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Cornell’s NanoScale Science and Technology Facility (CNF) hosted its 2025 Annual Meeting on November 18 at the Statler Hotel, bringing together researchers, industry partners, faculty, students, and national collaborators to spotlight CNF’s leadership in micro- and nanotechnology. 

The program showcased advances in photonics, quantum devices, semiconductor fabrication, sustainability, life sciences and workforce development. Speakers across academia and industry emphasized a shared mission: strengthening U.S. semiconductor leadership through collaboration and a robust innovation pipeline

Decision-Making Amid Uncertainty 

Invited keynote speaker Cheryl Strauss Einhorn, Cornell Graduate, author and founder of Decisive, a decision sciences company, chose to address the audience through an informal interview/Q&A led by Prof.  Judy Cha, Director of the CNF. It was an engaging conversation providing insight into complex problem solving and decision-making process.   

IBM: Wafer Scale Semiconductor Lab to Fab Process Development and Prototyping 

Dr. Dirk Pfeiffer, Director of IBM’s Microelectronics Research Laboratory (MRL), was a plenary speaker at the CNF Annual Meeting. In his presentation, Dirk outlined MRL’s core mission of accelerating semiconductor technologies from early-stage innovation to wafer-scale development and manufacturing, bringing concepts effectively from “lab to fab”.  Dirk highlighted the importance of academic partners like the CNF that remain vital for understanding emerging materials before they reach manufacturing. 

Driving Innovation Through Community and Collaboration

The meeting also featured talks from Cornell researchers, including flying microrobots developed in Itai Cohen’s lab, advances in assisted reproduction from Alireza Abbaspourrad’s group, and new Creative Technologies for Teaching and Workforce Training led by Becky Lane at the Center for Teaching Innovation.

CNF Director Judy Cha presented the Nellie Whetten Award to Ph.D. student Yeryun Cheon recognizing the achievements of women in science, while a special panel of CNF staff introduced a new suite of tools.  Attendees were able to ask questions and hear directly from CNF experts about the equipment and the expanded capabilities now available to the research community. Throughout the day, participants engaged with vendors and student posters featuring emerging work in nanofabrication, materials research, and device innovation.

Across presentations, one theme resonated: CNF’s unique position as a national nanofabrication user facility for research, prototyping, product development, nanofabrication training, and cross-disciplinary discovery. As quantum and nanofabrication technologies continue to accelerate, CNF is helping to equip researchers, industry partners, and future engineers for the next wave of innovation.

The event was made possible with support from CNF’s sponsors: AJA International, JEOL, Oxford Instruments, REYNOLDSTECH, Corning, 3C Technical, ASML, Edwards, EFC Gases and Advanced Materials, Evident, GenISys, Heidelberg Instruments, IEEE, Kurt J. Lesker, LAB 14, Lam Research, Pozzetta, Plasma-Therm, Samco, Semi, Tescan, Xallent, Applied Energy Systems, RedBarnHPC, C&D Semiconductor Services, The Cornell Store, and Wegmans.

As for Wilcox, he’s long been one of that small group of privacy zealots who buys his SIM cards in cash with a fake name. But he hopes Phreeli will offer an easier path—not just for people like him, but for normies too.

“I don’t know of anybody who’s ever offered this credibly before,” says Wilcox. “Not the usual telecom-strip-mining-your-data phone, not a black-hoodie hacker phone, but a privacy-is-normal phone.”

Even so, enough tech companies have pitched privacy as a feature for their commercial product that jaded consumers may not buy into a for-profit telecom like Phreeli purporting to offer anonymity. But the EFF’s Cohn says that Merrill’s track record shows he’s not just using the fight against surveillance as a marketing gimmick to sell something. “Having watched Nick for a long time, it’s all a means to an end for him,” she says. “And the end is privacy for everyone.”

Merrill may not like the implications of describing Phreeli as a cellular carrier where every phone is a burner phone. But there’s little doubt that some of the company’s customers will use its privacy protections for crime—just as with every surveillance-resistant tool, from Signal to Tor to briefcases of cash.

Phreeli won’t, at least, offer a platform for spammers and robocallers, Merrill says. Even without knowing users’ identities, he says the company will block that kind of bad behavior by limiting how many calls and texts users are allowed, and banning users who appear to be gaming the system. “If people think this is going to be a safe haven for abusing the phone network, that’s not going to work,” Merrill says.

But some customers of his phone company will, to Merrill’s regret, do bad things, he says—just as they sometimes used to with pay phones, that anonymous, cash-based phone service that once existed on every block of American cities. “You put a quarter in, you didn’t need to identify yourself, and you could call whoever you wanted,” he reminisces. “And 99.9 percent of the time, people weren’t doing bad stuff.” The small minority who were, he argues, didn’t justify the involuntary societal slide into the cellular panopticon we all live in today, where a phone call not tied to freely traded data on the caller’s identity is a rare phenomenon.

Ly shows that one function this serves is to send versions of a protein to different parts of the cell. Many proteins contain ZIP code-like sequences that tell the cell’s machinery where to deliver them so the proteins can do their jobs. Ly found many examples in which longer and shorter versions of the same protein contained different ZIP codes and ended up in different places within the cell.

In particular, Ly found many cases in which one version of a protein ended up in mitochondria, structures that provide energy to cells, while another version ended up elsewhere. Because of the mitochondria’s role in the essential process of energy production, mutations to mitochondrial genes are often implicated in disease.

