Water molecules mute the dependence of the double-layer potential profile on ionic strength.

We present the results of molecular dynamics simulations of a nanoscale electrochemical cell. The simulations include an aqueous electrolyte solution with varying ionic strength (i.e., concentrations ranging from 0-4 M) between a pair of metallic electrodes held at constant potential difference. We analyze these simulations by computing the electrostatic potential profile of the electric double-layer region and find it to be nearly independent of ionic concentration, in stark contrast to the predictions of standard continuum-based theories. We attribute this lack of concentration dependence to the molecular influences of water molecules at the electrode-solution interface. These influences include the molecular manifestation of water's dielectric response, which tends to drown out the comparatively weak screening requirement of the ions. To support our analysis, we decompose water's interfacial response into three primary contributions: molecular layering, intrinsic (zero-field) orientational polarization, and the dipolar dielectric response.

Publisher Correction: Photoswitching topology in polymer networks with metal-organic cages as crosslinks.

The green arrow in Fig. 3 has been restored online.

Photoswitching topology in polymer networks with metal-organic cages as crosslinks.

Polymer networks can have a range of desirable properties such as mechanical strength, wide compositional diversity between different materials, permanent porosity, convenient processability and broad solvent compatibility1,2. Designing polymer networks from the bottom up with new structural motifs and chemical compositions can be used to impart dynamic features such as malleability or self-healing, or to allow the material to respond to environmental stimuli3-8. However, many existing systems exhibit only one operational state that is defined by the material's composition and topology3-6; or their responsiveness may be irreversible7,9,10 and limited to a single network property11,12 (such as stiffness). Here we use cooperative self-assembly as a design principle to prepare a material that can be switched between two topological states. By using networks of polymer-linked metal-organic cages in which the cages change shape and size on irradiation, we can reversibly switch the network topology with ultraviolet or green light. This photoswitching produces coherent changes in several network properties at once, including branch functionality, junction fluctuations, defect tolerance, shear modulus, stress-relaxation behaviour and self-healing. Topology-switching materials could prove useful in fields such as soft robotics and photo-actuators as well as providing model systems for fundamental polymer physics studies.

Terahertz Field-Induced Reemergence of Quenched Photoluminescence in Quantum Dots.

The continuous and concerted development of colloidal quantum dot light-emitting diodes over the past two decades has established them as a bedrock technology for the next generation of displays. However, a fundamental issue that limits the performance of these devices is the quenching of photoluminescence due to excess charges from conductive charge transport layers. Although device designs have leveraged various workarounds, doing so often comes at the cost of limiting efficient charge injection. Here we demonstrate that high-field terahertz (THz) pulses can dramatically brighten quenched QDs on metallic surfaces, an effect that persists for minutes after THz irradiation. This phenomenon is attributed to the ability of the THz field to remove excess charges, thereby reducing trion and nonradiative Auger recombination. Our findings show that THz technologies can be used to suppress and control such undesired nonradiative decay, potentially in a variety of luminescent materials for future device applications.

Designing excitonic circuits for the Deutsch-Jozsa algorithm: mitigating fidelity loss by merging gate operations.

In this manuscript, we examine design strategies for the development of excitonic circuits that are capable of performing simple 2-qubit multi-step quantum algorithms. Specifically, we compare two different strategies for designing dye-based systems that prescribe exciton evolution encoding a particular quantum algorithm. A serial strategy implements the computation as a step-by-step series of circuits, with each carrying out a single operation of the quantum algorithm, and a combined strategy implements the entire computation in a single circuit. We apply these two approaches to the well-studied Deutsch-Jozsa algorithm and evaluate circuit fidelity in an idealized system under a model harmonic bath, and also for a bath that is parameterized to reflect the thermal fluctuations of an explicit molecular environment. We find that the combined strategy tends to yield higher fidelity and that the harmonic bath approximation leads to lower fidelity than a model molecular bath. These results imply that the programming of excitonic circuits for quantum computation should favor hard-coded modules that incorporate multiple algorithmic steps and should represent the molecular nature of the circuit environment.

