Stabilization of Charge-Transfer Excited States in Biological Systems: A Computational Focus on the Special Pair in Photosystem II Reaction Centers

Charge-transfer (CT) excited states play an important role in many biological processes. However, many computational approaches often inadequately address the equilibration effects of nuclear and environmental degrees of freedom on these states. One prominent example of systems in which CT states are of utmost importance is reaction centers (RC) in photosystems. Here we use a multiscale approach combined with time-dependent density functional theory to explore the lowest CT excited state of the special pair PD1-PD2 in the Photosystem II-RC of a cyanobacterium. We find that the nonequilibrium CT excited state resides near the Soret band, making an exciton the lowest-energy excited state. However, accounting for nuclear and state-specific dielectric equilibration along the CT potential energy surface (PES), the CT state PD1--PD2+ stabilizes energetically below the excitonic state. This underscores the crucial role of state-specific solvation in mapping the PES of CT states, as demonstrated in a simplified dimer model.

Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential

Atomistic simulation has a broad range of applications from drug design to materials discovery. Machine learning interatomic potentials (MLIPs) have become an efficient alternative to computationally expensive ab initio simulations. For this reason, chemistry and materials science would greatly benefit from a general reactive MLIP, that is, an MLIP that is applicable to a broad range of reactive chemistry without the need for refitting. Here we develop a general reactive MLIP (ANI-1xnr) through automated sampling of condensed-phase reactions. ANI-1xnr is then applied to study five distinct systems: carbon solid-phase nucleation, graphene ring formation from acetylene, biofuel additives, combustion of methane and the spontaneous formation of glycine from early earth small molecules. In all studies, ANI-1xnr closely matches experiment (when available) and/or previous studies using traditional model chemistry methods. As such, ANI-1xnr proves to be a highly general reactive MLIP for C, H, N and O elements in the condensed phase, enabling high-throughput in silico reactive chemistry experimentation.

Machine Learning Potentials with the Iterative Boltzmann Inversion: Training to Experiment

Methodologies for training machine learning potentials (MLPs) with quantum-mechanical simulation data have recently seen tremendous progress. Experimental data have a very different character than simulated data, and most MLP training procedures cannot be easily adapted to incorporate both types of data into the training process. We investigate a training procedure based on iterative Boltzmann inversion that produces a pair potential correction to an existing MLP using equilibrium radial distribution function data. By applying these corrections to an MLP for pure aluminum based on density functional theory, we observe that the resulting model largely addresses previous overstructuring in the melt phase. Interestingly, the corrected MLP also exhibits improved performance in predicting experimental diffusion constants, which are not included in the training procedure. The presented method does not require autodifferentiating through a molecular dynamics solver and does not make assumptions about the MLP architecture. Our results suggest a practical framework for incorporating experimental data into machine learning models to improve the accuracy of molecular dynamics simulations.

Machine Learning Framework for Modeling Exciton Polaritons in Molecular Materials

A light-matter hybrid quasiparticle, called a polariton, is formed when molecules are strongly coupled to an optical cavity. Recent experiments have shown that polariton chemistry can manipulate chemical reactions. Polariton chemistry is a collective phenomenon, and its effects increase with the number of molecules in a cavity. However, simulating an ensemble of molecules in the excited state coupled to a cavity mode is theoretically and computationally challenging. Recent advances in machine learning (ML) techniques have shown promising capabilities in modeling ground-state chemical systems. This work presents a general protocol to predict excited-state properties, such as energies, transition dipoles, and nonadiabatic coupling vectors with the hierarchically interacting particle neural network. ML predictions are then applied to compute the potential energy surfaces and electronic spectra of a prototype azomethane molecule in the collective coupling scenario. These computational tools provide a much-needed framework to model and understand many molecules' emerging excited-state polariton chemistry.

Dielectric Screening and Charge-Transfer in 2D Lead-Halide Perovskites for Reduced Exciton Binding Energies

Layered lead-halide perovskites have shown tremendous success as an active material for optoelectronics. This is attributed to the electronic structure of the inorganic sublattice and large exciton binding energies due to quantum and dielectric confinement. Expanding functionalities for applications that depend on free-carrier generation requires new material design routes to decrease the binding energy. Here we use electronic structure methods with model Bethe-Salpeter equation (BSE) to examine the contributions of the dielectric screening and charge-transfer excited-states to the exciton binding energy of phenylethylammonium (PEA2PbBr4) and naphthlethylammonium (NEA2PbBr4) lead-bromide perovskites. Our model BSE calculations show that NEA introduces hole acceptor states which impose charge-transfer character on the exciton along with larger dielectric screening. This substantially decreases the exciton binding compared to PEA. This result suggests the use of organic cations with high dielectric screening and hole acceptor states as a viable strategy for reducing exciton binding energies in two-dimensional halide perovskites.

Quantum Simulation of Molecular Response Properties in the NISQ Era

Accurate modeling of the response of molecular systems to an external electromagnetic field is challenging on classical computers, especially in the regime of strong electronic correlation. In this article, we develop a quantum linear response (qLR) theory to calculate molecular response properties on near-term quantum computers. Inspired by the recently developed variants of the quantum counterpart of equation of motion (qEOM) theory, the qLR formalism employs "killer condition" satisfying excitation operator manifolds that offer a number of theoretical advantages along with reduced quantum resource requirements. We also used the qEOM framework in this work to calculate the state-specific response properties. Further, through noiseless quantum simulations, we show that response properties calculated using the qLR approach are more accurate than the ones obtained from the classical coupled-cluster-based linear response models due to the improved quality of the ground-state wave function obtained using the ADAPT-VQE algorithm.

Plasmon mediated coherent population oscillations in molecular aggregates

The strong coherent coupling of quantum emitters to vacuum fluctuations of the light field offers opportunities for manipulating the optical and transport properties of nanomaterials, with potential applications ranging from ultrasensitive all-optical switching to creating polariton condensates. Often, ubiquitous decoherence processes at ambient conditions limit these couplings to such short time scales that the quantum dynamics of the interacting system remains elusive. Prominent examples are strongly coupled exciton-plasmon systems, which, so far, have mostly been investigated by linear optical spectroscopy. Here, we use ultrafast two-dimensional electronic spectroscopy to probe the quantum dynamics of J-aggregate excitons collectively coupled to the spatially structured plasmonic fields of a gold nanoslit array. We observe rich coherent Rabi oscillation dynamics reflecting a plasmon-driven coherent exciton population transfer over mesoscopic distances at room temperature. This opens up new opportunities to manipulate the coherent transport of matter excitations by coupling to vacuum fields.

