Ali lashani zand
Active Learning via Bayesian Optimization for Materials Discovery
25 Jun 2021 | | Contributor(s):: Hieu Doan, Garvit Agarwal
In this tutorial, we will demonstrate the use of active learning via Bayesian optimization (BO) to identify ideal molecular candidates for an energy storage application.
Bayesian optimization tutorial using Jupyter notebook
11 Jun 2021 | | Contributor(s):: Hieu Doan, Garvit Agarwal
Active learning via Bayesian optimization for materials discovery
My encounter with Li-ion batteries happened during my Masters and I almost fall for it. I'm currently working as a battery modeling engineer at Nunam.A battery modeling engineer is quite a...
Symposium on Nanomaterials for Energy: Atomic Force Microscopy for Energy Applications - A Review
05 Feb 2021 | | Contributor(s):: Arvind Raman
Atomic Force Microscopy is unique in its ability to measure sub -nanonewton forces arising from a variety physical phenomena between a sharp tip and a sample. In this talk we review the most recent applications of atomic force microscopy to explore and characterize quantitatively the properties...
Krishna Sai Kaligotla
Module 7: Active Learning for Design of Experiments
30 Sep 2020 | | Contributor(s):: Alejandro Strachan, Juan Carlos Verduzco Gastelum
This module introduces active learning in the context of materials discovery with hands-on online simulations. Active learning is a subset of machine learning where the information available at a given time is used to decide what areas of space to explore next. In this module, we will explore...
romdegradation: Physics-based, Reduced Order Degradation Model of Lithium-ion Batteries
24 Jul 2020 | | Contributor(s):: Aniruddha Jana, Surya Mitra Ayalasomayajula, Edwin Garcia
Physics-based, Reduced Order Degradation Model of Lithium-ion Batteries
Austine Francisco Fernando
Maria Salvacion Esmalla
Electrical Engineer Focused on Energy Storage
The Quest for Safer Rechargeable Batteries
19 Dec 2018 | | Contributor(s):: Vilas Pol
The ViPER (Vilas Pol Energy Research) laboratory focuses on the development of high-capacity electrode materials, their engineering for longer cycle life and improved safety.
DFT Study of Anisotropic Elastic Property of LiCoO2 During Lithium Intercalation and Deintercalation Process
06 Dec 2018 | | Contributor(s):: Lingbin Meng, Alejandro Strachan
Lithium cobalt oxide (LiCoO2) is a popular cathode material of lithium-ion batteries due to its excellent electrochemical properties. In this study, the anisotropic elastic property of LiCoO2 has been studied by comparing the ratio of C11 and C33 between LiCoO2 and CoO2. As a result, the...
Bridging Mechanics and Electrochemistry: Experiments and Modeling on Battery Materials
03 Oct 2018 | | Contributor(s):: Kejie Zhao
This talk focuses on the interplay of mechanics, such as large deformation, plasticity, and fracture, with chemical reactions in Li-ion batteries. I will discuss the theories of coupled diffusion and stress, stress regulated interfacial reactions, reactive flow, and corrosive fracture in...