Chemists at Brown University have shown the first experimental evidence that carbon buckyballs, which launched the nanotechnology revolution, have a cousin made from 80 atoms of the element boron.

The nanoscale world appears to have a new ball to kick around.

Researchers from Brown University have shown the first experimental evidence for a “buckyball” molecule made from 80 boron atoms. The new structure is the cousin of the carbon buckyball, known formally as Buckminsterfullerene — a soccer ball-shaped molecule made from 60 carbon atoms that helped launch the nanotechnology revolution when it was discovered just over 40 years ago.

The evidence for the new nanostructure comes from photoelectron spectroscopy, which provides a sort of fingerprint for different molecular shapes and structures.

“I really didn’t think this structure was going to be stable and that we were going to disprove its existence,” said Lai-Sheng Wang, a professor of chemistry at Brown and the paper’s corresponding author. “But when my student showed me the spectrum for the boron-80 cluster after I returned from a trip, I couldn’t believe it.”

The study is published in Chemical Science.

Carbon has long been the star of the nanotechnology world. The configuration of its electrons enables it to make all kinds of interesting shapes — including buckyballs, nanotubes and one-atom-thick graphene sheets — which have found uses in energy technology, medicine and more. Wang has been working for nearly 30 years to see if boron, carbon’s neighbor on the periodic table, could make similar structures. If so, the structures could have even more interesting properties than their carbon cousins.

In 2013, Wang’s team showed that clusters of 36 boron atoms formed a planar, one-atom-thick disc. By stitching those discs together, it would be possible to make borophene (a boron equivalent to graphene) — which two other labs indeed synthesized two years after Wang’s discovery. In 2014, Wang’s team showed that a 40-atom boron cluster formed a hollow cage similar to a buckyball, but lacking the perfect spherical symmetry.

For this latest research, Brown graduate students Hyun Wook Choi and Deniz Kahraman started by blasting a boron target with a high-powered laser. The impact knocks off a plume of boron atoms, which are then cooled quickly to form nanoclusters with various numbers of atoms. The clusters are then weighed to figure out how many atoms are present in each in a mass spectrometer.

To investigate the shapes of the clusters, the researchers use photoelectron spectroscopy. They zap each cluster with a second laser, which knocks an electron out of the structure and sends it flying down a long tube that Wang calls his “electron racetrack.” The speed at which the electron flies down the racetrack is used to determine the cluster’s electron binding energy spectrum — a readout of how tightly the cluster holds its electrons. That spectrum encodes information about the cluster’s structure.

The photoelectron spectra of highly symmetrical structures have distinct peaks in their electron binding energy distribution. As Wang and his team investigated boron clusters larger than the 40-atom cage, the spectral readouts started to become relatively featureless, suggesting that the structures weren’t particularly interesting. Wang said he started to doubt that the 80-atom cluster — which had previously been theorized to be a symmetrical ball — was actually going to be interesting.

“My attitude at that time was that this was probably going to be a low-symmetry thing,” Wang said. “I thought, we’ll get this ugly spectrum, publish it, then it’s the end of the story for this B₈₀ cluster.”

But the photoelectron spectrum for the cluster told a different story. The peaks in the spectrum stuck out like sore thumbs, which suggests a highly stable and highly symmetric structure. Working with colleagues in other labs around the world, Wang and his team determined that the only structure that could produce that surprisingly simple spectrum was the buckyball.

The findings are not without controversy. Density functional theory (DFT), the gold-standard method for determining molecular properties, suggests that the boron buckyball shouldn’t be stable. Yet after an exhaustive search of possible 80-atom boron configurations, all signs pointed to the buckyball.

“I think the DFT calculations are wrong in this case,” he said. “I think DFT has some of the bond lengths wrong for the B₈₀ buckyball, and that leads to incorrect predictions for its stability.”

