A filter bleeding measurement arrangement for the pressure-neutral determination of the fuel vapor emissions of a fuel vapor filter includes a flame ionization detector with a gas inlet and a gas outlet, and a measurement adapter including a measurement connection for connection of the fuel vapor filter, a separate detector connection for connection of the flame ionization detector, and an air inlet fluidically connected to an external atmosphere.

A mass analyzer includes a main substrate, an upper substrate adhered to the main substrate, and a lower substrate. A mass analysis room (cavity) is formed in the main substrate and penetrates from an upper surface of the first main substrate to a lower surface of the first main substrate. A vertical direction (Z direction) to the main substrate by the upper substrate, both sides of the lower substrate, a travelling direction (X direction) of charged particles and a right angle to the Z direction by the main substrate, and both sides of a right-angled direction (Y to Z direction) and the X direction by a side surface of the main substrate are surrounded. A central hole is open in the side plate of the main substrate that the charged particles enter. The charged particles enter the mass analysis room through the central hole formed in the first main substrate.

A spray area in which a large number of droplets of a liquid sample sprayed from a spray nozzle is separated from the tip of a needle electrode for corona discharge by a sufficiently large distance, with a grid electrode facing the needle electrode placed in between. Ring electrodes for creating an electric field which drives primary ions that should react with the sample and generate sample-derived ions are provided within an ion chamber between the grid electrode and the spray area. Primary ions generated by corona discharge within the space between the needle electrode and the grid electrode pass through the opening of the grid electrode, reach the spray area under the effect of the electric field, and ionize sample components. Since the droplets are prevented from adhering to the needle electrode, the corona discharge is maintained in a stable state.

A method of mud logging is disclosed which the chemical constituents and concentrations of formation fluid are calculated based on pulse power plasma parameters and the constituent species and concentrations of drilling mud, including reaction products, upon which the pulse power plasma has acted. Based on correlation between pulse power plasma parameters, including drilling parameters, drilling can be optimized for identified formation and formation fluid species. An offset between the chemical makeup of the drilling mud exposed to pules power plasma and the chemical makeup of formation fluid is calculated. Based on the calculated offset, pulse power plasma drilling can be controlled as a function of drilling mud concentration including in other wellbores in the formation or field.

A method of mud logging is disclosed which the chemical constituents and concentrations of formation fluid are calculated based on pulse power plasma parameters and the constituent species and concentrations of drilling mud, including reaction products, upon which the pulse power plasma has acted. Based on correlation between pulse power plasma parameters, including drilling parameters, drilling can be optimized for identified formation and formation fluid species. An offset between the chemical makeup of the drilling mud exposed to pules power plasma and the chemical makeup of formation fluid is calculated. Based on the calculated offset, pulse power plasma drilling can be controlled as a function of drilling mud concentration including in other wellbores in the formation or field.

An ion analyzer including: a base member fixed to a ion outflow port and having a cylindrical concave part; a cylindrical first conductive member accommodated in the concave part; a first ion flow controller fixed to an exposed end of the first conductive member; a cylindrical insulating member inserted into the first conductive member; a rod-shaped second conductive member inserted into the insulating member; a second ion flow controller being fixed to an exposed end of the second conductive member; a first power feeding unit that, when accommodated in the concave part, comes into contact with the first conductive member; and a second power feeding unit that, when accommodated in the concave part, comes into contact with the second conductive member when the first conductive member accommodates the second conductive member and the insulating member.

A plurality of known compounds with known CCS values is analyzed using a DMS device. The DMS device determines how the intensities of their transmitted ions vary with different separation voltages (SVs) and compensation voltages (CVs). A machine learning algorithm builds a data model from the known m/z value, known CCS value, and measured pairs of CV and SV values that provide optimal transmission through the DMS device for each of the known compounds. An unknown compound with an unknown CCS value is then analyzed. The DMS device determines how the intensity of its ions varies with the same different SVs and CVs. Finally, the machine learning algorithm predicts the CCS value of the unknown compound from the data model, the known m/z of the unknown compound, and the measured pairs of CV and SV values that provide optimal transmission through the DMS device for the unknown compound.

A plurality of known compounds with known CCS values is analyzed using a DMS device. The DMS device determines how the intensities of their transmitted ions vary with different separation voltages (SVs) and compensation voltages (CVs). A machine learning algorithm builds a data model from the known m/z value, known CCS value, and measured pairs of CV and SV values that provide optimal transmission through the DMS device for each of the known compounds. An unknown compound with an unknown CCS value is then analyzed. The DMS device determines how the intensity of its ions varies with the same different SVs and CVs. Finally, the machine learning algorithm predicts the CCS value of the unknown compound from the data model, the known m/z of the unknown compound, and the measured pairs of CV and SV values that provide optimal transmission through the DMS device for the unknown compound.

A system on a chip (SoC) for smoke detection includes power regulator circuits coupled to respective pins and analog sensor amplifier circuits that are each coupled to a respective pin of the pins coupled to the power regulator circuits. A first analog sensor amplifier circuit of the analog sensor amplifier circuits has a photoelectric amplifier circuit, a first LED driver and a second LED driver. The SoC also has a digital core that includes a digital logic circuit, register bits, and an MCU communication circuit. The MCU communication circuit is coupled to a data pin, the register bits are coupled to control or modify operation of the power regulator circuits and the analog sensor amplifier circuits, and the register bits are operable to be written to by an MCU.

A system on a chip (SoC) for smoke detection includes power regulator circuits coupled to respective pins and analog sensor amplifier circuits that are each coupled to a respective pin of the pins coupled to the power regulator circuits. A first analog sensor amplifier circuit of the analog sensor amplifier circuits has a photoelectric amplifier circuit, a first LED driver and a second LED driver. The SoC also has a digital core that includes a digital logic circuit, register bits, and an MCU communication circuit. The MCU communication circuit is coupled to a data pin, the register bits are coupled to control or modify operation of the power regulator circuits and the analog sensor amplifier circuits, and the register bits are operable to be written to by an MCU.