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Hybrid 2D layered perovskites are solution-processed quantum wells whose optoelectronic properties are tunable by varying the thickness of the inorganic slab. Here Blancon et al. work out a general behavior for dependence of the excitonic properties in layered 2D perovskites.

INTRODUCTION. Upper extremity fractures comprise 84 % of all extremity fractures in children.MATERIAL AND METHODS. In 2004–2013, 504 operations were performed in children aged 5 to 17 years for various injuries of the upper extremity using image intensifiers, in Minsk clinical centre of Trauma and orthopaedics of 6th Minsk clinical Hospital (children’s Department)RESULTS. Immediate results were good or excellent in 98.8 % of patients. In 1.2 % of patients, post-traumatic transient neuropathy of the radial and median nerves was observed.CONCLUSIONS. Minimally invasive operations with image intensifiers performed to treat injuries of the upper extremity in children are highly effective and allow open reduction and skeletal traction to be avoided.

The field of data-driven chemistry is undergoing an evolution, driven by innovations in machine learning models for predicting molecular properties and behavior. Recent strides in ML-based interatomic potentials have paved the way for accurate modeling of diverse chemical and structural properties at the atomic level. The key determinant defining MLIP reliability remains the quality of the training data. A paramount challenge lies in constructing training sets that capture specific domains in the vast chemical and structural space. This Review navigates the intricate landscape of essential components and integrity of training data that ensure the extensibility and transferability of the resulting models. We delve into the details of active learning, discussing its various facets and implementations. We outline different types of uncertainty quantification applied to atomistic data acquisition and the correlations between estimated uncertainty and true error. The role of atomistic data samplers in generating diverse and informative structures is highlighted. Furthermore, we discuss data acquisition via modified and surrogate potential energy surfaces as an innovative approach to diversify training data. The Review also provides a list of publicly available data sets that cover essential domains of chemical space.

In this article, the nonadiabatic excited-state Molecular dynamics (NEXMD) package is linked with the SANDER package, provided by AMBERTOOLS. The combination of these software packages enables the simulation of photoinduced dynamics of large multichromophoric conjugated molecules involving several coupled electronic excited states embedded in an explicit solvent by using the quantum/mechanics/molecular mechanics (QM/MM) methodology. The fewest switches surface hopping algorithm, as implemented in NEXMD, is used to account for quantum transitions among the adiabatic excited-state simulations of the photoexcitation and subsequent nonadiabatic electronic transitions, and vibrational energy relaxation of a substituted polyphenylenevinylene oligomer (PPV3-NO2) in vacuum and methanol as an explicit solvent has been used as a test case. The impact of including specific solvent molecules in the QM region is also analyzed. Our NEXMD-SANDER QM/MM implementation provides a useful computational tool to simulate qualitatively solvent-dependent effects, like electron transfer, stabilization of charge-separated excited states, and the role of solvent reorganization in the molecular optical properties, observed in solution-based spectroscopic experiments.

We demonstrate a macrocoherent regime in exciton-polariton systems, where nonequilibrium polariton Bose-Einstein condensation coexists with macroscopically occupied vibrational states. Strong exciton-vibration coupling induces an effective optomechanical interaction between cavity polaritons and vibrational degrees of freedom of molecules, leading to vibrational amplification in a resonant blue-detuned configuration. This interaction provides a sympathetic mechanism to achieve vibrational condensation with potential applications in cavity-controlled chemistry, nonlinear, and quantum optics.

Dendrimers are branched polymers with wide applications to photosensitization, photocatalysis, photodynamic therapy, photovoltaic conversion, and light sensor amplification. The primary step of numerous photophysical and photochemical processes in many molecules involves ultrafast coherent electronic dynamics and charge oscillations triggered by photoexcitation. This electronic wavepacket motion at short times where the nuclei are frozen is known as attosecond charge migration. We show how charge migration in a dendrimer can be manipulated by placing it in an optical cavity and monitored by time-resolved X-ray diffraction. Our simulations demonstrate that the dendrimer charge migration modes and the character of photoexcited wave function can be significantly influenced by the strong light-matter interaction in the cavity. This presents a new avenue for modulating initial ultrafast charge dynamics and subsequently controlling coherent energy transfer in dendritic nanostructures.

Small metal-rich semiconducting quantum dots (QDs) are promising for solid-state lighting and single-photon emission due to their highly tunable yet narrow emission line widths. Nonetheless, the anionic ligands commonly employed to passivate these QDs exert a substantial influence on the optoelectronic characteristics, primarily owing to strong electron-phonon interactions. In this work, we combine time-domain density functional theory and nonadiabatic molecular dynamics to investigate the excited charge carrier dynamics of Cd 28 Se 17 X 22 QDs (X = HCOO - , OH - , Cl - , and SH - ) at ambient conditions. These chemically distinct but regularly used molecular groups influence the dynamic surface-ligand interfacial interactions in Cd-rich QDs, drastically modifying their vibrational characteristics. The strong electron-phonon coupling leads to substantial transient variations at the band edge states. The strength of these interactions closely depends on the physicochemical characteristics of passivating ligands. Consequently, the ligands largely control the nonradiative recombination rates and emission characteristics in these QDs. Our simulations indicate that Cd 28 Se 17 (OH) 22 has the fastest nonradiative recombination rate due to the strongest electron-phonon interactions. Conversely, QDs passivated with thiolate or chloride exhibit considerably longer carrier lifetimes and suppressed nonradiative processes. The ligand-controlled electron-phonon interactions further give rise to the broadest and narrowest intrinsic optical line widths for OH and Cl-passivated single QDs, respectively. Obtained computational insights lay the groundwork for designing appropriate passivating ligands on metal-rich QDs, making them suitable for a wide range of applications, from blue LEDs to quantum emitters.