Benchmark Data Set of Crystalline Organic Semiconductors

This work reports a Benchmark Data set of Crystalline Organic Semiconductors to test calculations of the structural and electronic properties of these materials in the solid state. The data set contains 67 crystals consisting of mostly rigid molecules with a single dominant conformer, covering the majority of known structural types. The experimental crystal structure is available for the entire data set, whereas zero-temperature unit cell volume can be reliably estimated for a subset of 28 crystals. Using this subset, we benchmark r2SCAN-D3 and PBE-D3 density functionals. Then, for the entire data set, we benchmark approximate density functional theory (DFT) methods, including GFN1-xTB and DFTB3(3ob-3-1), with various dispersion corrections against r2SCAN-D3. Our results show that r2SCAN-D3 geometries are accurate within a few percent, which is comparable to the statistical uncertainty of experimental data at a fixed temperature, but the unit cell volume is systematically underestimated by 2% on average. The several times faster PBE-D3 provides an unbiased estimate of the volume for all systems except for molecules with highly polar bonds, for which the volume is substantially overestimated in correlation with the underestimation of atomic charges. Considered approximate DFT methods are orders of magnitude faster and provide qualitatively correct but overcompressed crystal structures unless the dispersion corrections are fitted by unit cell volume.

Twisting Aromaticity and Photoinduced Dynamics in Hexapole Helicenes

Curved aromatic molecules are attractive electronic materials, where an additional internal strain uniquely modifies their structure, aromaticity, dynamics, and optical properties. Helicenes are examples of such twisted conjugated systems. Herein, we analyze the photoinduced dynamics in different stereoisomers of a hexapole helicene by using nonadiabatic excited-state molecular dynamics simulations. We explore how changes in symmetry and structural distortion modulate the intramolecular energy redistribution. We find that distinct helical assembly leads to different rigid distorted structures that in turn impact the nonradiative energy relaxation and ultimately formation of the self-trapped exciton. Subsequently, the value of the twisting angles relative to the central triphenylene core structure controls the global molecular aromaticity and electronic localization during the internal conversion process. Our work sheds light on how the future synthesis of novel curved aromatic compounds can be directed to attain specific desired electronic properties through the modulation of their twisted aromaticity.

Composition Dependent Strain Engineering of Lead-Free Halide Double Perovskite: Computational Insights

The critical photophysical properties of lead-free halide double perovskites (HDPs) must be substantially improved for various applications. In this regard, strain engineering is a powerful tool for enhancing optoelectronic performance with precise control. Here, we employ ab initio simulations to investigate the impact of mild compressive and tensile strains on the photophysics of Cs2AgB'X6 (B' = Sb, Bi; X = Cl, Br) perovskites. Depending on the pnictogen and halide atoms, the band gap and band edge positions of HDPs can be tuned to a significant extent by controlling the applied external strain. Cs2AgSbBr6 has the most substantial strain response under structural perturbations. The subtle electronic interactions among the participating orbitals and the band dispersion at the edge states are enhanced under compressive strain, reducing the carrier effective masses. The exciton binding energies for these Br-based HDPs are in the range 59-78 meV and weaken in the compressed lattices, suggesting improved free carrier generation. Overall, the study emphasizes the potential of lattice strain engineering to boost the photophysical properties of HDPs that can ultimately improve their optoelectronic performance.

NWChem: Recent and Ongoing Developments

This paper summarizes developments in the NWChem computational chemistry suite since the last major release (NWChem 7.0.0). Specifically, we focus on functionality, along with input blocks, that is accessible in the current stable release (NWChem 7.2.0) and in the "master" development branch, interfaces to quantum computing simulators, interfaces to external libraries, the NWChem github repository, and containerization of NWChem executable images. Some ongoing developments that will be available in the near future are also discussed.

X-ray and Optical Circular Dichroism as Local and Global Ultrafast Chiral Probes of [12]Helicene Racemization

Chirality is a fundamental molecular property that plays a crucial role in biophysics and drug design. Optical circular dichroism (OCD) is a well-established chiral spectroscopic probe in the UV-visible regime. Chirality is most commonly associated with a localized chiral center. However, some compounds such as helicenes (Figure 1) are chiral due to their screwlike global structure. In these highly conjugated systems, some electric and magnetic allowed transitions are distributed across the entire molecule, and OCD thus probes the global molecular chirality. Recent advances in X-ray sources, in particular the control of their polarization and spatial profiles, have enabled X-ray circular dichroism (XCD), which, in contrast to OCD, can exploit the localized and element-specific nature of X-ray electronic transitions. XCD therefore is more sensitive to local structures, and the chirality probed with it can be referred to as local. During the racemization of helicene, between opposite helical structures, the screw handedness can flip locally, making the molecule globally achiral while retaining a local handedness. Here, we use the racemization mechanism of [12]helicene as a model to demonstrate the capabilities of OCD and XCD as time-dependent probes for global and local chiralities, respectively. Our simulations demonstrate that XCD provides an excellent spectroscopic probe for the time-dependent local chirality of molecules.

Synergy of semiempirical models and machine learning in computational chemistry

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.

NEXMD v2.0 Software Package for Nonadiabatic Excited State Molecular Dynamics Simulations

We present NEXMD version 2.0, the second release of the NEXMD (Nonadiabatic EXcited-state Molecular Dynamics) software package. Across a variety of new features, NEXMD v2.0 incorporates new implementations of two hybrid quantum-classical dynamics methods, namely, Ehrenfest dynamics (EHR) and the Ab-Initio Multiple Cloning sampling technique for Multiconfigurational Ehrenfest quantum dynamics (MCE-AIMC or simply AIMC), which are alternative options to the previously implemented trajectory surface hopping (TSH) method. To illustrate these methodologies, we outline a direct comparison of these three hybrid quantum-classical dynamics methods as implemented in the same NEXMD framework, discussing their weaknesses and strengths, using the modeled photodynamics of a polyphenylene ethylene dendrimer building block as a representative example. We also describe the expanded normal-mode analysis and constraints for both the ground and excited states, newly implemented in the NEXMD v2.0 framework, which allow for a deeper analysis of the main vibrational motions involved in vibronic dynamics. Overall, NEXMD v2.0 expands the range of applications of NEXMD to a larger variety of multichromophore organic molecules and photophysical processes involving quantum coherences and persistent couplings between electronic excited states and nuclear velocity.

