When you look back at the early days of computing, some familiar names pop up, including John von Neumann, Nicholas Metropolis and Richard Feynman. But they were not lonely pioneers – they were part of a much larger group, using mechanical and then electronic computers to do calculations that had never been possible before.

These people, many of whom were women, were the first scientific programmers and computational scientists. Skilled in the complicated operation of early computing devices, they often had degrees in maths or science, and were an integral part of research efforts. And yet, their fundamental contributions are mostly forgotten.

This was in part because of their gender – it was an age when sexism was rife, and it was standard for women to be fired from their job after getting married. However, there is another important factor that is often overlooked, even in today’s scientific community – people in technical roles are often underappreciated and underacknowledged, even though they are the ones who make research possible.

Human and mechanical computers

Originally, a “computer” was a human being who did calculations by hand or with the help of a mechanical calculator. It is thought that the world’s first computational lab was set up in 1937 at Columbia University. But it wasn’t until the Second World War that the demand for computation really exploded; with the need for artillery calculations, new technologies and code breaking.

In the US, the development of the atomic bomb during the Manhattan Project (established in 1943) required huge computational efforts, so it wasn’t long before the New Mexico site had a hand-computing group. Called the T-5 group of the Theoretical Division, it initially consisted of about 20 people. Most were women, including the spouses of other scientific staff. Among them was Mary Frankel, a mathematician married to physicist Stan Frankel; mathematician Augusta “Mici” Teller who was married to Edward Teller, the “father of the hydrogen bomb”; and Jean Bacher, the wife of physicist Robert Bacher.

As the war continued, the T-5 group expanded to include civilian recruits from the nearby towns and members of the Women’s Army Corps. Its staff worked around the clock, using printed mathematical tables and desk calculators in four-hour shifts – but that was not enough to keep up with the computational needs for bomb development. In the early spring of 1944, IBM punch-card machines were brought in to supplement the human power. They became so effective that the machines were soon being used for all large calculations, 24 hours a day, in three shifts.

The computational group continued to grow, and among the new recruits were Naomi Livesay and Eleonor Ewing. Livesay held an advanced degree in mathematics and had done a course in operating and programming IBM electric calculating machines, making her an ideal candidate for the T-5 division. She in turn recruited Ewing, a fellow mathematician who was a former colleague. The two young women supervised the running of the IBM machines around the clock.

The frantic pace of the T-5 group continued until the end of the war in September 1945. The development of the atomic bomb required an immense computational effort, which was made possible through hand and punch-card calculations.

Electronic computers

Shortly after the war ended, the first fully electronic, general-purpose computer – the Electronic Numerical Integrator and Computer (ENIAC) – became operational at the University of Pennsylvania, following two years of development. The project had been led by physicist John Mauchly and electrical engineer J Presper Eckert. The machine was operated and coded by six women – mathematicians Betty Jean Jennings (later Bartik); Kathleen, or Kay, McNulty (later Mauchly, then Antonelli); Frances Bilas (Spence); Marlyn Wescoff (Meltzer) and Ruth Lichterman (Teitelbaum); as well as Betty Snyder (Holberton) who had studied journalism.

Polymath John von Neumann also got involved when looking for more computing power for projects at the new Los Alamos Laboratory, established in New Mexico in 1947. In fact, although originally designed to solve ballistic trajectory problems, the first problem to be run on the ENIAC was “the Los Alamos problem” – a thermonuclear feasibility calculation for Teller’s group studying the H-bomb.

Like in the Manhattan Project, several husband-and-wife teams worked on the ENIAC, the most famous being von Neumann and his wife Klara Dán, and mathematicians Adele and Herman Goldstine. Dán von Neumann in particular worked closely with Nicholas Metropolis, who alongside mathematician Stanislaw Ulam had coined the term Monte Carlo to describe numerical methods based on random sampling. Indeed, between 1948 and 1949 Dán von Neumann and Metropolis ran the first series of Monte Carlo simulations on an electronic computer.

Work began on a new machine at Los Alamos in 1948 – the Mathematical Analyzer Numerical Integrator and Automatic Computer (MANIAC) – which ran its first large-scale hydrodynamic calculation in March 1952. Many of its users were physicists, and its operators and coders included mathematicians Mary Tsingou (later Tsingou-Menzel), Marjorie Jones (Devaney) and Elaine Felix (Alei); plus Verna Ellingson (later Gardiner) and Lois Cook (Leurgans).

