Stability and Reactivity of Aromatic Radical Anions in Solution with Relevance to Birch Reduction.

We investigate the electronic structure of aromatic radical anions in the solution phase employing a combination of liquid-jet (LJ) photoelectron (PE) spectroscopy measurements and electronic structure calculations. By using recently developed protocols, we accurately determine the vertical ionization energies of valence electrons of both the solvent and the solute molecules. In particular, we first characterize the pure solvent of tetrahydrofuran (THF) by LJ-PE measurements in conjunction with ab initio molecular dynamics simulations and G0W0 calculations. Next, we determine the electronic structure of neutral naphthalene (Np) and benzophenone (Bp) as well as their radical anion counterparts Np- and Bp- in THF. Wherever feasible, we performed orbital assignments of the measured PE features of the aromatic radical anions, with comparisons to UV-vis absorption spectra of the corresponding neutral molecules being instrumental in rationalizing the assignments. Analysis of the electronic structure differences between the neutral species and their anionic counterparts provides understanding of the primarily electrostatic stabilization of the radical anions in solution. Finally, we obtain a very good agreement of the reduction potentials extracted from the present LJ-PES measurements of Np- and Bp- in THF with previous electrochemical data from cyclic voltammetry measurements. In this context, we discuss how the choice of solvent holds significant implications for optimizing conditions for the Birch reduction process, wherein aromatic radical anions play crucial roles as reactive intermediates.

Reducing the Cost of Neural Network Potential Generation for Reactive Molecular Systems.

Although machine learning potentials have recently had a substantial impact on molecular simulations, the construction of a robust training set can still become a limiting factor, especially due to the requirement of a reference ab initio simulation that covers all the relevant geometries of the system. Recognizing that this can be prohibitive for certain systems, we develop the method of transition tube sampling that mitigates the computational cost of training set and model generation. In this approach, we generate classical or quantum thermal geometries around a transition path describing a conformational change or a chemical reaction using only a sparse set of local normal mode expansions along this path and select from these geometries by an active learning protocol. This yields a training set with geometries that characterize the whole transition without the need for a costly reference trajectory. The performance of the method is evaluated on different molecular systems with the complexity of the potential energy landscape increasing from a single minimum to a double proton-transfer reaction with high barriers. Our results show that the method leads to training sets that give rise to models applicable in classical and path integral simulations alike that are on par with those based directly on ab initio calculations while providing the computational speedup we have come to expect from machine learning potentials.

Electronic structure of the solvated benzene radical anion.

The benzene radical anion is a molecular ion pertinent to several organic reactions, including the Birch reduction of benzene in liquid ammonia. The species exhibits a dynamic Jahn-Teller effect due to its open-shell nature and undergoes pseudorotation of its geometry. Here, we characterize the complex electronic structure of this condensed-phase system based on ab initio molecular dynamics simulations and GW calculations of the benzene radical anion solvated in liquid ammonia. Using detailed analysis of the molecular and electronic structure, we find that the spatial character of the excess electron of the solvated radical anion follows the underlying Jahn-Teller distortions of the molecular geometry. We decompose the electronic density of states to isolate the contribution of the solute and to examine the response of the solvent to its presence. Our findings show the correspondence between instantaneous molecular structure and spin density; provide important insights into the electronic stability of the species, revealing that it is, indeed, a bound state in the condensed phase; and offer electronic densities of states that aid in the interpretation of experimental photoelectron spectra.

Photoelectron Spectroscopy of Benzene in the Liquid Phase and Dissolved in Liquid Ammonia.

We report valence band photoelectron spectroscopy measurements of gas-phase and liquid-phase benzene as well as those of benzene dissolved in liquid ammonia, complemented by electronic structure calculations. The origins of the sizable gas-to-liquid-phase shifts in electron binding energies deduced from the benzene valence band spectral features are quantitatively characterized in terms of the Born-Haber solvation model. This model also allows to rationalize the observation of almost identical shifts in liquid ammonia and benzene despite the fact that the former solvent is polar while the latter is not. For neutral solutes like benzene, it is the electronic polarization response determined by the high frequency dielectric constant of the solvent, which is practically the same in the two liquids, that primarily determines the observed gas-to-liquid shifts.

Benzene Radical Anion Microsolvated in Ammonia Clusters: Modeling the Transition from an Unbound Resonance to a Bound Species.

The benzene radical anion, well-known in organic chemistry as the first intermediate in the Birch reduction of benzene in liquid ammonia, exhibits intriguing properties from the point of view of quantum chemistry. Notably, it has the character of a metastable shape resonance in the gas phase, while measurements in solution find it to be experimentally detectable and stable. In this light, our previous calculations performed in bulk liquid ammonia explicitly reveal that solvation leads to stabilization. Here, we focus on the transition of the benzene radical anion from an unstable gas-phase ion to a fully solvated bound species by explicit ionization calculations of the radical anion solvated in molecular clusters of increasing size. The computational cost of the largest systems is mitigated by combining density functional theory with auxiliary methods including effective fragment potentials or approximating the bulk by polarizable continuum models. Using this methodology, we obtain the cluster size dependence of the vertical binding energy of the benzene radical anion converging to the value of -2.3 eV at a modest computational cost.

