The 2026 Nobel prize in chemistry has been awarded to Henri Kagan and Kenso Soai for their discovery of how to make molecules form the correct kind of mirror image. This has enabled the molecules to be mass produced with chemical properties that are useful in various applications, such as medicines and agriculture.

Some molecules exist in two forms that are mirror images of each other, which chemists call right- and left-handed. “Like my hands, they are one another’s mirror image, they look alike but they are not identical,” , chair of the Nobel committee for chemistry, said at a press conference. “Such molecules are called chiral from the Greek word for hand.”

For decades, whenever chemists carried out chemical reactions, they produced two forms of mirrored molecules in equal proportions. But they only wanted to make one of the mirror images when producing molecules that would interact with life, like medicines, because only one would have the desired effect.

“Many active drugs in pharmaceutical applications are chiral: one hand may have the desired therapeutic effect, while the other hand might have no effect, or in the worst case might even be harmful,” said Linke.

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In 1986, at Paris-Saclay University, France, discovered a way to tilt chemical reactions towards generating more of one mirror molecule over the other.

Taking this further, in 1995, at the Tokyo University of Science, Japan, started designing chemical reactions to produce only one mirror image. In 2003, he achieved this. His “Soai reaction” gets one form of mirror molecule to amplify itself, in a process known as autocatalysis, so it makes up most of the reaction products.

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The 2026 Nobel prize in physics has been won by Francis Halzen for his work on neutrinos, which serve as ‘ghost-like messengers from the cosmos’

This has enabled the mass production of drugs, from painkillers to antidepressants and drugs that treat Parkinson’s disease. It has also helped to produce pesticides that improve crop yields.

“This is one of the most exciting days in my life,” said Soai, who phoned in to the press conference.

at the University of Wisconsin–Madison has won the 2026 Nobel prize in physics for his work on spotting ghostly particles called neutrinos using a detector at the South Pole.

Neutrinos are subatomic particles that rarely interact with material, are electrically neutral and perfuse the whole universe. Because of this, we can detect neutrinos that originated far away in the cosmos, trace their origin and learn more about the nature of the universe. Cosmic neutrinos are produced when a proton collides with another particle.

If you hold your hand out flat, more than a billion neutrinos will pass through it every second. These originate from the sun, but Halzen’s work concerns the much more rare and high-energy neutrinos coming from deep within the cosmos and what their detection can tell us about the universe.

Neutrinos act like “ghost-like messengers from the cosmos”, said , chair of the Nobel committee for physics, at a press conference. “It’s a way of bringing us information about distant cosmic sources which we’re unable to acquire in other ways.”

In 1988, Halzen proposed using the Antarctic ice as a neutrino detector, then went on to spearhead an international collaboration of more than 450 people from 58 institutions in 14 countries to make the IceCube Neutrino Observatory a reality.

The detector uses thousands of light sensors buried 2 kilometres under the surface of the ice in deep holes drilled using hot water. As neutrinos shoot through Earth, they interact with the ice, creating what’s known as Cherenkov radiation and emitting blue light. The network of light sensors allows researchers to trace their trajectory back to their origin point, revealing vital information about their formation.

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Halzen calculated that, if you built a neutrino collector 1 cubic kilometre in size, you would detect one neutrino per day. IceCube was completed in 2010 and began full operations the following year. The first high-energy extraterrestrial neutrinos were detected in 2013.

“When I reflect on this moment, I have to emphasise how lucky I was,” said Halzen, addressing the press conference by phone. “Because when we started this project, everybody realised this was maybe a good idea, but very few thought it would work – including myself. So this was kind of an adventure where success was not guaranteed, and we were lucky to overcome the various challenges. It was a long journey, but finally it worked.”

Halzen said he hopes the prize will reflect on the collaborators who worked on the project in the early days.

The IceCube detector has gone on to make many more discoveries. In 2017, it helped identify the first definitive source for a single high-energy cosmic neutrino: a blazar called TXS 0506+056 that blasted a huge jet of energy towards Earth. In 2023, it identified neutrinos from within our own galaxy, the Milky Way, which are typically overwhelmed by stronger signals from the rest of the universe.

Of winning the award, Halzen said: “It was a great surprise and I didn’t expect it. It’s a great pleasure.”

The 2026 Nobel prize in physiology or medicine has been awarded to Karl Deisseroth, Peter Hegemann and Georg Nagel for the development of techniques for controlling nerve cells with light, known as optogenetics.

“It’s a tremendous step forward to be able to link nerve cells and their function to specific behaviours,” said , a member of the Nobel committee. “It’s a completely new dimension of understanding of the function of the brain.”