Organic color centers (OCCs), generated by the covalent functionalization of single-walled carbon nanotubes, have been exploited for chemical sensing, bioimaging, and quantum technologies. However, monovalent OCCs can assume at least 6 different bonding configurations on the sp 2 carbon lattice of a chiral nanotube, resulting in heterogeneous OCC photoluminescence emissions. Herein, we show that a heat-activated [2 + 2] cycloaddition reaction enables the synthesis of divalent OCCs with a reduced number of atomic bonding configurations. The chemistry occurs by simply mixing enophile molecules (e.g., methylmaleimide, maleic anhydride, and 4-cyclopentene-1,3-dione) with an ethylene glycol suspension of SWCNTs at elevated temperature (70-140 °C). Unlike monovalent OCC chemistries, we observe just three OCC emission peaks that can be assigned to the three possible bonding configurations of the divalent OCCs based on density functional theory calculations. Notably, these OCC photoluminescence peaks can be controlled by temperature to decrease the emission heterogeneity even further. This divalent chemistry provides a scalable way to synthesize OCCs with tightly controlled emissions for emerging applications.

The chirality transfer phenomenon is attractive for enhancing the optical functionality of nanomaterials by inducing sensitivity to the circular polarization states of photons. An underexplored aspect is how material properties of the achiral semiconductor impact the induced chiroptical signatures. Here we apply atomistic time-dependent density functional theory simulations to investigate the material properties that influence the chiroptical signatures of a lead halide perovskite nanocrystal with a chiral molecule bound to the surface. First, we find that both lattice disorder created by surface strain and halide substitution can increase the chiroptical response of the perovskite quantum dots by an order of magnitude. Both phenomena are attributed to a broadening of the density of the electronically excited states. Second, the intensity of the anisotropy spectra decreases with increasing dot size with a power law decay. Overall, these insights can be used to help guide experimental realization of highly resolvable polarized optical features in semiconducting nanomaterials.

Energy transfer processes among units of light-harvesting homo-oligomers impact the efficiency of these materials as components in organic optoelectronic devices such as solar cells. Perylene diimide (PDI), a prototypical dye, features exceptional light absorption and highly tunable optical and electronic properties. These properties can be modulated by varying the number of PDI units and linkers between them. Herein, atomistic nonadiabatic excited state molecular dynamics is used to explore the energy transfer during the internal conversion of acetylene and diacetylene bridged dimeric and trimeric PDIs. Our simulations reveal a significant impact of the bridge type on the transient exciton localization/delocalization between units of PDI dimers. After electronic relaxation, larger exciton delocalization occurs in the PDI dimer connected by the diacetylene bridge with respect to the one connected by the shorter acetylene bridge. These changes can be rationalized by the Frenkel exciton model. We outline a technique for deriving parameters for this model using inputs provided by nonadiabatic dynamics simulations. Frenkel exciton description reveals an interplay between the relative strengths of the diagonal and off-diagonal disorders. Moreover, atomistic simulations and the Frenkel exciton model of the PDI trimer systems corroborate in detail the localization properties of the exciton on the molecular units during the internal conversion to the lowest-energy excited state when the units become effectively decoupled. Overall, atomistic nonadiabatic simulations in combination with the Frenkel exciton model can serve as a predictive framework for analyzing and predicting desired exciton traps in PDI-based oligomers designed for organic electronics and photonic devices.

Intentional distortions of [BX 6 ] octahedra within perovskite structures have been recognized as a potent strategy for precise band gap adjustments and optimization of their photovoltaic properties, yet information regarding charge carrier dynamics linked to octahedral distortion under ambient conditions for chalcogenide perovskites remains limited. In this study, we utilize ab initio nonadiabatic molecular dynamics to explore the dynamics of photogenerated carriers in a representative two-dimensional Ba 3 Zr 2 S 7 material in the Ruddlesden-Popper phase. The theoretical results highlight the influence of octahedral rotation on the materials' stability and carrier recombination lifetime of the system. Specifically, the octahedrally rotating P 4 2 / mnm phase exhibits a prolonged nonradiative carrier recombination lifetime attributed to the stabilized electron-phonon coupling. These findings offer valuable insights into the fundamental physical characteristics of imposed octahedral distortion and its potential for optimizing the optoelectronic performance of 2D Ruddlesden-Popper Ba-Zr-S chalcogenide materials.

