Journal of Chemical Theory and Computation最新文献

Two-dimensional coherent spectroscopy (2DCS) offers significant advantages in terms of high temporal and frequency resolutions and a signal-to-noise ratio. Until now, the response-function (RF) formalism has been the prevalent theoretical description. In this study, we compare the non-Hermitian Hamiltonian (NHH) method with the RF formalism in a three-level system with a constant control field. We obtain the signals from both approaches and compare their population dynamics and 2DCS. We propose quasi-Green functions for the NHH method, which allows all dominant Liouville paths to be inferred. We further simulated the 2DCS of Rh(CO)₂C₅H₇O₂ (RDC) dissolved in hexane with the NHH method, which is in good agreement with the previous experiments. Although the NHH method overestimates relaxations, it provides all important paths by analytical solutions, which are different from the four paths used in the RF formalism. Our results demonstrate that the NHH method is more suitable than the RF formalism for investigating the systems, including relaxation and control fields via the 2DCS.

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. By preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

Nonadiabatic molecular dynamics (NAMD) simulations are crucial for revealing the underlying mechanisms of photochemical and photophysical processes. Typical NAMD simulation software packages rely on on-the-fly ab initio electronic structure and nonadiabatic coupling calculations, and thus become challenging when dealing with large complex systems. We here introduce a new Simulation Package for non-Adiabatic Dynamics in Extended systems (SPADE), which is designed to address the limitations of traditional surface hopping methods in dealing with these problems. By design, SPADE enables the users to define arbitrary quasi-diabatic Hamiltonians through parametrized functions and incorporates a variety of algorithms (e.g., global flux hopping probabilities, complex crossing and decoherence corrections), which can realize efficient and reliable NAMD simulations without using nonadiabatic couplings at all. All the employed methods and expressions for diabatic Hamiltonian matrix elements can be flexibly set through the input files. SPADE is mainly written in Fortran based on a modular design and has a great capacity for further implementation of new methods. SPADE can be used to simulate both model and atomistic systems as long as proper Hamiltonians are provided. As demonstrations, a series of representative models are studied to show the main features and capabilities.

Liquid-liquid phase separation (LLPS) is a vital process in forming membrane-free organelles, crucial for cell physiology and recently gaining significant attention. However, the effects of nonequilibrium factors, which are common in real life, on the process of LLPS have not been fully explored. To address this issue, we developed a model for nonequilibrium phase separation involving three components (A, B, and C) by integrating a nonequilibrium term into the chemical potential for active component B. We find significant changes in the morphology and dynamics of nonequilibrium phase-separated droplets compared to their equilibrium counterparts. Remarkably, with a large enough activity, the B-A-C structure (B at the center, surrounded by A, then enveloped by C) under equilibrium conditions may change to a C-A-B structure. Further simulations give a global picture of the system under both active and passive conditions, revealing the shifts of the phase boundaries and unraveling the effect of activity on different droplet structures. We derived an effective free energy for the active LLPS system to provide a qualitative understanding of our observations. Our study presents a basic model for nonequilibrium phase separation processes, providing crucial insights into LLPS alongside intracellular nonequilibrium phenomena.

This work introduces a semiempirical method, named aTB, based on the tight-binding model and named for its zero-order Hamiltonian that utilizes density-fitting atomic densities. This method can calculate the molecular structure, vibrational frequencies, noncovalent interactions, and excited states of large molecular systems. The parameters of aTB cover elements from Hydrogen (H) to Radium (Ra), and for ground state calculations, it supports the analysis of first- and second-order derivatives. The Hamiltonian of aTB contains a zero-order Hamiltonian, Coulomb term, an explicit second- and third-order expansion of the exchange-correlation term, and a spin-polarization term with only one additional parameter. A series of extensive tests were conducted to compare aTB with existing semiempirical methods.