In the 1990s, , then at the Max Planck Institute for Biochemistry in Germany, wondered how a single-celled alga, called Chlamydomonas, can swim towards light. He discovered the key to this is a light-sensitive protein.

In the 2000s, Hegemann teamed up with , then at the Max Planck Institute for Biophysics in Frankfurt, Germany. They showed that this light-sensitive protein acts as a switch, opening a channel that lets ions flow through the protein when exposed to light. They called the protein channel-rhodopsin.

“They had just discovered the switch neuroscientists had long dreamed of,” , a neuroscientist and member of the Nobel Committee, said during the prize announcement.

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The discovery of channel-rhodopsin was a major breakthrough in itself, said El Manira, but , at Stanford University, California, took things even further by showing that this protein could be used to control nerve cells.

Deisseroth genetically engineered rats to produce channel-rhodopsin in their nerve cells, meaning these cells could be activated by shining light on them. This work, published in 2005, enabled researchers to study the function of specific groups of neurons.    

“For the first time, causal links between specific brain circuits and behaviour had been achieved,” said El Manira. “The technology transformed neuroscience. Optogenetics was rapidly and widely adopted all over the world.”

More light-sensitive proteins have since been discovered, which respond to different colours, enabling even more precise control of engineered nerve cells.

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Therapies based on optogenetics are also being developed. For instance, it is being explored as a way to restore some sight to people who are blind because they have lost the light-detecting rod and cone cells in the retina. Optogenetic techniques can be used to make nerve cells in the retina respond directly to light instead, but this does require wearing special goggles.

There are several clinical trials ongoing with this approach, said , chair of the Nobel Committee.

The downside of optogenetics is that light can’t penetrate far into the body. So, several groups around the world are trying to develop equivalent methods based on ultrasound or magnetism.

The 2025 Nobel prize in chemistry has gone to , and for the development of materials full of cavities that can store and release gases such as carbon dioxide, known as metal-organic frameworks.

“A small amount of such material can be almost like Hermione’s handbag in Harry Potter,” said Heiner Linke, chair of the Nobel Committee for Chemistry. “It can store huge amounts of gas in a tiny volume.”

Tens of thousands of different metal-organic frameworks have now been created. They have many potential applications, from helping to capture CO₂ in chimneys to cleaning up forever chemicals and harvesting water from the air.

In the late 1980s, Richard Robson at the University of Melbourne in Australia was inspired by the ordered structure of diamonds to create the first metal-organic frameworks. Robson realised that it might be possible to use metal ions as nodes, and link them together with carbon-based, or organic, molecules.

When the metal ions and organic molecules are mixed together, they self-assemble into ordered frameworks. While the cavities in the diamond framework are small, the cavities in metal-organic frameworks can be much bigger.

The cavities in the metal-organic frameworks created by Robson were filled with water. It was Susumu Kitagawa at Kyoto University in Japan who first created a framework that was stable enough to be dried out and who managed to fill the empty cavities with gas.

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“He showed that the gases could be taken up, absorbed by the material, and could also be released from the material,” said Olof Ramström, a member of the Nobel Committee for Chemistry.

Kitagawa also went on to create metal-organic frameworks that change shape when gases are added or removed.

Omar Yaghi at the University of California, Berkeley, managed to create frameworks that were even more stable by using metal ion clusters containing zinc and oxygen, and linkers containing carboxylate groups.

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“This is an astonishing framework because it was highly stable. It was stable all the way up to 300 degrees Celsius,” said Ramström. “But even more remarkable was that it contains an enormous surface area. So just a few grams of this porous material, roughly the same as a small sugar cube, contains as much surface area as a large football pitch that is several thousands of square meters.”

Yaghi also went on to show that the cavities in these materials can be made larger, simply by making the linkers longer.

After these fundamental breakthroughs, the field evolved very rapidly, Ramström said. “We see new metal-organic frameworks developed almost every day.”

The 2025 Nobel prize in physics has been awarded to , and for their work on showing how quantum particles can mysteriously tunnel through matter, a process that helped produce the superconducting quantum technology that forms the backbone of today’s quantum computers.

“I’m completely stunned,” Clarke told the Nobel committee upon hearing he had received the prize. “It had never occurred to me in any way that this might be the basis of a Nobel prize.”

Quantum particles have a variety of strange behaviours, such as their probabilistic nature and the fact that they can only have specific energy levels, rather than a continuum. This leads them to sometimes behave in unexpected ways, such as tunnelling through an apparently solid barrier. Such oddities were discovered by physicists like Erwin Schrödinger in the first decades after quantum mechanics began.

