RATIONALE: Many chemical processes operate at unsteady state and require a rapid mass analysis of transients with high resolution. An atmospheric pressure interface multi-reflection time-of-flight mass spectrometer (API-MRTOF-MS) has the potential to be a powerful process analytical tool. METHODS: The ion flight path of the API-MRTOF-MS was extended from meters to over one kilometer, and the mass resolution was increased to an ultra-high level. Furthermore, the mass analysis could be done at around ten milliseconds due to the rapidity of TOFMS. The mass analyzer reflects ions via electrostatic mirrors and directs them along a folded flight path, significantly increasing flight distances and theoretically with no upper limit. The powerful API, equipped with two quadrupoles, makes the API-MRTOF-MS suitable for complex mass spectrometry methods with alternative ion selection schemes. RESULTS: A mass resolution of 116,050 for Cs + ions is achieved within a total time-of-flight of only 18 ms. An ion transmission efficiency of over 50% was achieved after 600 cycles. CONCLUSIONS: The performance of the API-MRTOF-MS demonstrates that it is exceedingly suitable for high-resolution process analysis, particularly for transient process analysis, due to its fast analysis speed and high-selectivity.

RATIONALE: The multi-reflection time-of-flight mass spectrograph (MRTOF-MS) is a complex nonlinear system with dozens of variables that are impossible to determine in theory. Numerical analysis is the only method to determine a solution. Therefore, a numerical simulation is applied with a modified Nelder–Mead simplex (MNMS) algorithm for optimizing voltage configurations. METHODS: Ion trajectories for injection and confinement are simulated using the software SIMION 8.1. The goal of optimization is to find a more suitable configuration for the electric field. This task becomes more challenging as the number of variables, the complexity of the objective function, and the accuracy of the variable intervals increase. A simplex search algorithm was used to perform the optimization process. We modified the searching algorithm by incorporating a variable transformation to ensure that the variables have smooth boundaries. Additionally, we introduced a dedicated benchmark to facilitate global searches. RESULTS: By iteratively using the MNMS algorithm, a total of eight electrodes have been optimized, resulting in a smaller beam size and more efficient ion transport. CONCLUSIONS: The MNMS algorithm is effectively for optimizing nonlinear MRTOF-MS system. It improves the adaptability and globality of the original algorithm, making it applicable for the numerical analysis of complex mass spectrometry systems and problems in engineering.