Showing papers by "Sergei Tretiak published in 2021"
TL;DR: The AIMNet-NSE (Neural Spin Equilibration) architecture is introduced, which can predict molecular energies for an arbitrary combination of molecular charge and spin multiplicity with errors of about 2–3 kcal/mol and spin-charges with error errors ~0.01e for small and medium-sized organic molecules, compared to the reference QM simulations.
Abstract: Interatomic potentials derived with Machine Learning algorithms such as Deep-Neural Networks (DNNs), achieve the accuracy of high-fidelity quantum mechanical (QM) methods in areas traditionally dominated by empirical force fields and allow performing massive simulations. Most DNN potentials were parametrized for neutral molecules or closed-shell ions due to architectural limitations. In this work, we propose an improved machine learning framework for simulating open-shell anions and cations. We introduce the AIMNet-NSE (Neural Spin Equilibration) architecture, which can predict molecular energies for an arbitrary combination of molecular charge and spin multiplicity with errors of about 2–3 kcal/mol and spin-charges with error errors ~0.01e for small and medium-sized organic molecules, compared to the reference QM simulations. The AIMNet-NSE model allows to fully bypass QM calculations and derive the ionization potential, electron affinity, and conceptual Density Functional Theory quantities like electronegativity, hardness, and condensed Fukui functions. We show that these descriptors, along with learned atomic representations, could be used to model chemical reactivity through an example of regioselectivity in electrophilic aromatic substitution reactions. Quantum mechanical calculations of molecular ionized states are computationally quite expensive. This work reports a successful extension of a previous deep-neural networks approach towards transferable neural-network models for predicting multiple properties of open shell anions and cations.
45 citations
TL;DR: In this paper, an active learning approach is proposed to automatically construct general-purpose machine-learning potentials for the aluminum case, which makes very accurate predictions of radial distribution function in melt, liquid-solid coexistence curve, and crystal properties such as defect energies and barriers.
Abstract: Machine learning, trained on quantum mechanics (QM) calculations, is a powerful tool for modeling potential energy surfaces. A critical factor is the quality and diversity of the training dataset. Here we present a highly automated approach to dataset construction and demonstrate the method by building a potential for elemental aluminum (ANI-Al). In our active learning scheme, the ML potential under development is used to drive non-equilibrium molecular dynamics simulations with time-varying applied temperatures. Whenever a configuration is reached for which the ML uncertainty is large, new QM data is collected. The ML model is periodically retrained on all available QM data. The final ANI-Al potential makes very accurate predictions of radial distribution function in melt, liquid-solid coexistence curve, and crystal properties such as defect energies and barriers. We perform a 1.3M atom shock simulation and show that ANI-Al force predictions shine in their agreement with new reference DFT calculations. The accuracy of a machine-learned potential is limited by the quality and diversity of the training dataset. Here the authors propose an active learning approach to automatically construct general purpose machine-learning potentials here demonstrated for the aluminum case.
28 citations
TL;DR: The Noyori-Ikariya chiral molecular ruthenium complex has been the catalyst for asymmetric transfer hydrogenation (ATH) in the fragrance and pharmaceutical industries as mentioned in this paper.
24 citations
09 Jun 2021
TL;DR: A permutation scheme allows solving high complexity problems in quantum chemistry with simple and short quantum circuits as mentioned in this paper, which offers simple solutions to complex problems: permutation schemes offer simple solutions for complex problems.
Abstract: Symmetries offer simple solutions to complex problems: A permutation scheme allows solving high complexity problems in quantum chemistry with simple and short quantum circuits.
23 citations
TL;DR: In this article, the authors summarized some recent advances in the development of neural network-based interatomic potentials, including active learning, active transfer learning, and quantum theory based transfer learning.
Abstract: Machine learning (ML) is quickly becoming a premier tool for modeling chemical processes and materials. ML-based force fields, trained on large data sets of high-quality electron structure calculations, are particularly attractive due their unique combination of computational efficiency and physical accuracy. This Perspective summarizes some recent advances in the development of neural network-based interatomic potentials. Designing high-quality training data sets is crucial to overall model accuracy. One strategy is active learning, in which new data are automatically collected for atomic configurations that produce large ML uncertainties. Another strategy is to use the highest levels of quantum theory possible. Transfer learning allows training to a data set of mixed fidelity. A model initially trained to a large data set of density functional theory calculations can be significantly improved by retraining to a relatively small data set of expensive coupled cluster theory calculations. These advances are exemplified by applications to molecules and materials.
