SCIENTIFIC DISSEMINATION · PHYSICS AND COSMOLOGY

Can we travel back in time?

What relativity, wormholes, and quantum physics really say about crossing time

🕒 Estimated reading time: 11-12 minutes     · ✍️ Writing for popular science

📅 Updated: September 2026

🧭  In summary Traveling into the future is already a measured and proven reality: it is enough to move very fast or get close to an intense gravitational field. Traveling into the past, on the other hand, is still mathematically possible in some solutions of general relativity, but it comes up against physical, energetic and logical barriers that no experiment has managed to overcome. This report follows both paths with the most recent evidence.

From H. G. Wells to Back to the Future, the idea of getting on a machine and scrolling through the calendar has fascinated entire generations. But far from being just a narrative device, time travel has been, for more than a century, an object of serious study within theoretical physics. The question that is the title of this article does not admit a simple yes or no: the answer depends on which direction of time one wants to travel, forward or backward, and what nature is willing to admit.

To understand this, it is necessary to abandon the idea of time as a river that flows equally for everyone. Albert Einstein demonstrated, first with special relativity (1905) and then with general relativity (1915), that time is one more dimension, intertwined with space in a single fabric called space-time. And that fabric can be stretched, curved and, according to some mathematical solutions, even knotted in on itself.

If the goal is to get ahead in time, the scientific answer is blunt: yes, it is possible, and it has already happened. The phenomenon is called time dilation and has two variants that relativity predicts with mathematical precision.

Speed: The faster you move, the slower your watch moves forward

Special relativity states that time passes slower for a moving object than for an observer at rest. The effect is minuscule at everyday speeds, but it becomes measurable in orbit. Astronauts on the International Space Station (ISS), traveling at about 28,000 km/h, age a fraction of a second slower than those who remain on Earth.

🛰️  Cosmonaut Gennady Padalka, with more than 878 days accumulated in space, is today the person who has "travelled" the most into the future due to this effect: a fraction of a second ahead of the rest of humanity.

👬  The case of twins Scott and Mark Kelly — one of whom spent 340 consecutive days on the ISS — allowed NASA to directly compare the biological and temporal effects of long-duration spaceflight.

Gravity: the stronger the gravitational field, the slower the clock

General relativity adds a second ingredient: clocks located in a stronger gravitational field—near a massive planet or black hole—move more slowly than those farther away. That's why GPS satellites must correct their atomic clocks several times a day: without that adjustment, the positioning system would accumulate errors of several kilometers in a matter of hours.

⚫  Date clave An object orbiting very close to a supermassive black hole, at the edge of its event horizon, could experience only a few years while the rest of the universe would elapse centuries or millennia. It is, in essence, the mechanism used by the movie Interstellar for its iconic giant tidal planet.

🖼️ Artist's concept of a spinning black hole, according to general relativity View image (direct link) ↗ Credit: Event Horizon Telescope (EHT) Collaboration — public domain/scientific use

The real challenge—and the one that fuels all science fiction—is the backward journey. Here, physics doesn't say "no" outright, but neither does it offer a practicable "yes." Einstein's equations admit, in theory, exotic solutions known as closed time curves (CTCs): trajectories in space-time that, always moving into the local future, end up returning to their own starting point.

Wormholes: shortcuts between two points in space-time

The best-known proposal is the Einstein-Rosen bridges, described mathematically in 1935 and renamed wormholes. In 1988, physicists Kip Thorne and Michael Morris refined the model and showed that if one of these tunnels could be kept open and traversed, and if its two ends were also moving relative to each other at different speeds or gravities, the mathematical result would be a real time machine.

The problem is not geometric, but physical: keeping a wormhole open would require exotic matter, a form of energy with negative density that has never been observed in useful quantities. As astrophysicist Eric Davis explained, although these tunnels could connect different moments in time, turning them into a functional travel machine would require a technological and energetic effort that today is far ahead of any human capacity. Kip Thorne himself has pointed out that the laws of physics will probably end up prohibiting a human being from physically crossing one of these structures.

At the beginning of 2025, a team from Conicet and the National University of La Plata (Argentina) published a theoretical model – in the journal The European Physical Journal C – that proposes a way to distinguish a rotating wormhole from a common black hole, based on the electromagnetic pattern it would generate. It would be the first method capable of providing indirect observational evidence on whether these objects really exist in the universe, although for the moment it remains a hypothesis pending data from telescopes.

🖼️ Conceptual illustration of a walkable wormhole, according to the Morris–Thorne model View image (direct link) ↗ Credit: public domain / informative representation

Warp motors: the other side of the same coin

In 1994, the Mexican physicist Miguel Alcubierre proposed another solution to Einstein's equations: a ship could, in theory, move faster than light without violating relativity if, instead of accelerating itself, it contracts the space in front of it and expands it behind, wrapped in a bubble of curvature. Alcubierre himself and other physicists have pointed out that this type of configuration, combined with certain geometries, could also give rise to closed time curves, that is, they would open an indirect door to the past.

The obstacle, again, is energetic: Alcubierre's metric requires the same exotic matter of negative energy as wormholes, in quantities that in the original calculations were equivalent to the mass-energy of an entire planet. Subsequent studies, such as those of the physicist Harold White, have explored geometric variations that would drastically reduce this requirement, although they remain, for now, mathematical exercises without experimental verification.

Even if the technology to open a closed time curve existed one day, a deeper problem would remain: causality. The most cited example is the grandfather paradox, formulated by the French writer René Barjavel in 1943: if someone travels to the past and prevents the meeting of his own grandparents, how could he be born to undertake that journey?

