9 papers · ranked by Valyu relevance
Authors not listed
Hyperstructures and their hierarchical extensions—SuperHyperStructures—provide a versatile algebraic language for modeling multi-level and interdependent systems [1,2]. In materials and chemical sciences, structural descriptions naturally span a broad spectrum of characteristic length scales, commonly organized as…
Authors not listed
Hyperstructures and their hierarchical extensions [1]—SuperHyperStructures—provide a versatile formalism for modeling multi-layered and complex phenomena [2, 3]. A MicroStructure is a measurable mapping that assigns to each material point a single local state, representing attributes such as phase, crystal orientation…
Authors not listed
Curried functions provide a systematic way of transforming multi-argument functions into nested singleargument functions. This transformation allows partial application and supports many central principles of functional programming. Their extension, called curried 𝑘-ary functions, naturally generalizes the familiar…
Michael Hutcheon, Andrew Teale
Algorithms are presented for performing a topological analysis of an arbitrary function, evaluated on an arbitrary grid of points. These algorithms work strictly by post-processing the data and require no additional function evaluations. This is achieved by connecting the grid points with a neighbourhood graph…
Authors not listed
This paper develops a unified, geometry-aware framework for representing molecules and their higher-order organization. We formalize 𝑑-dimensional molecular structures, hyperstructures, and superhyperstructures by combining labeled (hyper)graphs with Euclidean embeddings and rank-aware operations on iterated power…
Authors not listed
We present an open source collection of scripts and programs for the setup, management and evaluation of calculations with the Vienna ab-initio simulation package (VASP), called utils4VASP. It contains 20 independent Python scripts and Fortran programs, all with a unified and intuitive handling concept based on command…
Jordan Ehrman, Victoria T. Lim, Caitlin C. Bannan, Nam Thi + 2 more
Many molecular simulation methods use force fields to help model and simulate molecules and their behavior in various environments. Force fields are sets of functions and parameters used to calculate the potential energy of a chemical system as a function of the atomic coordinates. Despite the widespread use of force…
Fergus Boyles, Charlotte M Deane, Garrett Morris
Machine learning scoring functions for protein-ligand binding affinity prediction have been found to consistently outperform classical scoring functions. Structure-based scoring functions for universal affinity prediction typically use features describing interactions derived from the protein-ligand complex, with…
Owen Madin, Michael Shirts
Dispersion-repulsion interactions, commonly represented in atomistic force fields by the Lennard-Jones (LJ) potential, play an important role in the accuracy of molecular simulations. Training the force field parameters used in the LJ potential is challenging, generally requiring adjustment based on simulations of…