Neural network atomistic potentials for global energy minima search in carbon clusters

The global energy optimization problem is an acute and important problem in chemistry. It is crucial to know the geometry of the lowest energy isomer (global minimum, GM) of a given compound for the evaluation of its chemical and physical properties. This problem is especially relevant for atomic clusters. Due to the exponential growth of the number of local minima geometries with the increase of the number of atoms in the cluster, it is important to find a computationally efficient and reliable method to navigate the energy landscape and locate a true global minima structure. Newly developed neural network (NN) atomistic potentials offer a numerically efficient and relatively accurate approach for molecular structure optimization. An important question that needs to be answered is "Can NN potentials, trained on a given set, represent the potential energy surface (PES) of a neighboring domain?". In this work, we tested the applicability of ANI-1ccx and ANI-nr NN atomistic potentials for the global minima optimization of carbon clusters Cn (n = 3-10). We showed that with the introduction of the cluster connectivity restriction and consequent DFT or ab initio calculations, ANI-1ccx and ANI-nr can be considered as robust PES pre-samplers that can capture the GM structure even for large clusters such as C20.

Partitioning Quantum Chemistry Simulations with Clifford Circuits

Current quantum computing hardware is restricted by the availability of only few, noisy qubits which limits the investigation of larger, more complex molecules in quantum chemistry calculations on quantum computers in the near term. In this work, we investigate the limits of their classical and near-classical treatment while staying within the framework of quantum circuits and the variational quantum eigensolver. To this end, we consider naive and physically motivated, classically efficient product ansatz for the parametrized wavefunction adapting the separable-pair ansatz form. We combine it with post-treatment to account for interactions between subsystems originating from this ansatz. The classical treatment is given by another quantum circuit that has support between the enforced subsystems and is folded into the Hamiltonian. To avoid an exponential increase in the number of Hamiltonian terms, the entangling operations are constructed from purely Clifford or near-Clifford circuits. While Clifford circuits can be simulated efficiently classically, they are not universal. In order to account for missing expressibility, near-Clifford circuits with only few, selected non-Clifford gates are employed. The exact circuit structure to achieve this objective is molecule-dependent and is constructed using simulated annealing and genetic algorithms. We demonstrate our approach on a set of molecules of interest and investigate the extent of our methodology's reach.

Constructing the Mechanism of Dinoflagellate Luciferin Bioluminescence Using Computation

Dinoflagellate luciferin bioluminescence is unique since it does not rely on decarboxylation but is poorly understood compared to that of firefly, bacteria, and coelenterata luciferins. Here we computationally investigate possible protonation states, stereoisomers, a chemical mechanism, and the dynamics of the bioluminescence intermediate that is responsible for chemiexcitation. Using semiempirical dynamics, time-dependent density functional theory static calculations, and a correlation diagram, we find that the intermediate's functional group that is likely responsible for chemiexcitation is a 4-member ring, a dioxetanol, that undergoes [2π + 2π] cycloreversion and the biolumiphore is the cleaved structure. The simulated emission spectra and luciferase-dependent absorbance spectra agree with the experimental data, giving support to our proposed mechanism and biolumiphore. We also compute circular dichroism spectra of the intermediate's four stereoisomers to guide future experiments in differentiating them.

Vibrational Funnels for Energy Transfer in Organic Chromophores

Photoinduced intramolecular energy transfers in multichromophoric molecules involve nonadiabatic vibronic channels that act as energy transfer funnels. They commonly take place through specific directions of motion dictated by the nonadiabatic coupling vectors. Vibrational funnels may support persistent coherences between electronic states and sometimes delineate the presence of minor alternative energy transfer pathways. The ultimate confirmation of their role on the interchromophoric energy transfer can be achieved by performing nonadiabatic excited-state molecular dynamics simulations by selectively freezing the nuclear motions in question. Our results point out this strategy as a useful tool to identify and evaluate the impact of these vibrational funnels on the energy transfer processes and guide the in silico design of materials with tunable properties and enhanced functionalities. Our work encourages applications of this methodology to different chemical and biochemical processes such as reactive scattering and protein conformational changes, to name a few.

Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation

Extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) in its most recent shadow potential energy version has been implemented in the semiempirical PyTorch-based software PySeQM. The implementation includes finite electronic temperatures, canonical density matrix perturbation theory, and an adaptive Krylov subspace approximation for the integration of the electronic equations of motion within the XL-BOMB approach (KSA-XL-BOMD). The PyTorch implementation leverages the use of GPU and machine learning hardware accelerators for the simulations. The new XL-BOMD formulation allows studying more challenging chemical systems with charge instabilities and low electronic energy gaps. The current public release of PySeQM continues our development of modular architecture for large-scale simulations employing semi-empirical quantum-mechanical treatment. Applied to molecular dynamics, simulation of 840 carbon atoms, one integration time step executes in 4 s on a single Nvidia RTX A6000 GPU.

Molecular dynamics study of plasmon-mediated chemical transformations

Heterogeneous catalysis of adsorbates on metallic surfaces mediated by plasmons has potential high photoelectric conversion efficiency and controllable reaction selectivity. Theoretical modeling of dynamical reaction processes enables in-depth analyses complementing experimental investigations. Especially for plasmon-mediated chemical transformations, light absorption, photoelectric conversion, electron-electron scattering, and electron-phonon coupling occur simultaneously on different timescales, making it very challenging to delineate the complex interplay of different factors. In this work, a trajectory surface hopping non-adiabatic molecular dynamics method is used to investigate the dynamics of plasmon excitation in an Au₂₀-CO system, including hot carrier generation, plasmon energy relaxation, and CO activation induced by electron-vibration coupling. The electronic properties indicate that when Au₂₀-CO is excited, a partial charge transfer takes place from Au₂₀ to CO. On the other hand, dynamical simulations show that hot carriers generated after plasmon excitation transfer back and forth between Au₂₀ and CO. Meanwhile, the C-O stretching mode is activated due to non-adiabatic couplings. The efficiency of plasmon-mediated transformations (∼40%) is obtained based on the ensemble average of these quantities. Our simulations provide important dynamical and atomistic insights into plasmon-mediated chemical transformations from the perspective of non-adiabatic simulations.

