Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Marco Ragone"'
Autor:
Ishraque Zaman Borshon, Marco Ragone, Abhijit H. Phakatkar, Lance Long, Reza Shahbazian-Yassar, Farzad Mashayek, Vitaliy Yurkiv
Publikováno v:
npj Computational Materials, Vol 10, Iss 1, Pp 1-14 (2024)
Abstract A novel approach is presented by integrating images-driven deep learning (DL) with high entropy oxides (HEOs) analysis. A fully convolutional neural network (FCN) is used to interpret experimental scanning transmission electron microscopy (S
Externí odkaz:
https://doaj.org/article/36b5de58823e4aa3992d6aed7e804769
Publikováno v:
Journal of Visualization. 24:771-785
Accurate extraction of features in fluid flows is of importance due to the presence in many natural and technological systems. Recently, methods based on machine learning have emerged as an alternative to traditional Eulerian-based methods to extract
Autor:
Reza Shahbazian-Yassar, Tara Foroozan, Marco Ragone, Farzad Mashayek, Ajaykrishna Ramasubramanian, Vitaliy Yurkiv
Publikováno v:
ACS Applied Energy Materials. 3:10560-10567
The structural character and mechanical stability of solid-electrolyte interphase (SEI) play a critical role in the formation of dendrites in lithium metal batteries (LMBs). However, due to the com...
Autor:
Basab Ranjan Das Goswami, Massimiliano Mastrogiorgio, Marco Ragone, Vahid Jabbari, Reza Shahbazian-Yassar, Farzad Mashayek, Vitaliy Yurkiv
Publikováno v:
SSRN Electronic Journal.
Autor:
Basab Ranjan Das Goswami, Massimiliano Mastrogiorgio, Marco Ragone, Farzad Mashayek, Vitaliy Yurkiv
Publikováno v:
ECS Meeting Abstracts. :230-230
Li-ion cells have been widely used in battery electric vehicles (BEV), hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), and stationary energy storage units due to their high specific energy and excellent cycle life. However, t
Autor:
Farzad Mashayek, Reza Shahbazian-Yassar, Marco Ragone, Tara Foroozan, Ajaykrishna Ramasubramanian, Vitaliy Yurkiv
Publikováno v:
The Journal of Physical Chemistry C. 123:10237-10245
The composition, structure, and the formation mechanism of the solid–electrolyte interphase (SEI) in lithium-based (e.g., Li-ion and Li metal) batteries have been widely explored in the literature....
Autor:
Massimiliano Mastrogiorgio, Basab Ranjan Das Goswami, Marco Ragone, Farzad Mashayek, Vitaliy Yurkiv
Publikováno v:
ECS Meeting Abstracts. :434-434
With the rapid development and widespread applications of lithium-ion batteries (LIBs), there is an ongoing need to extend and apply theoretical models that assist LIB’s safety aspects. It is particularly important for electric vehicles (EVs) due t
Autor:
Vitaliy Yurkiv, Vahid Jabbari, Massimiliano Mastrogiorgio, Basab Ranjan Das Goswami, Marco Ragone, Reza Shahbazian-Yassar, Farzad Mashayek
Publikováno v:
ECS Meeting Abstracts. :251-251
The formation, structure and composition of the solid-electrolyte interphase (SEI) in lithium batteries have been extensively explored in the prior literature. It is commonly accepted that the SEI consists of two inorganic layer followed by organic l
Autor:
Basab Ranjan Das Goswami, Massimiliano Mastrogiorgio, Marco Ragone, Farzad Mashayek, Vitaliy Yurkiv
Publikováno v:
ECS Meeting Abstracts. :190-190
Safety aspects of Li-ion batteries (LIBs) operation become increasingly important due to their integration into large-scale systems such as electric vehicles (EVs). Recent events involving many EVs explosions endangering consumers’ lives have shown
Autor:
Farzad Mashayek, Mahmoud Tamadoni Saray, Reza Shahbazian-Yassar, Lance Long, Marco Ragone, Vitaliy Yurkiv
Publikováno v:
Computational Materials Science. 201:110905
The latest developments of machine learning (ML) and deep learning (DL) algorithms have paved the way to effectively analyze the atomic structure of chemically-complex materials. In this work, we present a DL model built upon a fully convolutional ne