Machine Learning: An Advanced Platform for Materials Development and State Prediction in Lithium‐Ion Batteries

An Advanced Machine Learning Based Energy Management of Renewable Microgrids Considering Hybrid Electric Vehicles’ Charging Demand

(2021) Tianze Lan et al.   Energies

Prognostics of battery cycle life in the early-cycle stage based on hybrid model

(2021) Yu Zhang et al.   ENERGY

Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning

(2021) Paul Gasper et al.   JOURNAL OF THE ELECTROCHEMICAL SOCIETY

Perspective—Combining Physics and Machine Learning to Predict Battery Lifetime

(2021) Muratahan Aykol et al.   JOURNAL OF THE ELECTROCHEMICAL SOCIETY

Data‐Driven Safety Risk Prediction of Lithium‐Ion Battery

(2021) Yikai Jia et al.   Advanced Energy Materials

Guiding the Design of Heterogeneous Electrode Microstructures for Li‐Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning

(2021) Hongyi Xu et al.   Advanced Energy Materials

An Effective Deep Neural Network Method for Prediction of Battery State at Cell and Module Level

(2021) T. Nguyen-Thoi et al.   Energy Technology

How Machine Learning Will Revolutionize Electrochemical Sciences

(2021) Aashutosh Mistry et al.   ACS Energy Letters

A machine-learning prediction method of lithium-ion battery life based on charge process for different applications

(2021) Yixin Yang   APPLIED ENERGY

State of charge estimation of lithium-ion battery using denoising autoencoder and gated recurrent unit recurrent neural network

(2021) Junxiong Chen et al.   ENERGY

Early prediction of battery lifetime via a machine learning based framework

(2021) Zicheng Fei et al.   ENERGY

Sequent extended Kalman filter capacity estimation method for lithium-ion batteries based on discrete battery aging model and support vector machine

(2021) Tao Sun et al.   Journal of Energy Storage

A Critical Review of Machine Learning of Energy Materials

(2020) Chi Chen et al.   Advanced Energy Materials

Internal short circuit detection in Li-ion batteries using supervised machine learning

(2020) Arunava Naha et al.   Scientific Reports

Lithium Ion Conduction in Cathode Coating Materials from On-the-Fly Machine Learning

(2020) Chuhong Wang et al.   CHEMISTRY OF MATERIALS

Toward Designing Highly Conductive Polymer Electrolytes by Machine Learning Assisted Coarse-Grained Molecular Dynamics

(2020) Yanming Wang et al.   CHEMISTRY OF MATERIALS

Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning

(2020) Yunwei Zhang et al.   Nature Communications

An accurate machine-learning calculator for optimization of Li-ion battery cathodes

(2020) Gregory Houchins et al.   JOURNAL OF CHEMICAL PHYSICS

Machine learning for continuous innovation in battery technologies

(2020) Muratahan Aykol et al.   Nature Reviews Materials

Deep learning networks for capacity estimation for monitoring SOH of Li‐ion batteries for electric vehicles

(2020) Kirandeep Kaur et al.   INTERNATIONAL JOURNAL OF ENERGY RESEARCH

A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems

(2020) Yujie Wang et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Machine learning assisted materials design and discovery for rechargeable batteries

(2020) Yue Liu et al.   Energy Storage Materials

Synchrotron Imaging of Pore Formation in Li Metal Solid-State Batteries Aided by Machine Learning

(2020) Marm B. Dixit et al.   ACS Applied Energy Materials

Battery state-of-health estimation based on a metabolic extreme learning machine combining degradation state model and error compensation

(2020) Lin Chen et al.   ENERGY

An Intelligent Fault Diagnosis Method for Lithium Battery Systems Based on Grid Search Support Vector Machine

(2020) Lei Yao et al.   ENERGY

Machine learning‐based model for lithium‐ion batteries in BMS of electric/hybrid electric aircraft

(2020) Seyed Reza Hashemi et al.   INTERNATIONAL JOURNAL OF ENERGY RESEARCH

Prediction of compression force evolution over degradation for a lithium-ion battery