Machine Learning Models Capture Plasmon Dynamics in Ag Nanoparticles

Highly energetic electron-hole pairs (hot carriers) formed from plasmon decay in metallic nanostructures promise sustainable pathways for energy-harvesting devices. However, efficient collection before thermalization remains an obstacle for realization of their full energy generating potential. Addressing this challenge requires detailed understanding of physical processes from plasmon excitation in the metal to their collection in a molecule or a semiconductor, where atomistic theoretical investigation may be particularly beneficial. Unfortunately, first-principles theoretical modeling of these processes is extremely costly, preventing a detailed analysis over a large number of potential nanostructures and limiting the analysis to systems with a few 100s of atoms. Recent advances in machine learned interatomic potentials suggest that dynamics can be accelerated with surrogate models which replace the full solution of the Schrödinger Equation. Here, we modify an existing neural network, Hierarchically Interacting Particle Neural Network (HIP-NN), to predict plasmon dynamics in Ag nanoparticles. The model takes as a minimum as three time steps of the reference real-time time-dependent density functional theory (rt-TDDFT) calculated charges as history and predicts trajectories for 5 fs in great agreement with the reference simulation. Further, we show that a multistep training approach in which the loss function includes errors from future time-step predictions can stabilize the model predictions for the entire simulated trajectory (∼25 fs). This extends the model's capability to accurately predict plasmon dynamics in large nanoparticles of up to 561 atoms, not present in the training data set. More importantly, with machine learning models on GPUs, we gain a speed-up factor of ∼10³ as compared with the rt-TDDFT calculations when predicting important physical quantities such as dynamic dipole moments in Ag₅₅ and a factor of ∼10⁴ for extended nanoparticles that are 10 times larger. This underscores the promise of future machine learning accelerated electron/nuclear dynamics simulations for understanding fundamental properties of plasmon-driven hot carrier devices.

How structural and vibrational features affect optoelectronic properties of non-stoichiometric quantum dots: computational insights

While stoichiometric quantum dots (QDs) have been well studied, a significant knowledge gap remains in the atomistic understanding of the non-stoichiometric ones, which are predominantly present during the experimental synthesis. Here, we investigate the effect of thermal fluctuations on structural and vibrational properties of non-stoichiometric cadmium selenide (CdSe) nanoclusters: anion-rich (Se-rich) and cation-rich (Cd-rich) using ab initio molecular dynamics (AIMD) simulations. While the excess atoms on the surface fluctuate more for a given QD type, the optical phonon modes are mostly composed of Se atoms dynamics, irrespective of the composition. Moreover, Se-rich QDs have higher bandgap fluctuations compared to Cd-rich QDs, suggesting poor optical properties of Se-rich QDs. Additionally, non-adiabatic molecular dynamics (NAMD) suggests faster non-radiative recombination for Cd-rich QDs. Altogether, this work provides insights into the dynamic electronic properties of non-stoichiometric QDs and proposes a rationale for the observed optical stability and superiority of cation-rich candidates for light emission applications.

On-the-Fly Nonadiabatic Dynamics Simulations of Single-Walled Carbon Nanotubes with Covalent Defects

Single-walled carbon nanotubes (SWCNTs) with covalent surface defects have been explored recently due to their promise for use in single-photon telecommunication emission and in spintronic applications. The all-atom dynamic evolution of electrostatically bound excitons (the primary electronic excitations) in these systems has only been loosely explored from a theoretical perspective due to the size limitations of these large systems (>500 atoms). In this work, we present computational modeling of nonradiative relaxation in a variety of SWCNT chiralities with single-defect functionalizations. Our excited-state dynamics modeling uses a trajectory surface hopping algorithm accounting for excitonic effects with a configuration interaction approach. We find a strong chirality and defect-composition dependence on the population relaxation (varying over 50-500 fs) between the primary nanotube band gap excitation E₁₁ and the defect-associated, single-photon-emitting E₁₁* state. These simulations give direct insight into the relaxation between the band-edge states and the localized excitonic state, in competition with dynamic trapping/detrapping processes observed in experiment. Engineering fast population decay into the quasi-two-level subsystem with weak coupling to higher-energy states increases the effectiveness and controllability of these quantum light emitters.

Monitoring vibronic coherences and molecular aromaticity in photoexcited cyclooctatetraene with an X-ray probe: a simulation study

Understanding conical intersection (CI) dynamics and subsequent conformational changes is key for exploring and controlling photo-reactions in aromatic molecules. Monitoring of their time-resolved dynamics remains a formidable experimental challenge. In this study, we simulate the photoinduced S₃ to S₁ non-adiabatic dynamics of cyclooctatetraene (COT), involving multiple CIs with relaxation times in good agreement with experiment. We further investigate the possibility to directly probe the CI passages in COT by off-resonant X-ray Raman spectroscopy (TRUECARS) and time-resolved X-ray diffraction (TRXD). We find that these signals sensitively monitor key chemical features during the ultrafast dynamics. First, we distinguish two CIs by using TRUECARS signals with their appearances at different Raman shifts. Second, we demonstrate that TRXD, where X-ray photons scatter off electron densities, can resolve ultrafast changes in the aromaticity of COT. It can further distinguish between planar and non-planar geometries explored during the dynamics, as e.g. two different tetraradical-type CIs. The knowledge gained from these measurements can give unique insight into fundamental chemical properties that dynamically change during non-adiabatic passages.

Uncertainty-driven dynamics for active learning of interatomic potentials

Machine learning (ML) models, if trained to data sets of high-fidelity quantum simulations, produce accurate and efficient interatomic potentials. Active learning (AL) is a powerful tool to iteratively generate diverse data sets. In this approach, the ML model provides an uncertainty estimate along with its prediction for each new atomic configuration. If the uncertainty estimate passes a certain threshold, then the configuration is included in the data set. Here we develop a strategy to more rapidly discover configurations that meaningfully augment the training data set. The approach, uncertainty-driven dynamics for active learning (UDD-AL), modifies the potential energy surface used in molecular dynamics simulations to favor regions of configuration space for which there is large model uncertainty. The performance of UDD-AL is demonstrated for two AL tasks: sampling the conformational space of glycine and sampling the promotion of proton transfer in acetylacetone. The method is shown to efficiently explore the chemically relevant configuration space, which may be inaccessible using regular dynamical sampling at target temperature conditions.