22 citations
21 citations
TL;DR: In this paper, chemical functionalization of GQD edges is a strategy to increase their solubility and processability, which can improve the processability of the GQDs.
Abstract: Graphene quantum dots (GQDs) are promising semiconducting materials for practical applications. Chemical functionalization of GQD edges is a strategy to increase their solubility and processability...
20 citations
TL;DR: In this paper, a deep neural network is trained to reproduce orbital energies and densities derived from density functional theory, and the resulting model retains interpretability and reproduces insightful features of the original empirical parameterization.
Abstract: The Huckel Hamiltonian is an incredibly simple tight-binding model known for its ability to capture qualitative physics phenomena arising from electron interactions in molecules and materials. Part of its simplicity arises from using only two types of empirically fit physics-motivated parameters: the first describes the orbital energies on each atom and the second describes electronic interactions and bonding between atoms. By replacing these empirical parameters with machine-learned dynamic values, we vastly increase the accuracy of the extended Huckel model. The dynamic values are generated with a deep neural network, which is trained to reproduce orbital energies and densities derived from density functional theory. The resulting model retains interpretability, while the deep neural network parameterization is smooth and accurate and reproduces insightful features of the original empirical parameterization. Overall, this work shows the promise of utilizing machine learning to formulate simple, accurate, and dynamically parameterized physics models.
19 citations
TL;DR: Two-dimensional electronic spectroscopy reveals the existence of intermolecular conical intersections in molecular aggregates relevant for photovoltaics and indicates that intermolescular CoIns may effectively steer energy pathways in functional nanostructures for optoelectronics.
Abstract: Conical intersections (CoIns) of multidimensional potential energy surfaces are ubiquitous in nature and control pathways and yields of many photo-initiated intramolecular processes. Such topologies can be potentially involved in the energy transport in aggregated molecules or polymers but are yet to be uncovered. Here, using ultrafast two-dimensional electronic spectroscopy (2DES), we reveal the existence of intermolecular CoIns in molecular aggregates relevant for photovoltaics. Ultrafast, sub-10-fs 2DES tracks the coherent motion of a vibrational wave packet on an optically bright state and its abrupt transition into a dark state via a CoIn after only 40 fs. Non-adiabatic dynamics simulations identify an intermolecular CoIn as the source of these unusual dynamics. Our results indicate that intermolecular CoIns may effectively steer energy pathways in functional nanostructures for optoelectronics. Two-dimensional electronic spectroscopy reveals the existence of intermolecular conical intersections in molecular aggregates relevant for photovoltaics.
18 citations
TL;DR: The role of quantum-mechanical coherences in the elementary photophysics of functional optoelectronic molecular materials is currently under active study as mentioned in this paper, where the energy transfer properties of a rigid synthetic heterodimer that has been experimentally engineered to study co-herences are investigated.
Abstract: The role of quantum-mechanical coherences in the elementary photophysics of functional optoelectronic molecular materials is currently under active study. Designing and controlling stable coherences arising from concerted vibronic dynamics in organic chromophores is the key for numerous applications. Here, we present fundamental insight into the energy transfer properties of a rigid synthetic heterodimer that has been experimentally engineered to study coherences. Quantum non-adiabatic excited state simulations are used to compute X-ray Raman signals, which are able to sensitively monitor the coherence evolution. Our results verify their vibronic nature, that survives multiple conical intersection passages for several hundred femtoseconds at room temperature. Despite the contributions of highly heterogeneous evolution pathways, the coherences are unambiguously visualized by the experimentally accessible X-ray signals. They offer direct information on the dynamics of electronic and structural degrees of freedom, paving the way for detailed coherence measurements in functional organic materials.
15 citations
TL;DR: In this paper, the authors demonstrate the use of a D-Wave quantum annealer for the calculation of excited electronic states of molecular systems using two methods, timedependent Hartree-Fock (TDHF) and time-dependent density-functional theory (TDDFT), both within a commonly used Tamm-Dancoff approximation (TDA).
