The charge reduction rate for multiply charged polymer ions via ion-ion recombination at atmospheric pressure

Evaluation of Hydrogen-Deuterium Exchange during Transient Vapor Binding of MeOD with Model Peptide Systems Angiotensin II and Bradykinin

The advancement of hybrid mass spectrometric tools as an indirect probe of molecular structure and dynamics relies heavily upon a clear understanding between gas-phase ion reactivity and ion structural characteristics. This work provides new insights into gas-phase ion-neutral reactions of the model peptides (i.e., angiotensin II and bradykinin) on a per-residue basis by integrating hydrogen/deuterium exchange, ion mobility, tandem mass spectrometry, selective vapor binding, and molecular dynamics simulations. By comparing fragmentation patterns with simulated probabilities of vapor uptake, a clear link between gas-phase hydrogen/deuterium exchange and the probabilities of localized vapor association is established. The observed molecular dynamics trends related to the sites and duration of vapor binding track closely with experimental observation. Additionally, the influence of additional charges and structural characteristics on exchange kinetics and ion-neutral cluster formation is examined. These data provide a foundation for the analysis of solvation dynamics of larger, native-like conformations of proteins in the gas phase.

A neural network parametrized coagulation rate model for <3 nm titanium dioxide nanoclusters

Coagulation is a key factor governing the size distribution of nanoclusters during the high temperature synthesis of metal oxide nanomaterials. Population balance models are strongly influenced by the coagulation rate coefficient utilized. Although simplified coagulation models are often invoked, the coagulation process, particularly for nanoscale particles, is complex, affected by the coagulating nanocluster sizes, the surrounding temperature, and potential interactions. Toward developing improved models of nanocluster and nanoparticle growth, we have developed a neural network (NN) model to describe titanium dioxide (TiO₂) nanocluster coagulation rate coefficients, trained with molecular dynamics (MD) trajectory calculations. Specifically, we first calculated TiO₂ nanocluster coagulation probabilities via MD trajectory calculations varying the nanocluster diameters from 0.6 to 3.0 nm, initial relative velocity from 20 to 700 m s^-1, and impact parameter from 0.0 to 8.0 nm. Calculations consider dipole-dipole interactions, dispersion interactions, and short-range repulsive interactions. We trained a NN model to predict whether a given set of nanocluster diameters, impact parameter, and initial velocity would lead to the outcome of coagulation. The accuracy between the predicted outcomes from the NN model and the MD trajectory calculation results is >95%. We subsequently utilized both the NN model and MD trajectory calculations to examine coagulation rate coefficients at 300 and 1000 K. The NN model predictions are largely within the range 0.65-1.54 of MD predictions, and importantly NN predictions capture the local minimum coagulation rate coefficients observed in MD trajectory calculations. The NN model can be directly implemented in population balances of TiO₂ formation.

Condensable Vapor Sorption by Low Charge State Protein Ions

Measurement of the gas-phase ion mobility of proteins provides a means to quantitatively assess the relative sizes of charged proteins. However, protein ion mobility measurements are typically singular values. Here, we apply tandem mobility analysis to low charge state protein ions (+1 and +2 ions) introduced into the gas phase by nanodroplet nebulization. We first determine protein ion mobilities in dry air and subsequently examine shifts in mobilities brought about by the clustering of vapor molecules. Tandem mobility analysis yields mobility-vapor concentration curves for each protein ion, expanding the information obtained from mobility analysis. This experimental procedure and analysis is extended to bovine serum albumin, transferrin, immunoglobulin G, and apoferritin with water, 1-butanol, and nonane. All protein ions appear to adsorb vapor molecules, with mobility "diameter" shifts of up to 6-7% at conditions just below vapor saturation. We parametrize results using κ-Köhler theory, where the term κ quantifies the extent of uptake beyond Köhler model expectations. For 1-butanol and nonane, κ decreases with increasing protein ion size, while it increases with increasing protein ion size for water. For the systems probed, the extent of mobility shift for the organic vapors is unaffected by the nebulized solution pH, while shifts with water are sensitive to pH.