On the design of molecular excitonic circuits for quantum computing: the universal quantum gates.

This manuscript presents a strategy for controlling the transformation of excitonic states through the design of circuits made up of coupled organic dye molecules. Specifically, we show how unitary transformation matrices can be mapped to the Hamiltonians of physical systems of dye molecules with specified geometric and chemical properties. The evolution of these systems over specific time scales encodes the action of the unitary transformation. We identify bounds on the complexity of the transformations that can be represented by these circuits and on the optoelectronic properties of the dye molecules that comprise them. We formalize this strategy and apply it to determine the excitonic circuits of the four universal quantum logic gates: NOT, Hadamard, π/8 and CNOT. We discuss the properties of these circuits and how their performance is expected to be influenced by the presence of environmental noise.

The limited influence of transference number on the performance of nanoscale batteries.

We present a model of a nanoscale Li-ion-type battery that includes explicit, atomistic representation of the current-carrying cations and their counter-ions. We use this model to simulate the dependence of battery performance on the transference number of the electrolyte. We report simulated values of the current at constant applied voltage for a series of model electrolytes with varying cation and anion mobilities. Unlike the predictions of macroscopic device models, our simulation results reveal that under conditions of fixed cation mobility, the performance of a nanoscale battery is not improved by increasing the transference number of the electrolyte. We attribute this model discrepancy to the ability of the electrolyte to support deviations from charge neutrality over nanometer length scales and conclude that models for nanoscale electrochemical systems need to include the possibility of deviations from electroneutrality.

Machine learning Frenkel Hamiltonian parameters to accelerate simulations of exciton dynamics.

In this manuscript, we develop multiple machine learning (ML) models to accelerate a scheme for parameterizing site-based models of exciton dynamics from all-atom configurations of condensed phase sexithiophene systems. This scheme encodes the details of a system's specific molecular morphology in the correlated distributions of model parameters through the analysis of many single-molecule excited-state electronic-structure calculations. These calculations yield excitation energies for each molecule in the system and the network of pair-wise intermolecular electronic couplings. Here, we demonstrate that the excitation energies can be accurately predicted using a kernel ridge regression (KRR) model with Coulomb matrix featurization. We present two ML models for predicting intermolecular couplings. The first one utilizes a deep neural network and bi-molecular featurization to predict the coupling directly, which we find to perform poorly. The second one utilizes a KRR model to predict unimolecular transition densities, which can subsequently be analyzed to compute the coupling. We find that the latter approach performs excellently, indicating that an effective, generalizable strategy for predicting simple bimolecular properties is through the indirect application of ML to predict higher-order unimolecular properties. Such an approach necessitates a much smaller feature space and can incorporate the insight of well-established molecular physics.

Understanding attenuated solvent reorganization energies near electrode interfaces.

In this manuscript, we examine the role of image charge effects on the electrostatic potential fluctuations experienced by ionic species in the vicinity of an electrode surface. We combine simulation and theory to quantify these fluctuations and how they vary with distance from the electrode surface. We observe that the potential distribution narrows significantly for species within a few electrolyte screening lengths of the electrode. We attribute this narrowing to the effects of image charge fluctuations originating from the polarization response of the electrode. We show that the physical consequences of these image charge effects can be captured in the context of a simple analytical field theory with anti-symmetric boundary conditions. We contextualize these results by discussing their implications for rates of Marcus-like outer-sphere interfacial electron transfer.

Microscopic dynamics of charge separation at the aqueous electrochemical interface.

