Goldman Computational Approaches for Chemistry Under Extreme Conditions

1. Auflage 2019
ISBN: 978-3-030-05600-1
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 28, 293 Seiten, eBook

Reihe: Challenges and Advances in Computational Chemistry and Physics

This book presents recently developed computational approaches for the study of reactive materials under extreme physical and thermodynamic conditions. It delves into cutting edge developments in simulation methods for reactive materials, including quantum calculations spanning nanometer length scales and picosecond timescales, to reactive force fields, coarse-grained approaches, and machine learning methods spanning microns and nanoseconds and beyond. These methods are discussed in the context of a broad range of fields, including prebiotic chemistry in impacting comets, studies of planetary interiors, high pressure synthesis of new compounds, and detonations of energetic materials. The book presents a pedagogical approach for these state-of-the-art approaches, compiled into a single source for the first time. Ultimately, the volume aims to make valuable research tools accessible to experimentalists and theoreticians alike for any number of scientific efforts, spanning many different types of compounds and reactive conditions.

Zielgruppe

Research

Autoren/Hrsg.

Goldman, Nir

Inhaltsverzeichnis

Simulations of Hydrocarbon Polymers Related to Compression Experiments on Sandia’s Z Machine.- Computational Discovery of New High Nitrogen Energetic Materials.- Accelerated Molecular Dynamics Simulations of Shock-induced Chemistry: Application to Liquid Benzene.- Force Matching Approaches to Extend Density Functional Theory to Large Time and Length Scales.- Free energy calculations of electric field induced chemistry.- Force Field Development and Nanoreactor Chemistry.- Application of ReaxFF Reactive Molecular Dynamics and Continuum Methods in High Temperature/Pressure Pyrolysis of Fuel Mixtures.- Shock-induced chemistry: molecular dynamics and coarse grain modeling.- Data-Driven Methods for Building Reduced Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations.- Toward a predictive hierarchical multiscale modelling approach for energetic materials.

Über Autor(innen)

Dr. Nir Goldman is a scientist based in the Materials Science Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, USA. His current research interests involve the development of novel approaches to quantum and classical molecular dynamics simulations of chemical reactivity within condensed matter. This includes corrosion processes, soft matter degradation phenomena, the modeling of laser-driven dynamic compression experiments, and astrobiological synthesis of life-building compounds under extreme thermodynamic conditions.