A method of analysis using mass spectrometry and/or ion mobility spectrometry is disclosed. The method comprises: using a first device to generate smoke, aerosol or vapour from a target comprising or consisting of a microbial population; mass analysing and/or ion mobility analysing said smoke, aerosol or vapour, or ions derived therefrom, in order to obtain spectrometric data; and analysing said spectrometric data in order to analyse said microbial population.

A method of analysis using mass spectrometry and/or ion mobility spectrometry is disclosed. The method comprises: using a first device to generate smoke, aerosol or vapour from a target comprising or consisting of a microbial population; mass analysing and/or ion mobility analysing said smoke, aerosol or vapour, or ions derived therefrom, in order to obtain spectrometric data; and analysing said spectrometric data in order to analyse said microbial population.

A method of analysis using mass and/or ion mobility spectrometry or ion mobility spectrometry is disclosed comprising: using a first device to generate aerosol, smoke or vapour from one or more regions of a first target of biological material; and mass and/or ion mobility analysing and/or ion mobility analysing said aerosol, smoke, or vapour, or ions derived therefrom so as to obtain first spectrometric data. The method may use an ambient ionisation method.

A method of analysis using mass and/or ion mobility spectrometry or ion mobility spectrometry is disclosed comprising: using a first device to generate aerosol, smoke or vapour from one or more regions of a first target of biological material; and mass and/or ion mobility analysing and/or ion mobility analysing said aerosol, smoke, or vapour, or ions derived therefrom so as to obtain first spectrometric data. The method may use an ambient ionisation method.

An additive manufacturing system comprising at least one electronic nose (e-nose) is provided. The e-nose may comprise a housing and gas sensors. The housing may have an air channel. The active sensor portion of the sensors are positioned in the air channel. The housing may be mounted to an extruder head of an additive manufacturing device. The system may also comprise a processor. The processor may determine whether there is an abnormality in an additive manufacturing process based on one or more combinations of outputs from the gas sensors received during the additive manufacturing process input into a deployed machine learning model; and generate a report for the additive manufacturing process containing the determination.

A system for determining an age and/or quality of food or beverage based on one or more combinations of outputs from gas sensors input into a deployed machine learning model is provided. The system may comprise an electronic nose which may comprise a housing and the gas sensors. The housing may have an air channel. Each sensor has its active sensor portion in the air channel. A system for predicting one or more natural language descriptors associated with aromas of an item based on one or more outputs of the gas sensors and calculated one or more ratios input into a logistic regression model is also provided.

A system for predicting one or more analytes based on outputs from thin film gas sensors is provided. The system may comprise an electronic nose (e-nose). The e-nose may comprise the gas sensors and a first processor. The system may further comprise a second processor. The second processor may be configured to receive the output from each of the gas sensors, evaluate a prediction accuracy using an evaluation parameter of each of a plurality of models which are trained and tested and select a model from among the plurality of models to deploy based on a comparison of the evaluation parameter for each of the plurality of models and use the same. The second processor may also receive, an output of each of the gas sensors caused by unknown one or more analytes; and predict, using the deployed model, the one or more analytes that causes the output.

An integrated multifunctional environmental characterization system (IMECS) is provided. The IMECS may comprises a memory, one or more interfaces and a processor. The processor may be configured to predict an environment condition adjacent to a thin film using one or more machine learned models from one or more measured properties of the thin film received via the one or more interfaces; and/or predict values for one or more properties of the thin film using the one or more machine learned models from an environmental condition received via one of the one or more interfaces; and display the predicted environment condition and/or the predicted one or more properties. The processor may also adjust the acquisition parameters used to acquire values of one or more properties of the thin film from received acquisition parameters via a user interface based on measured values for the same properties.

An integrated multifunctional environmental characterization system (IMECS) is provided. The IMECS may comprises a memory, one or more interfaces and a processor. The processor may be configured to predict an environment condition adjacent to a thin film using one or more machine learned models from one or more measured properties of the thin film received via the one or more interfaces; and/or predict values for one or more properties of the thin film using the one or more machine learned models from an environmental condition received via one of the one or more interfaces; and display the predicted environment condition and/or the predicted one or more properties. The processor may also adjust the acquisition parameters used to acquire values of one or more properties of the thin film from received acquisition parameters via a user interface based on measured values for the same properties.

A method of analysis using mass spectrometry and/or ion mobility spectrometry is disclosed. The method comprises: using a first device to generate smoke, aerosol or vapour from a target comprising or consisting of a microbial population; mass analysing and/or ion mobility analysing said smoke, aerosol or vapour, or ions derived therefrom, in order to obtain spectrometric data; and analysing said spectrometric data in order to analyse said microbial population.