Quantum self-consistent equation-of-motion method for computing molecular excitation energies, ionization potentials, and electron affinities on a quantum computer

Near-term quantum computers are expected to facilitate material and chemical research through accurate molecular simulations. Several developments have already shown that accurate ground-state energies for small molecules can be evaluated on present-day quantum devices. Although electronically excited states play a vital role in chemical processes and applications, the search for a reliable and practical approach for routine excited-state calculations on near-term quantum devices is ongoing. Inspired by excited-state methods developed for the unitary coupled-cluster theory in quantum chemistry, we present an equation-of-motion-based method to compute excitation energies following the variational quantum eigensolver algorithm for ground-state calculations on a quantum computer. We perform numerical simulations on H2, H4, H2O, and LiH molecules to test our quantum self-consistent equation-of-motion (q-sc-EOM) method and compare it to other current state-of-the-art methods. q-sc-EOM makes use of self-consistent operators to satisfy the vacuum annihilation condition, a critical property for accurate calculations. It provides real and size-intensive energy differences corresponding to vertical excitation energies, ionization potentials and electron affinities. We also find that q-sc-EOM is more suitable for implementation on NISQ devices as it is expected to be more resilient to noise compared with the currently available methods.

Signatures of Chemical Dopants in Simulated Resonance Raman Spectroscopy of Carbon Nanotubes

Single-walled carbon nanotubes (SWCNTs) with organic sp² or sp³ hybridization defects allow the robust tunability of many optoelectronic properties in these topologically interesting quasi-one-dimensional materials. Recent resonant Raman experiments have illuminated new features in the intermediate-frequency region upon functionalization that change with the degree of functionalization as well as with interactions between defect sites. In this Letter, we report ab initio simulated near-resonant Raman spectroscopy results for pristine and chemically functionalized SWCNT models and find new features concomitant with experimental observations. We are able to assign the character of these features by varying the frequency of the external Raman laser frequency near the defect-induced E₁₁* optical transition using a perturbative treatment of the electronic structure of the system. The obtained insights establish relationships between the nanotube atomistic structure and Raman spectra facilitating further exploration of SWCNTs with tunable optical properties tuned by chemical functionalization.

Light-Induced Structural Dynamics and Charge Transport in Layered Halide Perovskite Thin Films

The dynamic nature of the metal halide perovskite lattice upon photoexcitation plays a vital role in their properties. Here we report an observation of light-induced structure dynamics in quasi-2D Ruddlesden-Popper phase perovskite thin films and its impact on the carrier transport properties. By a time-resolved X-ray scattering technique, we observe a rapid lattice expansion upon photoexcitation, followed by a slow relaxation over the course of 100 ns in the dark. Theoretical modeling suggests that the expansion originates from the lattice's thermal fluctuations caused by photon energy deposition. Power dependent optical spectroscopy and photoconductivity indicate that high laser powers triggered a strong local structural disorder, which increased the charge dissociation activation energy that results in localized transport. Our study investigates the impact of laser energy deposition on the lattices and the subsequent carrier transport properties, that are relevant to device operations.

Investigation of plasmon relaxation mechanisms using nonadiabatic molecular dynamics

Hot carriers generated from the decay of plasmon excitation can be harvested to drive a wide range of physical or chemical processes. However, their generation efficiency is limited by the concomitant phonon-induced relaxation processes by which the energy in excited carriers is transformed into heat. However, simulations of dynamics of nanoscale clusters are challenging due to the computational complexity involved. Here, we adopt our newly developed Trajectory Surface Hopping (TSH) nonadiabatic molecular dynamics algorithm to simulate plasmon relaxation in Au20 clusters, taking the atomistic details into account. The electronic properties are treated within the Linear Response Time-Dependent Tight-binding Density Functional Theory (LR-TDDFTB) framework. The relaxation of plasmon due to coupling to phonon modes in Au20 beyond the Born–Oppenheimer approximation is described by the TSH algorithm. The numerically efficient LR-TDDFTB method allows us to address a dense manifold of excited states to ensure the inclusion of plasmon excitation. Starting from the photoexcited plasmon states in Au20 cluster, we find that the time constant for relaxation from plasmon excited states to the lowest excited states is about 2.7 ps, mainly resulting from a stepwise decay process caused by low-frequency phonons of the Au20 cluster. Furthermore, our simulations show that the lifetime of the phonon-induced plasmon dephasing process is ∼10.4 fs and that such a swift process can be attributed to the strong nonadiabatic effect in small clusters. Our simulations demonstrate a detailed description of the dynamic processes in nanoclusters, including plasmon excitation, hot carrier generation from plasmon excitation dephasing, and the subsequent phonon-induced relaxation process.

Charge Delocalization and Vibronic Couplings in Quadrupolar Squaraine Dyes

Squaraines are prototypical quadrupolar charge-transfer chromophores that have recently attracted much attention as building blocks for solution-processed photovoltaics, fluorescent probes with large two-photon absorption cross sections, and aggregates with large circular dichroism. Their optical properties are often rationalized in terms of phenomenological essential state models, considering the coupling of two zwitterionic excited states to a neutral ground state. As a result, optical transitions to the lowest S1 excited state are one-photon allowed, whereas the next higher S2 state can only be accessed by two-photon transitions. A further implication of these models is a substantial reduction of vibronic coupling to the ubiquitous high-frequency vinyl-stretching modes of organic materials. Here, we combine time-resolved vibrational spectroscopy, two-dimensional electronic spectroscopy, and quantum-chemical simulations to test and rationalize these predictions for nonaggregated molecules. We find small Huang-Rhys factors below 0.01 for the high-frequency, 1500 cm^-1 modes in particular, as well as a noticeable reduction for those of lower frequency modes in general for the electronic S0 → S1 transition. The two-photon allowed state S2 is well separated energetically from S1 and has weak vibronic signatures as well. Thus, the resulting pronounced concentration of the oscillator strength in a narrow region relevant to the lowest electronic transition makes squaraines and their aggregates exceptionally interesting for strong and ultrastrong coupling of excitons to localized light modes in external resonators with chiral properties that can largely be controlled by the molecular architecture.

Exciton-vibrational dynamics induces efficient self-trapping in a substituted nanoring

Cycloparaphenylenes, being the smallest segments of carbon nanotubes, have emerged as prototypes of the simplest carbon nanohoops. Their unique structure-dynamics-optical properties relationships have motivated a wide variety of synthesis of new related nanohoop species. Studies of how chemical changes, introduced in these new materials, lead to systems with new structural, dynamics and optical properties, expand their functionalities for optoelectronics applications. Herein, we study the effect that conjugation extension of a cycloparaphenylene through the introduction of a satellite tetraphenyl substitution has on its structural and dynamical properties. Our non-adiabatic excited state molecular dynamics simulations suggest that this substitution accelerates the electronic relaxation from the high-energy band to the lowest excited state. This is partially due to efficient conjugation achieved between specific phenyl units as introduced by the tetraphenyl substitution. We observe a particular exciton redistribution during relaxation, in which the tetraphenyl substitution plays a significant role. As a result, an efficient inter-band energy transfer takes place. Besides, the observed phonon-exciton interplay induces a significant exciton self-trapping. Our results encourage and guide the future studies of new phenyl substitutions in carbon nanorings with desired optoelectronic properties.

