Gas chromatography is widely used to identify and quantify volatile organic compounds for applications ranging from environmental monitoring to homeland security. We investigate a new architecture for microfabricated gas chromatography systems that can significantly improve the range, speed, and efficiency of such systems. By using a cellular approach, it performs a partial separation of analytes even as the sampling is being performed. The subsequent separation step is then rapidly performed within each cell. The cells, each of which contains a preconcentrator and separation column, are arranged in progression of retentiveness. While accommodating a wide range of analytes, this progressive cellular architecture (PCA) also provides a pathway to improving energy efficiency and lifetime by reducing the need for heating the separation columns. As a proof of concept, a three-cell subsystem (PCA3mv) has been built; it incorporates a number of microfabricated components, including preconcentrators, separation columns, valves, connectors, and a carrier gas filter. The preconcentrator and separation column of each cell are monolithically implemented as a single chip that has a footprint of 1.8 × 5.2 cm². This subsystem also incorporates two manifold arrays of microfabricated valves, each of which has a footprint of 1.3 × 1.4 cm². Operated together with a commercial flame ionization detector, the subsystem has been tested against polar and nonpolar analytes (including alkanes, alcohols, aromatics, and phosphonate esters) over a molecular weight range of 32–212 g/mol and a vapor pressure range of 0.005–231 mmHg. The separations require an average column temperature of 63–68 °C within a duration of 12 min, and provide separation resolutions >2 for any two homologues that differ by one methyl group.

Microscale gas chromatography (μGC) systems are miniaturized instruments that typically incorporate one or several microfabricated fluidic elements; such systems are generally well suited for the automated sampling and analysis of gas-phase chemicals. Advanced μGC systems may incorporate more than 15 elements and operate these elements in different coordinated sequences to execute complex operations. In particular, the control software must manage the sampling and analysis operations of the μGC system in a time-sensitive manner; while operating multiple control loops, it must also manage error conditions, data acquisition, and user interactions when necessary. To address these challenges, this work describes the investigation of multithreaded control software and its evaluation with a representative μGC system. The μGC system is based on a progressive cellular architecture that uses multiple μGC cells to efficiently broaden the range of chemical analytes, with each cell incorporating multiple detectors. Implemented in Python language version 3.7.3 and executed by an embedded single-board computer, the control software enables the concurrent control of heaters, pumps, and valves while also gathering data from thermistors, pressure sensors, capacitive detectors, and photoionization detectors. A graphical user interface (UI) that operates on a laptop provides visualization of control parameters in real time. In experimental evaluations, the control software provided successful operation and readout for all the components, including eight sets of thermistors and heaters that form temperature feedback loops, two sets of pressure sensors and tunable gas pumps that form pressure head feedback loops, six capacitive detectors, three photoionization detectors, six valves, and an additional fixed-flow gas pump. A typical run analyzing 18 chemicals is presented. Although the operating system does not guarantee real-time operation, the relative standard deviations of the control loop timings were 1000 μGC runs that analyzed various chemical mixtures.

The rapid expansion of the Internet of Things (IoT) has increased the demand for self-powered wireless microsystems, with energy harvesters emerging as a key approach for powering distributed IoT nodes. Among energy harvesters, triboelectric nanogenerators (TENGs) are promising for harvesting mechanical energy; yet converting their high-voltage, low-current pulsed output into a stable, low-voltage supply for microsystems remains a key challenge. This work introduces a self-powered microsystem capable of continuous sensing and wireless communication, powered exclusively by a TENG harvesting low-frequency mechanical energy. System-level integration and optimization address the impedance mismatch between the energy harvester and the microsystem electronics, enabling a five-fold increase in harvested energy compared to conventional full-bridge rectification. The system cold-starts from 0 V to 4.2 V within 525 s and transitions to high-efficiency power management, providing ~110 μW under 5 Hz mechanical excitation. Enabled by low-power system operation, a self-powered wireless gas monitoring system is demonstrated. This system establishes a pathway toward battery-less IoT nodes and highlights the potential of TENG-powered microsystems for long-term, maintenance-free IoT applications.