(2020) Eunji Kwak et al.   JOURNAL OF POWER SOURCES

Data-driven analysis on thermal effects and temperature changes of lithium-ion battery

(2020) Shan Zhu et al.   JOURNAL OF POWER SOURCES

The Application of Data-Driven Methods and Physics-Based Learning for Improving Battery Safety

(2020) Donal P. Finegan et al.   Joule

A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system

(2020) Yuanjun Guo et al.   ENERGY

Online state-of-health estimation of lithium-ion battery based on dynamic parameter identification at multi timescale and support vector regression

(2020) Xiaojun Tan et al.   JOURNAL OF POWER SOURCES

Decoupling of heat generated from ejected and non-ejected contents of 18650-format lithium-ion cells using statistical methods

(2019) William Q. Walker et al.   JOURNAL OF POWER SOURCES

Data-driven prediction of battery cycle life before capacity degradation

(2019) Kristen A. Severson et al.   Nature Energy

A Data-Driven Predictive Prognostic Model for Lithium-Ion Batteries based on a Deep Learning Algorithm

(2019) Phattara Khumprom et al.   Energies

Machine Learning the Voltage of Electrode Materials in Metal-Ion Batteries

(2019) Rajendra P. Joshi et al.   ACS Applied Materials & Interfaces

A review on battery management system from the modeling efforts to its multiapplication and integration

(2019) Ming Shen et al.   INTERNATIONAL JOURNAL OF ENERGY RESEARCH

Special Issue on Artificial Intelligence and Machine Learning for Networking and Communications

(2019) Prosper Chemouil et al.   IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS

Machine-learning-guided directed evolution for protein engineering

(2019) Kevin K. Yang et al.   NATURE METHODS

A new MaterialGo database and its comparison with other high-throughput electronic structure databases for their predicted energy band gaps

(2019) JianShu Jie et al.   Science China-Technological Sciences

Machine Learning Optimization of p-Type Transparent Conducting Films

(2019) Lingfei Wei et al.   CHEMISTRY OF MATERIALS

Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design

(2019) Teng Zhou et al.   Engineering

Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review

(2019) Yi Li et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Unsupervised discovery of solid-state lithium ion conductors

(2019) Ying Zhang et al.   Nature Communications

Attribute driven inverse materials design using deep learning Bayesian framework

(2019) Piyush M. Tagade et al.   npj Computational Materials

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Battery State-of-Charge Estimation Based on Regular/Recurrent Gaussian Process Regression

(2018) Gozde O. Sahinoglu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A quick on-line state of health estimation method for Li-ion battery with incremental capacity curves processed by Gaussian filter

(2018) Yi Li et al.   JOURNAL OF POWER SOURCES

Application of artificial neural networks in design of lithium-ion batteries

(2018) Bin Wu et al.   JOURNAL OF POWER SOURCES

A New Method for Determining the Concentration of Electrolyte Components in Lithium-Ion Cells, Using Fourier Transform Infrared Spectroscopy and Machine Learning

(2018) L. D. Ellis et al.   JOURNAL OF THE ELECTROCHEMICAL SOCIETY

Data Science Approaches for Electrochemical Engineers: An Introduction through Surrogate Model Development for Lithium-Ion Batteries

(2018) Neal Dawson-Elli et al.   JOURNAL OF THE ELECTROCHEMICAL SOCIETY

Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries

(2018) M. Schimpe et al.   JOURNAL OF THE ELECTROCHEMICAL SOCIETY

Liquid electrolyte informatics using an exhaustive search with linear regression

(2018) Keitaro Sodeyama et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Bayesian-Driven First-Principles Calculations for Accelerating Exploration of Fast Ion Conductors for Rechargeable Battery Application

(2018) Randy Jalem et al.   Scientific Reports

A review on first principles based studies for improvement of cathode material of lithium ion batteries