Wang says he hopes to work with colleagues at Brown and elsewhere to better understand why DFT might have gone awry in this case. In the meantime, Wang also hopes to work with colleagues in other labs to investigate the chemical reactivity of the B₈₀ buckyball that will be important to assess if boron buckyballs can be synthesized in bulk form. Wang’s lab creates clusters in a vacuum, and it’s not yet clear if boron buckyballs would be too reactive to stay intact in ambient conditions.

Just as with two-dimensional borophene, Wang is hopeful that the challenge of trying to make boron buckyballs in bulk can be overcome soon.

“It only took two years for borophene,” Wang said, “so we’ll see.”

Source: Brown University

Key takeaways

• Transparency obligations under Article 50 become enforceable on 2 August 2026 – chatbot disclosure, synthetic content marking and deepfake labelling.
• High-risk obligations did not arrive. Stand-alone Annex III systems now have until 2 December 2027; AI embedded in regulated products under Annex I has until 2 August 2028.
• The change came through the Digital Omnibus on AI, signed on 8 July 2026 and awaiting publication in the Official Journal.
• A new prohibition on AI-generated non-consensual intimate imagery was added to Article 5.
• The AI Office gained broader supervisory reach over vertically integrated AI providers.

Two speeds, one deadline

For two years, 2 August 2026 sat in compliance calendars as the date the EU AI Act would become substantially applicable. Regulation (EU) 2024/1689 entered into force on 1 August 2024 with a staggered timetable, and August 2026 was meant to be the moment the framework’s core obligations – including those for high-risk systems – switched on across the single market.

That is no longer what happens. The deadline still arrives, but it arrives carrying far less than planned. A late amendment package known as the Digital Omnibus on AI has split the calendar into two speeds: transparency rules land on schedule, while the heavier high-risk regime slides more than a year into the future.

The practical consequence for anyone reading older guidance is blunt. A large share of the “AI Act 2026” material published before July describes a legal position that no longer exists.

What switches on in August

Article 50 is the part that survives the reshuffle intact. Its general transparency requirements – paragraphs 1, 3 and 4 – apply from 2 August 2026 to any AI system placed on the EU market. In practice, that covers three things.

Systems that interact directly with people must make clear that a person is dealing with a machine, unless that is obvious from context. Deepfakes and manipulated audio, image or video content must be disclosed as artificially generated. Emotion recognition and biometric categorisation systems must inform the people exposed to them.

The machine-readable marking obligation in Article 50(2) – watermarking of synthetic audio, image, video and text – also applies from 2 August for newly placed systems. Providers whose systems were already on the market before that date get until 2 December 2026 to comply, a concession aimed at retrofitting rather than redesign.

The Act’s other early layers remain untouched. Prohibited practices have applied since February 2025, and the general-purpose AI rules since August 2025. The risk-based architecture itself was never on the negotiating table.

What moved, and by how much

The Omnibus deferred the high-risk regime in two tranches. Stand-alone systems listed in Annex III – recruitment tools, credit scoring, education, law enforcement, border control, critical infrastructure – now face full compliance on 2 December 2027 rather than 2 August 2026. That is a seventeen-month extension.

AI embedded in products already covered by EU product safety law under Annex I – medical devices, machinery, toys – moves further still, to 2 August 2028.

The reason for the deferral is procedural rather than philosophical. Implementation had stalled on two fronts: member states were slow to designate national competent authorities, and the harmonised standards and conformity assessment tools that high-risk compliance depends on were not finished. Regulators found themselves in the position of demanding conformity against benchmarks that did not yet exist.

The obligations themselves have not been softened. Providers of Annex III systems gain runway, not relief.

How the Omnibus got here

The timeline is worth recording, because it explains why so much published guidance is stale.

The European Commission proposed the package on 19 November 2025 as part of a wider simplification effort touching the GDPR, the ePrivacy Directive, NIS2 and the Data Act. A second political trilogue on 28 April 2026 collapsed without agreement. Negotiators returned and reached a provisional deal on 7 May, which member state representatives confirmed on 13 May.

