News
University of Michigan uses recycled Kevlar fiber to solve lithium-sulfur battery life cycle issues
The University of Michigan Chemical Sciences and Engineering team, led by Professor Nicholas Kotov, has developed a “new biologically inspired battery membrane” with recycled Kevlar fibers that could quintuple electric vehicle ranges and have a lifespan of 1,000 cycles.
The Ann Arbor, Michigan research facility is one of the best in the world, and Kotov, whose research focuses on the development of biomimetic nanocomposites, the self-assembly of nanoparticles, and chiral nanostructures, has worked to change the narrative on lithium-sulfur cells. “There are a number of reports claiming several hundred cycles for lithium-sulfur batteries, but it is achieved at the expense of other parameters—capacity, charging rate, resilience, and safety,” Kotov said in a press release from the University. “The challenge nowadays is to make a battery that increases the cycling rate from the former 10 cycles to hundreds of cycles and satisfies multiple other requirements including cost.”
Lithium-sulfur batteries can enable five times the capacity of standard lithium-ion cells, which are used in electric vehicles. However, as Professor Kotov mentioned in his quote, the lifespan is significantly decreased due to chemical reactions between molecules. The most common reason for reduced life cycles in lithium-sulfur batteries is dendrites, which are appendages that are designed to receive communications from other cells. These can pierce the membrane of cells, reducing the life span and thus the life cycle of a battery cell.
Another problem is polysulfides, or small molecules of lithium and sulfur, can form and flow to the lithium. They bond and cause blockages, reducing the effectiveness of the membrane. “The membrane is needed to allow lithium ions to flow from the lithium to the sulfur and back—and to block the lithium and sulfur particles, known as lithium polysulfides.”
However, Kevlar, the same material used in bulletproof vests, can stop dendrites from penetrating the membrane using dense aramid fibers found in the material. The cells that Kotov and his team developed use recycled Kevlar fibers. The Kevlar “can enable lithium-sulfur batteries to overcome their Achilles heel of cycle life,” caused by the two previously mentioned reactions between molecules.
An example of the Kevlar system is shown in the images below, as the typical Celgard membrane on the left allows lithium polysulfides to flow through. The Kevlar membrane (right) blocked the polysulfides from traveling through.
“Just half an hour on, the Celgard membrane (left) leaks lithium polysulfides. However, the U-M membrane (right) completely blocks the lithium polysulfides 96 hours later. Image credit: Ahmet Emre, Kotov Lab.” Credit: University of Michigan
“Achieving record levels for multiple parameters for multiple materials properties is what is needed now for car batteries,” Kotov stated. Kotov added that the design of the lithium-sulfur batteries is “nearly perfect” due to its capacity and efficiency reaching theoretical limits. It can also behave more resiliently than lithium-ion cells in warm and cold weather climates, which both have effects on range and efficiency. However, fast charging could reduce the number of lifespans, Kotov added.
Lithium-sulfur batteries could be a good alternative as sulfur is more readily available and abundant than cobalt, which is controversial due to its mining practices. However, automakers like Tesla are reducing cobalt in their batteries vying for other metals, like nickel, instead. Sulfur’s low lifespan and instability, as it changes in size by 78 percent during charging, reduced the possibility of automakers using it in the past, The Independent reported.
The research was funded by the National Science Foundation and the Department of Defense.
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Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.