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We develop a Stockmayer fluid model that accounts for the dielectric responses of polar solvents (water, MeOH, EtOH, acetone, 1-propanol, DMSO, and DMF) and NaCl solutions. These solvent molecules are represented by Lennard-Jones (LJ) spheres with permanent dipole moments and the ions by charged LJ spheres. The simulated dielectric constants of these liquids are comparable to experimental values, including the substantial decrease in the dielectric constant of water upon the addition of NaCl. Moreover, the simulations predict an increase in the dielectric constant when considering the influence of ion translations in addition to the orientation of permanent dipoles., (© 2023 Author(s). Published under an exclusive license by AIP Publishing.)

Catalyzed by enormous success in the industrial sector, many research programs have been exploring data-driven, machine learning approaches. Performance can be poor when the model is extrapolated to new regions of chemical space, e.g., new bonding types, new many-body interactions. Another important limitation is the spatial locality assumption in model architecture, and this limitation cannot be overcome with larger or more diverse datasets. The outlined challenges are primarily associated with the lack of electronic structure information in surrogate models such as interatomic potentials. Given the fast development of machine learning and computational chemistry methods, we expect some limitations of surrogate models to be addressed in the near future; nevertheless spatial locality assumption will likely remain a limiting factor for their transferability. Here, we suggest focusing on an equally important effort-design of physics-informed models that leverage the domain knowledge and employ machine learning only as a corrective tool. In the context of material science, we will focus on semi-empirical quantum mechanics, using machine learning to predict corrections to the reduced-order Hamiltonian model parameters. The resulting models are broadly applicable, retain the speed of semiempirical chemistry, and frequently achieve accuracy on par with much more expensive ab initio calculations. These early results indicate that future work, in which machine learning and quantum chemistry methods are developed jointly, may provide the best of all worlds for chemistry applications that demand both high accuracy and high numerical efficiency., (© 2023 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).)

A gold surface is functionalized by chemisorption of the enantiopure N,N'-bis-[2,2';5',2″]tert-thiophene-5-yl methylcyclohexane-1,2-diamine (2T3N), a chiral oligothiophene derivative, via overnight incubation in a 2T3N ethanol solution. The Au|2T3N interface is characterized by x-ray photoelectron circular dichroism and comparing x-ray photoemission spectroscopy and electro-desorption results. Charge transmission at the Au|2T3N| solution interface is characterized by recording the cyclic voltammetry of the Fe(III)/Fe(II) reversible redox couple, finding a charge transfer rate constant, k°, variation from 1 × 10-1 to 3.3 × 10-2 cm s-1, when comparing the bare Au and the Au|2T3N interfaces, respectively. The "anomalous" high value of k° found for the chiral Au|2T3N interface can be rationalized on the basis of the chiral-induced spin selectivity effect, as further proved by magnetic-conductive atomic force microscopy measurements at room temperature. A spin polarization of about 30% is found., (© 2023 Author(s). Published under an exclusive license by AIP Publishing.)

