Molecular dynamics simulation of shockwaves including some nonadiabatic effects

The recently developed ab initio multiple cloning (AIMC) approach based on the multiconfigurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems. The AIMC method is a controlled approximation to nonadiabatic dynamics with a particular strength in the proper description of decoherence effects because of the branching of vibrational wavepackets at a level crossing. Here, we report a new implementation of the AIMC algorithm in the open source NWChem computational chemistry program. The framework combines linear-response time-dependent density functional theory with Ehrenfest mean-field theory to determine the equations of motion for classical trajectories. The multidimensional wave function is decomposed into a superposition of Gaussian coherent states guided by Ehrenfest trajectories (i.e., MCE approach), which can clone with fully quantum mechanical amplitudes and phases. By using an efficient time-derivative based nonadiabatic coupling approach within the AIMC method, all observables are calculated on-the-fly in the nonadiabatic molecular dynamics process. As a representative example, we apply our implementation to study the ultrafast photoinduced electronic and vibrational energy transfer in a pyridine molecule. The effects of the cloning procedure on electronic and vibrational coherence, relaxation and unidirectional energy transfer are discussed. This new AIMC implementation provides a high-level nonadiabatic molecular dynamics framework for simulating photoexcited dynamics in complex molecular systems and experimentally relevant ultrafast spectroscopic probes, such as nonlinear coherent optical and X-ray signals.

A multiscale approach is proposed to address short-time nonadiabatic dynamics and long-time decay. We show the role of both radiative and non-radiative processes in cluster decay mechanisms on examples of rare-gas cluster fragmentation after electron impact ionization. Nonadiabatic molecular dynamics is used as an efficient tool for theoretical study on femto- and picosecond scales and a multiscale approach based on kinetic rates of radiative as well as non-radiative transitions, both considered as parallel reaction channels, is used for the analysis of the long-time system relaxation spanning times over microseconds to infinity. While the radiative processes are typically slow, the system relaxation through non-radiative electronic transitions connected with electron-nuclear interchange of energy may, on the other hand, significantly vary in kinetic rates according to kinetic couplings between relevant adiabatic states. While the predictions of picosecond molecular dynamics themselves fail, the results of the multiscale model for the electron-impact post-ionization fragmentation of krypton and xenon tetramers are in agreement with experiment, namely, in leading to the conclusion that charged monomers prevail. More specifically, on microsecond and longer scales, mainly slow radiative processes are substantial for krypton cluster decay, while for xenon the radiative and slow non-radiative processes compete. In general, the role of slow decay processes through non-radiative transitions is comparable with the role of radiative decay mechanism. The novel multiscale model substantially improves theoretical predictions for the xenon tetramer decay and also further improves the good agreement between theory and experiment we reached previously for krypton.

We present an approach for carrying out nonadiabatic molecular dynamics simulations of systems in which nonadiabatic transitions arise from the coupling between the classical atomic motions and a quasicontinuum of electronic quantum states. Such conditions occur in many research areas, including chemistry at metal surfaces, radiation damage of materials, and warm-dense-matter physics. The classical atomic motions are governed by stochastic Langevin-like equations, while the quantum electron dynamics is described by a master equation for the populations of the electronic states. These working equations are obtained from a first-principles derivation. Remarkably, unlike the widely used Ehrenfest and surface-hopping methods, the approach naturally satisfies the principle of detailed balance at equilibrium and therefore can describe the evolution to thermal equilibrium from an arbitrary initial state. A practical algorithm is cast in the form of the widely used fewest-switches surface-hopping algorithm but with switching probabilities that are not specified ad hoc like in the standard algorithm but are instead derived.

Nonadiabatic ab initio molecular dynamics (MD) including spin-orbit coupling (SOC) and laser fields is investigated as a general tool for studies of excited-state processes. Up to now, SOCs are not included in standard ab initio MD packages. Therefore, transitions to triplet states cannot be treated in a straightforward way. Nevertheless, triplet states play an important role in a large variety of systems and can now be treated within the given framework. The laser interaction is treated on a non-perturbative level that allows nonlinear effects like strong Stark shifts to be considered. As MD allows for the handling of many atoms, the interplay between triplet and singlet states of large molecular systems will be accessible. In order to test the method, IBr is taken as a model system, where SOC plays a crucial role for the shape of the potential curves and thus the dynamics. Moreover, the influence of the nonresonant dynamic Stark effect is considered. The latter is capable of controlling reaction barriers by electric fields in time-reversible conditions, and thus a control laser using this effect acts like a photonic catalyst. In the IBr molecule, the branching ratio at an avoided crossing, which arises from SOC, can be influenced.