Early algorithms

The Los Alamos scientists tried all sorts of problems on the MANIAC, including a chess-playing program – the first documented case of a machine defeating a human at the game. However, two of these projects stand out because they had profound implications on computational science.

In 1953 the Tellers, together with Metropolis and physicists Arianna and Marshall Rosenbluth, published the seminal article “Equation of state calculations by fast computing machines” (J. Chem. Phys. 21 1087). The work introduced the ideas behind the “Metropolis (later renamed Metropolis–Hastings) algorithm”, which is a Monte Carlo method that is based on the concept of “importance sampling”. (While Metropolis was involved in the development of Monte Carlo methods, it appears that he did not contribute directly to the article, but provided access to the MANIAC nightshift.) This is the progenitor of the Markov Chain Monte Carlo methods, which are widely used today throughout science and engineering.

Marshall later recalled how the research came about when he and Arianna had proposed using the MANIAC to study how solids melt (AIP Conf. Proc. 690 22).

Edward Teller meanwhile had the idea of using statistical mechanics and taking ensemble averages instead of following detailed kinematics for each individual disk, and Mici helped with programming during the initial stages. However, the Rosenbluths did most of the work, with Arianna translating and programming the concepts into an algorithm.

The 1953 article is remarkable, not only because it led to the Metropolis algorithm, but also as one of the earliest examples of using a digital computer to simulate a physical system. The main innovation of this work was in developing “importance sampling”. Instead of sampling from random configurations, it samples with a bias toward physically important configurations which contribute more towards the integral.

Furthermore, the article also introduced another computational trick, known as “periodic boundary conditions” (PBCs): a set of conditions which are often used to approximate an infinitely large system by using a small part known as a “unit cell”. Both importance sampling and PBCs went on to become workhorse methods in computational physics.

In the summer of 1953, physicist Enrico Fermi, Ulam, Tsingou and physicist John Pasta also made a significant breakthrough using the MANIAC. They ran a “numerical experiment” as part of a series meant to illustrate possible uses of electronic computers in studying various physical phenomena.

The team modelled a 1D chain of oscillators with a small nonlinearity to see if it would behave as hypothesized, reaching an equilibrium with the energy redistributed equally across the modes (doi.org/10.2172/4376203). However, their work showed that this was not guaranteed for small perturbations – a non-trivial and non-intuitive observation that would not have been apparent without the simulations. It is the first example of a physics discovery made not by theoretical or experimental means, but through a computational approach. It would later lead to the discovery of solitons and integrable models, the development of chaos theory, and a deeper understanding of ergodic limits.

Although the paper says the work was done by all four scientists, Tsingou’s role was forgotten, and the results became known as the Fermi–Pasta–Ulam problem. It was not until 2008, when French physicist Thierry Dauxois advocated for giving her credit in a Physics Today article, that Tsingou’s contribution was properly acknowledged. Today the finding is called the Fermi–Pasta–Ulam–Tsingou problem.

The year 1953 also saw IBM’s first commercial, fully electronic computer – an IBM 701 – arrive at Los Alamos. Soon the theoretical division had two of these machines, which, alongside the MANIAC, gave the scientists unprecedented computing power. Among those to take advantage of the new devices were Martha Evans (whom very little is known about) and theoretical physicist Francis Harlow, who began to tackle the largely unexplored subject of computational fluid dynamics.

The idea was to use a mesh of cells through which the fluid, represented as particles, would move. This computational method made it possible to solve complex hydrodynamics problems (involving large distortions and compressions of the fluid) in 2D and 3D. Indeed, the method proved so effective that it became a standard tool in plasma physics where it has been applied to every conceivable topic from astrophysical plasmas to fusion energy.

The resulting internal Los Alamos report – The Particle-in-cell Method for Hydrodynamic Calculations, published in 1955 – showed Evans as first author and acknowledged eight people (including Evans) for the machine calculations. However, while Harlow is remembered as one of the pioneers of computational fluid dynamics, Evans was forgotten.

A clear-cut division of labour?

In an age where women had very limited access to the frontlines of research, the computational war effort brought many female researchers and technical staff in. As their contributions come more into the light, it becomes clearer that their role was not a simple clerical one.