While the implications of these behaviours were clearly profound, underpinning, for example, the theory of nuclear decay, scientists could only observe them in single particles and simple systems. It was unclear whether more complex systems, such as electronic circuits, previously only described by classical physics, were also subject to these rules. Quantum tunnelling effects, for instance, seemed to disappear when looking at large-scale systems.

In 1985, Clarke, Martinis and Devoret, then all based at the University of California, Berkeley, set out to change that. They measured the properties of charged particles moving through superconducting circuits called Josephson junctions, a device that won British physicist Brian Josephson the 1973 Nobel prize in physics. These junctions use wires that have zero electrical resistance and are separated by an insulating material.

The researchers showed that particles moving through these junctions acted as a single particle and took on distinct energy levels, a distinctly quantum effect, and also registered a voltage that would be impossible without it having jumped over the insulating boundary, a clear example of quantum tunnelling.

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This discovery, and its help in understanding how to manipulate superconducting quantum systems similar to this, revolutionised the field of quantum science, allowing other scientists to test precise quantum physics on silicon chips.

Superconducting quantum circuits also formed the basis for the basic building blocks of quantum computers – the quantum bit, or qubit. The most powerful quantum computers today, built by companies like Google and IBM, use machines made up of hundreds of superconducting qubits, which Clarke, Martinis and Devoret’s findings led to. “Our discovery, in some ways, is the basis of quantum computing,” said Clarke.

Martinis and Devoret have both worked for Google Quantum AI, which produced the first superconducting quantum computer displaying quantum advantage over a classical machine, in 2019. But Clarke told the Nobel committee that it wasn’t clear, at the time, how influential their 1985 research would go on to be. “It had not occurred to us in any way that this discovery would have such significant impact.”

The 2025 Nobel prize in physiology or medicine has been awarded to three researchers – , and – who discovered a key kind of immune cell that helps stop the immune system attacking itself.

“It unleashed a whole new field in immunology,” said at the Karolinska Institute in Sweden.

Immune cells called T-cells play a key role in immunity by grabbing hold of invasive viruses and bacteria via receptors on their surface. New kinds of T-cells are generated throughout our lives.

Sometimes the receptors on newly-generated T-cells grab hold of our own proteins instead of viral or bacterial ones, which can cause conditions such as type 1 diabetes and rheumatoid arthritis.

The body does have a system for weeding out self-reactive T-cells. T-cells originate in the bone marrow and then migrate to the thymus, a small organ in the chest, where they undergo a selection process. This was long believed to be the only way that self-targeting T-cells are eliminated.

But in 1995, Sakaguchi, now at Osaka University in Japan, showed in mouse experiments that some other cells circulating in the bloodstream must also somehow protect against auto-reactive T-cells. If the thymus of mice is removed after birth, Sakaguchi found, the animals develop autoimmune conditions. But if T-cells from healthy mice are injected into them, this is prevented. His team found that the specific T-cells responsible for this have a protein called CD25 on their surface, and called them CD25 regulatory T-cells.

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Meanwhile, Brunkow, now at the Institute for Systems Biology in Seattle, Washington, and Ramsdell, a scientific adviser at Sonoma Biotherapeutics in San Francisco, California, were studying a strain of mice that is especially likely to get autoimmune conditions. In 2001, Brunkow and Ramsdell found that these mice have a mutation in a gene on the X chromosome called FOXP3.

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People with mutations in this gene are also especially likely to get autoimmune disease, due to a condition known as IPEX syndrome. In 2003, Sakaguchi showed that these two discoveries are linked – the FOXP3 gene plays a key role in the development of the CD25 regulatory cells that his team discovered. Many researchers had been sceptical about Sakaguchi’s earlier claims, said Wahren-Herlenius. But the work of Brunkow and Ramsdell clinched the case.

The discovery of regulatory T-cells could lead to better treatments for a wide range of conditions. On the one hand, boosting the number of regulatory T-cells could help suppress the autoimmune reactions that cause conditions such as type 1 diabetes. On the other, reducing the number of regulatory T-cells could boost the immune response against cancers. A number of clinical trials are now underway.

“Their discoveries have been decisive for our understanding of how the immune system functions and why we do not all develop serious autoimmune diseases,” , chair of the Nobel committee, said in a .

It is that time of year when congratulations are in order, as some of the best minds in science are awarded a Nobel prize. The latest winners have a few things in common: they undoubtedly have an impressive body of work – and they are all men, they live in high-income countries and none of them is Black.

