arXiv subjects

Juan Carlos Verduzco

Publications and source records attributed to Juan Carlos Verduzco.

3 recordsLinked to original sources

arXiv2023

nanoHUB services for FAIR simulations and data: ResultsDB and Sim2Ls

nanoHUB is an open cyber platform for online simulation, data, and education that seeks to make scientific software and associated data widely available and useful. This paper describes recent developments in our simulation infrastructure to address modern data needs. nanoHUB's Sim2Ls (pronounced sim tools) make simulation, modeling, and data workflows discoverable and accessible to all users for cloud computing using standard APIs. In addition, published tools are findable (with digital object identifiers), reusable (via documented requirements and services), and reproducible via containerization. In addition, all Sim2L runs are automatically cached, and their results indexed into a global and queryable database (ResultsDB). We believe this infrastructure significantly lowers the barriers towards making simulation/data workflows and their data findable, accessible, interoperable, and reusable (FAIR). This frictionless access to simulations and data enables researchers, instructors, and students to focus on the application of these products to advance their fields.

cond-mat.mtrl-sci↗

arXiv2023

Mapping microstructure to shock-induced temperature fields using deep learning

The response of materials to dynamical, or shock, loading is important to planetary science, aerospace engineering, and energetic materials. Thermal-activated processes, including chemical reactions and phase transitions, are significantly accelerated by the localization of the energy deposited into hotspots. These results from the interaction of a supersonic wave with the materials microstructure and are governed by complex, coupled processes, including the collapse of porosity, interfacial friction, and localized plastic deformation. These mechanisms are not fully understood and today we lack predictive models to, for example, predict the shock to detonation transition from chemistry and microstructure alone. We demonstrate that deep learning techniques can be used to predict the resulting shock-induced temperature fields in complex composite materials obtained from large-scale molecular dynamics simulations with the initial microstructure as the only input. The accuracy of the Microstructure-Informed Shock-induced Temperature net (MISTnet) model is higher than the current state of the art at a fraction of the computation cost.

cond-mat.mtrl-sci↗

arXiv2021

Ionic conductivity optimization of composite polymer electrolytes through filler particle chemical modification

The addition of filler particles to polymer electrolytes is known to increment their ionic conductivity (IC). A detailed understanding of how the interactions between the constituent materials are responsible for the enhancement, remains to be developed. A significant contribution is ascribed to an increment of the polymer amorphous fraction, induced by the fillers, resulting in the formation of higher ionic conductivity channels in the polymer matrix. However, the dependence of IC on the particle weight load and its composition on the polymer morphology is not fully understood. This work investigates Li ion transport in composite polymer electrolytes (CPE) comprising Bi-doped LLZO particles embedded in PEO: LiTFSI matrixes. We find that the IC optimizes for very low particle weight loads (5 to 10%) and that both its magnitude and the load required, strongly depend on the garnet particle composition. Based on structural characterization results and electrochemical impedance spectroscopy, a mechanism is proposed to explain these findings. It is suggested that the Li-molar content in the garnet particle controls its interactions with the polymer matrix, resulting at the optimum loads reported, in the formation of high ionic conductivity channels. We propose that filler particle chemical manipulation of the polymer morphology is a promising avenue for the further development of composite polymer electrolytes.

cond-mat.mtrl-sci↗