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We show that in contrast to other models, AP-Net produces smooth, physically meaningful intermolecular potentials exhibiting correct asymptotic behavior. Initially trained on only a limited number of mostly hydrogen-bonded dimers, AP-Net makes accurate predictions across the chemically diverse S66x8 dataset, demonstrating significant transferability. On a test set including experimental hydrogen-bonded dimers, AP-Net predicts total interaction energies with a mean absolute error of 0.37 kcal mol-1, reducing errors by a factor of 2-5 across SAPT components from previous neural network potentials. The pairwise interaction energies of the model are physically interpretable, and an investigation of predicted electrostatic energies suggests that the model “learns” the physics of hydrogen-bonded interactions.We have presented a mechanism for electron attachment to solvated nucleobases using accurate wave-function based hybrid quantum/classical (QM/MM) simulations and uracil as a test case. The initial electron attached state is found to be localized in the bulk water, and this water-bound state acts as a doorway to the formation of the final nucleobase bound state. The electron transfer from water to uracil takes place because of the mixing of electronic and nuclear degrees of freedom. The water molecules around the uracil stabilize the uracil-bound anion by creating an extensive hydrogen-bonding network and accelerate the rate of electron attachment to uracil. The complete transfer of the electron from water to the uracil occurs in a picosecond time scale, which is consistent with the experimentally observed rate of reduction of nucleobases in the presence of water. The degree of solvation of the aqueous electron can lead to a difference in the initial stabilization of the uracil-bound anion. However, the anions formed due to the attachment of both surface-bound and bulk-solvated electrons behave similarly to each other at a longer time scale.Machine learning driven interatomic potentials, including Gaussian approximation potential (GAP) models, are emerging tools for atomistic simulations. Here, we address the methodological question of how one can fit GAP models that accurately predict vibrational properties in specific regions of configuration space while retaining flexibility and transferability to others. We use an adaptive regularization of the GAP fit that scales with the absolute force magnitude on any given atom, thereby exploring the Bayesian interpretation of GAP regularization as an “expected error” and its impact on the prediction of physical properties for a material of interest. The approach enables excellent predictions of phonon modes (to within 0.1 THz-0.2 THz) for structurally diverse silicon allotropes, and it can be coupled with existing fitting databases for high transferability across different regions of configuration space, which we demonstrate for liquid and amorphous silicon. These findings and workflows are expected to be useful for GAP-driven materials modeling more generally.When a highly charged globular macromolecule, such as a dendritic polyelectrolyte or charged nanogel, is immersed into a physiological electrolyte solution, monovalent and divalent counterions from the solution bind to the macromolecule in a certain ratio and thereby almost completely electroneutralize it. For charged macromolecules in biological media, the number ratio of bound monovalent vs divalent ions is decisive for the desired function. A theoretical prediction of such a sorption ratio is challenging because of the competition of electrostatic (valency), ion-specific, and binding saturation effects. Here, we devise and discuss a few approximate models to predict such an equilibrium sorption ratio by extending and combining established electrostatic binding theories such as Donnan, Langmuir, Manning, and Poisson-Boltzmann approaches, to systematically study the competitive uptake of monovalent and divalent counterions by the macromolecule. We compare and fit our models to coarse-grained (implicit-solvent) computer simulation data of the globular polyelectrolyte dendritic polyglycerol sulfate (dPGS) in salt solutions of mixed valencies. The dPGS molecule has high potential to serve in macromolecular carrier applications in biological systems and at the same time constitutes a good model system for a highly charged macromolecule. We finally use the simulation-informed models to extrapolate and predict electrostatic features such as the effective charge as a function of the divalent ion concentration for a wide range of dPGS generations (sizes).Solutions of polyvinyl alcohol (PVA) in water can form gels upon repeated freezing and thawing. These PVA cryogels have applications as biomaterials, including artificial tissue and drug delivery systems. We have studied the dielectric properties of PVA cryogels within the freeze-thaw cycles as a function of both frequency and temperature in order to understand the physical changes that take place during the thermal cycling process. Our results indicate that most of the changes in dielectric properties occur during the cooling phase of the first cycle and suggest that the solution must be cooled below a critical temperature of about 263 K for the formation of a gel that persists after thawing. The material’s dielectric spectrum shows the presence of several relaxation processes. read more We identify one of these with the dielectric relaxation of ice and two others with motions of the PVA polymer chains. The temperature dependence of the polymeric relaxation times suggests that they are both thermally activated, with an activation energy of roughly 300 kJ/mol.First-principles modeling of nonlinear optical spectra in the condensed phase is highly challenging because both environment and vibronic interactions can play a large role in determining spectral shapes and excited state dynamics. Here, we compute two dimensional electronic spectroscopy (2DES) signals based on a cumulant expansion of the energy gap fluctuation operator, with specific focus on analyzing mode mixing effects introduced by the Duschinsky rotation and the role of the third order term in the cumulant expansion for both model and realistic condensed phase systems. We show that for a harmonic model system, the third order cumulant correction captures effects introduced by a mismatch in curvatures of ground and excited state potential energy surfaces, as well as effects of mode mixing. We also demonstrate that 2DES signals can be accurately reconstructed from purely classical correlation functions using quantum correction factors. We then compute nonlinear optical spectra for the Nile red and methylene blue chromophores in solution, assessing the third order cumulant contribution for realistic systems.