Gary Ruvkun and Victor Ambros won the prize for physiology or medicine for their discovery of microRNAs and the role they play in controlling genes, which could help treat cancer. A string of papers led to this discovery, many of which list Rosalind Lee – Ambros’s wife – as an author. The Nobel committee for physiology or medicine was , but didn’t go as far as awarding her a medal. Maybe it thinks that one per household is good enough.

Lee’s omission may seem familiar. In 1962, James Watson, Francis Crick and Maurice Wilkins took home the same prize for discovering the molecular structure of DNA. This was off the back . One was co-authored by Wilkins, one by Watson and Crick, and the third by Rosalind Franklin, who captured an image of DNA having two chains. Prior to the image’s publication, , and informed their model of DNA as a double helix. Franklin, who died from ovarian cancer in 1958, was left off the Nobel trophy due to a rule against posthumous awards.

Perhaps the committee dislikes the name Rosalind. But since their inception in 1901, and only . The hit rate for the physics prize, awarded this year to John Hopfield and Geoffrey Hinton for discoveries related to machine learning, is particularly bad – only five women have ever won.

At least women in science have seen some recognition. No Black person has ever won a science Nobel, and there have only been 17 Black winners in total across the peace, literature and economics prizes. Many argue that Charles Drew, , should have won for medicine, while Percy Julian, who figured out , was snubbed for chemistry.

Geography also seems to play a key role in deciding winners. More than half the prizes have , and among the handful of winners from lower income countries, most had moved to North America or Europe by the time they were awarded.

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Some may say all of this simply reflects the demographics of science. , for example. But failing to give credit where it is due doesn’t help, particularly when the physiology or medicine Nobel committee flagged a paper led by Lee .

The Royal Swedish Academy of Sciences, which administers the physics and chemistry prizes, does at least recognise that this lack of diversity is a problem. Since 2019, nominators have been asked to be aware of gender, ethnicity and geography when selecting nominees, who cannot put themselves forward. It sounds good on paper, but only six women and no Black people have won in the science categories since.

You may wonder why this matters. Awards are a nice accolade, but shouldn’t drive scientists. Yet being a Nobel laureate opens doors for researchers and puts their work in the public consciousness. For many people, the annual Nobels may be the only time they see a scientist named in news headlines, and the awards play a big role in shaping our perception of science.

Part of the problem is that the structure of the prizes, as dictated by the will of Alfred Nobel, tend to enforce a “great man of history” approach to science that doesn’t reflect the reality of modern research. The rules allow no more than three individuals to share a prize, although this doesn’t explain why Lee was excluded from the Ruvkun-Ambros prizewinning duo. Meanwhile, the rule against posthumous awards has denied worthy people like Franklin their dues.

Such problems aren’t new, of course, and it seems unlikely that the Nobel committees will deviate from their patron’s wishes, but that isn’t a reason to ignore diversity. The committees must cast a wider net, not only for fairness’ sake, but also if they want the awards to continue to be taken seriously.

Alexandra Thompson is an assistant news editor at New Scientist.

The 2024 Nobel prize in chemistry has been awarded to , �����Ի��� for their work on understanding the structure of proteins, which play vital roles in all living organisms. Hassabis and Jumper, of Google DeepMind, developed an artificial intelligence that predicts the structure of proteins. Baker, at the University of Washington in Seattle, has been recognised for his work on designing new proteins.

Proteins are the molecules that make life happen. All of the key machinery of life is made of proteins, from the muscles that power us and the molecules that read and copy DNA to the antibodies that protect us from infections.

“To understand life, you first need to understand the shape of proteins,” said Heiner Linke, chair of the Nobel committee for chemistry, at a press conference.

All proteins are made of chains of amino acids, and there are around 20 different kinds of these compounds. The shape of proteins is determined by the sequence of amino acids, but the way in which the chains fold up is so complex that predicting a protein’s structure from its sequence is extremely challenging.

“For several decades, this was considered impossible,” said Linke.

Several teams have developed various computational methods of predicting protein structures, but their accuracy was low. Then Hassabis and Jumper developed an AI called AlphaFold.

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The first version of AlphaFold, unveiled in 2018, was an improvement on other methods. The second, released in 2020, was a massive leap forward, predicting two-thirds of protein structures with more than 90 per cent accuracy.

By 2022, AlphaFold had been used to predict the structure of almost all known proteins, with the results made freely available.

“It was an enormous breakthrough,” said Johan Åqvist, a member of the Nobel committee for chemistry. “This is a fantastic resource for chemical and biological research.”

