What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Operating system
- Enzyme
Peter V. Coveney mainly focuses on Statistical physics, Molecular dynamics, Dissipative particle dynamics, Lattice Boltzmann methods and Montmorillonite.
His Statistical physics research incorporates themes from Second law of thermodynamics, Quantum simulator, Phenomenology and HPP model.
As a part of the same scientific family, Peter V. Coveney mostly works in the field of Molecular dynamics, focusing on Chemical physics and, on occasion, Self-assembly and Nanotechnology.
His Dissipative particle dynamics research incorporates elements of Rheology, Classical mechanics, Mesoscopic physics, Volume fraction and Colloid.
His research integrates issues of Fluid dynamics, Computational science and Boltzmann equation in his study of Lattice Boltzmann methods.
His biological study deals with issues like Clay minerals, which deal with fields such as Nanocomposite.
His most cited work include:
- Scalable Quantum Simulation of Molecular Energies (522 citations)
- Monte Carlo Molecular Modeling Studies of Hydrated Li-, Na-, and K-Smectites: Understanding the Role of Potassium as a Clay Swelling Inhibitor (354 citations)
- Clay swelling — A challenge in the oilfield (324 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Molecular dynamics, Statistical physics, Lattice Boltzmann methods, Supercomputer and Data science.
His Molecular dynamics study combines topics from a wide range of disciplines, such as Chemical physics, Scale and Molecule.
His Statistical physics study which covers Dissipative particle dynamics that intersects with Classical mechanics.
Many of his studies on Lattice Boltzmann methods involve topics that are commonly interrelated, such as Gyroid.
His Supercomputer research focuses on Computational science and how it connects with Grid.
The study incorporates disciplines such as Middleware, Distributed computing and Computational steering in addition to Grid.
He most often published in these fields:
- Molecular dynamics (17.79%)
- Statistical physics (13.34%)
- Lattice Boltzmann methods (11.53%)
What were the highlights of his more recent work (between 2015-2021)?
- Molecular dynamics (17.79%)
- Uncertainty quantification (5.11%)
- Supercomputer (9.06%)
In recent papers he was focusing on the following fields of study:
Peter V. Coveney spends much of his time researching Molecular dynamics, Uncertainty quantification, Supercomputer, Data science and Scale.
The concepts of his Molecular dynamics study are interwoven with issues in Biological system, Binding affinities and Drug discovery.
As part of his studies on Binding affinities, Peter V. Coveney often connects relevant areas like Statistical physics.
The concepts of his Statistical physics study are interwoven with issues in Energy and Quantum simulator.
His biological study spans a wide range of topics, including Multiscale modeling, Software, Lattice Boltzmann methods and Workflow.
His work is dedicated to discovering how Data science, Big data are connected with Scientific method and Complex system and other disciplines.
Between 2015 and 2021, his most popular works were:
- Scalable Quantum Simulation of Molecular Energies (522 citations)
- Big data need big theory too (99 citations)
- Non-canonical Wnt signalling modulates the endothelial shear stress flow sensor in vascular remodelling. (75 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Operating system
- Enzyme
His main research concerns Molecular dynamics, Supercomputer, Statistical physics, Uncertainty quantification and Energy.
In the subject of general Molecular dynamics, his work in Thermodynamic integration is often linked to In silico, thereby combining diverse domains of study.
His study in Supercomputer is interdisciplinary in nature, drawing from both Software, Distributed computing and Computational science.
His Statistical physics research is multidisciplinary, incorporating elements of Electronic structure, Quantum computer, Quantum simulator and Qubit.
The study incorporates disciplines such as Computation and Coupled cluster in addition to Qubit.
His Uncertainty quantification study also includes
- Python and related Systems engineering, Software engineering, Multiscale modeling and Use case,
- Workflow and related Command-line interface and Unix.
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