Abstract: The possibility of using quantum computers for electronic structure calculations has opened up a promising avenue for computational chemistry. Towards this direction, numerous algorithmic advances have been made in the last five years. The potential of quantum annealers, which are the prototypes of adiabatic quantum computers, is yet to be fully explored. In this work, we demonstrate the use of a D-Wave quantum annealer for the calculation of excited electronic states of molecular systems. These simulations play an important role in a number of areas, such as photovoltaics, semiconductor technology and nanoscience. The excited states are treated using two methods, time-dependent Hartree–Fock (TDHF) and time-dependent density-functional theory (TDDFT), both within a commonly used Tamm–Dancoff approximation (TDA). The resulting TDA eigenvalue equations are solved on a D-Wave quantum annealer using the Quantum Annealer Eigensolver (QAE), developed previously. The method is shown to reproduce a typical basis set convergence on the example $$\hbox {H}_2$$
molecule and is also applied to several other molecular species. Characteristic properties such as transition dipole moments and oscillator strengths are computed as well. Three potential energy profiles for excited states are computed for $$\hbox {NH}_3$$
as a function of the molecular geometry. Similar to previous studies, the accuracy of the method is dependent on the accuracy of the intermediate meta-heuristic software called qbsolv.
TL;DR: In this paper, the authors compare three popular methods for large chromophores: Ehrenfest, surface hopping, and multiconfigurational EhrenFest with ab initio multiple cloning (MCE-AIMC).
Abstract: Direct atomistic simulation of nonadiabatic molecular dynamics is a challenging goal that allows important insights into fundamental physical phenomena. A variety of frameworks, ranging from fully quantum treatment of nuclei to semiclassical and mixed quantum-classical approaches, were developed. These algorithms are then coupled to specific electronic structure techniques. Such diversity and lack of standardized implementation make it difficult to compare the performance of different methodologies when treating realistic systems. Here, we compare three popular methods for large chromophores: Ehrenfest, surface hopping, and multiconfigurational Ehrenfest with ab initio multiple cloning (MCE-AIMC). These approaches are implemented in the NEXMD software, which features a common computational chemistry model. The resulting comparisons reveal the method performance for population relaxation and coherent vibronic dynamics. Finally, we study the numerical convergence of MCE-AIMC algorithms by considering the number of trajectories, cloning thresholds, and Gaussian wavepacket width. Our results provide helpful reference data for selecting an optimal methodology for simulating excited-state molecular dynamics.
TL;DR: In this article, the authors introduce localization layers in a neural network model that weight atomic contributions to the energy gap, thereby allowing the model to isolate the most determinative chemical environments.
Abstract: Phosphorescence is commonly utilized for applications including light-emitting diodes and photovoltaics. Machine learning (ML) approaches trained on ab initio datasets of singlet–triplet energy gaps may expedite the discovery of phosphorescent compounds with the desired emission energies. However, we show that standard ML approaches for modeling potential energy surfaces inaccurately predict singlet–triplet energy gaps due to the failure to account for spatial localities of spin transitions. To solve this, we introduce localization layers in a neural network model that weight atomic contributions to the energy gap, thereby allowing the model to isolate the most determinative chemical environments. Trained on the singlet–triplet energy gaps of organic molecules, we apply our method to an out-of-sample test set of large phosphorescent compounds and demonstrate the substantial improvement that localization layers have on predicting their phosphorescence energies. Remarkably, the inferred localization weights have a strong relationship with the ab initio spin density of the singlet–triplet transition, and thus infer localities of the molecule that determine the spin transition, despite the fact that no direct electronic information was provided during training. The use of localization layers is expected to improve the modeling of many localized, non-extensive phenomena and could be implemented in any atom-centered neural network model.
TL;DR: This study finds that the QD perovskites retain their defect tolerance with limited perturbance to the simulated UV-vis spectra, providing insight into the tunability of CsPbBr3 QDs optical properties by understanding the nature of the electronic excitations and guiding improved development for high-performance LEDs.