The efficiency of light-harvesting and energy transfer in multi-chromophore ensembles underpins natural photosynthesis. Dendrimers are highly branched synthetic multi-chromophoric conjugated supra-molecules that mimic these natural processes. After photoexcitation, their repeated units participate in a number of intramolecular electronic energy relaxation and redistribution pathways that ultimately funnel to a sink. Here, a model four-branched dendrimer with a pyrene core is theoretically studied using nonadiabatic molecular dynamics simulations. We evaluate excited-state photoinduced dynamics of the dendrimer, and demonstrate on-the-fly simulations of its transient absorption pump-probe (TA-PP) spectra. We show how the evolutions of the simulated TA-PP spectra monitor in real time photoinduced energy relaxation and redistribution, and provide a detailed microscopic picture of the relevant energy-transfer pathways. To the best of our knowledge, this is the first of this kind of on-the-fly atomistic simulation of TA-PP signals reported for a large molecular system., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Absorption spectroscopy probing transitions from shallow-core d and f orbitals in lanthanides and actinides reveals information about bonding and the electronic structure in compounds containing these elements. However, spectroscopy in this photon energy range is challenging because of the limited availability of light sources and extremely short penetration depths. In this work, we address these challenges using a tabletop extreme ultraviolet (XUV), ultrafast, laser-driven, high harmonic generation light source, which generates femtosecond pulses in the 40-140 eV range. We present reflection spectroscopy measurements at the N 4,5 (i.e., predominantly 4d to 5f transitions) and O 4,5 (i.e., 5d to 5f transitions) absorption edges on several lanthanide and uranium oxide crystals. We compare these results to density functional theory calculations to assign the electronic transitions and predict the spectra for other lanthanides. This work paves the way for laboratory-scale XUV absorption experiments for studying crystalline and molecular f-electron systems, with applications ranging from surface chemistry, photochemistry, and electronic or chemical structure determination to nuclear forensics.

We explore the potential of nanocrystals (a term used equivalently to nanoparticles) as building blocks for nanomaterials, and the current advances and open challenges for fundamental science developments and applications. Nanocrystal assemblies are inherently multiscale, and the generation of revolutionary material properties requires a precise understanding of the relationship between structure and function, the former being determined by classical effects and the latter often by quantum effects. With an emphasis on theory and computation, we discuss challenges that hamper current assembly strategies and to what extent nanocrystal assemblies represent thermodynamic equilibrium or kinetically trapped metastable states. We also examine dynamic effects and optimization of assembly protocols. Finally, we discuss promising material functions and examples of their realization with nanocrystal assemblies.

We report the development of a novel diagnostic tool, named wave function overlap tool (WFOT), designed to evaluate the overlap between wave functions computed at single-reference [i.e., time-dependent density functional theory or configuration interaction singles (CIS)] and multireference (i.e., CASSCF/CASPT2) electronic structure levels of theory. It relies on truncating the single- and multireference WFs to CIS-like expansions spanning the same configurational space and maximizing the molecular orbital overlap by means of a unitary transformation. To demonstrate the functionality of the tool, we calculate the transient spectrum of acetylacetone by evaluating excited state absorption signals with multireference quality on top of single-reference on-the-fly dynamics simulations. Semiautomatic spectra generation is facilitated by interfacing the tool with the COBRAMM package, which also allows one to use WFOT with several quantum chemistry codes such as Gaussian, NWChem, and OpenMolcas. Other exciting possibilities for the utilization of the code beyond the simulation of transient absorption spectroscopy are eventually discussed.

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., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

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 P D1 -P D2 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 P D1 - -P D2 + 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.

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.

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.

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 (PEA 2 PbBr 4 ) and naphthlethylammonium (NEA 2 PbBr 4 ) 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.

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.

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., (© 2023. The Author(s).)

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 r 2 SCAN-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 r 2 SCAN-D3. Our results show that r 2 SCAN-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.

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.

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 Cs 2 AgB'X 6 (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. Cs 2 AgSbBr 6 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.

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.

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.

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

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.

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 C n ( 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 C 20 .

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.

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.

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.

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.

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 ∼10 3 as compared with the rt-TDDFT calculations when predicting important physical quantities such as dynamic dipole moments in Ag 55 and a factor of ∼10 4 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.

Clostridium (C.) perfringens is the causative agent of necrotic enteritis (NE), an important enteric disease in poultry. Although a variety of virulence factors have been identified and as such the pathogenesis is well studied, data on colonization and sporulation during passage in the intestinal tract are scarce. This study, therefore, evaluated the behaviour of C. perfringens in the different intestinal compartments of broiler chickens during a NE trial. Necrotic enteritis-associated lesions were mostly found in the jejunum, where they were significantly more severe compared to the duodenum and ileum. Furthermore, a positive correlation between the total number of vegetative C. perfringens cells in the duodenum, jejunum, ileum, or distal colon and disease severity was observed. Additionally, in the caecum and distal colon, C. perfringens was mainly present as a spore. This observation has important consequences for NE treatment and prevention, as both the vegetative cells and C. perfringens spores should be targeted to avoid uptake of spores from the litter and reinfection of the birds after antibiotic treatment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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.

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 E 11 and the defect-associated, single-photon-emitting E 11 * 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.