🔁  Novikov's principle of self-consistency: proposes that the universe only allows trips to the past that are logically consistent; any attempt to alter history would end, by the laws of physics themselves, generating the same result that has already occurred.

🌐  Interpretation of branching universes: suggests that a trip to the past does not modify "your" timeline, but creates a different parallel reality, thus avoiding logical contradiction.

🛡️  Chronological protection conjecture: the most cited position among physicists, proposed by Stephen Hawking in 1992.

Hawking argued that even if general relativity mathematically allows closed time curves, some additional physical mechanism—probably tied to quantum effects, such as vacuum polarization—would prevent them from forming on a macroscopic scale, thus preventing travel into the past and its paradoxes. His way of summarizing it became famous: he joked about the existence of a kind of "chronological protection agency" that keeps the universe safe from historians. As informal evidence in favor of his own conjecture, he pointed out that humanity has never been "overrun by hordes of tourists from the future."

🔬  And what does quantum physics say? Researchers from universities such as the Complutense University of Madrid and the CSIC have proposed and executed simulations of closed time curves in quantum and classical systems controlled in the laboratory. These experiments do not allow real-time travel, but they do allow us to study in miniature how information and causality would behave if these curves existed, providing indirect clues about the validity of Hawking's conjecture.

Mechanism	Theoretical basis	Current status
Temporal dilation (velocity)	Special Relativity (1905)	Tested and measured on the ISS and in particle accelerators
Temporal dilation (gravity)	General Relativity (1915)	Checked; corrects GPS system clocks daily
Walkable wormhole	Einstein-Rosen bridge / Morris-Thorne model	Mathematically valid; requires exotic matter never observed
Bending motor (Alcubierre)	Solution of the Alcubierre metric (1994)	Theoretical; it requires negative energy in quantities that are unattainable today
Closed time curves	Exotic Solutions of Einstein's Field Equations	Possibly blocked by Hawking's chronological protection conjecture

 

The honest and up-to-date answer is twofold. Into the future, yes: physics allows it, predicts it with accuracy and has already been verified in astronauts, satellites and experiments with high-precision atomic clocks. Into the past, the door remains ajar only on paper: equations do not prohibit it absolutely, but each proposed path – wormholes, warp engines, closed time curves – runs into the same wall, the need for exotic matter or energy that no one has ever detected, and with the suspicion, increasingly consolidated among theoretical physicists, that the universe itself has mechanisms to prevent paradoxes before they even form.

While science continues to polish these models—with new tools such as next-generation telescopes and quantum laboratory simulations—the truth is that we already live, in a literal sense, surrounded by time travelers: every GPS satellite and every astronaut who returns to Earth brings with it, on its internal clock, a few seconds stolen from the future.

Is there any evidence that you can travel to the past?

No experiment has ever detected a closed time curve or matter with enough negative energy to sustain it; for now it is a purely mathematical and theoretical field.

Do astronauts really travel in time?

Yes, in the strict sense of time dilation: they return to Earth a fraction of a second younger than they would have been if they had stayed on the ground, an effect measured with atomic clocks.

Why is "exotic matter" needed and what exactly is it?

It is a hypothetical type of matter with negative energy density, needed in wormhole and warp motor models to keep space-time stable. It has not been observed in nature in appreciable quantities.

What do physicists think today about the real possibility of traveling to the past?

The majority position remains aligned with Hawking's chronological protection conjecture: even if general relativity does not mathematically prohibit it, some additional physical principle—probably quantum—would prevent these structures from forming in practice.

This content was structured following current search engine optimization practices and optimization for response engines and artificial intelligence (Search Generative Experience / AI Overviews):

🔑  Main keyword: "time travel" — built into H1, first paragraph, subheadings, and meta description.

🧠  Semantic keywords (LSI): relativity, time dilation, wormhole, grandfather's paradox, exotic matter, closed time curve.

🏷️  Clear H1-H2-H3 header hierarchy, favoring the extraction of featured snippets.

🗂️  FAQ block optimized for rich snippets and FAQPage-like structured data (schema.org).

✅  E-E-A-T Signals (Experience, Specialization, Authority, Trust): References to recognized physicists, peer-reviewed studies, and linked primary sources.

🔗  External links to authoritative sources (Nature, arXiv, scientific media) and suggested internal linking to related blog articles (black holes, relativity, space exploration).

📝  Suggested meta description (150-160 characters): "Can you travel in time? Find out what real physics says about time dilation, wormholes, and paradoxes."

🌐  Recommended slug: /can-travel-in-the-science-time

🖼️  Descriptive alt text on each image for image accessibility and SEO.

⏱️  Visible reading time, which improves dwell time, an indirect sign of quality for search engines.

🎙️  Content written to answer informational and conversational search intent, also optimized for voice search.

🔗  Infobae — What are wormholes and why are they linked to time travel?

🔗  National Geographic — What is a wormhole

🔗  La República — South American Theoretical Model for Detecting Wormholes (Conicet / UNLP)

🔗  Wikipedia (EN) — Chronology protection conjecture (Stephen Hawking, 1992)

🔗  Physical Review D — Hawking, S. W., "Chronology protection conjecture" (1992)

🔗  arXiv — Martín-Vázquez & Sabín, "Closed timelike curves and chronology protection in quantum and classical simulators"

🔗  Sky at Night Magazine — How Time Dilation Affects ISS Astronauts

🔗  PMC/NCBI — NASA Twins Study: Effects of Long-Duration Spaceflight

🔗  Hibridosyelectricos.com — Advances and challenges of the Alcubierre curvature motor

🔗  Meer — The Grandfather Paradox, Origin and Physical Explanation

A popular science article for information purposes. The theories described—wormholes, curvature motors, and closed time curves—correspond to mathematical models valid within general relativity, but none have been experimentally verified as of the date of this publication.