DNA strands are polymeric ligands that both protect and tune molecular-sized silver cluster chromophores. We studied single-stranded DNA C 4 AC 4 TC 3 XT 4 with X = guanosine and inosine that form a green fluorescent Ag 10 6+ cluster, but these two hosts are distinguished by their binding sites and the brightness of their Ag 10 of the X = guanosine, an interaction that is precluded for inosine. Furthermore, this single nucleobase controls the cluster fluorescence as the X = guanosine complex is ∼2.5× dimmer. We discuss the electronic relaxation in these two complexes using transient absorption spectroscopy in the time window 200 fs-400 µs. Three prominent features emerged: a ground state bleach, an excited state absorption, and a stimulated emission. Stimulated emission at the earliest delay time (200 fs) suggests that the emissive state is populated promptly following photoexcitation. Concurrently, the excited state decays and the ground state recovers, and these changes are ∼2× faster for the X = guanosine compared to the X = inosine cluster, paralleling their brightness difference. In contrast to similar radiative decay rates, the nonradiative decay rate is 7× higher with the X = guanosine vs inosine strand. A minor decay channel via a dark state is discussed. The possible correlation between the nonradiative decay and selective coordination with the X = guanosine/inosine suggests that specific nucleobase subunits within a DNA strand can modulate cluster-ligand interactions and, in turn, cluster brightness.6+ adducts. The nucleobase subunits in these oligomers collectively coordinate this cluster, and fs time-resolved infrared spectra previously identified one point of contact between the C2-NH 2 of the X = guanosine, an interaction that is precluded for inosine. Furthermore, this single nucleobase controls the cluster fluorescence as the X = guanosine complex is ∼2.5× dimmer. We discuss the electronic relaxation in these two complexes using transient absorption spectroscopy in the time window 200 fs-400 µs. Three prominent features emerged: a ground state bleach, an excited state absorption, and a stimulated emission. Stimulated emission at the earliest delay time (200 fs) suggests that the emissive state is populated promptly following photoexcitation. Concurrently, the excited state decays and the ground state recovers, and these changes are ∼2× faster for the X = guanosine compared to the X = inosine cluster, paralleling their brightness difference. In contrast to similar radiative decay rates, the nonradiative decay rate is 7× higher with the X = guanosine vs inosine strand. A minor decay channel via a dark state is discussed. The possible correlation between the nonradiative decay and selective coordination with the X = guanosine/inosine suggests that specific nucleobase subunits within a DNA strand can modulate cluster-ligand interactions and, in turn, cluster brightness.

Polymerization induced phase separation (PIPS) in a three component thermoset is studied using molecular dynamics simulations of a new coarse-grained thermoset model. The system includes two crosslinker molecules, which differ in their glass transition temperatures (T g ) and chain length and thus have the potential for phase separation. One crosslinker has a high T g corresponding to a rubbery behavior, and simulations were performed for a short length (4 beads) and a long length (33 beads). The resin and other crosslinker have low T g . A coarse-grained model is developed with these features and with interaction parameters determined so that for either rubbery crosslinker length, the system is in the liquid state at the cure temperature. For sufficiently slow reaction rates, the long rubbery molecule exhibits PIPS into a bicontinuous array of nanoscale domains, but the short one does not, reproducing recent experimental results. The simulations demonstrate that the reaction rates must be slow enough to allow diffusion to yield phase separation. Particularly, the reaction rate corresponding to the secondary amine must be very slow, else the structure of crosslinked clusters and the substantially increased diffusion time will prevent PIPS.

In polymer nanoparticle composites (PNCs) with attractive interactions between nanoparticles (NPs) and polymers, a bound layer of the polymer forms on the NP surface, with significant effects on the macroscopic properties of the PNCs. The adsorption and wetting behaviors of polymer solutions in the presence of a solid surface are critical to the fabrication process of PNCs. In this study, we use both classical density functional theory (cDFT) and molecular dynamics (MD) simulations to study dilute and semi-dilute solutions of short polymer chains near a solid surface. Using cDFT, we calculate the equilibrium properties of polymer solutions near a flat surface while varying the solvent quality, surface-fluid interactions, and the polymer chain lengths to investigate their effects on the polymer adsorption and wetting transitions. Using MD simulations, we simulate polymer solutions near solid surfaces with three different curvatures (a flat surface and NPs with two radii) to study the static conformation of the polymer bound layer near the surface and the dynamic chain adsorption process. We find that the bulk polymer concentration at which the wetting transition in the poor solvent system occurs is not affected by the difference in surface-fluid interactions; however, a threshold value of surface-fluid interaction is needed to observe the wetting transition. We also find that with good solvent, increasing the chain length or the difference in the surface-polymer interaction relative to the surface-solvent interaction increases the surface coverage of polymer segments and independent chains for all surface curvatures. Finally, we demonstrate that the polymer segmental adsorption times are heavily influenced only by the surface-fluid interactions, although polymers desorb more quickly from highly curved surfaces.