Charge-Transfer Luminescence in a Molecular Donor-Acceptor Complex: Computational Insights

Donor-acceptor molecular complexes are a popular class of materials utilizing charge-transfer states for practical applications. A recent class of donor-acceptor dyads based on the fluorescent BODIPY functionalized with triphenylamine (TPA) shows the peculiar property of dual fluorescence. It is hypothesized that instead of the sensitized charge-transfer state being optically dark, it provides an additional bright radiative pathway. Here we use time-dependent density functional theory to characterize the energetic alignment of excitonic and charge-transfer states in a BODIPY-TPA molecular complex. We observe that using a long-range exchange corrected functional in combination with state-specific solvation scheme gives a qualitatively correct alignment of the exciton and charge-transfer states and an enhancement in oscillator strength for the equilibrium solvated charge-transfer state, in agreement with experiment. This work provides rationalization of charge-transfer state emission and provides a foundation to explore charge-transfer using ab initio excited-state nonadiabatic dynamics.

Infinitene: Computational Insights from Nonadiabatic Excited State Dynamics

Progress in organic synthesis opens exploration of a rich diversity of molecules with interesting new structural topologies. This is the case of a recently synthesized helically twisted figure-eight molecule coined infinitene. The molecule belongs to a numerous family of looped polyarenes, where the degree of π-conjugation is controlled by high strain energies and steric hindrances. A particular balance of these ingredients leads to unusual optoelectronic properties potentially suitable for a range of applications in nanoelectronics and photonics. Due to its recent discovery, the photophysical properties of infinitene remain unexplored. In this Letter, atomistic nonadiabatic excited state molecular dynamics modeling unveils unique features of intramolecular electronic and vibrational energy relaxation and redistribution that take place after molecular photoexcitation. Our results detail relationships between optical and electronic properties providing useful knowledge for future molecular designs related to infinitene.

Adiabatic Excited-State Molecular Dynamics with an Explicit Solvent: NEXMD-SANDER Implementation

We present a method to link the Nonadiabatic EXcited-state Molecular Dynamics (NEXMD) package to the SANDER package supplied by AMBERTOOLS to provide excited-state adiabatic quantum mechanics/molecular mechanics (QM/MM) simulations. NEXMD is a computational package particularly developed to perform simulations of the photoexcitation and subsequent nonadiabatic electronic and vibrational energy relaxation in large multichromophoric conjugated molecules involving several coupled electronic excited states. The NEXMD-SANDER exchange has been optimized in order to achieve excited-state adiabatic dynamics simulations of large conjugated materials in a QM/MM environment, such as an explicit solvent. Dynamics of a substituted polyphenylene vinylene oligomer (PPV3-NO₂) in vacuum and different explicit solvents has been used as a test case by performing comparative analysis of changes in its optical spectrum, state-dependent conformational changes, and quantum bond orderings. The method has been tested and compared with respect to previous implicit solvent implementations. Also, the impact on the expansion of the QM region by including a variable number of solvent molecules has been analyzed. Altogether, these results encourage future implementations of NEXMD simulations using the same combination of methods.

Extending machine learning beyond interatomic potentials for predicting molecular properties

Machine learning (ML) is becoming a method of choice for modelling complex chemical processes and materials. ML provides a surrogate model trained on a reference dataset that can be used to establish a relationship between a molecular structure and its chemical properties. This Review highlights developments in the use of ML to evaluate chemical properties such as partial atomic charges, dipole moments, spin and electron densities, and chemical bonding, as well as to obtain a reduced quantum-mechanical description. We overview several modern neural network architectures, their predictive capabilities, generality and transferability, and illustrate their applicability to various chemical properties. We emphasize that learned molecular representations resemble quantum-mechanical analogues, demonstrating the ability of the models to capture the underlying physics. We also discuss how ML models can describe non-local quantum effects. Finally, we conclude by compiling a list of available ML toolboxes, summarizing the unresolved challenges and presenting an outlook for future development. The observed trends demonstrate that this field is evolving towards physics-based models augmented by ML, which is accompanied by the development of new methods and the rapid growth of user-friendly ML frameworks for chemistry.

Quantum Simulation of Molecular Electronic States with a Transcorrelated Hamiltonian: Higher Accuracy with Fewer Qubits

Simulation of electronic structure is one of the most promising applications on noisy intermediate-scale quantum (NISQ) era devices. However, NISQ devices suffer from a number of challenges like limited qubit connectivity, short coherence times, and sizable gate error rates. Thus, desired quantum algorithms should require shallow circuit depths and low qubit counts to take advantage of these devices. Here, we attempt to reduce quantum resource requirements for molecular simulations on a quantum computer while maintaining the desired accuracy with the help of classical quantum chemical theories of canonical transformation and explicit correlation. In this work, compact ab initio Hamiltonians are generated classically, in the second quantized form, through an approximate similarity transformation of the Hamiltonian with (a) an explicitly correlated two-body unitary operator with generalized pair excitations that remove the Coulombic electron-electron singularities from the Hamiltonian and (b) a unitary one-body operator to efficiently capture the orbital relaxation effects required for accurate description of the excited states. The resulting transcorrelated Hamiltonians are able to describe both the ground and the excited states of molecular systems in a balanced manner. Using the variational quantum eigensolver (VQE) method based on the unitary coupled cluster with singles and doubles (UCCSD) ansatz and only a minimal basis set (ANO-RCC-MB), we demonstrate that the transcorrelated Hamiltonians can produce ground state energies comparable to the reference CCSD energies with the much larger cc-pVTZ basis set. This leads to a reduction in the number of required CNOT gates by more than 3 orders of magnitude for the chemical species studied in this work. Furthermore, using the quantum equation of motion (qEOM) formalism in conjunction with the transcorrelated Hamiltonian, we are able to reduce the deviations in the excitation energies from the reference EOM-CCSD/cc-pVTZ values by an order of magnitude. The transcorrelated Hamiltonians developed here are Hermitian and contain only one- and two-body interaction terms and thus can be easily combined with any quantum algorithm for accurate electronic structure simulations.