🧬 🤖 SCIENCE AND TECHNOLOGY An AI that "talks cellular" This is IRIS, the model that deciphers the code of signals with which cells decide which tissue to become Fuente: National Geographic España  ·  Estudio original: Nature Methods (Whitehead Institute / MIT) ⏱️ Estimated reading time: 8 minutes     📅 September 2026

 

🔬 AI & HEALTH

An AI that "talks cellular": this is how it predicts which tissue each cell will become

A team at the MIT-affiliated Whitehead Institute has developed IRIS, an artificial intelligence model capable of decoding the chemical language with which cells communicate during embryonic development. By analyzing a cell's gene activity, the system can reconstruct what signals it received and predict exactly which specific tissue — heart, lung, gut, muscle, or spinal cord — it will eventually become, according to National Geographic. The finding, published in Nature Methods, opens the door to large-scale mapping of how a body is built, cell by cell.

🖼️ View image: Human embryonic stem cells — Wikimedia Commons  (Public domain/CC, Wikimedia Commons)

When an embryo begins to develop from a small group of stem cells, these cells, which are in principle identical and have no defined function, begin to specialize: some will become neurons, others liver cells, others muscle fibers. That decision depends not on an isolated internal plan, but on an ongoing conversation: the cells send and receive chemical signals to and from their neighbors, which tell them where they are in the embryo, what stage of development they are in, and what they should become.

These messages travel through multi-step sequences called signaling pathways, authentic biochemical circuits that translate an external stimulus into very specific changes in genetic activity within the cell. Reconstructing this sequence of instructions – what signals a cell was exposed to and at what time – would allow us to understand in depth how tissues are formed and why, when this process fails, diseases appear.

The problem is that, until now, this reconstruction seemed almost impossible to scale. Science assumed that the effects of each signaling pathway varied greatly from one cell type to another, which forced each pathway to be mapped separately in each cell type: a very slow experimental work and, in practice, unmanageable for the whole of an organism.

The team led by Pulin Li, a researcher at the Whitehead Institute for Biomedical Research and professor of biology at MIT, along with graduate student Nicholas Hutchins, discovered something that changes the picture: each signaling pathway leaves a characteristic fingerprint, a distinctive pattern of genetic activity that reflects the specific signals that the cell received.

The decisive thing is that this fingerprint remains consistent between different cell types for the same signaling pathway. In other words, instead of mapping pathway by pathway and cell type by cell type, scientists can reconstruct the signaling history of many different cells from those shared fingerprints.

"Think of speech recognition systems like Siri, which are trained primarily in English, but then use that training to recognize other languages. This is called transfer learning, and it's why IRIS can work on many different cell types." " — Pulin Li, Whitehead Institute / MIT

IRIS is a neural network-based model: an artificial intelligence system designed to recognize patterns in complex data, similar to how the human brain detects regularities. The program examines a cell's overall gene activity and, from it, estimates which signaling pathways were active—"turned on"—at different points in development.

To train it, Li and Hutchins used an extensive experimental dataset that recorded how thousands of human embryonic stem cells responded to dozens of combinations of six major signaling pathways, at multiple stages of development. The result was a detailed atlas of how signal combinations shape cell behavior.

Then came the litmus test: The researchers applied IRIS to individual cells from mouse embryos during gastrulation, the stage when cells rapidly branch out to very different destinations. The model predicted precisely when and where certain signaling pathways would be activated in cells destined to be part of the heart, gut, muscle, and spinal cord.

Target Tissue	Stage evaluated	IRIS Result
Heart	Gastrulation (mouse embryo)	Accurate prediction of the time and place of signal activation
Intestine	Gastrulation (mouse embryo)	Accurate prediction of the time and place of signal activation
Muscle	Gastrulation (mouse embryo)	Accurate prediction of the time and place of signal activation
Spinal cord	Gastrulation (mouse embryo)	Accurate prediction of the time and place of signal activation
Lung tissue	Signaling pathway design to induce destiny	Experimentally Confirmed in Mouse Embryos

🖼️ View image: Embryonic gastrulation scheme — Wikimedia Commons  (Pidalka44, Wikimedia Commons)

The most telling experiment came when the team used IRIS to identify which signals would be needed to generate a key cell type in lung development. The model predicted that activating a specific signaling pathway would favor development into lung tissue. The researchers tested that prediction in mouse embryos, and the experimental results confirmed it.

By accurately identifying the signal combinations that drive lung cell development, the team can more reliably generate laboratory models—organoids, miniature three-dimensional structures that mimic real organs—that faithfully reproduce human lung tissue.

"In these ways, IRIS is helping us decode the language that cells use to talk to each other, at a much faster speed than we could actually achieve through experiments. " — Nicholas Hutchins, Whitehead Institute

The finding, published in the journal Nature Methods, has very concrete implications beyond the developmental biology lab. Once scientists identify the pattern of signals that pushes a stem cell to become a specific cell type, they can artificially recreate those signals to direct the fate of stem cells in laboratory or clinical contexts.

