Related papers: Energy benchmarks for water clusters and ice struc…
The Microcanonical Ensemble computer simulation method (MCE) is used to evaluate the perturbation terms $A_i$ of the Helmholtz free energy of a Square-Well (SW) fluid. The MCE method offers a very efficient and accurate procedure for the…
Solving for the many-body wavefunction represents a significant challenge on both classical and quantum devices because of the exponential scaling of the Hilbert space with system size. While the complexity of the wavefunction can be…
Many-body interactions in water are known to be important but difficult to treat in atomistic models and often are included only as a correction. Polarizable models treat them explicitly, with long-range many-body potentials, within their…
We present a simple, robust and efficient method for varying the parameters in a many-body wave function to optimize the expectation value of the energy. The effectiveness of the method is demonstrated by optimizing the parameters in…
Fluid dynamics plays a crucial role in various multiphysics applications, including energy systems, electronics cooling, and biomedical engineering. Developing models for complex coupled systems can be challenging and time-consuming. In…
Non-equilibrium molecular dynamics (NEMD) techniques are widely used for investigating lattice thermal conductivity. Recently, machine learning force fields (MLFFs) have emerged as a promising approach to enhance the precision in NEMD…
High throughput screening of materials for technologically relevant areas, like identification of better catalysts, electronic materials, ceramics for high temperature applications and drug discovery, is an emerging topic of research. To…
Given the piecewise approach to modeling intermolecular interactions for force fields, they can be difficult to parameterize since they are fit to data like total energies that only indirectly connect to their separable functional forms.…
We develop a novel cluster expansion for finite-spin lattice systems subject to multi-body quantum -- and, in particular, classical -- interactions. Our approach is based on the use of ``decoupling parameters", advocated by Park [34], which…
This paper presents the implementation of the eXtended Finite Element Method (XFEM) in the general-purpose commercial software package COMSOL Multiphysics for multi-field thermo-hydro-mechanical problems in discontinuous porous media. To…
In this work, we derive a multi-fragment real-time extension of projected density matrix embedding theory (pDMET) designed to treat non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static…
It is well known that closed-form analytical solutions for AC power flow equations do not exist in general. This paper proposes a multi-dimensional holomorphic embedding method (MDHEM) to obtain an explicit approximate analytical AC…
Electromagnetic forming and perforations (EMFP) are complex and innovative high strain rate processes that involve electromagnetic-mechanical interactions for simultaneous metal forming and perforations. Instead of spending costly resources…
This work constructs an advanced force field, the Completely Multipolar Model (CMM), to quantitatively reproduce each term of an energy decomposition analysis (EDA) for aqueous solvated alkali metal cations and halide anions and their ion…
A combination of molecular quantum electrodynamics, perturbation theory, and ab initio calculations was used to create a computational methodology capable of estimating the rate of 3-body singlet upconversion in organic molecular…
Low-dimensional beryllium systems constitute interesting case studies for the test of correlation methods because of the importance of both static and dynamical correlation in the formation of the bond. Aiming to describe the whole…
Energy-based models (EBMs) offer a flexible framework for parameterizing probability distributions using neural networks. However, learning EBMs by exact maximum likelihood estimation (MLE) is generally intractable, due to the need to…
This paper describes the development of the Four Model Tree Ensemble (FMTE). The FMTE is a composite of machine learning models trained on experimental binding energies from the Atomic Mass Evaluation (AME) 2012. The FMTE predicts binding…
In this paper, we develop the constraint energy minimization generalized multiscale finite element method (CEM-GMsFEM) in mixed formulation applied to parabolic equations with heterogeneous diffusion coefficients. The construction of the…
We have developed a method to improve the doping computation efficiency, this method is based on first principles calculations and cluster expansion. First principles codes produce highly accurate total energies and optimized geometries for…