Synthetic Cannabinoids are the most complex branch of designer drugs encountered in forensic chemistry. A screening method has been developed that can accurately identify the correct structural category of an unknown Synthetic Cannabinoid. Knowledge of this information is very important when no reference data or standards are available since certain sub-categories contain Schedule I Controlled Dangerous Substances. The Bridge portion of these molecules present a unique carbonyl band cluster within a small 200 wavenumber interval of the mid-infrared region that can only exist in vapor phase through GC/FTIR light-pipe technology or heated static vapor cell FTIR. This special relationship is not applicable to any other forms of solid phase vibrational spectroscopy (FTIR, RAMAN) including GC/FTIR solid-deposit techniques. The carbonyl frequency from the Bridge is used as the first step in the screening process which separates the entire forensically encountered class of Synthetic Cannabinoids into 35 sub-categories. Additional bands within the cluster from secondary functional groups, rotational isomerism, and fermi resonance add further refinement within these categories.

Techniques and apparatus for performing target compound detection processes are described. In one embodiment, for example, an apparatus may include at least one memory, and logic coupled to the at least one memory. The logic may be configured to implement a targeted compound detection process, for example, by receiving raw data from analysis of a sample via an analytical device, generating cumulative data from the raw data, receiving compound specification information associated with the sample, and determining quantified compound information via performing targeted compound detection based on the cumulative data and the compound specification information to determine. Other embodiments are described.

Disclosed is a chromatography system (100) comprising: plural modules (1-25) including at least one pump and a column valve unit (8) connectable to plural chromatography columns; and a controller (600), the controller being operable to control the or each pump and the column valve to perform different chromatographic processes, including chromatography employing just one column, as well as chromatography employing two or more columns by selective valve opening in said unit. The system includes a housing (110) into which the plural modules (1-25) are interchangeably mountable in apertures of one generally vertical face of housing, the modules are adapted for selective fluidic interconnection by tubing substantially at said one face such that in use the modules and tubing occupy a generally vertically extending volume to minimize the footprint of the system.

Techniques for real-time or substantially real-time peak detection are described. In one embodiment, for example, logic coupled to memory may be configured to receive data from at least one analytical instrument and perform processing or analysis on the received data. Moreover, the logic may be configured to determine, via one or more GPUs or CPUs (or both), one or more peaks based on the processing or the analysis of the received data and generate peak detection data based on the detected one or more peaks in real-time or substantially real-time. Other embodiments are described.

Methods for classification of hydrocarbon mixtures that include performing two-dimensional gas chromatography on a hydrocarbon mixture to obtain a chromatogram using a two-dimensional gas chromatograph equipped with a flame ionization detector, a reversed phase column configuration with a primary mid-polar or polar column and a secondary non-polar column, and a standard mixture. Classification is performed in which groups of hydrocarbons are identified and labeled based on peaks associated with the standard mixture, after which a quantification process is performed.

The present invention relates to a method for reconstructing events related to a process run in a bioprocess purification system comprising hardware configured to control the events related to the purification of a liquid containing a sample in the bioprocess purification system. The method comprising: recording hardware state S11 related to the process run; recording readings from sensors S12 related to the process run; and synchronizing hardware state S13 with readings from sensors to link the hardware state with the result from the process run. The present invention also related to a method for simulating future events related to a process run in a bioprocess purification system comprising hardware configured to control the events related to the purification of a liquid containing a sample in the bioprocess purification system. The events are controlled by a number of instructions executed consecutively and the method comprising: establishing a current state S21 of the process run; assessing an outcome S23 of each non-executed instructions based on information stored in a data storage medium; and predicting future events S24 based on the current state of the process run and the assessed outcome of the non-executed instructions.

A confirmation ion ratio allowable value calculation unit calculates a confirmation ion ratio allowable value when a target ion and confirmation ions are interchanged based on a preset confirmation ion ratio allowable value, and a peak identification processing unit identifies mass peaks of the target ion and the confirmation ions based on the confirmation ion ratio allowable value. A peak waveform processing unit calculates peak areas of the target ion and the confirmation ions, and a calibration curve creation unit creates calibration curves for quantification based on the target ion and the confirmation ions from a peak area of a target compound included in a standard sample. A quantitative value calculation unit obtains quantitative values while referring to a calibration curve corresponding to a peak area for a target compound included in an unknown sample. A quantitative analysis result display processing unit displays the quantitative values and chromatogram peak waveforms.

A non-transitory computer readable medium (CRM) storing computer readable program code for monitoring a state of a chromatography apparatus embodied therein that: receives one or more monitoring conditions that each include a determination condition for parameters related to measurements taken using the chromatography apparatus; and displays, in parallel and using a combination operational expression: a first conditional expression based on at least one of the monitoring conditions that make up a first combined conditional expression, wherein the first combined conditional expression is based on a first combined monitoring condition that combines all of the received monitoring conditions, and a second conditional expression based on at least one of the monitoring conditions associated with the first conditional expression.

Systems and methods for detecting, decoupling and quantifying unresolved signals in trace signal data in the presence of noise with no prior knowledge of the signal characteristics (e.g., signal peak location, intensity and width) of the unresolved signals. The systems and methods are useful for analyzing any trace data signals having one or multiple constituent signals, including overlapping constituent signals, and particularly useful for analyzing data signals which often contain an unknown number of constituent signals with varying signal characteristics, such as peak location, peak intensity and peak width, and varying resolutions and varying amounts of asymmetry. A general signal model function is assumed for each unknown, constituent signal in the trace signal data.

There is provided a method of analysis of mass spectrometry data comprising obtaining raw experimental mass spectrometry data; performing a first deconvolution of the raw experimental mass spectrometry data using a deconvolution algorithm, a wide first input parameter set, and a wide first output parameter set to obtain a deconvolved output; obtaining discrete peak data from the deconvolved output; simulating raw data for a first peak of the discrete peak data to obtain reference simulated raw discrete data; simulating raw data for a second peak of the discrete peak data to obtain suspect simulated raw discrete data; and determining whether the second peak is likely an artefact or indicative of a mass by comparing the suspect simulated raw discrete data with the reference simulated raw discrete data.