CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post–Hartree–Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.
CoCo
(“complementary coordinates”) is a method for
ensemble enrichment based on principal component analysis (PCA) that
was developed originally for the investigation of NMR data. Here we
investigate the potential of the CoCo method, in combination with
molecular dynamics simulations (CoCo-MD), to be used more generally
for the enhanced sampling of conformational space. Using the alanine
penta-peptide as a model system, we find that an iterative workflow,
interleaving short multiple-walker MD simulations with long-range
jumps through conformational space informed by CoCo analysis, can
increase the rate of sampling of conformational space up to 10 times
for the same computational effort (total number of MD timesteps).
Combined with the reservoir-REMD method, free energies can be readily
calculated. An alternative, approximate but fast and practically useful,
alternative approach to unbiasing CoCo-MD generated data is also described.
Applied to cyclosporine A, we can achieve far greater conformational
sampling than has been reported previously, using a fraction of the
computational resource. Simulations of the maltose binding protein,
begun from the “open” state, effectively sample the
“closed” conformation associated with ligand binding.
The PCA-based approach means that optimal collective variables to
enhance sampling need not be defined in advance by the user but are
identified automatically and are adaptive, responding to the characteristics
of the developing ensemble. In addition, the approach does not require
any adaptations to the associated MD code and is compatible with any
conventional MD package.
Macro-modeling of cerebral blood flow can help determine the impact of thermal intervention during instances of head trauma to mitigate tissue damage. This work presents a bioheat model using a 3D fluid-porous domain coupled with intersecting 1D arterial and venous vessel trees. This combined vascular porous (VaPor) model resolves both cerebral blood flow and energy equations, including heat generated by metabolism, using vasculature extracted from MRI data and is extended using a tree generation algorithm. Counter-current flows are expected to increase thermal transfer within the brain and are enforced using either the vascular structure or flow reversal, represented by a flow reversal constant, CR. These methods exhibit larger average brain cooling (from 0.56 °C ± <0.01 °C to 0.58 °C ± <0.01 °C) compared with previous models (0.39 °C) when scalp temperature is reduced. An greater reduction in core brain temperature is observed (from 0.29 °C ± <0.01 °C to 0.45 °C ± <0.01 °C) compared to previous models (0.11 °C) due to the inclusion of counter-current cooling effects. The VaPor model also predicts that a hypothermic average temperature (<36 °C) can be reached in core regions of neonatal models using scalp cooling alone.
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