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Cintia A. Menéndez

Publications and source records attributed to Cintia A. Menéndez.

2 recordsLinked to original sources

Nanoscale Water Behavior and Its Impact on Adsorption: A case study with CNTs and Diclofenac

Water is a fundamental component of life, playing a critical role in regulating metabolic processes and facilitating the dissolution and transport of essential molecules. However, the presence of emerging contaminants, such as pharmaceuticals, poses significant challenges to water quality and safety. Nanomaterials-based technologies arise as a promising tool to remove those contaminants from water. Nevertheless, interfacial water plays a major role in the adsorption of chemical compounds in the nanomaterials - as it plays in biological processes such as protein folding, enzyme activity, and drug delivery. To understand this role, in this study we employ Molecular Dynamics (MD) simulations to explore the adsorption dynamics of potassium diclofenac (K-DCF) on single-walled (SWCNT) and double-walled (DWCNT) carbon nanotubes, considering both dry and wet conditions. Our findings reveal that the structuring of water molecules around CNTs creates hydration layers that significantly influence the accessibility of active sites and the interaction strength between contaminants and adsorbents. Our analysis indicates higher energy barriers for adsorption in DWCNTs compared to SWCNTs, which is attributed to stronger water-surface interactions. This research highlights the importance of understanding nanoscale water behavior for optimizing the design and functionality of nanomaterials for water purification. These findings can guide the development of more efficient and selective nanomaterials, enhancing contaminant removal and ensuring safer water resources, while also contributing to a deeper understanding of fundamental biological interactions.

cond-mat.soft↗

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system's configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this new tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

physics.comp-ph↗