Photochemical spin-state control of binding configuration for tailoring organic color center emission in carbon nanotubes

Incorporating fluorescent quantum defects in the sidewalls of semiconducting single-wall carbon nanotubes (SWCNTs) through chemical reaction is an emerging route to predictably modify nanotube electronic structures and develop advanced photonic functionality. Applications such as room-temperature single-photon emission and high-contrast bio-imaging have been advanced through aryl-functionalized SWCNTs, in which the binding configurations of the aryl group define the energies of the emitting states. However, the chemistry of binding with atomic precision at the single-bond level and tunable control over the binding configurations are yet to be achieved. Here, we explore recently reported photosynthetic protocol and find that it can control chemical binding configurations of quantum defects, which are often referred to as organic color centers, through the spin multiplicity of photoexcited intermediates. Specifically, photoexcited aromatics react with SWCNT sidewalls to undergo a singlet-state pathway in the presence of dissolved oxygen, leading to ortho binding configurations of the aryl group on the nanotube. In contrast, the oxygen-free photoreaction activates previously inaccessible para configurations through a triplet-state mechanism. These experimental results are corroborated by first principles simulations. Such spin-selective photochemistry diversifies SWCNT emission tunability by controlling the morphology of the emitting sites.

Chemical functionalization of the sidewalls of single-wall carbon nanotubes (SWCNTs) is an emerging route to introduce fluorescent quantum defects and tailor the emission properties. Here, authors demonstrate that spin-selective photochemistry diversifies SWCNT emission tunability by controlling the morphology of the emitting sites.

Nonadiabatic Molecular Dynamics Simulations Based on Time-Dependent Density Functional Tight-Binding Method

Nonadiabatic excited-state molecular dynamics underpin many photophysical and photochemical phenomena, such as exciton dynamics, charge separation and transport. In this work, we present an efficient nonadiabatic molecular dynamic (NAMD) simulation method based on time-dependent density functional tight-binding (TDDFTB) theory. Specifically, the adiabatic electronic structure, an essential NAMD input, is described at the TDDFTB level. The nonadiabatic effects originating from the coupled motions of electrons and nuclei are treated by the trajectory surface hopping algorithm. To improve the computational efficiency, nonadiabatic couplings between excited states within the TDDFTB method are derived and implemented using an analytical approach. Further, the time-dependent nonadiabatic coupling scalars are calculated based on the overlap between molecular orbitals rather than the Slater determinants to speed up the simulations. In addition, the electronic decoherence scheme and a state reassigned unavoided crossings algorithm, which has been implemented in the NEXMD software, are used to improve the accuracy of the simulated dynamics and handle trivial unavoided crossings. Finally, the photoinduced nonadiabatic dynamics of a benzene molecule are simulated to demonstrate our implementation. The results for excited state NAMD simulations of benzene molecule based on TDDFTB method compare well that obtained with numerically expensive time-dependent density functional theory. The proposed methodology provides an attractive theoretical simulation tool for predicting the photophysical and photochemical properties of complex materials.

Two Dimensional MOene: From Superconductors to Direct Semiconductors and Weyl Fermions

The number of semiconducting MXenes with direct band gaps is extremely low; thus, it is highly desirable to broaden the MXene family beyond carbides and nitrides to expand the palette of desired chemical and physical properties. Here, we theoretically report the existence of the single-layer (SL) dititanium oxide 2H-Ti₂O MOene (MXene-like 2D transition oxides), showing an Ising superconducting feature. Moreover, SL halogenated 2H- and 1T-Ti₂O monolayers display tunable semiconducting features and strong light-harvesting ability. In addition, the external strains can induce Weyl fermions via quantum phase transition in 2H-Ti₂OF₂ and Ti₂OCl₂ monolayers. Specifically, 2H- and 1T-Ti₂OF₂ are direct semiconductors with band gaps of 0.82 and 1.18 eV, respectively. Furthermore, the carrier lifetimes of SL 2H- and 1T-Ti₂OF₂ are evaluated to be 0.39 and 2.8 ns, respectively. This study extends emerging phenomena in a rich family of 2D MXene-like MOene materials, which provides a novel platform for next-generation optoelectronic and photovoltaic fields.

Impact of Graphene Quantum Dot Edge Morphologies on Their Optical Properties

The optoelectronic properties of functionalized graphene quantum dots (GQDs) have been explored by simulating electronic structure of three different shapes of GQDs containing exclusively zigzag or armchair edges in both pristine and functionalized forms. Absorption spectra and transition densities for the low-lying excited states are evaluated by using time-dependent density functional theory and compared for different functionalization species. The functionalization position dictates the optical properties of square GQDs, where isomers with CH₂ in the intermediate positions (excluding corner and center positions) have higher electronic transition energies and exciton delocalization than other isomers. Rhombic GQDs with all armchair edges exhibit high steric flexibility, and their complete passivation results in the largest structural deformation from planarity and strongest red-shifts. A steady red-shift in the absorption energy is observed following the order F, CH₃, Cl, and Br substitutions. This suggests that the steric effects due to large van der Waals radii overcome electronegative effects.

Control of Polaronic Behavior and Carrier Lifetimes via Metal and Anion Alloying in Chalcogenide Perovskites

Transition-metal perovskite chalcogenides (TMPCs) have emerged as lead-free alternatives to lead-halide perovskites and have been currently of increasing interest for optoelectronic applications because of their suitable band gaps, high carrier mobility, strong light absorption, and high stability. Here, we systematically report a study on the effects of Ti- and Se-alloying strategies on polaron behavior and carrier lifetimes in nonradiative recombination. Although such alloying can effectively tune the band gap of BaZrS₃, we observe localized small polaron formation upon Ti alloying and large polarons generating in Se alloying. Ti-alloying strengthens the electron-phonon coupling, leading to a reduced carrier lifetime. Remarkably, Se-alloying weakens the electron-phonon coupling and prolongs the nonradiative electron-hole recombination lifetime by up to 60% compared to that in pristine BaZrS₃ material. The simulations rationalize the difference in carrier lifetimes in TMPC alloys and provide guidelines for further improvements in TMPC-based photoelectronic devices.

