Latent-to-sensible heat conversion kinetics during nanoparticle coalescence.

Coagulational growth in an aerosol is a multistep process; first particles collide, and then they coalesce with one another. Coalescence kinetics have been investigated in numerous prior studies, largely through atomistic simulations of nanoclusters (102-104 atoms). However, with a few exceptions, they have either assumed the process is completely isothermal or is a constant energy process. During coalescence, there is the formation of new bonds, decreasing potential energy, and correspondingly increasing internal kinetic (thermal) energy. Internal kinetic energy evolution is dependent not only on coalescence kinetics but also on heat transfer to the surrounding gas. Here, we develop and test a model of internal kinetic energy evolution in collisionally formed nanoclusters in the presence of a background gas. We find that internal kinetic energy dynamics hinge upon a power law relationship describing latent-to-sensible heat release as well as a modified thermal accommodation coefficient. The model is tested against atomistic models of 1.5-3.0 nm embedded-atom gold nanocluster sintering in argon and helium environments. The model results are in excellent agreement with the simulation results for all tested conditions. Results show that nanocluster effective temperatures can increase by hundreds of Kelvin due to coalescence, but that the rise and re-equilibration of the internal kinetic energy is strongly dependent on the background gas environment. Interestingly, internal kinetic energy change kinetics are also found to be distinct from surface area change kinetics, suggesting that modeling coalescence heat release solely due to surface area change is inaccurate.

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.

Ion-neutral clustering alters gas-phase hydrogen-deuterium exchange rates.

The rates and mechanisms of chemical reactions that occur at a phase boundary often differ considerably from chemical behavior in bulk solution, but remain difficult to quantify. Ion-neutral interactions are one such class of chemical reactions whose behavior during the nascent stages of solvation differs from bulk solution while occupying critical roles in aerosol formation, atmospheric chemistry, and gas-phase ion separations. Through a gas-phase ion separation technique utilizing a counter-current flow of deuterated vapor, we quantify the degree of hydrogen-deuterium exchange (HDX) and ion-neutral clustering on a series of model chemical systems (i.e. amino acids). By simultaneously quantifying the degree of vapor association and HDX, the effects of cluster formation on reaction kinetics are realized. These results imply that cluster formation cannot be ignored when modeling complex nucleation processes and biopolymer structural dynamics.

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

The charge reduction of multiply charged macromolecular ions via recombination with small ions in the gas phase is commonly employed to modulate the charge on macromolecules prior to mass spectrometric and mobility analyses. We employ a recently developed continuum-Molecular Dynamics (MD) calculation approach to determine the recombination rate coefficient of multiply charged (1 to 7 excess positive charged) polyethylene glycol ions (mass of 4600 Da) with smaller singly charged anions, modeled as NO2- ions. The continuum-MD approach accounts explicitly for the influence of the background gas on the recombination process, accounts explicitly for ion translational, vibrational, and rotational motion, and enables recombination rate coefficient calculation in nitrogen near atmospheric pressure, wherein neither low pressure nor high pressure recombination theories are strictly applicable. Continuum-MD simulations yield recombination rate coefficients near 3.9 × 10-14 m3 s-1 for singly charged ions, increasing to 3.0 × 10-11 m3 s-1 for the +7 ion. Pre-existing collision rate coefficient expressions for rigid ions are found to be within a factor of 2-5 of calculations for all charge states, but their use requires knowledge of an appropriate collision distance, which is not well-defined for flexible polymer ions. Continuum-MD-inferred rate coefficients are incorporated into a model of charge reduction, and the charge state distribution versus anion concentration determined with it is compared to charge reduction measurements made via atmospheric pressure differential mobility analysis. Good agreement is observed between simulations and experiments; although results are extremely sensitive to the recombination rate coefficients, experimental results are bound by models utilizing rates within a factor of 2 (0.5-2.0×) of the continuum-MD rates.

Calculation of the ion-ion recombination rate coefficient via a hybrid continuum-molecular dynamics approach.

Accurate calculation of the ion-ion recombination rate coefficient has been of long-standing interest as it controls the ion concentration in gas phase systems and in aerosols. We describe the development of a hybrid continuum-molecular dynamics (MD) approach to determine the ion-ion recombination rate coefficient. This approach is based on the limiting sphere method classically used for transition regime collision phenomena in aerosols. When ions are sufficiently far from one another, the ion-ion relative motion is described by diffusion equations, while within a critical distance, MD simulations are used to model ion-ion motion. MD simulations are parameterized using the Assisted Model Building with Energy Refinement force-field as well as by considering partial charges on atoms. Ion-neutral gas collisions are modeled in two mutually exclusive cubic domains composed of 103 gas atoms each, which remain centered on the recombining ions throughout calculations. Example calculations are reported for NH4 + recombination with NO2 - in He, across a pressure range from 10 kPa to 10 000 kPa. Excellent agreement is found in comparison with calculations to literature values for the 100 kPa recombination rate coefficient (1.0 × 10-12 m3 s-1) in He. We also recover the experimentally observed increase in the recombination rate coefficient with pressure at sub-atmospheric pressures, and the observed decrease in the recombination rate coefficient in the high pressure continuum limit. We additionally find that non-dimensionalized forms of rate coefficients are consistent with recently developed equations for the dimensionless charged particle-ion collision rate coefficient based on Langevin dynamics simulations.