Machine learning potential (MLP), by learning global potential energy surfaces (PES), has demonstrated its great value in finding unknown structures and reactions via global PES exploration. Due to the diversity and complexity of the global PES data set, an outstanding challenge emerges in achieving PES high accuracy (e.g., error <1 meV/atom), which is essential to determine the thermodynamics and kinetics properties. Here, we develop a lightweight fine-tuning MLP architecture, namely, AtomFT, that can explore PES globally and simultaneously describe the PES of a target system accurately. The AtomFT potential takes the pretrained many-body function corrected global neural network (MBNN) potential as the basis potential, exploits and iteratively updates the atomic features from the pretrained MBNN model, and finally generates the fine-tuning energy contribution. By implementing the AtomFT architecture on the commonly available CPU platform, we show the high efficiency of AtomFT potential in both training and inference and demonstrate the high performance in challenging PES problems, including the oxides with low defect content, molecular reactions, and molecular crystals─in all systems, the AtomFT potentials enhance significantly the PES prediction accuracy to 1 meV/atom.

Spatial derivatives of the natural orbitals (NOs) at their nodal surfaces are shown to encode information about the on-top two-electron density Φ₂(r⃗) in an approximate manner. This encoding, which becomes exact at the limit of an infinite number of nodal surfaces, allows the reconstruction of Φ₂(r⃗) up to a multiplicative constant that can be retrieved from an identity involving the NO in question and its occupation number. This reconstruction provides a new consistency check for electronic structure formalisms, such as the one-electron reduced density matrix theory, that employ NOs as primary quantities.

To investigate the ability of coarse-grained molecular dynamics simulations to predict the relative growth rates of crystal facets of pharmaceutical molecules, we apply two coarse-graining strategies to two drug molecules, phenytoin and carbamazepine. In the first method, we map an atomistic model to a MARTINI-level coarse-grained (CG) force field that uses 2 or 3 heavy atoms per bead. This is followed by applying Particle Swarm Optimization (PSO), a global optimum searching algorithm, to the CG Lennard-Jones intermolecular potentials to fit the radial distribution functions of both the crystalline and melt structures. In the second, a coarser-grained method, we map 5 or more heavy atoms into one bead with the help of the Iterative Boltzmann Inversion (IBI) method to derive a tabulated longer-range force field (FF). Simulations using the FF's derived from both strategies were able to stabilize the crystal in the correct structure and to predict crystal growth from the melt with modest computational resources. We evaluate the advantages and limitations of both methods and compare the relative growth rates of various facets of both drug crystals with those predicted by the Bravais-Friedel-Donnay-Harker (BFDH) and attachment energy (AE) theories. While all methods, except for the simulations conducted with the coarser-grained IBI-generated model, produced similarly good results for phenytoin, the finer-grained PSO-generated FF using MARTINI mapping rules outperformed the other methods in its prediction of the facet growth rates and resulting crystalline morphology for carbamazepine.

We present a theoretical model to investigate the dynamics and spectroscopic properties of a plexciton system consisting of a molecular exciton coupled to a single short-lived plasmonic mode. The exciton is described as a two-level system (TLS), while the plasmonic mode is treated as a dissipative harmonic oscillator. The hierarchical equations of motion method is employed to simulate energy transfer dynamics, absorption spectra, and two-dimensional electronic spectra (2DES) of the system across a range of coupling strengths. It is shown that increasing the exciton-plasmon coupling strength drives a transition in the absorption spectra from an asymmetric Fano line shape to a Rabi splitting pattern, while coupling the TLS to intramolecular vibrational modes reduces the central dip of the absorption spectra and makes the line shape more symmetric. The simulated 2DES exhibit distinct features compared to those of a coupled molecular dimer, highlighting the unique nonlinear response of plexciton systems. In addition, a "breathing mode" pattern observed in the strong coupling regime can serve as a direct evidence of Rabi oscillation.

The prediction of a specific chemical property across a vast library of derivatives represents a formidable challenge. Conventional computational methodologies typically rely on brute-force calculations involving the computation of the property of interest for the entire library or a significant subset. In this study, we present a novel phenomenological approach to address this challenge, employing a perturbation theory-like framework to describe substituent effects. This proposed methodology has the potential to forecast the molecular properties of millions of compounds based on information derived from just a few hundred. This method is applied to the design of molecular solar thermal (MOST) systems, which are devices permitting harvesting solar energy and storing it in a chemical form. The optimization of MOST performance is a critical issue in practical applications of this technology, so exploration of large libraries of derivatives at low computational cost is an interesting approach to tackle the problem. To accomplish this objective, we explore the functionalization of the norbornadiene/quadricyclane (NBD/QC) system utilizing the proposed perturbational approach predicting the energy of 350 derivatives from small sets of 5 and 50 calculated compounds.