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Enabling fast charging for lithium ion batteries is critical to accelerating the green energy transition. As such, there has been significant interest in tailored fast-charging protocols computed from the solutions of constrained optimal…

The ever-increasing demand for high-capacity rechargeable batteries highlights the need for sensitive and accurate diagnostic technology for determining the state of a cell, for identifying and localizing defects, or for sensing capacity…

We compile data and machine learned models of solid Li-ion electrolyte performance to assess the state of materials discovery efforts and build new insights for future efforts. Candidate electrolyte materials must satisfy several…

Machine learning (ML) techniques have rapidly found applications in many domains of materials chemistry and physics where large data sets are available. Aiming to accelerate the discovery of materials for battery applications, in this work,…

While the use of energy storage combined with grid-scale photovoltaic power plants continues to grow, given current lithium-ion battery prices, there remains uncertainty about the profitability of these solar-plus-storage projects. At the…

There is a growing interest in the development of functional metal oxides with mixed ionic electronic conduction for their application in different strategic fields. In particular, ionic transport-related phenomena are of primary importance…

Lithium-ion batteries are pivotal to technological advancements in transportation, electronics, and clean energy storage. The optimal operation and safety of these batteries require proper and reliable estimation of battery capacities to…

Rechargeable Zn batteries with aqueous electrolytes have been considered as promising alternative energy storage technology, with various advantages such as low cost, high volumetric capacity, environmentally friendly, and high safety.…

The development of new battery materials, particularly novel cathode chemistries, is essential for enabling next generation energy storage technologies. In this work, we employ a multi-fidelity screening protocol combining the Energy-GNoME…

In this study, we employ first-principles density functional theory (DFT) calculations to investigate the electrochemical properties of Nb2C and Nb2CO2 MXenes as potential anode materials for sodium-ion (SIBs) and lithium-ion batteries…

Lithium-ion (Li-ion) batteries are the primary power source in various applications due to their high energy and power density. Their market was estimated to be up to 48 billion U.S. dollars in 2022. However, the widespread adoption of…

Battery degradation remains a pivotal concern in the energy storage domain, with machine learning emerging as a potent tool to drive forward insights and solutions. However, this intersection of electrochemical science and machine learning…

As lithium-ion battery demand grows, so do fire safety challenges. Despite this, research on fire-damaged batteries remains limited. This study explores the distribution of valuable metals (such as Ni, Mn, Co, Cu) in two types of waste…

Sodium-ion batteries are a viable alternative to lithium-ion technology due to the plentiful sodium resources. However, certain commercialization challenges, such as low specific energies and poor cycling performance of current Na-ion…

Magnesium ion batteries (MIBs) are a potential field for the energy storage of the future but are restricted by insufficient rate capability and rapid capacity degradation. Magnesium-sodium hybrid ion batteries (MSHBs) are an effective way…

The penetrations of lithium-ion batteries in transport, energy and communication systems are increasing rapidly. A meticulous model applicable for precise in-situ monitoring and convenient online controlling is in sought to bridge the gap…

This paper presents the development of machine learning-enabled data-driven models for effective capacity predictions for lithium-ion batteries under different cyclic conditions. To achieve this, a model structure is first proposed with the…

Electrifying heavy-duty trucks offers a substantial opportunity to curtail carbon emissions, advancing toward a carbon-neutral future. However, the inherent challenges of limited battery energy and the sheer weight of heavy-duty trucks lead…

Charge unbalance is one of the key issues for series-connected Lithium-ion cells. Within this context, model-based optimization strategies have proven to be the most effective. In the present paper, an ad-hoc electrochemical model, tailored…

Lithium-ion (Li-ion) batteries are ubiquitous in modern energy storage systems, highlighting the critical need to comprehend and optimize their performance. Yet, battery models often exhibit poor parameter identifiability which hinders the…