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The impact of temperature and charge on the conformation of tryptamine (Tryp) is examined in the gas phase by infrared laser-vibrational predissociation spectroscopy in the 2800-3800 cm(-1) region. Previous studies of neutral Tryp(H(2)O)(n) clusters showed preferential stabilization of specific tryptamine conformers through hydrogen bonding. When complexed with the biologically significant potassium ion, the only conformers found to form under these experimental conditions are built on hitherto unobserved neutral Tryp conformers. The electrostatic interaction between K(+), the tryptamine NH(2) lone pair, and the indole ring in K(+)(Tryp) favors the formation of these new conformers. The observed K(+)(Tryp)(H(2)O) conformers vary significantly from the previously reported neutral Tryp(H(2)O) structure. Using the argon tagging method, we show how variations in temperature impact the observed infrared spectra, demonstrating that different conformers are populated under the different experimental conditions. In addition, the presence of a high-energy conformer of K(+)(Tryp)(H(2)O), trapped by the argon evaporative cooling process, was identified. Exploring the conformational landscape of hydrated cluster ions bearing flexible biomolecules is now possible.

Infrared photodissociation spectra of M(+)(tryptamine)(H(2)O)(0-3)Ar(0-1) (M = Na, K) are presented here to demonstrate the role of charge and temperature in directing the conformation of tryptamine, a derivative of the amino acid tryptophan. All of the cluster ions discussed here are built from the two high-energy tryptamine conformers that have never been previously observed in neutral gas-phase studies. The Na(+) or K(+) provides a positive charge that stabilizes the Gpy(in) and Gph(in) conformers. DFT calculations are used to identify stable conformers and their corresponding harmonic vibrational frequencies in the CH, NH, and OH stretching regions, which aid in the interpretation of the experimental spectra. In some cases this interpretation is fairly straightforward by using the global minimum-energy structures. The more complex spectra associated with the argonated cluster ions suggest that high-energy isomers, trapped during the cluster ion formation process, are also present.

IR-PD vibrational spectroscopy and DFT-based molecular dynamics simulations are combined in order to unravel the structures of M(+)(APE)(H2O)0-1 ionic clusters (M = Na, K), where APE (2-amino-1-phenyl ethanol) is commonly used as an analogue for the noradrenaline neurotransmitter. The strength of the synergy between experiments and simulations presented here is that DFT-MD provides anharmonic vibrational spectra that unambiguously help assign the ionic clusters structures. Depending on the interacting cation, we have found that the lowest energy conformers of K(+)(APE)(H2O)0-1 clusters are formed, while the lowest energy conformers of Na(+)(APE)(H2O)0-1 clusters can only be observed through water loss channel (i.e. without argon tagged to the clusters). Trapping of higher energy conformers is observed when the argon loss channel is recorded in the experiment. This has been rationalized by transition state energies. The dynamical anharmonic vibrational spectra unambiguously provide the prominent OH stretch due to the OH···NH2 H-bond, within 10 cm(-1) of the experiment, hence reproducing the 240-300 cm(-1) red-shift (depending on the interacting cation) from bare neutral APE. When this H-bond is not present, the dynamical anharmonic spectra provide the water O-H stretches as well as the rotational motion of the water molecule at finite temperature, as observed in the experiment.

As data science and instrumentation become key practices in common careers ranging from medicine to agriscience, chemistry as a core introductory course must introduce such topics to students early and at an accessible level. Advanced data acquisition and data science generally require expensive precision instrumentation and massive computation, often out-of-reach even for upper-level undergraduate laboratory courses. At the same time, a new generation of affordable do-it-yourself instruments presents an opportunity for incorporation of curricula focused on instrument design and computation into freshman-level courses. We present a new lab for integration into existing courses that starts with hands-on spectrometer building, moves to data collection, and finally introduces an advanced data science technique, singular value decomposition, at an appropriate level with minimal computing requirements. The hardware and software used are modular and inexpensive. The lab was tested in three community college general chemistry sections over two semesters. Previously, students taking these courses did not typically see advanced quantitative chemistry curricula before deciding whether to pursue a bachelor's degree. This lab allowed students to practice data collection and organization skills, use prewritten Jupyter notebooks that perform advanced data analysis, and gain presentation skills. A multiwave assessment completed by students highlights both successes and difficulties associated with incorporating multiple advanced topics involving instrument design, data collection, and analysis techniques in a single lab.