We utilize first-principles theory to investigate photo-induced excited-state dynamics of functionalized perylene diimide. This class of materials is highly suitable for solar energy conversion because of the strong optical absorbance, efficient energy transfer, and chemical tunability. We couple time-dependent density functional theory to a recently developed time-resolved non-adiabatic dynamics approach based on a semi-empirical description. By studying the monomer and dimer, we focus on the role stacking plays on the time-scales associated with excited-state non-radiative relaxation from a high excitonic state to the lowest energy exciton. We predict that the time-scale for energy conversion in the dimer is significantly faster than that in the monomer when equivalent excited states are accounted for. Additionally, for the dimer, the decay from the second to the nearly degenerate lowest energy excited-state involves two time-scales: a rapid decay on the order of ∼10 fs followed by a slower decay of ∼100 fs. Analysis of the spatial localization of the electronic transition density during the internal conversion process points out the existence of localized states on individual monomers, indicating that the strength of thermal fluctuations exceeds electronic couplings between the states such that the exciton hops between localized states throughout the simulation.

Predicting the functional properties of many molecular systems relies on understanding how atomistic interactions give rise to macroscale observables. However, current attempts to develop predictive models for the structural and thermodynamic properties of condensed-phase systems often rely on extensive parameter fitting to empirically selected functional forms whose effectiveness is limited to a narrow range of physical conditions. In this article, we illustrate how these traditional fitting paradigms can be superseded using machine learning. Specifically, we use the results of molecular dynamics simulations to train machine learning protocols that are able to produce the radial distribution function, pressure, and internal energy of a Lennard-Jones fluid with increased accuracy in comparison to previous theoretical methods. The radial distribution function is determined using a variant of the segmented linear regression with the multivariate function decomposition approach developed by Craven et al. [J. Phys. Chem. Lett. 11, 4372 (2020)]. The pressure and internal energy are determined using expressions containing the learned radial distribution function and also a kernel ridge regression process that is trained directly on thermodynamic properties measured in simulation. The presented results suggest that the structural and thermodynamic properties of fluids may be determined more accurately through machine learning than through human-guided functional forms.

The use of the varied chemical reactivity of precursors to drive the production of a desired nanocrystal architecture has become a common method to grow thick-shell graded alloy quantum dots (QDs) with robust optical properties. Conclusions on their behavior assume the ideal chemical gradation and uniform particle composition. Here, advanced analytical electron microscopy (high-resolution scanning transmission electron microscopy coupled with energy dispersive spectroscopy) is used to confirm the nature and extent of compositional gradation and these data are compared with performance behavior obtained from single-nanocrystal spectroscopy to elucidate structure, chemical-composition, and optical-property correlations. Specifically, the evolution of the chemical structure and single-nanocrystal luminescence was determined for a time-series of graded-alloy "CdZnSSe/ZnS" core/shell QDs prepared in a single-pot reaction. In a separate step, thick (∼6 monolayers) to giant (>14 monolayers) shells of ZnS were added to the alloyed QDs via a successive ionic layer adsorption and reaction (SILAR) process, and the impact of this shell on the optical performance was also assessed. By determining the degree of alloying for each component element on a per-particle basis, we observe that the actual product from the single-pot reaction is less "graded" in Cd and more so in Se than anticipated, with Se extending throughout the structure. The latter suggests much slower Se reaction kinetics than expected or an ability of Se to diffuse away from the initially nucleated core. It was also found that the subsequent growth of thick phase-pure ZnS shells by the SILAR method was required to significantly reduce blinking and photobleaching. However, correlated single-nanocrystal optical characterization and electron microscopy further revealed that these beneficial properties are only achieved if the thick ZnS shell is complete and without large lattice discontinuities. In this way, we identify the necessary structural design features that are required for ideal light emission properties in these green-visible emitting QDs.