Perovskite quantum dots (PQDs) are promising nanomaterials for optoelectronic and energy-conversion applications due to their high photoluminescence quantum yield, tunable bandgap, and defect tolerance. However, their soft ionic lattices exhibit dynamic disorder, anharmonic vibrations, and ion migration, leading to challenges in structural and optoelectronic stability. This review elucidates how molecular dynamics (MD) simulations decode the interplay of atomic fluctuations, lattice dynamics, and surface reconstruction in PQDs, revealing mechanisms governing their stability and performance. It highlights how multi-scale MD frameworks link femtosecond-scale atomic motions to microsecond-scale degradation processes, enabling predictive design of resilient PQDs. Key findings include the role of anharmonic lattice vibrations in defect tolerance, the impact of surface ligand dynamics on emission linewidth, and the mitigation of ion migration through matrix embedding, offering strategies for enhanced device reliability. Classical molecular dynamics (CMD) simulations employ Lennard-Jones, Buckingham, ReaxFF, and COMB3 force fields to model mesoscale phenomena, including ligand rearrangement and surface fusion. Ab initio molecular dynamics (AIMD) uses density functional theory (DFT) with PBE and HSE06 functionals, typically with plane-wave basis sets (e.g., PAW), to capture ion-electron coupling and lattice anharmonicity. Nonadiabatic molecular dynamics (NAMD) incorporates surface hopping to simulate ultrafast charge transfer. Machine-learning potentials, trained via neural networks and Gaussian processes, enhance sampling with metadynamics and replica-exchange techniques.

In this Letter, we combine first-principles calculations with the non-adiabatic molecular dynamics (NAMD) method to investigate the photocatalytic and excited-state properties of blue phosphorene (BlueP). Doping with Group III A elements not only maintains an appropriate bandgap and band edge positions for photocatalytic water splitting but also converts the indirect bandgap of BlueP to a direct bandgap, significantly enhancing photon absorption efficiency. The dopants effectively improve optical absorption in the visible and ultraviolet light regions, potentially enabling a solar-to-hydrogen conversion efficiency of 22.3% in the photocatalytic water splitting process. In NAMD calculations, we consider the dynamics of the electron–hole pair recombination process between the valence band maximum and conduction band minimum. We demonstrate the regulatory impact of dopant elements, temperature, and non-adiabatic coupling strength on the exciton lifetime of doped BlueP through ab initio molecular dynamics and NAMD methods. This study reveals the relationship between the charge transfer mechanism and non-adiabatic coupling in low-dimensional materials, offering valuable insights into the excited-state properties of optoelectronic materials. Ultimately, our findings contribute to the development of tunable, long-lived exciton lifetimes and high carrier mobilities in doped BlueP, which hold significant potential for photocatalytic water splitting to generate hydrogen.

We build on the concept of eigenvector continuation to develop an efficient multi-state method for the rigorous and smooth interpolation of a small training set of many-body wavefunctions through chemical space at mean-field cost. The inferred states are represented as variationally optimal linear combinations of the training states transferred between the many-body bases of different nuclear geometries. We show that analytic multi-state forces and nonadiabatic couplings from the model enable application to nonadiabatic molecular dynamics, developing an active learning scheme to ensure a compact and systematically improvable training set. This culminates in application to the nonadiabatic molecular dynamics of a photoexcited 28-atom hydrogen chain, with surprising complexity in the resulting nuclear motion. With just 22 DMRG calculations of training states from the low-energy correlated electronic structure at different geometries, we infer the multi-state energies, forces and nonadiabatic coupling vectors at 12 000 geometries with provable convergence to high accuracy along an ensemble of molecular trajectories, which would not be feasible with a brute force approach. This opens up a route to bridge the timescales between accurate single-point correlated electronic structure methods and timescales of relevance for photo-induced molecular dynamics.

In this paper, we explore in detail the way in which quantum decoherence is treated in different mixed quantum-classical molecular dynamics algorithms. The quantum decoherence time proves to be a key ingredient in the production of accurate nonadiabatic dynamics from computer simulations. Based on a short time expansion to a semiclassical golden rule expression due to Neria and Nitzan [J. Chem. Phys. 99, 1109 (1993)], we develop a new computationally efficient method for estimating the decay of quantum coherence in condensed phase molecular simulations. Using the hydrated electron as an example, application of this method finds that quantum decoherence times are on the order of a few femtoseconds for condensed phase chemical systems and that they play a direct role in determining nonadiabatic transition rates. The decay of quantum coherence for the solvated electron is found to take ≊50% longer in D2O than in H2O, providing a rationalization for a long standing puzzle concerning the lack of experimentally observed isotope effect on the nonadiabatic transition rate: Although the nonadiabatic coupling is smaller in D2O due to smaller nuclear velocities, the smaller coupling in D2O adds coherently for a longer time than in H2O, leading to nearly identical nonadiabatic transition rates. The implications of this isotope dependence of the nonadiabatic transition rate on changes in the quantum decoherence time for electron transfer and other important chemical reactions are discussed.