We have used molecular simulation and methods of importance sampling to study the thermodynamics and kinetics of ionic charge separation at a liquid water-metal interface. We have considered this process using canonical examples of two different classes of ions: a simple alkali-halide pair, Na+I-, or classical ions, and the products of water autoionization, H3O+OH-, or water ions. We find that for both ion classes, the microscopic mechanism of charge separation, including water's collective role in the process, is conserved between the bulk liquid and the electrode interface. However, the thermodynamic and kinetic details of the process differ between these two environments in a way that depends on ion type. In the case of the classical ion pairs, a higher free-energy barrier to charge separation and a smaller flux over that barrier at the interface result in a rate of dissociation that is 40 times slower relative to the bulk. For water ions, a slightly higher free-energy barrier is offset by a higher flux over the barrier from longer lived hydrogen-bonding patterns at the interface, resulting in a rate of association that is similar both at and away from the interface. We find that these differences in rates and stabilities of charge separation are due to the altered ability of water to solvate and reorganize in the vicinity of the metal interface.

Theoretical Bounds on Electron Energy Filtering in Disordered Nanomaterials.

Electron energy filters have recently been proposed as a method of reducing the effects of thermal broadening in device and sensing applications, enabling substantial improvements in their room temperature performance. Nanostructured materials can act as electron energy filters by funneling thermally broadened electrons through discrete energy levels. In this study, we develop a theoretical model of the electron filtering properties of nanostructured materials that explicitly includes the effects of thermal broadening and size heterogeneity on the heterogeneity of nanostructure energy levels. We find that under certain conditions quantum dot solids can perform as effective electronic energy filters. We identify a material-specific length scale parameter, Lcrit, that specifies the maximum mean quantum dot size that can yield effective energy filtering. Moreover, we show that energy filtering materials composed of quantum dots with size near Lcrit are maximally robust to heterogeneity in quantum dot size, tolerating variations ∼10% of the mean size. The length scale Lcrit can be estimated directly from the widely tabulated density of states effective mass and shows that semiconductors with light conduction band electrons, such as III-V type materials InSb and GaAs, are the most forgiving for energy filtering applications. Taken together, these results provide a practical set of quantitative design principles for semiconductor electron filters.

Terahertz-Driven Stark Spectroscopy of CdSe and CdSe-CdS Core-Shell Quantum Dots.

The effects of large external fields on semiconductor nanostructures could reveal much about field-induced shifting of electronic states and their dynamical responses and could enable electro-optic device applications that require large and rapid changes in optical properties. Studies of quasi-dc electric field modulation of quantum dot (QD) properties have been limited by electrostatic breakdown processes observed under high externally applied field levels. To circumvent this, here we apply ultrafast terahertz (THz) electric fields with switching times on the order of 1 ps. We show that a pulsed THz electric field, enhanced by a microslit field enhancement structure (FES), can strongly manipulate the optical absorption properties of a thin film of CdSe and CdSe-CdS core-shell QDs on the subpicosecond time scale with spectral shifts that span the visible to near-IR range. Numerical simulations using a semiempirical tight binding model show that the band gap of the QD film can be shifted by as much a 79 meV during these time scales. The results allow a basic understanding of the field-induced shifting of electronic levels and suggest electro-optic device applications.

Photoswitchable Sol-Gel Transitions and Catalysis Mediated by Polymer Networks with Coumarin-Decorated Cu24 L24 Metal-Organic Cages as Junctions.

Photoresponsive materials that change in response to light have been studied for a range of applications. These materials are often metastable during irradiation, returning to their pre-irradiated state after removal of the light source. Herein, we report a polymer gel comprising poly(ethylene glycol) star polymers linked by Cu24 L24 metal-organic cages/polyhedra (MOCs) with coumarin ligands. In the presence of UV light, a photosensitizer, and a hydrogen donor, this "polyMOC" material can be reversibly switched between CuII , CuI , and Cu0 . The instability of the MOC junctions in the CuI and Cu0 states leads to network disassembly, forming CuI /Cu0 solutions, respectively, that are stable until re-oxidation to CuII and supramolecular gelation. This reversible disassembly of the polyMOC network can occur in the presence of a fixed covalent second network generated in situ by copper-catalyzed azide-alkyne cycloaddition (CuAAC), providing interpenetrating supramolecular and covalent networks.