A coarse-grained model previously used to simulate Nafion using dissipative particle dynamics (DPD) is modified to describe sulfonated Diels-Alder poly(phenylene) (SDAPP) polymers. The model includes a proton-hopping mechanism similar to the Grotthuss mechanism. The intramolecular parameters for SDAPP are derived from atomistic molecular dynamics (MD) simulation using the iterative Boltzmann inversion. The polymer radii of gyration, domain morphologies, and cluster distributions obtained from our DPD model are in good agreement with previous atomistic MD simulations. As found in the atomistic simulations, the DPD simulations predict that the SDAPP nanophase separates into hydrophobic polymer domains and hydrophilic domains that percolate through the system at sufficiently high sulfonation and hydration levels. Increasing sulfonation and/or hydration leads to larger proton and water diffusion constants, in agreement with experimental measurements in SDAPP. In the DPD simulations, the proton hopping (Grotthuss) mechanism becomes important as sulfonation and hydration increase, in qualitative agreement with experiment. The turning on of the hopping mechanism also roughly correlates with the point at which the DPD simulations exhibit clear percolated, hydrophilic domains, demonstrating the important effects of morphology on proton transport.

Surface hopping (SH) is a popular mixed quantum-classical method for modeling nonadiabatic excited state processes in molecules and condensed phase materials. The method is simple, efficient, and easy to implement, but the use of classical and independent nuclear trajectories introduces an overcoherence in the electronic density matrix which, if ignored, often leads to spurious results, such as overestimated reaction rates. Several methods have been proposed to incorporate decoherence into SH simulations, but a lack of insightful benchmarks makes their relative accuracy unknown. Herein, we run numerical simulations of common coherence-corrected SH methods including Truhlar's decay-of-mixing (DOM) and Subotnik's augmented SH using a Donor-bridge-Acceptor (DbA) model system. Numerical simulations are carried out in the superexchange regime, where charge transfer proceeds from a donor to an acceptor as a result of donor-bridge and bridge-acceptor couplings. The computed donor-to-acceptor reaction rates are compared to the reference Marcus theory results. For the DbA model under consideration, augmented SH recovers Marcus theory with quantitative accuracy, whereas DOM is only qualitatively accurate depending on whether predefined parameters in the decoherence rate are chosen wisely. We propose a general method for parameterizing the decoherence rate in the DOM method, which improves the method's reaction rates and presumably increases its transferability. Overall, the decoherence method of choice must be chosen with great care and this work provides insight using an exactly solvable model.

The efficiency of the intramolecular energy transfer in light harvesting dendrimers is determined by their well-defined architecture with high degree of order. After photoexcitation, through-space and through-bond energy transfer mechanisms can take place, involving vectorial exciton migration among different chromophores within dendrimer highly branched structures. Their inherent intramolecular energy gradient depends on how the multiple chromophoric units have been assembled, subject to their inter-connects, spatial distances, and orientations. Herein, we compare the photoinduced nonadiabatic molecular dynamics simulations performed on a set of different combinations of a chain of linked dendrimer building blocks composed of two-, three-, and four-ring linear polyphenylene chromophoric units. The calculations are performed with the recently developed ab initio multiple cloning-time dependent diabatic basis implementation of the Multiconfigurational Ehrenfest (MCE) approach. Despite differences in short time relaxation pathways and different initial exciton localization, at longer time scales, electronic relaxation rates and exciton final redistributions are very similar for all combinations. Unlike the systems composed of two building blocks, considered previously, for the larger 3 block systems here we observe that bifurcation of the wave function accounted by cloning is important. In all the systems considered in this work, at the time scale of few hundreds of femtoseconds, cloning enhances the electronic energy relaxation by ∼13% compared to that of the MCE method without cloning. Thus, accurate description of quantum effects is essential for understanding of the energy exchange in dendrimers both at short and long time scales.

We performed microsecond-long, atomistic molecular dynamics simulations on a series of precise poly(ethylene-co-acrylic acid) ionomers neutralized with lithium, with three different spacer lengths between acid groups on the ionomers and at two temperatures. Ionic aggregates form in these systems with a variety of shapes ranging from isolated aggregates to percolated aggregates. At the lower temperature of 423 K, the ionic aggregate morphologies do not reach a steady-state distribution over the course of the simulations. At the higher temperature of 600 K, the aggregates are sufficiently mobile that they rearrange and reach steady state after hundreds of nanoseconds. For systems that are 100% neutralized with lithium, the ions form percolated aggregates that span the simulation box in three directions, for all three spacer lengths (9, 15, and 21). In the partially neutralized systems, the morphology includes lithium ion aggregates that may also include some unneutralized acid groups, along with a coexisting population of acid group aggregates that form through hydrogen bonding. In the lithium ion aggregates, unneutralized acid groups tend to be found on the ends or sides of the aggregates.

