurality of chromatographic features detected from the first sample. The system assigns the distinct predicted retention time offset value for each chromatographic feature included in the second subset.

Methods and systems for determining whether a base oil for use in drilling muds will be compatible with cement during subsequent cementing operations include: providing a drilling fluid that includes a base oil; using the drilling fluid to drill at least a portion of a wellbore penetrating at least a portion of a subterranean formation; measuring a compositional characteristic of the base oil using one or more analytical tests; determining whether the base oil is a compatible base oil or an incompatible base oil based at least in part on the compositional characteristic of the base oil; injecting an amount of spacer fluid into the wellbore, wherein the amount of spacer fluid is selected based on the determination of whether the base oil is a compatible base oil or an incompatible base oil; and injecting the one or more cementing or completion fluids into the wellbore.

An automated method of monitoring a state of an analyzer is provided including a mass spectrometer (MS) with an electrospray ionization (ESI) source coupled to a liquid chromatography (LC) stream, including monitoring an electrospray ionization current of the ESI source and identifying a condition of multiple conditions of the analyzer based on the monitored ionization current of the ESI source, one of the conditions being a presence of a dead volume in a liquid chromatography stream of the analyzer downstream of an LC column of the LC stream.

A data processing device that processes three-dimensional data having time, intensity, and wavelength collected from a sample serving as a measurement target includes: a chromatogram generator configured to generate a chromatogram from the three-dimensional data; a target peak determiner configured to determine a target peak from peaks appearing on the chromatogram; a time point specifier configured to specify a time point at which the size of a spectrum matches the size of a reference spectrum from a time range during which the target peak appears in the three-dimensional data; and a target spectrum generator configured to extract data at the time point from the three-dimensional data, thereby generating a spectrum at the time point. With this configuration, a spectrum that is not affected by distortion, saturation, or noise can be readily and reliably obtained from the three-dimensional data obtained through sample analysis.