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Dynamic mode decomposition (DMD) has proven to be a valuable tool for the analysis of complex flow-fields but the application of this technique to flows with moving boundaries is not straightforward. This is due to the difficulty in…

Fluid Dynamics · Physics 2020-07-28 Karthik Menon , Rajat Mittal

Dynamical Mean-Field Theory (DMFT) has opened new perspectives for the investigation of strongly correlated electron systems and greatly improved our understanding of correlation effects in models and materials. In contrast to…

Strongly Correlated Electrons · Physics 2020-07-16 Dieter Vollhardt

Dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D Fast Fourier…

Magnetic 2D materials have achieved significantly consideration owing to their encouraging applications. A variation of these 2D materials by occurrence of defects, by the transition-metal doping or adsorption or by the surface…

Materials Science · Physics 2025-06-27 Zarah Khan , Saleem Ayaz Khan , Ayesha Zaheer , Syed Rizwan

We consider the governing equations for the motion of the viscous fluids in two moving domains and an evolving surface from both energetic and thermodynamic points of view. We make mathematical models for multiphase flow with surface flow…

Mathematical Physics · Physics 2023-01-10 Hajime Koba

We have parameterized a reactive force field (ReaxFF) for lithium aluminum silicates using density functional theory (DFT) calculations of structural properties of a number of bulk phase oxides, silicates, and aluminates, as well as of…

The limited extrapolative power of structure-based machine learning (ML) models is a critical bottleneck in chemical discovery, particularly for industrial R&D, where navigating uncharted chemical space to find next-generation materials or…

Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex aqueous systems such as solid-liquid interfaces. Here, we present a machine learning…

We develop a fast numerical procedure for analysis of nonlinear and nonlocal electrodynamics of type-II superconducting films in transverse magnetic fields taking into account realistic boundary conditions. Using this procedure we explore…

Superconductivity · Physics 2015-05-20 J. I. Vestgarden , D. V. Shantsev , Y. M. Galperin , T. H. Johansen

Although of practical importance, there is no established modeling framework to accurately predict high-temperature cyclic oxidation kinetics of multi-component alloys due to the inherent complexity. We present a data analytics approach to…

Computational catalyst discovery involves the development of microkinetic reactor models based on estimated parameters determined from density functional theory (DFT). For complex surface chemistries, the cost of calculating the adsorption…

We introduce the optimized dynamic mode decomposition algorithm for constructing an adaptive and computationally efficient reduced order model and forecasting tool for global atmospheric chemistry dynamics. By exploiting a low-dimensional…

Machine Learning · Computer Science 2024-04-22 Meghana Velegar , Christoph Keller , J. Nathan Kutz

High mesh quality plays a crucial role in maintaining the stability of solutions in geometric flow problems. Duan and Li [Duan & Li, SIAM J. Sci. Comput. 46 (1) (2024) A587-A608] applied the minimal deformation (MD) formulation to propose…

Numerical Analysis · Mathematics 2025-01-23 Yihang Guo , Meng Li

Metal-organic frameworks (MOFs) are porous materials formed by interconnected metal atoms via organic linkers, resulting in high surface area and tuneable porosity, making them exceptional candidates for CO2 capture. However, their…

Materials Science · Physics 2025-07-23 Ashok Yacham , Tarak K. Patra , Jithin John Varghese , Richa Sharma

The formation energies of nanostructures play an important role in determining their properties, including the catalytic activity. For the case of 15 different rutile and 8 different perovskite metal oxides, we find that the density…

The saddle-to-scission dynamics of the induced fission process is explored using a microscopic finite-temperature model based on time-dependent nuclear density functional theory (TDDFT), that allows to follow the evolution of local…

Nuclear Theory · Physics 2023-07-27 B. Li , D. Vretenar , Z. X. Ren , T. Nikšić , J. Zhao , P. W. Zhao , J. Meng

Solar active regions are formed through the emergence of magnetic flux from the deeper convection zone. Recent satellite observations have shown that a horizontal divergent flow (HDF) stretches out over the solar surface just before the…

Solar and Stellar Astrophysics · Physics 2015-06-15 Shin Toriumi , Takaaki Yokoyama

Fluids with competing short range attraction and long range repulsive interactions between the particles can exhibit a variety of microphase separated structures. We develop a lattice-gas (generalised Ising) model and analyse the phase…

Soft Condensed Matter · Physics 2016-01-20 Blesson Chacko , Christopher Chalmers , Andrew J. Archer

The metal-organic framework (MOF) MFU-4l containing Co(II) centers and Cl- ligands has recently shown promising redox activity. Aiming for further improved MOF catalysts for oxidation processes employing molecular oxygen we present a…

Materials Science · Physics 2013-11-27 Jelena Jelic , Dmytro Denysenko , Dirk Volkmer , Karsten Reuter

In computational materials science, a common means for predicting macroscopic (e.g., mechanical) properties of an alloy is to define a model using combinations of descriptors that depend on some material properties (elastic constants,…

Materials Science · Physics 2022-10-17 Ivan Novikov , Olga Kovalyova , Alexander Shapeev , Max Hodapp