Very large molecular dynamics simulations with open ends between two solid adherends have been performed treating tensile deformation of coarse-grained, highly crosslinked polymer networks modeling epoxy systems. The open boundary and the presence of corners dramatically alter the fracture behavior. In contrast to systems with periodic boundaries, the failure strain decreases with increasing system size until a critical size is reached. This decrease greatly reduces the difference in the crack initiation strains between simulation and experiment. In the open geometry, the sides of the polymer network contract inward forming wedge shaped corners. The stress and strain are concentrated in the corners where the shear component is present and large. The nonuniformity of the strain results in accumulation of bond breaking in the corners and crack initiation there. Moreover, the corner strain is system size dependent, which results in a system size dependence of the failure strain.

We present simulations of the force-extension curves of strong polyelectrolytes with varying intrinsic stiffness as well as specifically treating hyaluronic acid, a polyelectrolyte of intermediate stiffness. Whereas fully flexible polyelectrolytes show a high-force regime where extension increases nearly logarithmically with force, we find that the addition of even a small amount of stiffness alters the short-range structure and removes this logarithmic elastic regime. This further confirms that the logarithmic regime is a consequence of the short-ranged "wrinkles" in the flexible chain. As the stiffness increases, the force-extension curves tend toward and reach the wormlike chain behavior. Using the screened Coulomb potential and a simple bead-spring model, the simulations are able to reproduce the hyaluronic acid experimental force-extension curves for salt concentrations ranging from 1 to 500 mM. Furthermore, the simulation data can be scaled to a universal curve like the experimental data. The scaling analysis is consistent with the interpretation that, in the low-salt limit, the hyaluronic acid chain stiffness scales with salt with an exponent of -0.7, rather than either of the two main theoretical predictions of -0.5 and -1. Furthermore, given the conditions of the simulation, we conclude that this exponent value is not due to counterion condensation effects, as had previously been suggested.

Young's elastic modulus and the persistence length are calculated for a coarse-grained model of tubule forming polymers. The model uses a wedge shaped composite of particles that previously has been shown to self-assemble into tubules. These calculations demonstrate that the model yields very large persistence lengths (corresponding to 78-126 μm) that are comparable to that observed in experiments for the microtubule lengths accessible to the calculations. The source for the stiffness is the restricted rotation of the monomer due to the excluded volume interactions between bonded macromolecular monomers as well as the binding between monomers. For this reason, large persistence lengths are common in tubule systems with a macromolecule as the monomer. The persistence length increases linearly with increased binding strength in the filament direction. No dependence in the persistence length is found for varying the tubule pitch for geometries with the protofilaments remaining straight.

We perform molecular dynamics simulations of a coarse-grained model of ionomer melts in an applied oscillating electric field. The frequency-dependent conductivity and susceptibility are calculated directly from the current density and polarization density, respectively. At high frequencies, we find a peak in the real part of the conductivity due to plasma oscillations of the ions. At lower frequencies, the dynamic response of the ionomers depends on the ionic aggregate morphology in the system, which consists of either percolated or isolated aggregates. We show that the dynamic response of the model ionomers to the applied oscillating field can be understood by comparison with relevant time scales in the systems, obtained from independent calculations.

The effects of solvent on molecular processes such as excited state relaxation and photochemical reaction often occurs in a nonequilibrium regime. Dynamic processes such as these can be simulated using excited statemolecular dynamics. In this work, we describe methods of simulating nonequilibrium solvent effects in excited statemolecular dynamics using linear-response time-dependent density functional theory and apparent surface charge methods. These developments include a propagation method for solvent degrees of freedom and analytical energy gradients for the calculation of forces. Molecular dynamics of acetaldehyde in water or acetonitrile are demonstrated where the solute-solvent system is out of equilibrium due to photoexcitation and emission.