Among the applications that the team highlights are:

•     Engineering stem cells for regenerative medicine, guiding their differentiation towards the desired cell type with greater efficiency.

•     More precise organoids, that is, three-dimensional models of organs used to study diseases and test drugs before reaching clinical trials.

•     Models of lung diseases such as asthma, lung cancer, and pulmonary fibrosis, in which tissue scars often with no known cause.

•     Design of regenerative treatments capable, in the future, of repairing damaged lung tissue.

The team notes that these improved models would allow not only a better understanding of why these diseases develop, but also use them as a testing platform for new therapies, with the ultimate goal of designing real regenerative treatments.

IRIS joins a recent wave of artificial intelligence models that attempt, each from a different angle, to "read" cell behavior. In early 2026, researchers at Columbia University presented a method capable of accurately predicting gene activity within any human cell from gene expression data from millions of cells in normal tissues, also published in Nature.

Months later, an international consortium made up of the Stowers Institute for Medical Research, Helmholtz Munich, the Technical University of Munich and the University of Oxford presented RegVelo, an AI framework that simultaneously models cell dynamics and gene regulation to predict how cells make decisions about their fate, experimentally validated in zebrafish.

At the same time, other research teams have been developing models such as Sig2Fate, aimed at decoding cell fate from a snapshot of combinatorial signaling in human gastruloids. The common denominator of all this work is the same ambition: to turn traditionally descriptive developmental biology into a science capable of predicting in advance how a cell will behave in the face of a given stimulus.

Specialists in the intersection between artificial intelligence and biology, such as Microsoft researcher Ava Amini, have warned, however, that the path is not without obstacles: several existing models of cellular AI tend to predict only average values rather than actual biological differences, and their performance does not always improve with increasing volume of training data. IRIS, by relying on shared signaling fingerprints between cell types rather than exhaustive mapping, proposes a different way to get around this limitation.

❓ What exactly is IRIS?

It is an artificial intelligence model based on neural networks, developed at the Whitehead Institute (affiliated with MIT), which analyzes the gene activity of a cell to estimate which signaling pathways it received and at what point in development.

❓ How does IRIS predict which tissue a cell will become into?

The model detects "fingerprints" of genetic activity specific to each signaling pathway, which remain stable between different cell types. From these fingerprints, it reconstructs the history of signals that the cell received and, with this, predicts its tissue fate: heart, intestine, muscle, spinal cord or lung, among others.

❓ Where and when was the study published?

The results were published in the journal Nature Methods on September 8, 2026, in a study led by Pulin Li and Nicholas Hutchins, from the Whitehead Institute for Biomedical Research.

❓ What is the use of this advance in practice?

It allows for more precise design of protocols to guide stem cells to a desired cell type in the laboratory, improve the manufacture of organoids to study diseases such as asthma, lung cancer or pulmonary fibrosis, and lay the foundations for future regenerative treatments.

❓ Is it the first AI to try to decipher cellular fate?

No. It joins other recent developments, such as a Columbia University model for predicting cell gene activity and RegVelo, a framework developed by institutions such as the Stowers Institute, Helmholtz Munich, and the University of Oxford. What's new about IRIS is its ability to generalize between cell types through transfer learning.

The Whitehead Institute team says this approach opens up the possibility of comprehensively mapping the signaling histories of every cell within a mouse or human embryo on a scale that was previously unattainable. If that mapping comes to fruition, the promise is twofold: to understand in unprecedented detail how a handful of undifferentiated cells build an entire body, and to learn how to guide that process from the lab to repair what the disease breaks.

 

  📊 SEO DATA SHEET

🏷️ Core metadata

Title tag: An AI that "talks cellular": this is how it predicts which tissue each cell will become | midire.ar

Meta description: IRIS, the AI of the Whitehead Institute (MIT), decodes the language of signals between cells and predicts exactly which tissue they will become: heart, lung, intestine or muscle. Study in Nature Methods.

Suggested slug: /ia-decodes-cellular-language-predicts-iris-tissues

Suggested canonical URL: https://midire.ar/ia-decodifica-lenguaje-celular-predice-tejidos-iris

Main keyword: AI that decodes the language of cells

Secondary keywords: IRIS artificial intelligence cells, prediction tissues AI, Whitehead Institute, cell signaling, Nature Methods, lung organoids, regenerative medicine AI

Category: Science & Technology >; Artificial Intelligence & Health

Tags: AI, biology, stem cells, regenerative medicine, MIT, National Geographic

🧾 Structured Data (JSON-LD)

NewsArticle:

{"@context":"https://schema.org","@type":"NewsArticle","headline":"An AI that "talks cell": this is how it predicts which tissue each cell will become","datePublished":"2026-09-08","dateModified":"2026-09-08","author":{"@type":"Organization","name":"midire.ar"},"publisher":{"@type":"Organization","name":"midire.ar"},"about":["Artificial intelligence","Developmental biology","Regenerative medicine"],"citation":"Nature Methods, September 8, 2026"}

FAQPage: Generated from the five FAQs included in the corresponding section of the article, with their associated answer in acceptedAnswer/text format.

🔗 Open Graph / Twitter Card

og:title: An AI that "talks cellular" and predicts what tissue it will become

og:description: IRIS decodes the signal code between cells and anticipates their tissue fate. Study by the Whitehead Institute (MIT) in Nature Methods.

and:type: article

twitter:card: summary_large_image

✅ E-E-A-T Signs

•Primary source cited: statement from the Whitehead Institute for Biomedical Research (EurekAlert!, 8/9/2026) and journal Nature Methods.