The European Parliament adopted the text on 16 June 2026. The Council gave final approval on 29 June, closing file 2025/0359(COD). The final act was signed on 8 July 2026 and now awaits publication in the Official Journal, entering into force on the third day after that publication.

This leaves a narrow procedural window. For the new dates to be binding before the original deadline bites, publication needs to happen in the second half of July. Until it does, the letter of the law still points at 2 August 2026 for high-risk obligations – a gap that matters mainly to organisations that already demobilised their compliance programmes on the strength of a political agreement.

The parts nobody expected

Two changes went further than simplification.

The first is a new prohibition. Article 5 now bans AI systems designed to generate non-consensual intimate imagery – the so-called nudifier applications – alongside child sexual abuse material. Parliament pushed for this during the trilogue, and the new prohibited practices apply from 2 December 2026. A package sold as deregulation ended up adding a ban.

The second is institutional. The AI Office gained expanded supervisory powers, extending beyond general-purpose AI models to the systems built on them where model and system come from the same business group. For vertically integrated providers – which describes most of the frontier labs – this consolidates oversight in Brussels rather than across twenty-seven national regulators.

The amending regulation also reaches outside the AI Act itself, touching the EASA civil aviation rules and the Machinery Regulation. For products inside the Machinery Regulation’s scope, direct application of the AI Act is excluded; the Commission may instead introduce health and safety requirements for high-risk AI within that framework.

Regulatory sandboxes slipped too. Member states must have at least one national sandbox operational by 2 August 2027, a year later than the AI Act originally required, with an EU-level sandbox now available as an option for testing at continental scale.

What this means in practice

For companies deploying chatbots, generative media tools or synthetic content pipelines into the EU, August is real and close. Disclosure and labelling are engineering work, and the exemption for context-obvious interactions is narrower than it sounds.

For companies building recruitment screening, credit scoring or biometric systems, the pressure has genuinely eased – but the December 2027 date assumes standards arrive in time. If harmonised standards slip again, the industry will be back in the same argument in eighteen months, with less credibility for a second extension.

The broader signal is about how the EU now handles its own digital rulebook. The AI Act took years to negotiate and was amended for the first time within two years of adoption, before its central provisions ever applied. Whether that reads as responsiveness or as a regulator flinching under industry pressure depends largely on what the harmonised standards look like when they finally land.

Written by Alius Noreika

Sources

• Council of the EU – Artificial intelligence: Council gives final green light to simplify and streamline rules (29 June 2026): https://www.consilium.europa.eu/en/press/press-releases/2026/06/29/artificial-intelligence-council-gives-final-green-light-to-simplify-and-streamline-rules/
• Council of the EU – Artificial intelligence act policy page: https://www.consilium.europa.eu/en/policies/artificial-intelligence-act/
• European Commission – AI Act, Shaping Europe’s digital future: https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
• European Parliament Think Tank – Digital Omnibus on AI briefing: https://www.europarl.europa.eu/thinktank/en/document/EPRS_BRI(2026)782651
• Freshfields – EU AI Act unpacked #34: The final Digital Omnibus on AI: https://www.freshfields.com/en/our-thinking/blogs/technology-quotient/eu-ai-act-unpacked-34-the-final-digital-omnibus-on-ai-key-amendments-to-the-a-102nber
• Gibson Dunn – EU AI Act Omnibus Agreement: Postponed High-Risk Deadlines and Other Key Changes: https://www.gibsondunn.com/eu-ai-act-omnibus-agreement-postponed-high-risk-deadlines-and-other-key-changes/
• Sidley Data Matters – EU Lawmakers Reach Provisional Agreement to Delay Key EU AI Act Obligations: https://datamatters.sidley.com/2026/06/22/eu-lawmakers-reach-provisional-agreement-to-delay-key-eu-ai-act-obligations/
• DLA Piper – The Digital AI Omnibus: Proposed deferral of high risk AI obligations under the AI Act: https://knowledge.dlapiper.com/dlapiperknowledge/globalemploymentlatestdevelopments/2026/The-Digital-AI-Omnibus-Proposed-deferral-of-high-risk-AI-obligations-under-the-AI-Act
• White & Case – EU agrees Digital Omnibus deal to simplify AI rules: https://www.whitecase.com/insight-alert/eu-agrees-digital-omnibus-deal-simplify-ai-rules
• Digital Watch Observatory – Digital Omnibus on AI: the EU’s AI Act simplification and new AI Office powers: https://dig.watch/updates/digital-omnibus-eu-ai-act-new-ai-office-powers
• Bird & Bird – AI Act and Provisionally Agreed AI Digital Omnibus Consolidated Version: https://www.twobirds.com/en/insights/2026/ai-act-,-a-,-provisionally-agreed-ai-digital-omnibus-consolidated-version
• NicFab – Digital Omnibus on AI: the Council’s Final Green Light: https://www.nicfab.eu/en/posts/digital-omnibus-ai-council-adoption/