There is a view that the coders’ work was “the vital link between the physicist’s concepts (about which the coders more often than not didn’t have a clue) and their translation into a set of instructions that the computer was able to perform, in a language about which, more often than not, the physicists didn’t have a clue either”, as physicists Giovanni Battimelli and Giovanni Ciccotti wrote in 2018 (Eur. Phys. J. H 43 303). But the examples we have seen show that some of the coders had a solid grasp of the physics, and some of the physicists had a good understanding of the machine operation. Rather than a skilled–non-skilled/men–women separation, the division of labour was blurred. Indeed, it was more of an effective collaboration between physicists, mathematicians and engineers.

Even in the early days of the T-5 division before electronic computers existed, Livesay and Ewing, for example, attended maths lectures from von Neumann, and introduced him to punch-card operations. As has been documented in books including Their Day in the Sun by Ruth Howes and Caroline Herzenberg, they also took part in the weekly colloquia held by J Robert Oppenheimer and other project leaders. This shows they should not be dismissed as mere human calculators and machine operators who supposedly “didn’t have a clue” about physics.

Verna Ellingson (Gardiner) is another forgotten coder who worked at Los Alamos. While little information about her can be found, she appears as the last author on a 1955 paper (Science 122 465) written with Metropolis and physicist Joseph Hoffman – “Study of tumor cell populations by Monte Carlo methods”. The next year she was first author of “On certain sequences of integers defined by sieves” with mathematical physicist Roger Lazarus, Metropolis and Ulam (Mathematics Magazine 29 117). She also worked with physicist George Gamow on attempts to discover the code for DNA selection of amino acids, which just shows the breadth of projects she was involved in.

Evans not only worked with Harlow but took part in a 1959 conference on self-organizing systems, where she queried AI pioneer Frank Rosenblatt on his ideas about human and machine learning. Her attendance at such a meeting, in an age when women were not common attendees, implies we should not view her as “just a coder”.

With their many and wide-ranging contributions, it is more than likely that Evans, Gardiner, Tsingou and many others were full-fledged researchers, and were perhaps even the first computational scientists. “These women were doing work that modern computational physicists in the [Los Alamos] lab’s XCP [Weapons Computational Physics] Division do,” says Nicholas Lewis, a historian at Los Alamos. “They needed a deep understanding of both the physics being studied, and of how to map the problem to the particular architecture of the machine being used.”

Overlooked then, overlooked now

Credited or not, these pioneering women and their contributions have been mostly forgotten, and only in recent decades have their roles come to light again. But why were they obscured by history in the first place?

Secrecy and sexism seem to be the main factors at play. For example, Livesay was not allowed to pursue a PhD in mathematics because she was a woman, and in the cases of the many married couples, the team contributions were attributed exclusively to the husband. The existence of the Manhattan Project was publicly announced in 1945, but documents that contain certain nuclear-weapons-related information remain classified today. Because these are likely to remain secret, we will never know the full extent of these pioneers’ contributions.

But another often overlooked reason is the widespread underappreciation of the key role of computational scientists and research software engineers, a term that was only coined just over a decade ago. Even today, these non-traditional research roles end up being undervalued. A 2022 survey by the UK Software Sustainability Institute, for example, showed that only 59% of research software engineers were named as authors, with barely a quarter (24%) mentioned in the acknowledgements or main text, while a sixth (16%) were not mentioned at all.

The separation between those who understand the physics and those who write the code, understand and operate the hardware goes back to the early days of computing (see box above), but it wasn’t entirely accurate even then. People who implement complex scientific computations are not just coders or skilled operators of supercomputers, but truly multidisciplinary scientists who have a deep understanding of the scientific problems, mathematics, computational methods and hardware.

Such people – whatever their gender – play a key role in advancing science and yet remain the unsung heroes of the discoveries their work enables. Perhaps what this story of the forgotten pioneers of computational physics tells us is that some views rooted in the 1950s are still influencing us today. It’s high time we moved on.

The post The forgotten pioneers of computational physics appeared first on Physics World.

Gravity might be able to quantum-entangle particles even if the gravitational field itself is classical. That is the conclusion of a new study by Joseph Aziz and Richard Howl at Royal Holloway University of London. This challenges a popular view that such entanglement would necessarily imply that gravity must be quantized. This could be important in the ongoing attempt to develop a theory of quantum gravity that unites quantum mechanics with Einstein’s general theory of relativity.

“When you try to quantize the gravitational interaction in exactly the same way we tried to mathematically quantize the other forces, you end up with mathematically inconsistent results – you end up with infinities in your calculations that you can’t do anything about,” Howl tells Physics World.

