Structural relaxation made simple.

By E. Bitzek, Pekka Koskinen, Franz Gähler, M. Moseler, Peter Gumbsch. Physical Review Letters, 2006

1,419 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Biomedical Engineering, Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/315d478ae21782b50da523fe2673b4ad5f3d772b

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In Atomic and Molecular Physics, and Optics

In Biomedical Engineering

In Computational Mechanics

Citations in the corpus

Efficient and Modular Implicit Differentiation (2021, methodology): “6, which we optimize with a domain-specific optimizer [13].”
HOOMD-blue: A Python package for high-performance molecular dynamics and hard particle Monte Carlo simulations (2013, background): “HOOMD-blue has MD integrators for many different thermodynamic ensembles including NVE, NVT, NPH, NPT, Langevin dynamics, Brownian dynamics, and dissipative particle dynamics, and also supports FIRE [28] energy minimization.”
Mean-field avalanches in jammed spheres. (2016, methodology): “We first prepare the system generating amorphous energy minima at packing fractions φ ≥ φJ , and then we study the effect of an applied shear according to the athermal quasi-static protocol, letting the system relax after every perturbation via a dissipative molecular dynamics [32].”
End-to-End Differentiable , Hardware Accelerated , Molecular Dynamics in Pure Python (2019, methodology): “JAX MD also supports Fast Inertial Relaxation Engine (Fire) Descent (Bitzek et al., 2006) and Gradient Descent to minimize the energy of systems.”
Mechanistic origin of high strength in refractory BCC high entropy alloys up to 1900K (2019, methodology): “Atomic positions are then relaxed by using a combination of the FIRE algorithm [35] and relaxation of the cell dimensions until convergence is achieved (force tolerance 10−6 eV/atom and stresses σXX , σXZ and σZZ < 1 MPa).”
Excitations Are Localized and Relaxation Is Hierarchical in Glass-Forming Liquids (2011, neutral): “The inherent structure of a configuration of an N -particle system is obtained by steepest descent to the nearest minimum in the potential energy landscape [27].”
Gradients are Not All You Need (2021, methodology): “To generate packings, we use JAX MD [Schoenholz and Cubuk, 2020] to produce some initial conﬁguration of disks and then use a momentum-based optimizer called FIRE [Bitzek et al., 2006] to quench the conﬁguration to the nearest minimum.”