Abstract: CsPbBr3 quantum dots (QDs) have been recently suggested for their application as bright green light-emitting diodes (LEDs); however, their optical properties are yet to be fully understood and characterized. In this work, we utilize time-dependent density functional theory to analyze the ground and excited states of the CsPbBr3 clusters in the presence of various low formation energy vacancy defects. Our study finds that the QD perovskites retain their defect tolerance with limited perturbance to the simulated UV-vis spectra. The exception to this general trend is that Br vacancies must be avoided, as they cause molecular orbital localization, resulting in trap states and lower LED performance. Blinking will likely still plague CsPbBr3 QDs, given that the charged defects critically perturb the spectra via red-shifting and lower absorbance. Our study provides insight into the tunability of CsPbBr3 QDs optical properties by understanding the nature of the electronic excitations and guiding improved development for high-performance LEDs.
TL;DR: In this paper, the authors report efficient, regenerative and low-cost electron sources based on solution-processed halide perovskites thin films when they are excited with light with energy equal to or above their bandgap.
Abstract: Electron sources are a critical component in a wide range of applications such as electron-beam accelerator facilities, photomultipliers, and image intensifiers for night vision. We report efficient, regenerative and low-cost electron sources based on solution-processed halide perovskites thin films when they are excited with light with energy equal to or above their bandgap. We measure a quantum efficiency up to 2.2% and a lifetime of more than 25 h. Importantly, even after degradation, the electron emission can be completely regenerated to its maximum efficiency by deposition of a monolayer of Cs. The electron emission from halide perovskites can be tuned over the visible and ultraviolet spectrum, and operates at vacuum levels with pressures at least two-orders higher than in state-of-the-art semiconductor electron sources.
TL;DR: In this paper, the relationship between molecular structure and solid-state arrangement informs the design of new organic semiconductor (OSC) materials with improved optoelectronic properties, which can be used to improve the performance of organic semiconductors.
Abstract: Understanding the relationship between molecular structure and solid-state arrangement informs about the design of new organic semiconductor (OSC) materials with improved optoelectronic properties....
TL;DR: In this paper, the authors measured the photoluminescence (PL) decay for single-stranded DNA (ssDNA) functionalized carbon nanotubes (SWCNTs) as a function of the guanine content of the ssDNA oligo that dictates the redshifting of their PL emission peaks relative to the band-edge exciton.
Abstract: Chemical reactions between semiconducting single-wall carbon nanotubes (SWCNTs) and single-stranded DNA (ssDNA) achieve spatially patterned covalent functionalization sites and create coupled fluorescent quantum defects on the nanotube surface, tailoring SWCNT photophysics for applications such as single-photon emitters in quantum information technologies. The evaluation of relaxation dynamics of photoluminescence (PL) from those coupled quantum defects is essential for understanding the nanotube electronic structure and beneficial to the design of quantum light emitters. Here, we measured the PL decay for ssDNA-functionalized SWCNTs as a function of the guanine content of the ssDNA oligo that dictates the red-shifting of their PL emission peaks relative to the band-edge exciton. We then correlate the observed dependence of PL decay dynamics on energy red-shifts to the exciton potential energy landscape, which is modeled using first-principles approaches based upon the morphology of ssDNA-altered SWCNTs obtained by atomic force microscopy (AFM) imaging. Our simulations illustrate that the multiple guanine defects introduced within a single ssDNA strand strongly interact to create a deep exciton trapping well, acting as a single hybrid trap. The emission decay from the distinctive trapping potential landscape is found to be biexponential for ssDNA-modified SWCNTs. We attributed the fast time component of the biexponential PL decay to the redistribution of exciton population among the lowest energy bright states and a manifold of dark states emerging from the coupling of multiple guanine defects. The long lifetime component in the biexponential decay, on the other hand, is attributed to the redistribution of exciton population among different exciton trapping sites that arise from the binding of multiple ssDNA strands along the nanotube axis. AFM measurements indicate that those trapping sites are separated on average by ∼8 nm along the nanotube axis.
TL;DR: In this paper, an ab initio multiple cloning (AIMC) approach based on the multiconfigurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems.