“With the other interactions, we quantized them assuming they live within an independent background of classical space and time,” Howl explains. “But with quantum gravity, arguably you cannot do this [because] gravity describes space−time itself rather than something within space−time.”

Quantum entanglement occurs when two particles share linked quantum states even when separated. While it has become a powerful probe of the gravitational field, the central question is whether gravity can mediate entanglement only if it is itself quantum in nature.

General treatment

“It has generally been considered that the gravitational interaction can only entangle matter if the gravitational field is quantum,” Howl says. “We have argued that you could treat the gravitational interaction as more general than just the mediation of the gravitational field such that even if the field is classical, you could in principle entangle matter.”

Quantum field theory postulates that entanglement between masses arises through the exchange of virtual gravitons. These are hypothetical, transient quantum excitations of the gravitational field. Aziz and Howl propose that even if the field remains classical, virtual-matter processes can still generate entanglement indirectly. These processes, he says, “will persist even when the gravitational field is considered classical and could in principle allow for entanglement”.

The idea of probing the quantum nature of gravity through entanglement goes back to a suggestion by Richard Feynman in the 1950s. He envisioned placing a tiny mass in a superposition of two locations and checking whether its gravitational field was also superposed. Though elegant, the idea seemed untestable at the time.

Recent proposals − most notably by teams led by Sougato Bose and by Chiara Marletto and Vlatko Vedral – revived Feynman’s insight in a more practical form.

Feasible tests

“Recently, two proposals showed that one way you could test that the field is in a superposition (and thus quantum) is by putting two masses in a quantum superposition of two locations and seeing if they become entangled through the gravitational interaction,” says Howl. “This also seemed to be much more feasible than Feynman’s original idea.” Such experiments might use levitated diamonds, metallic spheres, or cold atoms – systems where both position and gravitational effects can be precisely controlled.

Aziz and Howl’s work, however, considers whether such entanglement could arise even if gravity is not quantum. They find that certain classical-gravity processes can in principle entangle particles, though the predicted effects are extremely small.

“These classical-gravity entangling effects are likely to be very small in near-future experiments,” Howl says. “This though is actually a good thing: it means that if we see entanglement…we can be confident that this means that gravity is quantized.”

The paper has drawn a strong response from some leading figures in the field, including Marletto at the University of Oxford, who co-developed the original idea of using gravitationally induced entanglement as a test of quantum gravity.

“The phenomenon of gravitationally induced entanglement … is a game changer in the search for quantum gravity, as it provides a way to detect quantum effects in the gravitational field indirectly, with laboratory-scale equipment,” she says. Detecting it would, she adds, “constitute the first experimental confirmation that gravity is quantum, and the first experimental refutation of Einstein’s relativity as an adequate theory of gravity”.

However, Marletto disputes Aziz and Howl’s interpretation. “No classical theory of gravity can mediate entanglement via local means, contrary to what the study purports to show,” she says. “What the study actually shows is that a classical theory with direct, non-local interactions between the quantum probes can get them entangled.” In her view, that mechanism “is not new and has been known for a long time”.

Despite the controversy, Howl and Marletto agree that experiments capable of detecting gravitationally induced entanglement would be transformative. “We see our work as strengthening the case for these proposed experiments,” Howl says. Marletto concurs that “detecting gravitationally induced entanglement will be a major milestone … and I hope and expect it will happen within the next decade.”

Howl hopes the work will encourage further discussion about quantum gravity. “It may also lead to more work on what other ways you could argue that classical gravity can lead to entanglement,” he says.

The research is described in Nature.

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“Drain the swamp!”

In the intense first few months of his second US presidency, Donald Trump has been enacting his old campaign promise with a vengeance. He’s ridding all the muck from the American federal bureaucracy, he claims, and finally bringing it back under control.

Scientific projects and institutions are particular targets of his, with one recent casualty being the High Energy Physics Advisory Panel (HEPAP). Outsiders might shrug their shoulders at a panel of scientists being axed. Panels come and go. Also, any development in Washington these days is accompanied by confusion, uncertainty, and the possibility of reversal.

But HEPAP’s dissolution is different. Set up in 1967, it’s been a valuable and long-standing advisory committee of the Office of Science at the US Department of Energy (DOE). HEPAP has a distinguished track record of developing, supporting and reviewing high-energy physics programmes, setting priorities and balancing different areas. Many scientists are horrified by its axing.