This study describes variational energy expressions and analytical excited state energy gradients for time-dependent self-consistent field methods with polarizable solvent effects. Linear response, vertical excitation, and state-specific solvent models are examined. Enforcing a variational ground state energy expression in the state-specific model is found to reduce it to the vertical excitation model. Variational excited state energy expressions are then provided for the linear response and vertical excitation models and analytical gradients are formulated. Using semiempirical model chemistry, the variational expressions are verified by numerical and analytical differentiation with respect to a static external electric field. Analytical gradients are further tested by performing microcanonical excited state molecular dynamics with p-nitroaniline.

Exciton scattering theory attributes excited electronic states to standing waves in quasi-one-dimensional molecular materials by assuming a quasi-particle picture of optical excitations. The quasi-particle properties at branching centers are described by the corresponding scattering matrices. Here, we identify the topological invariant of a scattering center, referred to as its winding number, and apply topological intersection theory to count the number of quantum states in a quasi-one-dimensional system.

We implement and examine three excited state solvent models in time-dependent self-consistent field methods using a consistent formalism which unambiguously shows their relationship. These are the linear response, state specific, and vertical excitation solvent models. Their effects on energies calculated with the equivalent of COSMO/CIS/AM1 are given for a set of test molecules with varying excited state charge transfer character. The resulting solvent effects are explained qualitatively using a dipole approximation. It is shown that the fundamental differences between these solvent models are reflected by the character of the calculated excitations.

We perform atomistic molecular dynamics simulations of melts of four precise acid copolymers, two poly(ethylene-co-acrylic acid) (PEAA) copolymers, and two poly(ethylene-co-sulfonic acid) (PESA) copolymers. The acid groups are spaced by either 9 or 21 carbons along the polymer backbones. Hydrogen bonding causes the acid groups to form aggregates. These aggregates give rise to a low wavevector peak in the structure factors, in agreement with X-ray scattering data for the PEAA materials. The structure factors for the PESA copolymers are very similar to those for the PEAA copolymers, indicating a similar distance between aggregates which depends on the spacer length but not on the nature of the acid group. The PEAA copolymers are found to form more dimers and other small aggregates than do the PESA copolymers, while the PESA copolymers have both more free acid groups and more large aggregates.

Within the fewest switches surface hopping (FSSH) formulation, a swarm of independent trajectories is propagated and the equations of motion for the quantum coefficients are evolved coherently along each independent nuclear trajectory. That is, the phase factors, or quantum amplitudes, are retained. At a region of strong coupling, a trajectory can branch into multiple wavepackets. Directly following a hop, the two wavepackets remain in a region of nonadiabatic coupling and continue exchanging population. After these wavepackets have sufficiently separated in phase space, they should begin to evolve independently from one another, the process known as decoherence. Decoherence is not accounted for in the standard surface hopping algorithm and leads to internal inconsistency. FSSH is designed to ensure that at any time, the fraction of classical trajectories evolving on each quantum state is equal to the average quantum probability for that state. However, in many systems this internal consistency requirement is violated. Treating decoherence is an inherent problem that can be addressed by implementing some form of decoherence correction to the standard FSSH algorithm. In this study, we have implemented two forms of the instantaneous decoherence procedure where coefficients are reinitialized following hops. We also test the energy-based decoherence correction (EDC) scheme proposed by Granucci et al. and a related version where the form of the decoherence time is taken from Truhlar's Coherent Switching with Decay of Mixing method. The sensitivity of the EDC results to changes in parameters is also evaluated. The application of these computationally inexpensive ad hoc methods is demonstrated in the simulation of nonradiative relaxation in two conjugated oligomer systems, specifically poly-phenylene vinylene and poly-phenylene ethynylene. We find that methods that have been used successfully for treating small systems do not necessarily translate to large polyatomic systems and their success depends on the particular system under study.