Abstract: The recently developed ab initio multiple cloning (AIMC) approach based on the multiconfigurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems. The AIMC method is a controlled approximation to nonadiabatic dynamics with a particular strength in the proper description of decoherence effects because of the branching of vibrational wavepackets at a level crossing. Here, we report a new implementation of the AIMC algorithm in the open source NWChem computational chemistry program. The framework combines linear-response time-dependent density functional theory with Ehrenfest mean-field theory to determine the equations of motion for classical trajectories. The multidimensional wave function is decomposed into a superposition of Gaussian coherent states guided by Ehrenfest trajectories (i.e., MCE approach), which can clone with fully quantum mechanical amplitudes and phases. By using an efficient time-derivative based nonadiabatic coupling approach within the AIMC method, all observables are calculated on-the-fly in the nonadiabatic molecular dynamics process. As a representative example, we apply our implementation to study the ultrafast photoinduced electronic and vibrational energy transfer in a pyridine molecule. The effects of the cloning procedure on electronic and vibrational coherence, relaxation and unidirectional energy transfer are discussed. This new AIMC implementation provides a high-level nonadiabatic molecular dynamics framework for simulating photoexcited dynamics in complex molecular systems and experimentally relevant ultrafast spectroscopic probes, such as nonlinear coherent optical and X-ray signals.
TL;DR: In this paper, the sp3-defect due to covalent functionalization of a single-walled carbon nanotube (SWCNT) results in a new red-shifted emissive excitons.
Abstract: Formation of the sp3-defect due to covalent functionalization of a single-walled carbon nanotube (SWCNT) results in a new red-shifted emissive excitons. Using density functional theory, we study th...
TL;DR: In this article, the authors reported the existence of the single-layer (SL) dititanium oxide Ti2O (labeled as MOene) that constructs a novel family of MXene based on transition-metal oxides.
Abstract: Using the first-principles calculations, we report the existence of the single-layer (SL) dititanium oxide Ti2O (labeled as MOene) that constructs a novel family of MXene based on transition-metal oxides. This MOene material strongly contrasts the conventional ones consisting of transition-metal carbides and/or nitrides. SL Ti2O has high thermal and dynamical stabilities because of the strong Ti-O ionic bonding interactions. Moreover, this material is an intrinsic electride and exhibits extremely low diffusion barriers of ∼12.0 and 6.3 meV for Li and Na diffusion, respectively. When applied as anode materials in lithium-ion batteries and sodium-ion batteries, it possesses a high energy storage capacity (960.23 mAhg-1), surpassing the traditional MXenes-based anodes. The superb electrochemical performance stems from the existing anionic electron on Ti2O surface. Astonishingly, SL Ti2O is also determined to be a superconductor with a superconducting transition temperature (Tc) of ∼9.8 K, which originates from the soft-mode of the first acoustic phonon branch and enhanced electron-phonon coupling in the low-frequency region. Furthermore, this soft-mode behaves much softer upon applying a compressive strain of 2%, leading to a higher Tc of 11.9 K. Our finding broadens the family of MXenes and could facilitate more experimental efforts toward future nanodevices.
TL;DR: In this article, the D-Wave quantum annealer was used to reduce the molecular Hamiltonian matrix in Slater determinant basis without chemical knowledge, and the connectivity between Slater determinants (as off-diagonal elements) was viewed as a graph adjacency matrix for determining multiple communities based on modularity maximization.
Abstract: Quantum chemistry is interested in calculating ground and excited states of molecular systems by solving the electronic Schrodinger equation. The exact numerical solution of this equation, frequently represented as an eigenvalue problem, remains unfeasible for most molecules and requires approximate methods. In this paper we introduce the use of Quantum Community Detection performed using the D-Wave quantum annealer to reduce the molecular Hamiltonian matrix in Slater determinant basis without chemical knowledge. Given a molecule represented by a matrix of Slater determinants, the connectivity between Slater determinants (as off-diagonal elements) is viewed as a graph adjacency matrix for determining multiple communities based on modularity maximization. A gauge metric based on perturbation theory is used to determine the lowest energy cluster. This cluster or sub-matrix of Slater determinants is used to calculate approximate ground state and excited state energies within chemical accuracy. The details of this method are described along with demonstrating its performance across multiple molecules of interest and bond dissociation cases. These examples provide proof-of-principle results for approximate solution of the electronic structure problem using quantum computing. This approach is general and shows potential to reduce the computational complexity of post-Hartree-Fock methods as future advances in quantum hardware become available.
TL;DR: In this article, the authors model the interactions between two sp3-defects placed at various distances in the (6,5) carbon nanotubes using time-dependent density functional theory.