The terminator

Since taking office in January 2025, Trump has issued a flurry of executive orders – presidential decrees that do not need Congressional approval, legislative review, or public debate. One order, which he signed in February, was entitled “Commencing the Reduction of the Federal Bureaucracy”.

It sought to reduce parts of the government “that the President has determined are unnecessary”, seeking to eliminate “waste and abuse, reduce inflation, and promote American freedom and innovation”. While supporters see those as laudable goals, opponents believe the order is driving a stake into the heart of US science.

Hugely valuable, long-standing scientific advisory committees have been axed at key federal agencies, including NASA, the National Science Foundation, the Environmental Protection Agency, the National Oceanic and Atmospheric Administration, the US Geological Service, the National Institute of Health, the Food and Drug Administration, and the Centers for Disease Control and Prevention.

What’s more, the committees were terminated without warning or debate, eliminating load-bearing pillars of the US science infrastructure. It was, as the Columbia University sociologist Gil Eyal put it in a recent talk, the “Trump 2.0 Blitzkrieg”.

Then, on 30 September, Trump’s enablers took aim at advisory committees at the DOE Office of Science. According to the DOE’s website, a new Office of Science Advisory Committee (SCAC) will take over functions of the six former discretionary (non-legislatively mandated) Office of Science advisory committees.

“Any current charged responsibilities of these former committees will be transferred to the SCAC,” the website states matter-of-factly. The committee will provide “independent, consensus advice regarding complex scientific and technical issues” to the entire Office of Science. Its members will be appointed by under secretary for science Dario Gil – a political appointee.

Apart from HEPAP, others axed without warning were the Nuclear Science Advisory Committee, the Basic Energy Sciences Advisory Committee, the Fusion Energy Sciences Advisory Committee, the Advanced Scientific Computing Advisory Committee, and the Biological and Environmental Research Advisory Committee.

Over the years, each committee served a different community and was represented by prominent research scientists who were closely in touch with other researchers. Each committee could therefore assemble the awareness of – and technical knowledge about – emerging promising initiatives and identify the less promising ones.

Many committee members only learned of the changes when they received letters or e-mails out of the blue informing them that their committee had been dissolved, that a new committee had replaced them, and that they were not on it. No explanation was given.

Closing HEPAP and the other Office of Science committees will hamper both the technical support and community input that it has relied on to promote the efficient, effective and robust growth of physics.

Physicists whom I have spoken to are appalled for two main reasons. One is that closing HEPAP and the other Office of Science committees will hamper both the technical support and community input that it has relied on to promote the efficient, effective and robust growth of physics.

“Speaking just for high-energy physics, HEPAP gave feedback on the DOE and NSF funding strategies and priorities for the high-energy physics experiments”, says Kay Kinoshita from the University of Cincinnati, a former HEPAP member. “The panel system provided a conduit for information between the agencies and the community, so the community felt heard and the agencies were (mostly) aligned with the community consensus”.

As Kinoshita continued: “There are complex questions that each panel has to deal with. even within the topical area. It’s hard to see how a broader panel is going to make better strategic decisions, ‘better’ meaning in terms of scientific advancement. In terms of community buy-in I expect it will be worse.”

Other physicists cite a second reason for alarm. The elimination of the advisory committees spreads the expertise so thinly as to increase the likelihood of political pressure on decisions. “If you have one committee you are not going to get the right kind of fine detail,” says Michael Lubell, a physicist and science-policy expert at the City College of New York, who has sat in on meetings of most of the Office of Science advisory committees.

“You’ll get opinions from people outside that area and you won’t be able to get information that you need as a policy maker to decide how the resources are to be allocated,” he adds. “A condensed-matter physicist for example, would probably have insufficient knowledge to advise DOE on particle physics. Instead, new committee members would be expected to vet programs based on ideological conformity to what the Administration wants.”

The critical point

At the end of the Second World War, the US began to construct an ambitious long-range plan to promote science that began with the establishment of the National Science Foundation in 1950 and developed and extended ever since. The plan aimed to incorporate both the ability of elected politicians to direct science towards social needs and the independence of scientists to explore what is possible.

US presidents have, of course, had pet scientific projects: the War on Cancer (Nixon), the Moon Shot (Kennedy), promoting renewable energy (Carter), to mention a few. But it is one thing for a president to set science to producing a socially desirable product and another to manipulate the scientific process itself.

