Tags: batteries

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  1. Ali lashani zand

    https://nanohub.org/members/352618

  2. Timothy Lambden

    https://nanohub.org/members/331325

  3. Active Learning via Bayesian Optimization for Materials Discovery

    Online Presentations | 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.

  4. Bayesian optimization tutorial using Jupyter notebook

    Tools | 11 Jun 2021 | Contributor(s):: Hieu Doan, Garvit Agarwal

    Active learning via Bayesian optimization for materials discovery

  5. Mihir Gaglani

    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...

    https://nanohub.org/members/320848

  6. Symposium on Nanomaterials for Energy: Atomic Force Microscopy for Energy Applications - A Review

    Online Presentations | 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...

  7. Krishna Sai Kaligotla

    https://nanohub.org/members/308153

  8. Jonathan Patricio

    https://nanohub.org/members/304315

  9. Evren Toptop

    https://nanohub.org/members/303331

  10. Module 7: Active Learning for Design of Experiments

    Online Presentations | 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...

  11. romdegradation: Physics-based, Reduced Order Degradation Model of Lithium-ion Batteries

    Tools | 24 Jul 2020 | Contributor(s):: Aniruddha Jana, Surya Mitra Ayalasomayajula, Edwin Garcia

    Physics-based, Reduced Order Degradation Model of Lithium-ion Batteries

  12. Austine Francisco Fernando

    https://nanohub.org/members/293181

  13. Maria Salvacion Esmalla

    https://nanohub.org/members/293069

  14. vivek kumar

    https://nanohub.org/members/291575

  15. Farimah Mousavi

    https://nanohub.org/members/279066

  16. Susheel Kalabathula

    Electrical Engineer Focused on Energy Storage

    https://nanohub.org/members/268015

  17. Chris Jones

    https://nanohub.org/members/221455

  18. The Quest for Safer Rechargeable Batteries

    Online Presentations | 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.

  19. DFT Study of Anisotropic Elastic Property of LiCoO2 During Lithium Intercalation and Deintercalation Process

    Presentation Materials | 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...

  20. Bridging Mechanics and Electrochemistry: Experiments and Modeling on Battery Materials

    Online Presentations | 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...