Abstract: Covalent functionalization of single-walled carbon nanotubes (SWCNTs) with organic molecules results in red-shifted emissive states associated with sp3-defects in the tube lattice, which facilitate their improved optical functionality, including single-photon emission. The energy of the defect-based electronic excitations (excitons) depends on the molecular adducts, the configuration of the defect, and concentration of defects. Here we model the interactions between two sp3-defects placed at various distances in the (6,5) SWCNT using time-dependent density functional theory. Calculations reveal that these interactions conform to the effective model of J-aggregates for well-spaced defects (>2 nm), leading to a red-shifted and optically allowed (bright) lowest energy exciton. H-aggregate behavior is not observed for any defect orientations, which is beneficial for emission. The splitting between the lowest energy bright and optically forbidden (dark) excitons and the pristine excitonic band are controlled by the single-defect configurations and their axial separation. These findings enable a synthetic design strategy for SWCNTs with tunable near-infrared emission.
TL;DR: In this paper, the authors measured the low-temperature photoluminescence (PL) dynamics and the polarization-resolved fluorescence line narrowing spectra from ensembles of these strained CdSe quantum dots.
Abstract: Colloidal CdSe quantum dots (QDs) designed with a high degree of asymmetric internal strain have recently been shown to host a number of desirable optical properties including subthermal room-temperature line widths, suppressed spectral diffusion, and high photoluminescence (PL) quantum yields. It remains an open question, however, whether they are well-suited for applications requiring emission of identical single photons. Here we measure the low-temperature PL dynamics and the polarization-resolved fluorescence line narrowing spectra from ensembles of these strained QDs. Our spectroscopy reveals the radiative recombination rates of bright and dark excitons, the relaxation rate between the two, and the energy spectra of the quantized acoustic phonons in the QDs that can contribute to relaxation processes. In comparison to conventional colloidal CdSe/ZnS core/shell QDs, we find that in asymmetrically strained CdSe QDs over six times more light is emitted directly by the bright exciton. These results are therefore encouraging for the prospects of chemically synthesized colloidal QDs as emitters of single indistinguishable photons.
TL;DR: In this article, the relationship between structural variations and the resulting charge carrier dynamics at finite temperature in 2D hybrid halide perovskites is investigated and the 3AMP and 4AMP spacer cations are found to have a profound impact on the structural dynamics.
Abstract: The past six years have witnessed the rapid growth of interest in Dion–Jacobson (DJ) phase two-dimensional (2D) hybrid halide perovskites as optoelectronic materials with considerable intrinsic stability. The precise relationships between structural variations and the resulting charge carrier dynamics at finite temperature in these materials are keys to practical applications and are not yet completely understood. Here, we study 3-(aminomethyl) piperidinium (3AMP) and 4-(aminomethyl) piperidinium (4AMP) spacer cation-based lead iodide DJ phase systems and find these spacer cations to have a profound impact on the structural dynamics. Particularly, large conformational dynamics of the 3AMP-based perovskite compared to that of the 4AMP at room temperature leads to pronounced state energy fluctuation near band edges and further results in a shorter quantum coherence. The faster quantum decoherence of the 3AMP spacer-based perovskite underpins a longer nonradiative lifetime, offering insight into its superior performance as an optoelectronic material. This work sheds light on the relationship between structural fluctuations and charge carrier dynamics that can help in designing 2D perovskites with superior photophysical properties.
TL;DR: In this paper, the authors explored the energy transfer in a dye-end-capped conjugated polymer by using atomistic nonadiabatic excited-state molecular dynamics.
Abstract: Polymer-based guest-host systems represent a promising class of materials for efficient light-emitting diodes. The energy transfer from the polymer host to the guest is the key process in light generation. Therefore, microscopic descriptions of the different mechanisms involved in the energy transfer can contribute to enlighten the basis of the highly efficient light harvesting observed in this kind of materials. Herein, the nature of intramolecular energy transfer in a dye-end-capped conjugated polymer is explored by using atomistic nonadiabatic excited-state molecular dynamics. Linear perylene end-capped (PEC) polyindenofluorenes (PIF), consisting of n (n = 2, 4, and 6) repeat units, i.e., PEC-PIFn oligomers, are considered as model systems. After photoexcitation at the oligomer absorption maximum, an initial exciton becomes self-trapped on one of the monomer units (donors). Thereafter, an efficient ultrafast through-space energy transfer from this unit to the perylene acceptor takes place. We observe that this energy transfer occurs equally well from any monomer unit on the chain. Effective specific vibronic couplings between each monomer and the acceptor are identified. These oligomer → end-cap energy transfer steps do not match with the rates predicted by Forster-type energy transfer. The through-space and through-bond mechanisms are two distinct channels of energy transfer. The former dominates the overall process, whereas the through-bond energy transfer between indenofluorene monomer units along the oligomer backbone only makes a minor contribution.