“This is another sad day for American science,” says Lubell. “If I were a young person just embarking on a career, I would get the hell out of the country. I would not want to waste the most creative years of my life waiting for things to turn around, if they ever do. What a way to destroy a legacy!”

The end of HEPAP is not draining a swamp but creating one.

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Better together. That’s the headline take on a newly inked technology partnership between Bluefors, a heavyweight Finnish supplier of cryogenic measurement systems, and Delft Circuits, a Dutch manufacturer of specialist I/O cabling solutions designed for the scale-up and industrial deployment of next-generation quantum computers.

The drivers behind the tie-up are clear: as quantum systems evolve – think vastly increased qubit counts plus ever-more exacting requirements on gate fidelity – developers in research and industry will reach a point where current coax cabling technology doesn’t cut it anymore. The answer? Collaboration, joined-up thinking and product innovation.

In short, by integrating Delft Circuits’ Cri/oFlex^® cabling technology into Bluefors’ dilution refrigerators, the vendors’ combined customer base will benefit from a complete, industrially proven and fully scalable I/O solution for their quantum systems. The end-game: to overcome the quantum tech industry’s biggest bottleneck, forging a development pathway from quantum computing systems with hundreds of qubits today to tens of thousands of qubits by 2030.

Joined-up thinking

For context, Cri/oFlex^® cryogenic RF cables comprise a stripline (a type of transmission line) based on planar microwave circuitry – essentially a conducting strip encapsulated in dielectric material and sandwiched between two conducting ground planes. The use of the polyimide Kapton^® as the dielectric ensures Cri/oFlex^® cables remain flexible in cryogenic environments (which are necessary to generate quantum states, manipulate them and read them out), with silver or superconducting NbTi providing the conductive strip and ground layer. The standard product comes as a multichannel flex (eight channels per flex) with a range of I/O channel configurations tailored to the customer’s application needs, including flux bias lines, microwave drive lines, signal lines or read-out lines.

“Reliability is a given with Cri/oFlex^®,” says Robby Ferdinandus, global chief commercial officer for Delft Circuits and a driving force behind the partnership with Bluefors. “By integrating components such as attenuators and filters directly into the flex,” he adds, “we eliminate extra parts and reduce points of failure. Combined with fast thermalization at every temperature stage, our technology ensures stable performance across thousands of channels, unmatched by any other I/O solution.”

Technology aside, the new partnership is informed by a “one-stop shop” mindset, offering the high-density Cri/oFlex^® solution pre-installed and fully tested in Bluefors cryogenic measurement systems. For the end-user, think turnkey efficiency: streamlined installation, commissioning, acceptance and, ultimately, enhanced system uptime.

Scalability is front-and-centre too, thanks to Delft Circuits’ pre-assembled and tested side-loading systems. The high-density I/O cabling solution delivers up to 50% more channels per side-loading port to Bluefors’ (current) High Density Wiring, providing a total of 1536 input or control lines to an XLDsl cryostat. In addition, more wiring lines can be added to multiple KF ports as a custom option.

Doubling up for growth

Reciprocally, there’s significant commercial upside to this partnership. Bluefors is the quantum industry’s leading cryogenic systems OEM and, by extension, Delft Circuits now has access to the former’s established global customer base, amplifying its channels to market by orders of magnitude. “We have stepped into the big league here and, working together, we will ensure that Cri/oFlex^® becomes a core enabling technology on the journey to quantum advantage,” notes Ferdinandus.

That view is amplified by Reetta Kaila, director for global technical sales and new products at Bluefors (and, alongside Ferdinandus, a main-mover behind the partnership). “Our market position in cryogenics is strong, so we have the ‘muscle’ and specialist know-how to integrate innovative technologies like Cri/oFlex^® into our dilution refrigerators,” she explains.

A win-win, it seems, along several coordinates. “The Bluefors sales teams are excited to add Cri/oFlex^® into the product portfolio,” Kaila adds. “It’s worth noting, though, that the collaboration extends across multiple functions – technical and commercial – and will therefore ensure close alignment of our respective innovation roadmaps.”

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Artificial muscles that offer flexible functionality could prove invaluable for a range of applications, from soft robotics and wearables to biomedical instrumentation and minimally invasive surgery. Current designs, however, are limited by complex actuation mechanisms and challenges in miniaturization. Aiming to overcome these obstacles, a research team headed up at the Acoustic Robotics Systems Lab (ETH Zürich) in Switzerland is using microbubbles to create soft, programmable artificial muscles that can be wirelessly controlled via targeted ultrasound activation.