(2018) Arslan Ullah et al.   Journal of Energy Chemistry

State-of-Health Identification of Lithium-Ion Batteries Based on Nonlinear Frequency Response Analysis: First Steps with Machine Learning

(2018) Nina Harting et al.   Applied Sciences-Basel

Robustness Evaluation of Extended and Unscented Kalman Filter for Battery State of Charge Estimation

(2018) Chao Huang et al.   IEEE Access

Performance and cost of materials for lithium-based rechargeable automotive batteries

(2018) Richard Schmuch et al.   Nature Energy

Current status and challenges for automotive battery production technologies

(2018) Arno Kwade et al.   Nature Energy

A Physics-Based Electrochemical Model for Lithium-Ion Battery State-of-Charge Estimation Solved by an Optimised Projection-Based Method and Moving-Window Filtering

(2018) Wei He et al.   Energies

State of charge estimation for electric vehicle power battery using advanced machine learning algorithm under diversified drive cycles

(2018) Taimoor Zahid et al.   ENERGY

The 2018 Materials by Design Roadmap

(2018) Kirstin Alberi et al.   JOURNAL OF PHYSICS D-APPLIED PHYSICS

State-of-charge estimation of Li-ion batteries using deep neural networks: A machine learning approach

(2018) Ephrem Chemali et al.   JOURNAL OF POWER SOURCES

Inverse molecular design using machine learning: Generative models for matter engineering

(2018) Benjamin Sanchez-Lengeling et al.   SCIENCE

Remaining Useful Life Prediction for Lithium-ion Battery: A Deep Learning Approach

(2018) Lei Ren et al.   IEEE Access

Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Suppression of Dendrite Formation in Lithium Metal Anodes

(2018) Zeeshan Ahmad et al.   ACS Central Science

Molecular dynamics simulations with machine learning potential for Nb-doped lithium garnet-type oxide Li7−xLa3(Zr2−xNbx)O12

(2018) Kazutoshi Miwa et al.   PHYSICAL REVIEW MATERIALS

Holistic computational structure screening of more than 12 000 candidates for solid lithium-ion conductor materials

(2017) Austin D. Sendek et al.   Energy & Environmental Science

Li(Ni,Co,Al)O2 Cathode Delithiation: A Combination of Topological Analysis, Density Functional Theory, Neutron Diffraction, and Machine Learning Techniques

(2017) Roman A. Eremin et al.   Journal of Physical Chemistry C

Gaussian process regression for forecasting battery state of health

(2017) Robert R. Richardson et al.   JOURNAL OF POWER SOURCES

Materials space of solid-state electrolytes: unraveling chemical composition–structure–ionic conductivity relationships in garnet-type metal oxides using cheminformatics virtual screening approaches

(2017) Natalia Kireeva et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Lithium battery chemistries enabled by solid-state electrolytes

(2017) Arumugam Manthiram et al.   Nature Reviews Materials

Simulations of inorganic–bioorganic interfaces to discover new materials: insights, comparisons to experiment, challenges, and opportunities

(2016) Hendrik Heinz et al.   CHEMICAL SOCIETY REVIEWS

Application of machine learning methods for the prediction of crystal system of cathode materials in lithium-ion batteries

(2016) M. Attarian Shandiz et al.   COMPUTATIONAL MATERIALS SCIENCE

Online state of health estimation on NMC cells based on predictive analytics

(2016) Maitane Berecibar et al.   JOURNAL OF POWER SOURCES

Review of simplified Pseudo-two-Dimensional models of lithium-ion batteries

(2016) Ali Jokar et al.   JOURNAL OF POWER SOURCES

A novel state of health estimation method of Li-ion battery using group method of data handling

(2016) Ji Wu et al.   JOURNAL OF POWER SOURCES

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

(2016) Rafael Gómez-Bombarelli et al.   NATURE MATERIALS

Critical review of state of health estimation methods of Li-ion batteries for real applications

(2016) M. Berecibar et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

The Cambridge Structural Database

(2016) Colin R. Groom et al.   Acta Crystallographica Section B-Structural Science Crystal Engineering and Materials

