H. J. Lewandowski

This paper reports on the use of a convolutional neural network (CNN) methodology to analyse fluorescence images of calcium-ion Coulomb crystals in the gas phase. A transfer-learning approach is adopted using the publicly available RESNET50 model. It is demonstrated that by training the neural network on around 500,000 simulated images, we are able to determine ion-numbers not only for a verification set of 100,000 simulated images, but also for experimental calcium-ion images from two different laboratories using a wide range of ion-trap parameters. Absolute ion numbers in the crystal were determined for the experimental data with a percentage error of approximately 10%. This analysis can be performed in a few seconds for an individual crystal image, and therefore the method enables the objective, and efficient, analysis of such images in real time, thereby facilitating time-dependent kinetic measurements on ion-molecule chemistry. The approach adopted also shows promising performance for identifying Ca+ ion numbers in images of mixed-species crystals.

The reaction of the acetylene cation (C2H2+) with acetonitrile (CH3CN) is measured in a linear Paul ion trap coupled to a time-of-flight mass spectrometer. C2H2+ and CH3CN are both noted for their astrochemical abundance and predicted relevance for understanding prebiotic chemistry. The observed primary products are c-C3H3+, C3H4+ and C2NH3+. The latter two products react with excess CH3CN to form the secondary product C2NH4+, protonated acetonitrile. The molecular formula of these ionic products can be verified with the aid of isotope substitution via deuteration of the reactants. Primary product reaction pathways and thermodynamics are investigated with quantum chemical calculations and demonstrate exothermic pathways to two isomers of C2NH3+, two isomers of C3H4+, and the cyclopropenyl cation c-C3H3+. This study deepens our understanding of the dynamics and products of a pertinent ion-molecule reaction between two astrochemically abundant molecules in conditions that mimic those of the interstellar medium.

Trapping cold, chemically important molecules with electromagnetic fields is a useful technique to study small molecules and their interactions. Traps provide long interaction times that are needed to precisely examine these low density molecular samples. However, the trapping fields lead to non-uniform molecular density distributions in these systems. Therefore, it is important to be able to experimentally characterize the spatial density distribution in the trap. Ionizing molecules in different locations in the trap using resonance enhanced multiphoton ionization (REMPI) and detecting the resulting ions can be used to probe the density distribution even with the low density present in these experiments because of the extremely high efficiency of detection. Until recently, one of the most chemically important molecules, OH, did not have a convenient REMPI scheme. Here, we use a newly developed 1 + 1' REMPI scheme to detect trapped cold OH molecules. We use this capability to measure trap dynamics of the central density of the cloud and the density distribution. These types of measurements can be used to optimize loading of molecules into traps, as well as to help characterize the energy distribution, which is critical knowledge for interpreting molecular collision experiments.