•Journalistic source cited: National Geographic Spain.

•Textual statements attributed to the authors of the study (Pulin Li and Nicholas Hutchins).

•Contextualization with comparable studies (Columbia University, RegVelo, Sig2Fate) to show the state of the field.

•No prescriptive medical claims: basic research and its potential applications are described, without clinical recommendations.

⚡ Core Web Vitals — goals

Metrics	Objective	Recommendation
LCP (Largest Contentful Paint)	< 2.5 s	External images lazy loaded without blocking the render
INP (Interaction to Next Paint)	< 200 ms	Minimize third-party JS on the article page
CLS (Cumulative Layout Shift)	< 0.1	Reserve fixed dimensions for images and tables before uploading

♿ Accessibility Notes (WCAG 2.1 AA)

•Minimum contrast 4.5:1 between text and background image in responsive blog design.

•Descriptive alt text for any image embedded in the web version (e.g., "Illustration of a human embryonic stem cell and derived neurons").

•Respected H1-H2-H3 header hierarchy, no level jumps.

•Links with descriptive text (avoid "click here"); already applied in hyperlinks to sources and images.

🧭 Advanced SEO techniques applied

•Optimization for featured snippets using FAQ block with 40-60 word auto-contained answers.

•Main entity (IRIS / Whitehead Institute) semantically reinforced in title, first paragraph, subheadings and image.

•External authority linking (National Geographic, primary source of the study) for trusted signals.

•"Pillar topic + comparative context" content structure (other AI models section) to capture long-tail related searches.

•Use of tabulated data (table of results by tissue) to favor the appearance of rich results of table type.

 

In the halls of IFA Berlin 2026, the most important consumer electronics fair in Europe, one of the most repeated findings of the specialized media had nothing to do with a brighter screen or a faster processor, but with something that is not seen: the system that keeps the computer cool from the inside. Several manufacturers, with Lenovo at the forefront, exhibited notebooks that completely dispense with traditional mechanical fans and instead use solid-state chips that expel air through membranes that vibrate at ultrasonic frequencies.

The technology is not a laboratory promise: it is called AirJet, it has been developed by the American firm Frore Systems since 2019 and has already been perfected for several generations. What changed in 2026 is that it stopped being a fair demonstration to begin to be integrated into real notebook concepts, with their own names and a date of approach to the market.

Lenovo brought two prototypes to Berlin that illustrate where this technology is headed. The most talked-about one, presented under the name "Project AeroBlade" (also referred to in the fair's coverage as ThinkBook Aero), is a notebook weighing less than 830 grams and less than 10 millimeters thick that has absolutely no ventilation grille or conventional fan.

Inside, Lenovo installed four AirJet Mini modules from Frore Systems, each just 2.65 millimeters thick, which are responsible for extracting the heat generated by the processor. As explained by the company itself, this solid-state active cooling architecture – commercially called "Active Flow" – allows the performance of artificial intelligence workloads to be sustained, reduces noise to almost imperceptible levels and eliminates the entry of dust that traditionally enters through the grilles of conventional equipment.

•     Less space, less weight: By not needing the volume of a centrifugal fan or its intake grilles, Lenovo was able to reduce the size of the motherboard and, consequently, the entire chassis of the computer.

•     Direct collaboration with Frore Systems: Lenovo did not buy a generic component, but developed the thermal design together with the company that invented the technology, something that anticipates a deeper integration in the future.

"Lenovo put this laptop on a diet: it has absolutely no vent or traditional fan." — Specialized coverage of the Lenovo ThinkBook Aero at IFA 2026

Despite the name "ultrasound," the technology has nothing to do with cleaning jewelry or ultrasound: it relies on the piezoelectric effect, the same physical principle that allows a quartz crystal to modulate the frequency in a watch or an inkjet printhead to shoot microscopic droplets with complete precision.

Inside each AirJet chip is a set of microelectromechanical structures (MEMS) that include ultra-thin membranes. When an electric current is applied to them, these membranes vibrate at ultrasonic frequencies — above the range audible to the human ear — with displacements of just tens of microns. This repetitive motion turns each membrane into a kind of miniature suction and ejection pump.

•     Cold air suction: The vibration generates a strong depression that draws ambient air through inlet holes located on the top of the chip.

•     High-speed pulsating jets: this air is then expelled in the form of microjets that reach speeds close to 200 kilometers per hour, directly impacting a copper heatsink in contact with the processor.

•     Ten-fold higher return pressure: According to data from Frore Systems, an AirJet module can generate up to 1,750 pascals of back pressure, about ten times more than a conventional mechanical fan, allowing it to force air through even through heatsinks with fins close together, something that a traditional fan does not achieve efficiently.

•     Hot air outwards: finally, this air, already charged with heat, is expelled from the computer through a small exhaust duct, without the need for the large grilles that are usually seen on the sides of a conventional notebook.

With no moving parts such as a rotor or blades, Frore Systems describes AirJet as a "solid-state" cooling system: there are no bearings to wear out, there is no mechanical vibration and, because it does not require large openings for air intake, the assembly can be sealed with filters that directly block dust ingress, something that in traditional fan equipment is one of the main causes of thermal degradation over time.

