simulation model

Central venous oxygen saturation (ScvO2) is an important parameter for assessing global oxygen usage and guiding clinical interventions. However, measuring ScvO2 requires invasive catheterization. As an alternative, we aim to noninvasively and continuously measure changes in oxygen saturation of the internal jugular vein (SijvO2) by a multi-channel near-infrared spectroscopy system. The relation between the measured reflectance and changes in SijvO2 is modeled by Monte Carlo simulations and used to build a prediction model using deep neural networks (DNNs)...

Soliton molecules, a frequently observed phenomenon in most mode-locked lasers, have intriguing characteristics comparable to their matter molecule counterparts. However, there are rare explorations of the deterministic control of the underlying physics within soliton molecules. Here, we demonstrate the bistable response of intramolecular motion to external stimuli and identify a general approach to excite their quasi-periodic oscillations. By introducing frequency-swept gain modulation, the intrinsic resonance frequency of the soliton molecule is observed in the simulation model...

We propose an optical analog of electron snake states based on an artificial gauge magnetic field in a photonic graphene implemented by varying distances between cavity pillars. We develop an intuitive and exhaustive continuous model based on tight-binding approximation and compare it with numerical simulations of a realistic photonic structure. The allowed lateral propagation direction is shown to be strongly coupled to the valley degree of freedom, and the proposed photonic structure may be used as a valley filter...

Accurate modeling of intermolecular repulsion is an integral component in force field development. Although repulsion can be explicitly calculated by applying the Pauli exclusion principle, this approach is computationally viable only for systems of limited sizes. Instead, it has previously been shown that repulsion can be reformulated in a "classical" picture: the Pauli exclusion principle prohibits electrons from occupying the same state, leading to a depletion of electronic charge between atoms, giving rise to an enhanced nuclear-nuclear electrostatic repulsion...

Quantum dynamics simulations are becoming a powerful tool for understanding photo-excited molecules. Their poor scaling, however, means that it is hard to study molecules with more than a few atoms accurately, and a major challenge at the moment is the inclusion of the molecular environment. Here, we present a proof of principle for a way to break the two bottlenecks preventing large but accurate simulations. First, the problem of providing the potential energy surfaces for a general system is addressed by parameterizing a standard force field to reproduce the potential surfaces of the molecule's excited-states, including the all-important vibronic coupling...

We develop a theory to calculate structural correlations and thermodynamic properties of a fluid confined in a random porous solid medium (matrix). We used density functional formalism to derive an annealed averaged expression for the density profile and excess free energy of fluid arising due to random fields of a particular realization of the matrix. After performing the second average over the quenched-disordered variables, the excess free energy is organized to give one- and two-body potentials for fluid particles...

Dynamic heterogeneity is a fundamental characteristic of glasses and undercooled liquids. The heterogeneous nature causes some of the key features of systems' dynamics such as the temperature dependence of nonexponentiality and spatial enthalpy fluctuations. Commonly used phenomenological models such as Tool-Narayanaswamy-Moynihan (TNM) and Kovacs-Aklonis-Hutchinson-Ramos fail to fully capture this phenomenon. Here we propose a model that can predict the temperature-dependent nonexponential behavior observed in glass-forming liquids and glasses by fitting standard differential scanning calorimetry curves...

Several enhanced sampling techniques rely on the definition of collective variables to effectively explore free energy landscapes. The existing variables that describe the progression along a reactive pathway offer an elegant solution but face a number of limitations. In this paper, we address these challenges by introducing a new path-like collective variable called the "deep-locally non-linear-embedding," which is inspired by principles of the locally linear embedding technique and is trained on a reactive trajectory...

Understanding the dynamics of photoinduced processes in complex systems is crucial for the development of advanced energy-conversion materials. In this study, we investigate the nonadiabatic dynamics using time-convolution (TC) and time-convolutionless (TCL) quantum master equations (QMEs) based on treating electronic couplings as perturbation within the framework of multistate harmonic (MSH) models. The MSH model Hamiltonians are mapped from all-atom simulations such that all pairwise reorganization energies are consistently incorporated, leading to a heterogeneous environment that couples to the multiple electronic states differently...

Coarse-grained (CG) molecular models greatly reduce the computational cost of simulations allowing for longer and larger simulations, but come with an artificially increased acceleration of the dynamics when compared to the parent atomistic (AA) simulation. This impedes their use for the quantitative study of dynamical properties. During coarse-graining, grouping several atoms into one CG bead not only reduces the number of degrees of freedom but also reduces the roughness on the molecular surfaces, leading to the acceleration of dynamics...