Committee neural network potentials control generalization errors and enable active learning.

It is well known in the field of machine learning that committee models improve accuracy, provide generalization error estimates, and enable active learning strategies. In this work, we adapt these concepts to interatomic potentials based on artificial neural networks. Instead of a single model, multiple models that share the same atomic environment descriptors yield an average that outperforms its individual members as well as a measure of the generalization error in the form of the committee disagreement. We not only use this disagreement to identify the most relevant configurations to build up the model's training set in an active learning procedure but also monitor and bias it during simulations to control the generalization error. This facilitates the adaptive development of committee neural network potentials and their training sets while keeping the number of ab initio calculations to a minimum. To illustrate the benefits of this methodology, we apply it to the development of a committee model for water in the condensed phase. Starting from a single reference ab initio simulation, we use active learning to expand into new state points and to describe the quantum nature of the nuclei. The final model, trained on 814 reference calculations, yields excellent results under a range of conditions, from liquid water at ambient and elevated temperatures and pressures to different phases of ice, and the air-water interface-all including nuclear quantum effects. This approach to committee models will enable the systematic development of robust machine learning models for a broad range of systems.

Benzene Radical Anion in the Context of the Birch Reduction: When Solvation Is the Key.

The benzene radical anion is an important intermediate in the Birch reduction of benzene by solvated electrons in liquid ammonia. Beyond organic chemistry, it is an intriguing subject of spectroscopic and theoretical studies due to its rich structural and dynamical behavior. In the gas phase, the species appears as a metastable shape resonance, while in the condensed phase, it remains stable. Here, we approach the system by ab initio molecular dynamics in liquid ammonia and demonstrate that the inclusion of solvent is crucial and indeed leads to stability. Beyond the mere existence of the radical anion species, our simulations explore its condensed-phase behavior at the molecular level and offer new insights into its properties. These include the dynamic Jahn-Teller distortions, vibrational spectra in liquid ammonia, and the structure of the solvent shell, including the motif of a π-hydrogen bond between ammonia molecules and the aromatic ring.

Photoelectron spectra of alkali metal-ammonia microjets: From blue electrolyte to bronze metal.

Experimental studies of the electronic structure of excess electrons in liquids-archetypal quantum solutes-have been largely restricted to very dilute electron concentrations. We overcame this limitation by applying soft x-ray photoelectron spectroscopy to characterize excess electrons originating from steadily increasing amounts of alkali metals dissolved in refrigerated liquid ammonia microjets. As concentration rises, a narrow peak at ~2 electron volts, corresponding to vertical photodetachment of localized solvated electrons and dielectrons, transforms continuously into a band with a sharp Fermi edge accompanied by a plasmon peak, characteristic of delocalized metallic electrons. Through our experimental approach combined with ab initio calculations of localized electrons and dielectrons, we obtain a clear picture of the energetics and density of states of the ammoniated electrons over the gradual transition from dilute blue electrolytes to concentrated bronze metallic solutions.

Valence and Core-Level X-ray Photoelectron Spectroscopy of a Liquid Ammonia Microjet.

Photoelectron spectroscopy of microjets expanded into vacuum allows access to orbital energies for solute or solvent molecules in the liquid phase. Microjets of water, acetonitrile and alcohols have previously been studied; however, it has been unclear whether jets of low temperature molecular solvents could be realized. Here we demonstrate a stable 20 µm jet of liquid ammonia (-60 °C) in a vacuum, which we use to record both valence and core-level band photoelectron spectra using soft X-ray synchrotron radiation. Significant shifts from isolated ammonia in the gas-phase are observed, as is the liquid-phase photoelectron angular anisotropy. Comparisons with spectra of ammonia in clusters and the solid phase, as well as spectra for water in various phases potentially reveal how hydrogen bonding is reflected in the condensed phase electronic structure.

Can Arginine Inhibit Insulin Aggregation? A Combined Protein Crystallography, Capillary Electrophoresis, and Molecular Simulation Study.

The oligomeric state of the storage form of human insulin in the pancreas, which may be affected by several endogenous components of ß-cell storage granules such as arginine, is not known. Here, the effect of arginine on insulin oligomerization is investigated independently by protein crystallography, molecular dynamics simulations, and capillary electrophoresis. The combined results point to a strong effect of ionic strength on insulin assembly. Molecular simulations and electrophoretic measurements at low/mM salt concentrations show no significant effect of arginine on insulin aggregation. In contrast, crystallographic data at high/molar ionic strength indicate inhibition of insulin hexamerization by arginine due to its binding at the site relevant for intermolecular contacts, which was also observed in MD simulations. Our results thus bracket the in vivo situation in pancreatic ß-cell storage granules, where the ionic strength is estimated to be in the hundreds of millimolar to submolar range. The present findings add to a molecular understanding of in vivo insulin oligomerization and storage, with additional implications for insulin stability in arginine-rich injections.