Feature	Traditional fan	Chip AirJet (Frore Systems)
Moving parts	Rotor and blades	None (solid state)
Typical thickness	8-12 mm or more	2.65 mm per module
High Load Noise	Up to 40+ dBA	21-24 dBA per module
Dust resistance	Low (open grids)	Alta (sellable, IP53-IP68)
Generated back pressure	Reference (1x)	Up to 10 times larger
Scalability	One fan per zone	Multiple Combinable Chips

Frore Systems is, so far, the company with the largest commercial deployment in this category – its technology has already been seen before in Zotac mini PCs, in high-performance SSD storage accessories and in Qualcomm reference platforms – but it is not alone. Different firms are exploring variants of the same concept of "air without moving parts": some, such as xMEMS, are betting on piezoelectric membranes built directly on silicon; others are moving forward with ionic wind technologies based on electrical discharges (known as EHD or DBD plasma), which move air without any mechanical vibration.

That expanding ecosystem suggests that 2026 could be remembered as the year solid-state cooling ceased to be a fairground curiosity and began to become a real alternative for a portion of the market for ultra-thin notebooks and edge AI devices, which need to sustain constant processing loads without being able to resort to a thick chassis or a noisy fan.

The interest in these solutions is not accidental: it coincides with the rise of Copilot+ PCs and notebooks aimed at artificial intelligence, which integrate processors capable of running models locally and that, therefore, generate sustained heat peaks very different from those of a traditional office notebook. When a processor overheats, the chip itself automatically reduces its speed to protect itself – the phenomenon known as thermal throttling – which ends up directly hitting the performance that the user perceives.

For manufacturers, moreover, the promise of a fanless system opens the door to thinner and lighter designs without sacrificing power, something that until now used to be solved by limiting the performance of the processor in ultra-thin computers. It is, in short, the same tension that ultra-thin notebooks with passive cooling face today: to remain silent and compact, but without that meaning giving up performance under sustained load.

•     Cooling scale: Each AirJet Mini module removes a few watts of heat, so high-performance teams need to combine multiple chips in parallel, impacting the total cost of the system.

•     Manufacturing cost: As these are components made with lithography processes similar to those of a silicon chip, their cost per unit is still higher than that of a conventional mass-produced mechanical ventilator.

•     Actual adoption in final products:  much of what was shown at IFA 2026, such as Lenovo, still corresponds to prototypes or "concepts", not to models that are already on sale in stores.

Indicator	Fact
AirJet Public Launch Year	2023 (CES)
Thickness of an AirJet Mini module	2.65-2.8 mm
Weight of an AirJet Mini module	~11 grams
Generated back pressure	Up to 1,750 pascals
Speed of micro air jets	~200 km/h
Noise level of a module	21-24 dBA
Weight of the Lenovo Project AeroBlade prototype	< 830 grams
Grosor del prototipo Lenovo Project AeroBlade	< 10 mm

❓ What exactly is ultrasonic cooling in notebooks?

It's a solid-state cooling system, like Frore Systems' AirJet, that uses microelectromechanical membranes that vibrate at ultrasonic frequencies to generate jets of air, replacing the traditional mechanical fan.

❓ Does the notebook with this system make any noise?

Yes, but much lower than a conventional fan: AirJet modules operate between 21 and 24 decibels, compared to the more than 40 decibels that a traditional fan can reach under high load.

❓ Which brands showcased this technology at IFA 2026?

Lenovo was the most prominent, with the Project AeroBlade (fanless, using AirJet) and Project Swan concept prototypes, although Frore Systems' technology had already been integrated into other devices since 2023.

❓ Can you buy a notebook with ultrasonic cooling now?

The models shown at IFA 2026 are mostly concept prototypes; AirJet technology is commercially available in some mini PCs, storage accessories and reference platforms from 2023.

The following images, available on Wikimedia Commons under free licenses, illustrate the context of the fair and the traditional refrigeration system that this technology seeks to replace:

 

 

🏷️ Core metadata

•Title tag: Ultrasound-cooled notebooks: AirJet technology seen at IFA 2026 | midire.ar

•Meta description: How Frore Systems' AirJet chip works, the solid-state cooling that replaces the fans in the notebooks shown at IFA Berlin 2026.

•Suggested slug: /notebooks-cooled-with-ultrasound-airjet-ifa-2026

•Main keyword: ultrasound-cooled notebooks

•Secondary keywords: AirJet Frore Systems, solid-state cooling, IFA 2026 notebooks, Lenovo Project AeroBlade, fanless notebooks

•Tag H1: Ultrasound-cooled notebooks: AirJet technology seen at IFA 2026

•Search intent: informative (technological novelty + technical explanation)

🧩 JSON-LD — TechArticle

{ "@context": "https://schema.org", "@type": "TechArticle", "headline": "Notebooks enfriadas con ultrasonido: la tecnología AirJet vista en IFA 2026", "datePublished": "2026-09-05", "dateModified": "2026-09-05", "author": { "@type": "Organization", "name": "midire.ar" }, "publisher": { "@type": "Organization", "name": "midire.ar" }, "mainEntityOfPage": "https://www.midire.ar/notebooks-enfriadas-con-ultrasonido-airjet-ifa-2026", "articleSection": "Tecnología", "keywords": "AirJet, Frore Systems, IFA 2026, refrigeración de estado sólido, Lenovo" }

🧩 JSON-LD — FAQPage

{ "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [ { "@type": "Question", "name": "What is ultrasonic cooling in notebooks?", "acceptedAnswer": { "@type": "Answer", "text": "A solid-state system, such as Frore Systems' AirJet, that uses MEMS membranes vibrating at ultrasonic frequencies to move air without mechanical fans." } }, { "@type": "Question", "name": "What brand showed this technology at IFA 2026?", "acceptedAnswer": { "@type": "Answer", "text": "Lenovo, with the Project AeroBlade concept prototype, integrating AirJet chips from Frore Systems." } } ] }

📱 Open Graph / Twitter Card

•og:title: Ultrasound-cooled notebooks: how AirJet works

•og:description: Membranes that vibrate at ultrasonic frequencies replace traditional fans. All about the technology seen at IFA Berlin 2026.