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TL;DR: ClusterVQE as discussed by the authors splits the initial qubit space into subspaces (qubit clusters) which are further distributed on individual (shallower) quantum circuits to obtain ground or excited states of molecules.
Abstract: The variational quantum eigensolver (VQE) is one of the most promising algorithms to find eigenvalues and eigenvectors of a given Hamiltonian on noisy intermediate-scale quantum (NISQ) devices. A particular application is to obtain ground or excited states of molecules. The practical realization is currently limited by the complexity of quantum circuits. Here we present a novel approach to reduce quantum circuit complexity in VQE for electronic structure calculations. Our algorithm, called ClusterVQE, splits the initial qubit space into subspaces (qubit clusters) which are further distributed on individual (shallower) quantum circuits. The clusters are obtained based on quantum mutual information reflecting maximal entanglement between qubits, whereas entanglement between different clusters is taken into account via a new "dressed" Hamiltonian. ClusterVQE therefore allows exact simulation of the problem by using fewer qubits and shallower circuit depth compared to standard VQE at the cost of additional classical resources. In addition, a new gradient measurement method without using an ancillary qubit is also developed in this work. Proof-of-principle demonstrations are presented for several molecular systems based on quantum simulators as well as an IBM quantum device with accompanying error mitigation. The efficiency of the new algorithm is comparable to or even improved over qubit-ADAPT-VQE and iterative Qubit Coupled Cluster (iQCC), state-of-the-art circuit-efficient VQE methods to obtain variational ground state energies of molecules on NISQ hardware. Above all, the new ClusterVQE algorithm simultaneously reduces the number of qubits and circuit depth, making it a potential leader for quantum chemistry simulations on NISQ devices.
TL;DR: In this article, the authors used density functional theory to explore the possible application of pure inorganic perovskites (CsPbBr3 and CsPbI3) as photocathodes.
Abstract: Photocathodes emit electrons when illuminated, a process utilized across many technologies. Cutting-edge applications require a set of operating conditions that are not met with current photocathode materials. Meanwhile, halide perovskites have been studied extensively and have shown a lot of promise for a wide variety of optoelectronic applications. Well-documented halide perovskite properties such as inexpensive growth techniques, improved carrier mobility, low trap density, and tunable direct band gaps make them promising candidates for next-generation photocathode materials. Here, we use density functional theory to explore the possible application of pure inorganic perovskites (CsPbBr3 and CsPbI3) as photocathodes. It is determined that the addition of a Cs coating improved the performance by lowering the work function anywhere between 1.5 and 3 eV depending on the material, crystal surface, and surface coverage. A phenomenological model, modified from that developed by Gyftopoulos and Levine, is used to predict the reduction in work function with Cs coverage. The results of this work aim to guide the further experimental development of Cs-coated halide perovskites for photocathode materials.
TL;DR: In this article, nonadiabatic (NAMD) and adiabatic molecular dynamics simulations of the transition-state dynamics of photoexcited cyclooctatetraene (COT) are presented.
Abstract: In the current study, we present nonadiabatic (NAMD) and adiabatic molecular dynamics simulations of the transition-state dynamics of photoexcited cyclooctatetraene (COT). The equilibrium-state structure and absorption spectra are analyzed using the semiempirical Austin Model 1 potential. The NAMD simulations are obtained by a surface-hopping algorithm. We analyzed in detail an active excited to ground state relaxation pathway accompanied by an S2/S3(D2d) → S1(D8h) → S0(D4h) → S0(D2d) double-bond shifting mechanism. The simulated excitation lifetime is in good agreement with experiment. The first excited singlet state S1 plays a crucial role in the photochemistry. The obtained critical molecular conformations, energy barrier, and transition-state lifetime results will provide a basis for further investigations of the bond-order inversion and photoswitching process of COT.