▎ 摘　　要

NOVELTY - Detecting and analyzing chemical compounds in a sample, comprises e.g. (1) subjecting the sample to chromatographic separation on a layered separating medium, (2) detecting chemical compounds in sample separated on layers of the separating medium with a detector, where the detector includes array of sensors printed on each layer of separating medium and generates data, the data includes string or array of measurement results from each sensor on each layer of separating medium, and the string or array of measurement results is an input for external memory, and (3) processing the data in external memory by applying machine-learning method on the measurement results to output a single bit whose value is '0' or '1', or array of bits, or array of integers, or array of complex numbers corresponds to an estimated frequency, voltage, sensor conductance, electrical resistance, time of chromatographic elution, or mass-to-charge ratio, thus providing information of compounds in the sample. USE - The method is useful for detecting and analyzing chemical compounds in a sample (claimed) for continuous monitoring of various volatile chemical/organic compounds released by human body to assess various diseases in early stage or monitoring the disease progression/remission during treatment completely non-invasively. ADVANTAGE - The method: adopts machine learning methods, which are shown to be the methods of choice when analyzing the spectrometry data, e.g. psychiatric genomics consortium (pGC) data, in a variety of scenarios and in a variety of applications, including real-time molecular analysis; can learn the spectroscopic and chromatographic models taking into account various kinetic and thermodynamic parameters and by that constitute an advantageous alternative to existing spectroscopic and chromatographic analytical methods; adopts layered medium together with the detectors in the volatile organic compounds (VOCs) sensing to utilize the unique time-space resolved geometry for effective semi-separation and instantaneous detection of various VOCs from a complex mixture in different instant of time; exhibits better estimation of complex VOC mixture than the existing measurements where sensor array is directly exposed to the mixture of VOCs; and is cost effective, robust, scalable, sustainable, wearable, highly reliable technological advancement and maturity. DETAILED DESCRIPTION - Detecting and analyzing chemical compounds in a sample, comprises (1) subjecting the sample to chromatographic separation on a layered separating medium, (2) detecting chemical compounds in the sample separated on the layers of the separating medium with a detector, where the detector includes array of sensors printed on each layer of the separating medium and generates data, the data includes string or array of measurement results from each sensor on each layer of the separating medium, and the string or array of the measurement results is an input for external memory, and (3) processing the data in the external memory by applying machine-learning method on the measurement results to output a single bit whose value is '0' or '1', or an array of bits, or an array of integers, or an array of complex numbers, where the single bit, or array of bits, or array of integers, or array of complex numbers corresponds to an estimated frequency, voltage, sensor conductance, electrical resistance, time of chromatographic elution, or mass-to-charge ratio, and to maximum availability or amplitude of the input, thus providing information on the presence and properties of the compounds in the sample. INDEPENDENT CLAIMS are also included for: (1) inkjet-printing of electronics and sensors on each layer of the layered separating medium, comprising applying inkjet-print grade graphene oxide heterostructures to the layers of the layered separating medium and reducing the graphene oxide heterostructures with dopamine to obtain reduced graphene oxide (rGO) heterostructures; (2) processing micro-gas chromatography data of sample containing compounds subjected to chromatographic separation on an origami or kirigami paper, comprising (i) subjecting the sample to chromatographic separation on the origami or kirigami paper and analysing the sample with the micro-gas chromatograph to generate string or array of measurements from each sensor on each layer of the origami or kirigami paper, where the string or array of the measurement results is an input for an external memory, and (ii) applying a machine-learning method on the measurement results in the external memory to output a single bit whose value is '0' or 1, or array of bits, or array of integers, or array of complex numbers, where the single bit, or array of bits, or array of integers, or array of complex numbers corresponds to an estimated frequency, voltage, sensor conductance, electrical resistance, time of chromatographic elution, or mass-to-charge ratio, and to maximum availability or amplitude of the input, thus providing information on the presence and properties of the compounds in the sample, and the data generated with micro-gas chromatograph includes an array of sensors inkjet-printed on each layer of the origami paper, and providing information on the presence and properties of the compounds in the sample; (3) detector for detection and analysis of chemical compounds in sample subjected to chromatographic separation on layered separating medium, comprising array of sensors printed on each layer of the layered separating medium, and providing information on the presence and properties of the compounds in the sample; and (4) system for detection and analysis of chemical compounds in sample subjected to chromatographic separation on layered separating medium, comprising (a) layered separating medium for chromatographic separation of the compounds contained in the sample and for providing physical support for embedded electronics and detector, (b) detector comprising array of sensors printed on each layer of the separating medium, and providing information on the presence and properties of the compounds in the sample, (c) embedded electronics printed on each layer of the separating medium, and (d) external memory.