Baker has long been working on the opposite problem, that of designing a protein with a desired structure. The possibilities here are endless – new proteins could be used to do pretty much anything, from treating diseases to creating complex nanomachines.

“David Baker opened up a completely new world of proteins that we had never seen before,” said Åqvist. “It’s a mind-blowing development.”

Baker has created software called Rosetta for doing this, which is also freely available. He and his team first demonstrated that Rosetta worked back in 2003, when they designed a protein, made it and then used a technique called X-ray crystallography to show it had the designed structure.

While Åqvist described this 2003 work as “the big breakthrough”, the protein created was small, simple and didn’t do anything.

Baker himself described the process as more gradual. “It really happened over many years,” he said. “Over the last 20 years, we’ve been able to design proteins with more and more complex and powerful functions.”

“As we got better and better at that, the scope of applications became more and more exciting,” said Baker. “It’s been this huge opening up of possibilities, because the proteins in nature do so many different things. They mediate all the processes in our bodies and in all living things.”

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Baker also gave credit to his colleagues: “I stood on the shoulders of giants. I have had, throughout my career, absolutely wonderful colleagues to work with.”

The award came as a surprise, despite speculation that he might get it, he said. “It’s turning out to be a unique, special day.”

The chemistry prize is the third Nobel awarded so far this year. On 8 October, the 2024 Nobel prize in physics was awarded to John Hopfield and Geoffrey Hinton for their work on artificial neural networks. On 7 October, the 2024 Nobel prize in physiology or medicine went to Victor Ambros and Gary Ruvkun for their discovery that tiny pieces of RNA called microRNAs play a key role in controlling genes.

Last year’s Nobel prize in chemistry went to three of the developers of quantum dots – particles so small that their electrical and optical properties are influenced by quantum physics.

The 2024 Nobel prize in physics has been awarded to John Hopfield and Geoffrey Hinton for their work on artificial neural networks and the fundamental algorithms that let machines learn, which are key to today’s large language models like ChatGPT.

“I’m flabbergasted, I had no idea this would happen,” Hinton told the Nobel committee upon hearing the prize announcement. “I’m very surprised.” Hinton, who has been vocal about his fears around the development of artificial intelligence, also reiterated that he regretted the work he had done. “In the same circumstances, I would do the same again, but I am worried that the overall consequences of this might be systems more intelligent than us that eventually take control,” he said.

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While AI might not seem like an obvious contender for the physics Nobel, the discovery of neural networks that can learn and their applications are two areas that are intimately connected to physics, said Ellen Moons, chair of the Nobel Committee for Physics, during the announcement. “These artificial neural networks have been used to advance research across physics topics as diverse as particle physics, material science and astrophysics.”

Many early approaches to artificial intelligence involved giving computer programs logical rules to follow to help solve problems, but this made it difficult for them to learn about new information or encounter situations they hadn’t seen before. In 1982, Hopfield, at Princeton University, created an architecture for a computer called a Hopfield network, which is a collection of nodes, or artificial neurons, that can change the strength of their connections with a learning algorithm that Hopfield invented.

That algorithm was inspired by work from physics that finds the energy of a magnetic system by describing it as collections of tiny magnets. The technique involves iteratively changing the strength of the connections between the magnets in an attempt to find a minimum value for the energy of the system.

In the same year, Hinton, at the University of Toronto, began developing Hopfield’s idea to help create a closely related machine learning structure called a Boltzmann machine. “I remember going to a meeting in Rochester where John Hopfield talked and I first learned about neural networks. After that, Terry [Sejnowski] and I worked feverishly to work out how to generalise neural networks,” he said.

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Hinton and his colleagues showed that, unlike previous machine learning architectures, Boltzmann machines could learn and extract patterns from large data sets. This principle, when combined with large amounts of data and computing power, has led to the success of many artificial intelligence systems today, such as image recognition and language translation tools.

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However, while the Boltzmann machine proved capable, it was also inefficient and slow, and it isn’t used in modern systems today. Instead, faster, modern machine learning architectures like transformer models, which power large language models like ChatGPT, are used.

At the Nobel award conference, Hinton was bullish on the impact that his and Hopfield’s discoveries would have. “It will be comparable with the industrial revolution, but instead of exceeding people in physical strength, it’s going to exceed people in intellectual ability,” he said. “We have no experience of what it’s like to have things smarter than us. It’s going to be wonderful in many respects… but we also have to worry about a number of bad consequences, particularly the threat of these things getting out of control.”