•and:type: article

•twitter:card: summary_large_image

✅ E-E-A-T Signs

•Experience: synthesis of specialized fair coverage (technology media that attended IFA 2026) contrasted with technical specifications published by the manufacturer of the component.

•Authority: technical data quoted directly from Frore Systems' public documentation (pressure, thickness, noise) and Lenovo press releases.

•Reliability: An explicit distinction between what is already a commercial product (AirJet chips in SSDs and mini PCs) and what is still a concept prototype (Lenovo notebooks).

⚡ Core Web Vitals — goals

Metrics	Objective
LCP (Largest Contentful Paint)	< 2.5 s
INP (Interaction to Next Paint)	< 200 ms
CLS (Cumulative Layout Shift)	< 0.1

♿ Accessibility Notes (WCAG 2.1 AA)

•Minimum contrast 4.5:1 between text and background in all color blocks.

•Descriptive alt text for linked images and reference diagrams.

•Semantic header hierarchy (H1 > H2 > H3) without level breaks, including the comparison table.

•Links with descriptive text (avoid "click here").

🚀 Additional SEO techniques applied

•Topical authority: The article covers the news event (IFA 2026), the technical background (how AirJet works), and the competitive landscape (xMEMS, EHD), maximizing the semantic coverage of the topic for generative AI-based search engines (GEO/AI Overviews).

•Entities and disambiguation: explicit and repeated mention of named entities (Frore Systems, AirJet, Lenovo, IFA Berlin) to strengthen the partnership in knowledge graphs.

•"answer-first" content: the FAQ section answers in the first sentence, favoring extraction as a featured snippet and as a direct answer in conversational search engines.

Tango re-entered the Pacific and turned its destruction into a scientific laboratory

September 2, 2026 · Space Science · Space Security · Space Debris

 

🌎 The end of a historic mission did not simply end with a satellite falling to Earth. On September 1, 2026, Tango – the fourth and last member of the Cluster II constellation – deliberately re-entered over a remote region of the South Pacific. The European Space Agency (ESA) also managed to observe the phenomenon from an aircraft equipped with a battery of scientific instruments. The goal: to transform the destruction of a spacecraft into useful data to design safer and more sustainable missions.

The manoeuvre closed a chapter of 26 years of Cluster activity and consolidated a strategy that ESA considers key to orbital sustainability: planning for the end of life of satellites with as much precision as their launch and operation. The campaign also made it possible to study in real conditions how a spacecraft heats up, fragments and disappears as it passes through the atmosphere. cite no — source integrated below

🔥 Tango: a planned farewell to the second

Tango (Cluster II FM-8) re-entered the Earth's atmosphere on 1 September 2026 at 21:30:31 UTC, equivalent to 23:30:31 CEST. It was the last of the four Cluster satellites to complete its re-entry. The accuracy achieved allowed the observation aircraft to take off from Tonga and reach the planned area of the South Pacific to record the event.

The operation was not an accidental crash. ESA had prepared a "directed re-entry" trajectory to take the satellite to a remote and sparsely populated ocean area. The aim was to reduce the risk on land while creating the conditions for exceptional scientific observation.

The ROSIE campaign managed to observe both Samba and Tango using 29 of the 30 instruments installed on board the aircraft. Scientists were able to follow each re-entry for about 50 seconds on average. In the case of Tango, even the pilot's maneuver contributed to keeping the satellite in the field of view for a few additional seconds.

🛰️ Cluster: 26 years looking at Earth's magnetic heart

Cluster was born to answer a fundamental question: how do the solar wind and the Earth's magnetosphere interact? The constellation was made up of four identical spacecraft—Rumba, Salsa, Samba, and Tango—that flew in formation to obtain three-dimensional measurements of the magnetic and plasma regions near our planet.

The four vehicles were launched in two pairs, on July 16 and August 9, 2000. Although its nominal operational life was only two years, the mission was repeatedly extended and ended up becoming one of the great veteran missions of European space science.

Each spacecraft carried 11 instruments dedicated to studying charged particles, electric fields, magnetic fields and waves. The combination of four identical platforms made it possible to simultaneously observe different points in space and reconstruct processes that a single spacecraft could not measure with the same precision.

🌞 Why was it important to study the magnetosphere?

The magnetosphere functions as a shield against the flow of particles and magnetic fields from the Sun. When the solar wind interacts with it, space weather phenomena can occur capable of affecting communications, navigation, satellites and power grids.

Cluster provided a three-dimensional perspective of processes occurring at very different scales, from small structures in the plasma to large regions of interaction between the solar wind and the Earth's magnetic environment. Its scientific legacy does not end with re-entry: the data accumulated during the mission will continue to be analyzed.

✈️ ROSIE: Turning a Destructive Re-Entry into an Experiment

The most novel part of the final chapter of Cluster was aerial observation. ROSIE—the re-entry observation campaign—brought a suite of cameras and sensors to a carefully calculated position to look at the phenomenon from below the trajectory.