As the most important solvent, water has been at the center of interest since the advent of computer simulations. While early molecular dynamics and Monte Carlo simulations had to make use of simple model potentials to describe the atomic interactions, accurate ab initio molecular dynamics simulations relying on the first-principles calculation of the energies and forces have opened the way to predictive simulations of aqueous systems. Still, these simulations are very demanding, which prevents the study of complex systems and their properties...

Molecular-based equations of state for describing the thermodynamics of chain molecules are often based on mean-field like arguments that reduce the problem of describing the interactions between chains to a simpler one involving only nonbonded monomers. While for dense liquids such arguments are known to work well, at low density they are typically less appropriate due to an incomplete description of the effect of chain connectivity on the local environment of the chains' monomer segments. To address this issue, we develop three semi-empirical approaches that significantly improve the thermodynamic description of chain molecules at low density...

Quantum dynamics simulations are becoming a standard tool for simulating photo-excited molecular systems involving a manifold of coupled states, known as non-adiabatic dynamics. While these simulations have had many successes in explaining experiments and giving details of non-adiabatic transitions, the question remains as to their predictive power. In this work, we present a set of quantum dynamics simulations on cyclobutanone using both grid-based multi-configuration time-dependent Hartree and direct dynamics variational multi-configuration Gaussian methods...

The celebrated generalized Stokes law predicts that the velocity of a particle pulled through a liquid by an external force, Fex, is directly proportional to the force and inversely proportional to the friction ζ acted by the medium on the particle. We investigate the range of validity of the generalized Stokes law at molecular length scales by employing computer simulations to calculate friction by pulling a tagged particle with a constant force. We thus calculate friction for two model interaction potentials, Lennard-Jones and soft sphere, for several particle sizes, ranging from radius (a) smaller than the solvent particles to three times larger...

Hybrid quantum mechanics/molecular mechanics (QM/MM) simulations have become an essential tool in computational chemistry, particularly for analyzing complex biological and condensed phase systems. Building on this foundation, our work presents a novel implementation of the Gaussian Electrostatic Model (GEM), a polarizable density-based force field, within the QM/MM framework. This advancement provides seamless integration, enabling efficient and optimized QM/GEM calculations in a single step using the LICHEM Code...

A fundamental equation of state in terms of the Helmholtz energy is presented for mixtures of nitrogen, oxygen, and argon at any composition. It is expressed in terms of the residual Helmholtz energy and can be used to calculate all thermodynamic equilibrium properties including vapor-liquid equilibria. The parameters of the equations for the pure-fluid and mixture contributions are fitted exclusively to molecular simulation data so that the model has a predictive character. The description of the mixture-specific reducing parameters is realized via generalized correlations of the critical parameters of the pure fluids so that an extension of the model to additional components can be implemented straightforwardly...

Ventilation is paramount in sanitary and stormwater sewer systems to mitigate odor problems and avert pressure surges. Existing numerical models have constraints in practical applications in actual sewer systems due to insufficient airflow modeling or suitability only for steady-state conditions. This research endeavors to formulate a mathematical model capable of accurately simulating various operational conditions of sewer systems under the natural ventilation condition. The dynamic water flow is modeled using a shock-capturing MacCormack scheme...

The connectivity of urban river networks plays an important role in cities in many aspects, such as urban water safety, water quality (WQ), and aquatic ecological balance. This study focuses on the river network and the Majiawan Wetland in the Chaoyang District of Beijing by establishing a two-dimensional hydrological WQ model employing various water allocation schemes between the river network and the wetland. Water circulation and WQ are the main indexes, and the effects of different scenarios on improving water circulation and WQ are simulated and compared...

With the widespread application of machine learning in various fields, enhancing its accuracy in hydrological forecasting has become a focal point of interest for hydrologists. This study, set against the backdrop of the Haihe River Basin, focuses on daily-scale streamflow and explores the application of the Lasso feature selection method alongside three machine learning models (long short-term memory, LSTM; transformer for time series, TTS; random forest, RF) in short-term streamflow prediction. Through comparative experiments, we found that the Lasso method significantly enhances the model's performance, with a respective increase in the generalization capabilities of the three models by 21, 12, and 14%...

Instantaneous peak flows (IPFs) are often required to derive design values for sizing various hydraulic structures, such as culverts, bridges, and small dams/levees, in addition to informing several water resources management-related activities. Compared to mean daily flows (MDFs), which represent averaged flows over a period of 24 h, information on IPFs is often missing or unavailable in instrumental records. In this study, conventional methods for estimating IPFs from MDFs are evaluated and new methods based on the nonlinear regression framework and machine learning architectures are proposed and evaluated using streamflow records from all Canadian hydrometric stations with natural and regulated flow regimes...