Regression Models Using Fully Discharged Voltage and Internal Resistance for State of Health Estimation of Lithium-Ion Batteries

(2015) Kuo-Hsin Tseng et al.   Energies

Informatics-Aided Density Functional Theory Study on the Li Ion Transport of Tavorite-Type LiMTO4F (M3+–T5+, M2+–T6+)

(2015) Randy Jalem et al.   Journal of Chemical Information and Modeling

A Bayesian approach for Li-Ion battery capacity fade modeling and cycles to failure prognostics

(2015) Jian Guo et al.   JOURNAL OF POWER SOURCES

Online estimation of lithium-ion battery capacity using sparse Bayesian learning

(2015) Chao Hu et al.   JOURNAL OF POWER SOURCES

Inverse methods for material design

(2014) Avni Jain et al.   AICHE JOURNAL

A new neural network model for the state-of-charge estimation in the battery degradation process

(2014) LiuWang Kang et al.   APPLIED ENERGY

State-of-charge estimation for battery management system using optimized support vector machine for regression

(2014) J.N. Hu et al.   JOURNAL OF POWER SOURCES

Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles

(2014) Wladislaw Waag et al.   JOURNAL OF POWER SOURCES

Battery state-of-charge estimator using the SVM technique

(2013) J.C. Álvarez Antón et al.   APPLIED MATHEMATICAL MODELLING

Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

(2013) James E. Saal et al.   JOM

Accelerated Materials Design of Lithium Superionic Conductors Based on First-Principles Calculations and Machine Learning Algorithms

(2013) Koji Fujimura et al.   Advanced Energy Materials

An efficient rule-based screening approach for discovering fast lithium ion conductors using density functional theory and artificial neural networks

(2013) Randy Jalem et al.   Journal of Materials Chemistry A

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

(2013) Anubhav Jain et al.   APL Materials

Multivariate Method-Assisted Ab Initio Study of Olivine-Type LiMXO4 (Main Group M2+–X5+ and M3+–X4+) Compositions as Potential Solid Electrolytes

(2012) Randy Jalem et al.   CHEMISTRY OF MATERIALS

AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations

(2012) Stefano Curtarolo et al.   COMPUTATIONAL MATERIALS SCIENCE

Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods

(2012) Adnan Nuhic et al.   JOURNAL OF POWER SOURCES

A review on the key issues for lithium-ion battery management in electric vehicles

(2012) Languang Lu et al.   JOURNAL OF POWER SOURCES

Accelerated computational discovery of high-performance materials for organic photovoltaics by means of cheminformatics

(2011) Roberto Olivares-Amaya et al.   Energy & Environmental Science

Challenges in the development of advanced Li-ion batteries: a review

(2011) Vinodkumar Etacheri et al.   Energy & Environmental Science

The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid

(2011) Johannes Hachmann et al.   Journal of Physical Chemistry Letters

Kinetic Monte Carlo Simulation of Surface Heterogeneity in Graphite Anodes for Lithium-Ion Batteries: Passive Layer Formation

(2011) Ravi N. Methekar et al.   JOURNAL OF THE ELECTROCHEMICAL SOCIETY

Modeling and Simulation of Lithium-Ion Batteries from a Systems Engineering Perspective

(2011) Venkatasailanathan Ramadesigan et al.   JOURNAL OF THE ELECTROCHEMICAL SOCIETY

Smart grids: The energy storage problem

(2010) David Lindley   NATURE

Key challenges in future Li-battery research

(2010) J.- M. Tarascon   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

First principles computational materials design for energy storage materials in lithium ion batteries

(2009) Ying Shirley Meng et al.   Energy & Environmental Science

Lithium-ion battery cell degradation resulting from realistic vehicle and vehicle-to-grid utilization

(2009) Scott B. Peterson et al.   JOURNAL OF POWER SOURCES

Data mining and accelerated electronic structure theory as a tool in the search for new functional materials

(2008) C. Ortiz et al.   COMPUTATIONAL MATERIALS SCIENCE