News
Shark Tank-backed Natrion unveils solid-state battery separator with near-zero fire risk
Mark Cuban-backed Natrion has unveiled its latest developments in solid-state battery manufacturing with the new LISIC278 separator in a traditional pouch cell. The separator allows for a higher thermal resistance than other EV batteries, decreasing the risk of fires and combustion. Additionally, the cell showed a 40 percent increase in the charge rate compared to a conventional battery with the same capacity.
Natrion’s LISIC278 material utilizes a Lithium Solid Ionic Composite (LISIC) electrolyte that mimics the performance and specs of a standard polyolefin separator, which sits between the anode and cathode. The purpose of the separator is to prevent short circuits by keeping the electrodes apart while also allowing ionic charges to flow through with the necessary passage of currents in a cell. The LISIC cell can utilize significantly less of the electrolyte liquid by delivering high ion transport capability at ambient conditions. This keeps the cells’ thermal resistance above 200° Celsius (392 F) without having any porosity.
The LISIC278 separator’s ability to remain stable at high temperatures nearly eliminates the risk of fire, while it also exhibits a reduced ability for a thermal event altogether.
CEO and Co-Founder Alex Kosyakov said that reducing flammable liquid electrolytes was a main focus because reducing the perception that battery cells will catch on fire is a key to growing mass EV adoption:
“Reducing our reliance on flammable liquids in EV batteries is key to reducing fire risk and ultimately making mass EV adoption more viable. So the fact that this data shows we can produce battery cells that are just as efficient with only a small fraction of that liquid is a huge win.”
Cycling performance of a two-layer pouch cell at C/3 charge and discharge using LISIC278 with an NMC532 cathode and natural graphite anode.
In addition to the LISIC278 cells’ stability, it also showed a 40 percent increase in charge rate, taking just 3 hours to charge as opposed to 5 hours for a conventional cell with the same capacity. Natrion utilized a standard pouch containing NMC532 cathode, LP40 liquid electrolyte, and a natural graphite anode with a state-of-the-art separator for its experiments. This was compared to the Natrion pouch, which was identical but utilized the LISIC279 separator instead of a conventional design.
The cell with the LISIC279 separator also displayed a high initial coulombic efficiency. Conventional lithium-ion cells “typically” have less energy available than they are charged with when used the first few times. Natrion cells did not display this issue and “exhibited higher initial coulombic efficiencies and resultantly improved capacity retention at higher C-rates,” the company said.
Dr. Jon Tuck, an expert in energy storage for Silent Koala, said using less electrolyte liquid while maintaining a high initial coulombic rate is difficult, especially at the capacity and C-rate threshold given here. “These results are highly promising and show a versatility of use for LISIC that we have yet to see from other solid-state electrolyte materials. It signals the potential of Natrion’s materials to really advance the industry and the technological feats being developed,” Dr. Tuck added.
Natrion is based in Binghamton, New York, and has operations in Champaign, Illinois.
Solid-state batteries utilize a solid material to allow energy to flow from the cathode to the anode, instead of traditional lithium-ion cells, which utilize a liquid electrolyte solution. EV makers have not been able to switch to solid-state technology due to its complex manufacturing processes. Additionally, researchers have not been able to find ideal solutions for the material it would utilize in the batteries, and this continues to be a severe bottleneck of solid-state development.
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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.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
