Research & Rescue: Drowning in Papers

16 papers from the last 8 days. Battery papers are printing at roll-2-roll gigascales.

We’re intercalating a summary of battery research publications that caught our eye. If you enjoy this newsletter please give us a share and subscribe! For business enquiries, reach out at


Research means searching, searching again, and searching some more. But we haven’t had to search very far to find an ocean of new battery research & reviews.

For transparency sake, these publications were cherrypicked by scrolling through the last week of Andrew’s tweet bookmarks. Inherent in this search strategy is the bias of his Twitter feed, personal interests, as well as the marketing prowess of certain institutions/journals. The 16 papers include topics on Li metal, degradation, big data, novel cell/material designs, and innovation rates. Whether you’re in the enthusiast, academia, or industry camps, we hope you find these of interest!

Metallic Lithium

If you’re in on the #BatteryTwitter discourse then you already know we have to start with the calendar ageing of lithium metal.

Boyle et al’s Corrosion of lithium metal anodes during calendar ageing and its microscopic origins” reported on capacity loss associated with letting a lithium-metal battery (with various liquid electrolytes) sit at rest.

Much of the fervour came from juxtaposing the key findings in the paper with the many commercial ventures betting on lithium metal. Steve Levine wrote about initial reactions in his publication The Mobilist, and Matt Lacey then expanded on comments with a very detailed Twitter thread analysis (click through for the full thread):

Some more reactions/comments plucked from the skirmish:

Research is often cyclical and sometimes it’s useful to look back on historical approaches, like this review that covered the degradation of lithium metal from 1967:

Twitter avatar for @ndrewwangAndrew Wang @ndrewwang
On "catastrophic" lithium metal electrode ageing in a review paper from 1967… Also, their 54-year-old recommendations to explore: (i) electrolyte additives (ii) alloying compounds (iii) insoluble anion salts (?) 1/ #battchat #batterytwitter Image

One of the solutions was to use alloying compounds with lithium metal. We previously covered Samsung’s lithium-silver alloy anodes, and more alloying research has followed:

Park et al’s Semi-solid alkali metal electrodes enabling high critical current densities in solid electrolyte batteries” discussed using lithium alloys to enable ultrafast charging without cracking/dendrites in solid-state electrolytes.

Touja et al’s “An Overview on Protecting Metal Anodes with Alloy‐Type Coating” reviews improving Li-metal anode efficiency with Na, K, and Mg.

Albertus et al’s Challenges for and Pathways toward Li-Metal-Based All-Solid-State Batteries” summarizes of ORNL’s workshop on sulfide, oxide, and polymer-based solid-state batteries with contributions from 30 authors.


Of course, plenty still to be said on degradation in Li-ion batteries.

Edge et al’s “Lithium ion battery degradation: what you need to know” tells you the effects of different mechanisms, as well as how to identify and model them.

Paul et al’s A Review of Existing and Emerging Methods for Lithium Detection and Characterization in Li‐Ion and Li‐Metal Batteries” goes through Li detection techniques in the context of minimizing battery degradation.

Dubarry et al’sPerspective on State-of-Health Determination in Lithium-Ion Batteries” reviews predicting and measuring capacity loss in battery management systems.

Big Data

The hottest battery research trend is applying machine learning techniques on big datasets.

Mistry et al’s “How Machine Learning Will Revolutionize Electrochemical Sciences” covers how data-driven predictions and can be helpful for battery research.

Hamar et al’s “Anode Potential Estimation in Lithium-Ion Batteries Using Data-Driven Models for Online Applications” use P2D generated training data to build a fast ML model that can be used online in EVs.

Mckay et al’s “Learning physics based models of Lithium-ion Batteries” use PyBaMM and neural networks to approximate battery dynamics.

Jia et al’s Data‐Driven Safety Risk Prediction of Lithium‐Ion Battery” use machine-learned mechanical models to predict short-circuiting.

New Cell & Material Designs

Plenty of work on different battery components and chemistries too.

Nisar et al’s “Valuation of Surface Coatings in High-Energy Density Lithium-ion Battery Cathode Materials” outlines different coating treatments which are critical in commercial cells.

Wang et al’s Intrinsically Nonflammable Ionic Liquid‐Based Localized Highly Concentrated Electrolytes Enable High‐Performance Li‐Metal Batteries” looks at safer advanced electrolyte formulations.

Xue et al’s Ultra-high-voltage Ni-rich layered cathodes in practical Li metal batteries enabled by a sulfonamide-based electrolyte” demonstrates the performance of a battery with high-Ni cathode, LiFSI electrolyte, and metal anode.

Robinson et al’s 2021 roadmap on lithium sulfur batteries” discusses the prospects of this beyond-Li-ion technology.

Rate of Improvement

Ziegler et al’s Re-examining rates of lithium-ion battery technology improvement and cost decline” estimates the price drop, market growth, patent activity, and performance improvements of LIBs.


We’ve just noticed that the majority of the papers listed were actually reviews, and recent research has shown that review papers get more attention, so let’s see how this “review-ception” newsletter does!


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About the writers:

Andrew is a PhD researcher at the University of Oxford (@ndrewwang). Nicholas is a business manager at UCL Business and Venture Fellow with Berkeley SkyDeck (@nicholasyiu). Ethan is a battery scientist with experience at startups, research labs, and EV manufacturers across the world (@ethandalter).