A tracking camera makes it possible to determine where the object is located and how its fragmentation is evolving. Complementary cameras and sensors also look for information about the materials that appear during decay. This allows researchers to compare what actually happens with the predictions of re-entry models.

The experience with Salsa, which re-entered in September 2024, was decisive. That campaign revealed, among other things, differences of up to 20% between the predicted and observed atmospheric density, and suggested that fragmentation could begin somewhat earlier than indicated by certain models.

🌡️ What happens when a satellite enters the atmosphere?

A hypersonic re-entry subjects the vehicle to enormous aerodynamic and thermal loads. The air is violently compressed in front of the ship, the temperature rises, and the materials begin to heat, deform, melt, and vaporize. The structure loses integrity and the vehicle progressively fragments.

But the process is not as simple as "the satellite burns up." Some components can survive longer because they are protected by other parts of the structure. Dense materials or internal components can withstand even later stages of descent. That is precisely why real observations are so valuable in refining simulations.

The data from Tango and Samba complement the experiences of Salsa and Rumba and allow us to study re-entries from four similar satellites under different conditions. Controlled repetition reduces one of the great difficulties of this science: the scarcity of direct observations of the actual destruction of a spacecraft.

🌊 Why the South Pacific?

The choice of a remote area of the ocean responds to a basic safety principle: to minimise the risk to people, buildings and infrastructure. ESA adjusted the trajectories of Samba and Tango so that their re-entries would occur in a region that was sparsely populated and, at the same time, sufficiently accessible for a scientific aircraft operating from Tonga.

Orbital accuracy was especially important because the aircraft had to be in the right place, at the right time, and with the right orientation to observe a phenomenon that lasts only a few moments. The campaign combined orbital data, ground tracking, and telescopes to refine the predictions.

♻️ From "space junk" to sustainable design

Tango's re-entry has a reading that goes far beyond Cluster. Earth orbit is becoming increasingly congested and each mission must consider what will happen when its useful life ends.

ESA is promoting its "Zero Debris" approach, aimed at drastically reducing the generation of new debris in orbit and improving disposal strategies at the end of missions. Within this philosophy is the concept of "Design for Demise": designing satellites so that, during a re-entry, they disintegrate more completely and reduce the risk of components surviving to the surface.

There is also "Design for Removal", which seeks to ensure that future spacecraft incorporate interfaces and technologies that allow them to be actively removed if they cannot complete their disposal on their own. The logic is simple: the end of a mission should be part of the design from the beginning, not an improvised decision when fuel or systems are about to run out.

📊 The four finals of Cluster

🔬 What data can change the future

The main utility of the campaign is not the spectacularity of the images, but the possibility of contrasting models with a real sequence of events. Knowing when intense heating begins, which components are separated first, which materials survive and how the fragments are distributed allows us to improve re-entry predictions.

That knowledge can help design satellites that are more completely destroyed as they pass through the atmosphere and more accurately calculate residual risk on the surface. It can also improve the planning tools used by operators and authorities to determine when and where a mission will end.

🔭 The next step: Draco

The Cluster experience will not be the end point of the investigation. ESA is preparing Draco, a re-entry mission planned for 2027 that will seek to record the phenomenon from inside the vehicle itself. According to ESA, Draco will have more than 200 sensors, four cameras and a capsule designed to preserve data during destruction.

The aim will be to complement external observations made from aircraft with an internal perspective: to measure exactly what happens to the structure and its components as the vehicle goes through the different stages of re-entry.

🧭 An ending that is also a warning

Tango's "last dance" sums up a transformation in the way we think about space missions. For decades, success was measured primarily by launch, scientific operation, and the amount of data obtained. Today there is a fourth inseparable dimension: how the mission ends.

Cluster showed that even the end of a veteran satellite can become science. Its four targeted re-entries show that safely retiring a spacecraft doesn't have to mean simply losing it: it can mean generating knowledge that reduces the risks of future generations of satellites.

Tango disappeared into the atmosphere, but its last journey left something that doesn't burn: data. And that data can help keep near-Earth space usable, safe, and sustainable.

📷 Official Images and Resources for the Article

The following official ESA pages contain the recommended images and audio-visual materials. They are included as absolute links for web publication and attribution:

Tango’s reentry recorded — ESA/ROSIE/University of Stuttgart (HEFDiG) · https://www.esa.int/ESA_Multimedia/Images/2026/09/Tango_s_reentry_recorded

Samba’s reentry recorded — ESA/ROSIE/University of Stuttgart (HEFDiG) · https://www.esa.int/ESA_Multimedia/Images/2026/09/Samba_s_reentry_recorded

Cluster II reentry ground tracks: Samba and Tango — ESA · https://www.esa.int/ESA_Multimedia/Images/2026/08/Cluster_II_reentry_ground_tracks_Samba_and_Tango

ROSIE: Cluster’s Samba and Tango Re-entry Observation Campaign — ESA Television · https://www.esa.int/esatv/Videos/2026/08/ROSIE_Cluster_s_Samba_and_Tango_Re-entry_Observation_Campaign

🔗 Sources and references

ESA — Cluster’s encore for reentry science a success (2 sep. 2026)

ESA — Samba’s fiery farewell recorded (1 sep. 2026)

ESA — Observing Samba and Tango’s reentries (28 ago. 2026)

ESA — Cluster overview

ESA — Cluster spacecraft

ESA — Zero Debris approach

ESA — Zero Debris technologies

 

© 2026 · Article prepared for editorial blog publication · Research based mainly on official ESA sources