Clothing That Dresses You

A team from South Korea’s KAIST and Stanford University has built clothing that puts itself on. No hands. No helper. The garment uses soft, flexible “vines” driven by air pressure, sewn into the fabric itself. Pressurise them, and they glide the cloth up along the wearer’s body like ivy climbing a wall. The person does not even have to stand still.

Key Takeaways

• Air-pressure “vines” embedded in clothing pull the fabric onto the body by turning it inside out as they advance, taking roughly 10 seconds for a full suit.
• The system needs no complex control algorithm and works while the wearer moves, unlike external dressing robots that require the user to stay still.
• Beyond elderly and disabled users, the team targets semiconductor cleanrooms and emergency responders who need protective gear on fast and hands-free.

It Started With Rain and a Bicycle

The idea came from a wet commute. “When I was riding a bicycle, it started to rain … and I thought it would be helpful if a raincoat could be put on automatically (as I ride),” said KAIST postdoctoral researcher Kim Nam Gyun, lead author on the paper.

The mechanism sounds odd until you watch it work. “The vine robot stays close to the person and dresses them by turning the clothing inside out as it moves, allowing it to climb stably along the shape of the body,” Kim said. He put the full-suit time at about 10 seconds.

Growing, Not Crawling

Ryu Jee-Hwan, a professor of civil and environmental engineering at KAIST, explained the borrowed biology. Ivy does not shuffle its whole body forward. It extends at the tip. The robot does the same, which is why it handles curves without falling apart.

“It can pass through narrow gaps, grow while adapting to the shape of its surrounding environment, and move regardless of whether the surface is slippery, sticky, or sloped,” Ryu said.

That property matters more than it sounds. Conventional robot-assisted dressing leans on an external arm plus heavy control software, and it usually asks the person to freeze in place. This design folds the machinery into the garment, so the clothing does the work and the wearer keeps moving.

Where It Could Actually Get Used

Helping older adults and people with disabilities is the obvious first case. Assistive robotics has been circling that need for years, and technology.org has covered efforts ranging from a robot that catches people mid-fall without a harness to full lower-limb exoskeletons. A recurring complaint runs through all of it: people do not want to strap into things. Clothing that dresses itself sidesteps that objection entirely.

The industrial case may arrive first. Semiconductor cleanroom staff climb into protective suits constantly. So do firefighters and medical crews, often under time pressure, often with their hands already occupied. The research group sees room in both.

The work also belongs to a longer thread in soft wearable robotics, where labs use compliant materials rather than rigid frames to work alongside the human body. Ryu made a related point about where attention goes. AI has grown explosively, and the software gets the coverage. His team’s self-dressing robot, he said, shows that mechanical engineering still has to meet software halfway. The same lab has now taken the field’s top paper award two years running.

The study appeared in IEEE Robotics and Automation Letters, a peer-reviewed journal. The paper, titled “Self-Wearing Adaptive Garments via Soft Robotic Unfurling,” was selected as one of only five winners from more than 1,700 papers published in the journal during 2025, and was written with Professor Allison M. Okamura’s group at Stanford.

Written by Vytautas Valinskas