Point Defects in Two-Dimensional Ruddlesden-Popper Perovskites Explored with Ab Initio Calculations

Two-dimensional Ruddlesden-Popper (RP) halide perovskites stand out as excellent layered materials with favorable optoelectronic properties for efficient light-emitting, spintronic, and other spin-related applications. However, properties often determined by defects are not well understood in these perovskite systems. This work investigates the ground state electronic structure of commonly formed defects in a typical RP perovskite structure by density functional theory. Our study reveals that these 2D perovskites generally retain their defect tolerance with limited perturbation of the electronic structure in the case of neutral-type point defects. In contrast, donor/acceptor defects induce deep midgap states, potentially causing harm to the material's electronic performance. To retain positive intrinsic properties, the halide vacancies and interstitial defects should be avoided. The observed strong electron localization results in trap states and consequently leads to reduced device performance. This understanding can guide experimental efforts that aim for improved 2D halide perovskite-based device performance.

Toward a QUBO-Based Density Matrix Electronic Structure Method

Density matrix electronic structure theory is used in many quantum chemistry methods to "alleviate" the computational cost that arises from directly using wave functions. Although density matrix based methods are computationally more efficient than wave function based methods, significant computational effort is involved. Because the Schrödinger equation needs to be solved as an eigenvalue problem, the time-to-solution scales cubically with the system size in mean-field type approaches such as Hartree-Fock and density functional theory and is solved as many times in order to reach charge or field self-consistency. We hereby propose and study a method to compute the density matrix by using a quadratic unconstrained binary optimization (QUBO) solver. This method could be useful to solve the problem with quantum computers and, more specifically, quantum annealers. Our proposed approach is based on a direct construction of the density matrix using a QUBO eigensolver. We explore the main parameters of the algorithm focusing on precision and efficiency. We show that, while direct construction of the density matrix using a QUBO formulation is possible, the efficiency and precision have room for improvement. Moreover, calculations performed with quantum annealing on D-Wave's new Advantage quantum computer are compared with results obtained with classical simulated annealing, further highlighting some problems of the proposed method. We also suggest alternative methods that could lead to a more efficient QUBO-based density matrix construction.

Ultrafast coherent photoexcited dynamics in a trimeric dendrimer probed by X-ray stimulated-Raman signals

The photoinduced ultrafast coherent inter-chromophore energy redistribution in a triarylamine trimer is explored using nonadiabatic excited state molecular dynamics followed by simulations of X-ray Raman signals. The nitrogencentered system ensures strong interchromophore interactions and, thus, the presence of coherences. Nevertheless, the multitude of non-deterministic photoinduced pathways during the ultrafast inter-branch migration of the excitation results in random confinement on some branches and, therefore, spatial exciton scrambling and loss of phase information at long times. We show that the vibronic coherence dynamics evolving into the incoherent scrambling mechanism on ultrafast 50 fs timescale, is accurately probed by the TRUECARS X-ray stimulated Raman signal. In combination with previous results, where the technique has revealed long-lived coherences in a rigid heterodimer, the signal is most valuable for detecting ultrafast molecular coherences or their absence. We demonstrate that X-ray Raman spectroscopy is a useful tool in the chemical design of functional molecular building blocks.

The photoinduced ultrafast coherent inter-chromophore energy redistribution in a triarylamine trimer is explored using nonadiabatic excited state molecular dynamics followed by simulations of X-ray Raman signals.

Plasmon-Enhanced Exciton Delocalization in Squaraine-Type Molecular Aggregates

Enlarging exciton coherence lengths in molecular aggregates is critical for enhancing the collective optical and transport properties of molecular thin film nanostructures or devices. We demonstrate that the exciton coherence length of squaraine aggregates can be increased from 10 to 24 molecular units at room temperature when preparing the aggregated thin film on a metallic rather than a dielectric substrate. Two-dimensional electronic spectroscopy measurements reveal a much lower degree of inhomogeneous line broadening for aggregates on a gold film, pointing to a reduced disorder. The result is corroborated by simulations based on a Frenkel exciton model including exciton-plasmon coupling effects. The simulation shows that localized, energetically nearly resonant excitons on spatially well separated segments can be radiatively coupled via delocalized surface plasmon polariton modes at a planar molecule-gold interface. Such plasmon-enhanced delocalization of the exciton wave function is of high importance for improving the coherent transport properties of molecular aggregates on the nanoscale. Additionally, it may help tailor the collective optical response of organic materials for quantum optical applications.

Sampling electronic structure quadratic unconstrained binary optimization problems (QUBOs) with Ocean and Mukai solvers

The most advanced D-Wave Advantage quantum annealer has 5000+ qubits, however, every qubit is connected to a small number of neighbors. As such, implementation of a fully-connected graph results in an order of magnitude reduction in qubit count. To compensate for the reduced number of qubits, one has to rely on special heuristic software such as qbsolv, the purpose of which is to decompose a large quadratic unconstrained binary optimization (QUBO) problem into smaller pieces that fit onto a quantum annealer. In this work, we compare the performance of the open-source qbsolv which is a part of the D-Wave Ocean tools and a new Mukai QUBO solver from Quantum Computing Inc. (QCI). The comparison is done for solving the electronic structure problem and is implemented in a classical mode (Tabu search techniques). The Quantum Annealer Eigensolver is used to map the electronic structure eigenvalue-eigenvector equation to a QUBO problem, solvable on a D-Wave annealer. We find that the Mukai QUBO solver outperforms the Ocean qbsolv with one to two orders of magnitude more accurate energies for all calculations done in the present work, both the ground and excited state calculations. This work stimulates the further development of software to assist in the utilization of modern quantum annealers.

Vibronic Photoexcitation Dynamics of Perylene Diimide: Computational Insights

Perylene diimide (PDI) represents a prototype material for organic optoelectronic devices because of its strong optical absorbance, chemical stability, efficient energy transfer, and optical and chemical tunability. Herein, we analyze in detail the vibronic relaxation of its photoexcitation using nonadiabatic excited-state molecular dynamics simulations. We find that after the absorption of a photon, which excites the electron to the second excited state, S₂, induced vibronic dynamics features persistent modulations in the spatial localization of electronic and vibrational excitations. These energy exchanges are dictated by strong vibronic couplings that overcome structural disorders and thermal fluctuations. Specifically, the electronic wavefunction periodically swaps between localizations on the right and left sides of the molecule. Within 1 ps of such dynamics, a nonradiative transition to the lowest electronic state, S₁, takes place, resulting in a complete delocalization of the wavefunction. The observed vibronic dynamics emerges following the electronic energy deposition in the direction that excites a combination of two dominant vibrational normal modes. This behavior is maintained even with a chemical substitution that breaks the symmetry of the molecule. We believe that our findings elucidate the nature of the complex dynamics of the optically excited states and, therefore, contribute to the development of tunable functionalities of PDIs and their derivatives.