In an athermal blend of nanoparticles and homopolymer near a hard wall, there is a first order phase transition in which the nanoparticles segregate to the wall and form a densely packed monolayer above a certain nanoparticle density. Previous investigations of this phase transition employed a fluids density functional theory (DFT) at constant packing fraction. Here we report further DFT calculations to probe the robustness of this phase transition. We find that the phase transition also occurs in athermal systems at constant pressure, the more natural experimental condition than constant packing fraction. Adding nanoparticle-polymer attractions increases the nanoparticle transition density, while sufficiently strong attractions suppress the first-order transition entirely. In this case the systems display a continuous transition to a bulk layered state. Adding attractions between the polymers and the wall has a similar effect of delaying and then suppressing the first-order nanoparticle segregation transition, but does not lead to any continuous phase transitions.

We perform direct three-dimensional density functional theory (DFT) calculations of two- and three-body interactions in polymer nanocomposites. The nanoparticles are modeled as hard spheres, immersed in a hard-sphere homopolymer melt of freely jointed chains. The two-particle potential of mean force obtained from the DFT is in near quantitative agreement with the potential of mean force obtained from self-consistent polymer reference interaction site model theory. Three-body interactions among three nanoparticles are found to be significant, such that it is not possible to describe these systems with a polymer-mediated two-body interaction calculated from the potential of mean force.

We study physical principles of optimal design of a nanoscale multiwell heterostructure functioning as an electrostatic energy storage device. We performed numerical optimization of the multiwell trapping potential for electrons in the nanostructure with the goal to obtain the maximum possible static polarizability of the system. The response of the heterostructure is modeled microscopically using nonlocal linear response theory within the random phase approximation. Three main design strategies are identified which lead to the maximization of the stored energy. We found that the efficiency of each strategy crucially depends on the temperature and the broadening of electron levels. The stored energy for optimized heterostructures can exceed the nonoptimized ones by a factor of 450. These findings provide a theoretical basis for the development of new nanoscale capacitors with high energy density storage capabilities.

We apply the self-consistent polymer reference interaction site model (SC/PRISM) to liquid state calculations of the chain dimensions in polymer melts with added nanoparticle fillers. The nanoparticles are assumed to be smaller than the polymer radius of gyration and are attracted to the polymer so that they are miscible. We find that the nanoparticles perturb the chain dimensions, causing an increase in the radius of gyration with increasing nanoparticle volume fractions, assuming reasonable interaction energies between the various components. The magnitude of the expansion is in qualitative agreement with recent neutron scattering results and suggests that the SC/PRISM approach is reasonable when dealing with these apparent nonlinear phenomena present in nanocomposites in the protein limit.

We present a theory for Raman scattering by current-carrying molecular junctions. The approach combines a nonequilibrium Green's function (NEGF) description of the nonequilibrium junction with a generalized scattering theory formulation for evaluating the light scattering signal. This generalizes our previous study [M. Galperin and A. Nitzan, Phys. Rev. Lett. 95, 206802 (2005); J. Chem. Phys. 124, 234709 (2006)] of junction spectroscopy by including molecular vibrations and developing machinery for calculation of state-to-state (Raman scattering) fluxes within the NEGF formalism. For large enough voltage bias, we find that the light scattering signal contains, in addition to the normal signal associated with the molecular ground electronic state, also a contribution from the inverse process originated from the excited molecular state as well as an interference component. The effects of coupling to the electrodes and of the imposed bias on the total Raman scattering as well as its components are discussed. Our result reduces to the standard expression for Raman scattering in the isolated molecule case, i.e., in the absence of coupling to the electrodes. The theory is used to discuss the charge-transfer contribution to surface enhanced Raman scattering for molecules adsorbed on metal surfaces and its manifestation in the biased junction.

We propose a scheme for calculation of linear optical response of current-carrying molecular junctions for the case when electronic tunneling through the junction is much faster than characteristic time of external laser field. We discuss relationships between nonequilibrium Green's function (NEGF) and time-dependent density functional theory (TDDFT) approaches and derive expressions for optical response and linear polarizability within NEGF-TDDFT scheme. Corresponding results for isolated molecule, derived within TDDFT approach previously, are reproduced when coupling to contacts is neglected.

Optimal control problem with a goal to squeeze wave packet of a trapped quantum particle is considered and solved analytically using adiabatic approximation. The analytical solution that drives the particle into a highly localized final state is presented for a case of an infinite well trapping potential. The presented solution may be applied to increase the resolution of atom lithography.