Exciton-Delocalizing Ligands Can Speed Up Energy Migration in Nanocrystal Solids.

Researchers have long sought to use surface ligands to enhance energy migration in nanocrystal solids by decreasing the physical separation between nanocrystals and strengthening their electronic coupling. Exciton-delocalizing ligands, which possess frontier molecular orbitals that strongly mix with nanocrystal band-edge states, are well-suited for this role because they can facilitate carrier-wave function extension beyond the nanocrystal core, reducing barriers for energy transfer. This report details the use of the exciton-delocalizing ligand phenyldithiocarbamate (PDTC) to tune the transport rate and diffusion length of excitons in CdSe nanocrystal solids. A film composed of oleate-terminated CdSe nanocrystals is subjected to a solid-state ligand exchange to replace oleate with PDTC. Exciton migration in the films is subsequently investigated by femtosecond transient absorption. Our experiments indicate that the treatment of nanocrystal films with PDTC leads to rapid (∼400 fs) downhill energy migration (∼80 meV), while no such migration occurs in oleate-capped films. Kinetic Monte Carlo simulations allow us to extract both rates and length scales for exciton diffusion in PDTC-treated films. These simulations reproduce dynamics observed in transient absorption measurements over a range of temperatures and confirm excitons hop via a Miller-Abrahams mechanism. Importantly, our experiments and simulations show PDTC treatment increases the exciton hopping rate to 200 fs, an improvement of 5 orders of magnitude relative to oleate-capped films. This exciton hopping rate stands as one of the fastest determined for CdSe solids. The facile, room-temperature processing and improved transport properties offered by the solid-state exchange of exciton-delocalizing ligands show they offer promise for the construction of strongly coupled nanocrystal arrays.

Stereochemical Sequence Dictates Unimolecular Diblock Copolymer Assembly.

Deciphering the significance of length, sequence, and stereochemistry in block copolymer self-assembly remains an ongoing challenge. A dearth of methods to access uniform block co-oligomers/polymers with precise stereochemical sequences has precluded such studies. Here, we develop iterative exponential growth methods for the synthesis of a small library of unimolecular stereoisomeric diblock 32-mers. X-ray scattering reveals that stereochemistry modulates the phase behavior of these polymers, which we rationalize based on simulations carried out on a theoretical model system. This work demonstrates that stereochemical sequence can play a crucial role in unimolecular polymer self-assembly.

Modeling the effects of molecular disorder on the properties of Frenkel excitons in organic molecular semiconductors.

The Frenkel exciton model provides a convenient framework for simulating electronic excitations in organic conjugated systems that are too large to address with atomistic level electronic structure methods. Parameterization of this model is typically based on analytical expressions that incompletely describe the spatial and temporal correlations that are inherent to many condensed phase molecular systems. In this manuscript, we present a general procedure for including these correlations in the Frenkel exciton model, by mapping them directly from all-atom molecular configurations, for instance from classical molecular dynamics. Regardless of system morphology, this mapping automatically captures the spatial and temporal molecular correlations that are otherwise difficult or impossible to represent in terms of low-dimensional correlation functions. We apply this procedure to study the excited state properties of condensed phase materials made up of thiophene oligomers. We show that Frenkel model parameters can be mapped from a series of single molecule electronic structure calculations, and that for these materials efficient semi-empirical methods are sufficient to accurately reproduce experimental spectral measurements. By analyzing the statistics of model parameters derived from materials with different characteristic morphologies, we highlight failures in some assumptions that are commonly applied when generating model parameters. Finally, by simulating exciton dynamics on a mapped Frenekel exciton model, we demonstrate the ability to quantify the effect of material morphology on the dynamic properties of excitons.