Gas-filled microbubbles can concentrate acoustic energy, providing a means to initiate movement with rapid response times and high spatial accuracy. In this study, reported in Nature, team leader Daniel Ahmed and colleagues built a synthetic muscle from a thin flexible membrane containing arrays of more than 10,000 microbubbles. When acoustically activated, the microbubbles generate thrust and cause the membrane to deform. And as different sized microbubbles resonate at different ultrasound frequencies, the arrays can be designed to provide programmable motion.

“Ultrasound is safe, non-invasive, can penetrate deep into the body and can generate large forces. However, without microbubbles, a much higher force is needed to deform the muscle, and selective activation is difficult,” Ahmed explains. “To overcome this limitation, we use microbubbles, which amplify force generation at specific sites and act as resonant systems. As a result, we can activate the artificial muscle at safe ultrasound power levels and generate complex motion.”

The team created the artificial muscles from a thin silicone membrane patterned with an array of cylindrical microcavities with the dimensions of the desired microbubbles. Submerging this membrane in a water-filled acoustic chamber trapped tens of thousands of gas bubbles within the cavities (one per cavity). The final device contains around 3000 microbubbles per mm² and weighs just 0.047 mg/mm².

To demonstrate acoustic activation, the researchers fabricated an artificial muscle containing uniform-sized microbubbles on one surface. They fixed one end of the muscle and exposed it to resonant frequency ultrasound, simultaneously exciting the entire microbubble array. The resulting oscillations generated acoustic streaming and radiation forces, causing the muscle to flex upward, with an amplitude dependent upon the ultrasound excitation voltage.

Next, the team designed an 80 µm-thick, 3 x 0.5 cm artificial muscle containing arrays of three different sized microbubbles. Stimulation at 96.5, 82.3 and 33.2 kHz induced deformations in regions containing bubbles with diameters of 12, 16 and 66 µm, respectively. Exposure to swept-frequency ultrasound covering the three resonant frequencies sequentially activated the different arrays, resulting in an undulatory motion.

A multitude of functions

Ahmed and colleagues showcased a range of applications for the artificial muscle by integrating microbubble arrays into functional devices, such as a miniature soft gripper for trapping and manipulating fragile live animals. The gripper comprises six to ten microbubble array-based “tentacles” that, when subjected to ultrasound, gently gripped a zebrafish larva with sub-100 ms response time. When the ultrasound was switched off, the tentacles opened and the larva swam away with no adverse effects.

The artificial muscle can function as a conformable robotic skin that sticks and imparts motion to a stationary object, which the team demonstrated by attaching it to the surface of an excised pig heart. It can also be employed for targeted drug delivery – shown by the use of a microbubble-array robotic patch for ultrasound-enhanced delivery of dye into an agar block.

The researchers also built an ultrasound-powered “stingraybot”, a soft surgical robot with artificial muscles (arrays of differently sized microbubbles) on either side to mimic the pectoral fins of a stingray. Exposure to swept-frequency ultrasound induced an undulatory motion that wirelessly propelled the 4 cm-long robot forward at a speed of about 0.8 body lengths per second.

To demonstrate future practical biomedical applications, such as supporting minimally invasive surgery or site-specific drug release within the gastrointestinal tract, the researchers encapsulated a rolled up stingraybot within a 27 x 12 mm edible capsule. Once released into the stomach, the robot could be propelled on demand under ultrasound actuation. They also pre-folded a linear artificial muscle into a wheel shape and showed that swept ultrasound frequencies could propel it along the complex mucosal surfaces of the stomach and intestine.

“Through the strategic use of microbubble configurations and voltage and frequency as ultrasound excitation parameters, we engineered a diverse range of preprogrammed movements and demonstrated their applicability across various robotic platforms,” the researchers write. “Looking ahead, these artificial muscles hold transformative potential across cutting-edge fields such as soft robotics, haptic medical devices and minimally invasive surgery.”

Ahmed says that the team is currently developing soft patches that can conform to biological surfaces for drug delivery inside the bladder. “We are also designing soft, flexible robots that can wrap around a tumour and release drugs directly at the target site,” he tells Physics World. “Basically, we’re creating mobile conformable drug-delivery patches.”

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