Ly wondered what would happen when a disease-causing mutation eliminates one version of a protein but leaves the other intact, causing the protein to only reach one of its two intended destinations. He looked through a database containing genetic information from people with rare diseases to see if such cases existed, and found that they did. In fact, there may be tens of thousands of such cases. However, without access to the people, Ly had no way of knowing what the consequences of this were in terms of symptoms and severity of disease.

Meanwhile, Cheeseman, who is also a professor of biology at MIT, had begun working with Boston Children’s Hospital to foster collaborations between Whitehead Institute and the hospital’s researchers and clinicians to accelerate the pathway from research discovery to clinical application. Through these efforts, Cheeseman and Ly met Fleming.

One group of Fleming’s patients have a type of anemia called SIFD — sideroblastic anemia with B-cell immunodeficiency, periodic fevers, and developmental delay — that is caused by mutations to the TRNT1 gene. TRNT1 is one of the genes Ly had identified as producing a mitochondrial version of its protein and another version that ends up elsewhere: in the nucleus.

Fleming shared anonymized patient data with Ly, and Ly found two cases of interest in the genetic data. Most of the patients had mutations that impaired both versions of the protein, but one patient had a mutation that eliminated only the mitochondrial version of the protein, while another patient had a mutation that eliminated only the nuclear version.

When Ly shared his results, Fleming revealed that both of those patients had very atypical presentations of SIFD, supporting Ly’s hypothesis that mutations affecting different versions of a protein would have different consequences. The patient who only had the mitochondrial version was anemic, but developmentally normal. The patient missing the mitochondrial version of the protein did not have developmental delays or chronic anemia, but did have other immune symptoms, and was not correctly diagnosed until his 50s. There are likely other factors contributing to each patient’s exact presentation of the disease, but Ly’s work begins to unravel the mystery of their atypical symptoms.

Cheeseman and Ly want to make more clinicians aware of the prevalence of genes coding for more than one protein, so they know to check for mutations affecting any of the protein versions that could contribute to disease. For example, several TRNT1 mutations that only eliminate the shorter version of the protein are not flagged as disease-causing by current assessment tools. Cheeseman lab researchers, including Ly and graduate student Matteo Di Bernardo, are now developing a new assessment tool for clinicians, called SwissIsoform, that will identify relevant mutations that affect specific protein versions, including mutations that would otherwise be missed.

“Jimmy and Iain’s work will globally support genetic disease variant interpretation and help with connecting genetic differences to variation in disease symptoms,” Fleming says. “In fact, we have recently identified two other patients with mutations affecting only the mitochondrial versions of two other proteins, who similarly have milder symptoms than patients with mutations that affect both versions.”

Long term, the researchers hope that their discoveries could aid in understanding the molecular basis of disease and in developing new gene therapies: Once researchers understand what has gone wrong within a cell to cause disease, they are better equipped to devise a solution. More immediately, the researchers hope that their work will make a difference by providing better information to clinicians and people with rare diseases.

“As a basic researcher who doesn’t typically interact with patients, there’s something very satisfying about knowing that the work you are doing is helping specific people,” Cheeseman says. “As my lab transitions to this new focus, I’ve heard many stories from people trying to navigate a rare disease and just get answers, and that has been really motivating to us, as we work to provide new insights into the disease biology.”

Go high or go wide? DeepSeek and ByteDance, the two leaders of China’s AI industry, are adopting vastly different strategies.

On Monday, DeepSeek released DeepSeek V3.2, another open-weight model that anyone can tinker with. The startup says it performs on par with the latest models from OpenAI and Google, and it even beats them on some key mathematics benchmarks.

That same day, ByteDance, whose dominance in AI applications we covered previously, introduced even more ways for people to use its chatbot, Doubao. ByteDance is now working with a Chinese smartphone manufacturer to embed Doubao into the operating system, giving it access to different apps and allowing it to conduct agentic tasks with them. In other words, it’s coming for Apple’s Siri.

Both ByteDance and DeepSeek have AI apps with over 140 million monthly users. But their latest announcements represent two diverging trends in China’s AI industry. While some companies are still competing with their Western counterparts to build ever more capable models, others have quietly withdrawn from that game and are focusing on how they can integrate their AI tools into people’s everyday lives.

DeepSeek Resurfaces

DeepSeek’s latest open-weight model may have disappointed some of its most loyal followers, who are still waiting for R2, a much-anticipated update to the initial model that rocked Silicon Valley in January. Instead, DeepSeek released V3.2 and V3.2-Speciale, which are better-optimized versions of its previous model V3.2-Exp, released in September.

Still, V3.2 caused a stir in the AI industry because DeepSeek claims it can solve the type of advanced math questions asked at the International Mathematical Olympiad, and its performance on other coding and reasoning tasks is supposedly on par with or above GPT 5 and Gemini 3. “It suddenly dawned on me why they call the company DeepSeek with the whale as a motif. Because just like a whale, it rarely surfaces, but every time it surfaces, it always makes a massive splash,” says Jen Zhu Scott, an AI investor and the cofounder and CEO of Power Dynamics, a modular data-center solutions firm.

However, I can’t help but feel like this arms race of AI models is getting a little tiring, particularly because so many new ones have been released in the last month, each claiming to take humanity one step higher. In less than 20 days, we had OpenAI’s GPT 5.1, Google’s Gemini 3 Pro, Anthropic’s Claude Opus 4.5; throw in Chinese open source models like Moonshot’s Kimi K2 and DeepSeek’s V3.2, and it becomes a total mess. My attention span can be summarized by this perfect meme.

“At the end of the day, we can’t keep up with all these hairline differences between different models, different releases,” Zhu says. “It actually doesn’t make a huge difference, apart from some kind of stock market speculation on who’s gonna win.”