ProtoMol is a high-performance framework in C++ for rapid prototyping of novel algorithms for molecular dynamics and related applications. Its flexibility is achieved primarily through the use of inheritance and design patterns (object-oriented programming). Performance is obtained by using templates that enable generation of efficient code for sections critical to performance (generic programming). The framework encapsulates important optimizations that can be used by developers, such as parallelism in the force computation. Its design is based on domain analysis of numerical integrators for molecular dynamics (MD) and of fast solvers for the force computation, particularly due to electrostatic interactions. Several new and efficient algorithms are implemented in ProtoMol. Finally, it is shown that ProtoMol's sequential performance is excellent when compared to a leading MD program, and that it scales well for moderate number of processors. Binaries and source codes for Windows, Linux, Solaris, IRIX, HP-UX, and AIX platforms are available under open source license at http://protomol.sourceforge.net.

Discrete approaches for the nonlinear analysis of in plane loaded masonry walls: Molecular dynamic and static algorithm solutions

Calculating the free energy of nearly jammed hard-particle packings using molecular dynamics

Additive manufacturing (AM) is an emerging technology that has significant geometric and material capabilities, because of which it is being used in different fields such as aerospace, healthcare, automotive, architecture, and construction. This process takes the digital data for the three-dimensional model to be made and adds materials accordingly in a layer-by-layer manner. Therefore, the understanding of materials at the atomic level may help in getting optimized output in the AM process, and it can have a significant impact on the final products. Molecular dynamics (MD) studies the dynamic behavior of molecules and materials at the atomic and molecular scales. The main objective of this review article is to briefly discuss how MD simulations may be utilized to examine AM processes. This review also covers the potential benefits of using MD to characterize AM processes, the current literature on using MD to simulate AM processes, the primary obstacles and limitations of MD simulations, and the methodologies utilized in AM simulations using MD. Finally, this article concludes with an in-depth discussion and outlines future research potentials.

The decay of cyclopropanone is a typical example of a photodecomposition process. Ethylene and carbon monoxide are formed following the excitation to the first singlet excited state through a symmetrical or asymmetrical pathway. The results obtained with non-adiabatic molecular dynamics (NAMD) using the delta self-consistent field (ΔSCF) method correspond well to previous experimental and multireference theoretical studies carried out in the gas phase. Moreover, this efficient methodology allows NAMD simulations of cyclopropanone in aqueous solution to be performed, which reveal analogue deactivation mechanisms, but a shorter lifetime and reduced photodissociation as compared to the gas-phase. The excited state dynamics of cyclopropanone hydrate, an enzyme inhibitor, in an aqueous environment are reported as well. Cyclopropanone hydrate strongly interacts with the surrounding solvent via the formation of hydrogen bonds. Excitation to the first singlet excited state shows an asymmetric pathway with cyclopropanone hydrate and propionic acid as the main photoproducts.

The diffusion coefficient of the water component in a freeze-concentrated matrix is a useful parameter for predicting and controlling the recrystallization rate of ice crystals in sugar solutions relevant to frozen desserts. Herein, application of molecular dynamics (MD) for estimating the water diffusion coefficient in a freeze-concentrated matrix of sugar solutions is described. Diffusion coefficients evaluated using MD with the optimized potentials for liquid simulations all atom force field and water models of three types (simple point charge, simple point charge extended, and transferable intermolecular potential-4 point) show a good positive linear relation with measured values, indicating that the MD methods used in this study are useful for predicting differences in water diffusion coefficients in a sugar freeze-concentrated matrix. Furthermore, similarly to measured values, the estimated diffusion coefficients show a good positive correlation with recrystallization rates of ice crystals, which suggests that MD is useful to predict differences in recrystallization rates of ice crystals in frozen sugar solutions.

We investigate the application of torsion angle molecular dynamics (TAMD) to augment conformational sampling of peptides and proteins. Interesting conformational changes in proteins mainly involve torsional degrees of freedom. Carrying out molecular dynamics in torsion space does not only explicitly sample the most relevant degrees of freedom, but also allows larger integration time steps with elimination of the bond and angle degrees of freedom. However, the covalent geometry needs to be fixed during internal coordinate dynamics, which can introduce severe distortions to the underlying potential surface in the extensively parameterized modern Cartesian-based protein force fields. A "projection" approach (Katritch et al. J Comput Chem 2003, 24, 254-265) is extended to construct an accurate internal coordinate force field (ICFF) from a source Cartesian force field. Torsion crossterm corrections constructed from local molecular fragments, together with softened van der Waals and electrostatic interactions, are used to recover the potential surface and incorporate implicit bond and angle flexibility. MD simulations of dipeptide models demonstrate that full flexibility in both the backbone phi/psi and side chain chi1 angles are virtually restored. The efficacy of TAMD in enhancing conformational sampling is then further examined by folding simulations of small peptides and refinement experiments of protein NMR structures. The results show that an increase of several fold in conformational sampling efficiency can be reliably achieved. The current study also reveals some complicated intrinsic properties of internal coordinate dynamics, beyond energy conservation, that can limit the maximum size of the integration time step and thus the achievable gain in sampling efficiency.