A new collision detector that mimics the neurological mechanisms that stops swarming locusts from crashing into each other has been developed by Saptarshi Das at Pennsylvania State University and colleagues. The team’s compact, low-power device could lead to a boost in efficiency for collision detection mechanisms in robots and autonomous vehicles.
Today’s most advanced robots can safely navigate through unfamiliar environments using algorithms that allow them to avoid collisions with surrounding objects. These algorithms can be used for general, non-specific purposes, but this makes them computationally expensive – meaning their hardware requires large energy budgets and spatial footprints. In their study, Das’ team investigated whether navigation could be achieved using more task-specific algorithms.
The researchers turn to the tried-and-tested method of seeking inspiration from nature. In this case, they considered swarms of locusts, which are best known for the widespread devastation they can unleash on crops. The insects fly in dense groups containing millions of individuals, but very rarely collide with each other. This requires individual locusts to carry out complex mathematical calculations in real time, despite their extremely limited brain sizes.
Specialized neuron
Locusts make up for their lack of brain power with a single specialized neuron named the “lobula giant movement detector” (LGMD), which operates using two visual stimuli: the angular sizes and relative angular velocities of approaching insects. The resulting firing frequency of the neuron peaks immediately before collision, driving the locust to change direction.
To mimic this behaviour, Das’ team started from an equation linking the stimuli with the LGMD’s time-varying firing rate. They then incorporated this mathematics into a device containing a molybdenum disulphide monolayer, stacked on top of a programable memory architecture. While the photoconductor increased the device’s current as objects approached, introducing an “excitatory” signal, the architecture underneath decreased its current when no visual stimuli were present – creating an “inhibitory” signal. The signals competed with each other, with the excitatory signal winning out immediately before a collision – creating a signal spike.
Like the LGMD, the team’s device consumes a tiny amount of energy (just a few nanojoules) and occupies a modest spatial footprint of just 1×5 µm. At the same time, it can identify potential collisions from a variety of objects, approaching at a range of different speeds with an efficiency that is lacking in current general-purpose devices.
Das and colleagues now hope to extend the responses of their device beyond head-on collisions, and to incorporate multi-pixel detectors for predicting collisions in 3D. Through these improvements, their technology could be an important step towards safe, affordable autonomous vehicles, and robotics applications including manufacturing and medical surgery.
Task Group 233 provides new guidance for CT performance assessment and addresses the challenges inherent in established CT imaging quality metrics. The Mercury 4.0 Phantom, designed by Dr Ehsan Samei at Duke University and commercialized by Gammex, now Sun Nuclear Corporation, assists with evaluations outlined in TG-233.
During this webinar, Timothy Szczykutowicz, PhD, DABR, of the University of Wisconsin-Madision, Department of Medical Physics, will present on how his department uses the Mercury 4.0 Phantom for common clinical CT tasks. You will hear about how the Mercury 4.0 Phantom addresses advanced features including automatic exposure control and tube current modulation. This webinar will enable you to understand how this new phantom lets the user check patient size for protocol optimization and proper dose management.
Timothy Szczykutowicz is an associate professor in the University of Wisconsin School of Medicine and Public Health Departments of Radiology, Medical Physics and Biomedical Engineering. His clinical and research activities include: optimizing CT scan protocols, monitoring patient dose, developing new metrics to define image quality in the clinical setting, developing protocol management methodologies, fluence field modulated CT, dual energy CT, and radiology department workflow and quality metrics.
Timothy is also the author of the book The CT Handbook: Optimizing protocols for today’s feature-rich scanners. He is an associate/section editor or on the board for multiple journals including: Medical Physics, Radiographics, Contemporary Diagnostic Radiology, and the Journal of Computer Assisted Tomography.
Chosen one: 81 Nobel laureates have voiced their support for Joe Biden in this year’s US presidential election on 3 November. (Courtesy: Michael Stokes/CC BY 2.0)
Over 80 US Nobel laurates have issued an open letter endorsing Democrat presidential candidate Joe Biden in the US election scheduled for 3 November. Biden – the vice-president under Barack Obama from 2009 to 2017 – will go up against president Donald Trump, who is seeking a second four-year term. The signatories of the open letter include 26 physics laureates, 31 medicine and physiology awardees and 24 chemistry Nobel winners.
The letter – signed by 81 laureates who received their Nobel prizes between 1975 and 2019 – focuses on Biden’s attitude to science. “At no time in our nation’s history has there been a greater need for our leaders to appreciate the value of science in formulating public policy,” the letter states. “During his long record of public service, Joe Biden has consistently demonstrated his willingness to listen to experts, his understanding of the value of international collaboration in research, and his respect for the contribution that immigrants make to the intellectual life of our country.”
They recognize the harm being done by ignoring science in public policy
Bill Foster
One of those to sign the letter is Barry Barish, who shared the 2017 physics prize for his contributions to the LIGO detector. “I support Joe Biden because of his long record of making policy, informed by science, to deal with large, complicated issues like cancer, climate change and nuclear proliferation,” Barish, who is at the California Institute of Technology, told CNN, adding that “we absolutely must elect Joe with his science-based approach to successfully lead us out of the COVID-19 pandemic”.
Facts and science
Nobel laureates’ support of Democratic presidential candidates isn’t new. Hillary Clinton received 70 such endorsements in 2016, while former president Barack Obama received the support of 76 in 2008. Carol Greider, who shared the 2009 prize in physiology or medicine for discovering the enzyme telomerase, asserted that elected leaders “should be making decisions based on facts and science,” adding that she “strongly endorses” Biden, in particular because of his “commitment to putting public health professionals, not politicians, back in charge”.
Democratic Representative Bill Foster of Illinois, the only physicist in Congress, organized the open letter saying it would be an “important” development for the Biden campaign. He says that “a core group” of laureates decided on which issues to raise in the letter. Foster, who received the endorsement of 31 laureates when he ran for Congress in 2007, says that when he started calling the laureates to back the intiative, “it was like pushing at an open door”. He adds that “there was a lot of enthusiasm because of the difference [the laureates] perceive in the scientific understanding” between the two candidates.
Foster believes that the letter reflects the view of much of the US scientific community. “They recognize the harm being done by ignoring science in public policy,” he says. “And it’s not only science; it’s logic and integrity. The scientific community wants to get to a situation in which they trust people’s word.” Foster sees the COVID-19 pandemic as a factor in refocusing voters on the importance of science. “The only reason we’re in a position to develop vaccines rapidly is decades of scientific research,” he says. “This may be an opportunity for the scientific community to remind everyone about long-term investment in science.”
Average magnetic forces per unit mass of the AYFFF aromatic peptide and a control non-aromatic peptide, IIIGK, in dissolved, dispersed and assembled states. (Courtesy: Haijun Yang, Feng Zhang and Haiping Fang)
Peptides exhibit surprisingly strong diamagnetism when they join together to form microfibres, say researchers in China. Haijun Yang, at the Chinese Academy of Sciences (CAS) in Shanghai, and colleagues measured the force exerted by peptide-containing liquids placed in a static magnetic field. They found that samples in which the peptides had been allowed to self-assemble had a diamagnetic mass susceptibility 11 times higher than samples in which the peptides were dissolved, and 175 times that of pure water. The unexpected result, reported in Chinese Physics Letters, helps to explain the origin of magnetism in biomolecules, and could have applications in magnetically controlled microfabrication, medical imaging and brain–computer interfaces.
A diverse range of biological structures – from entire cells down to DNA and other subcellular polymers – are known to change their orientation in response to magnetic fields. This effect is behind the ability of some animals to navigate using the Earth’s magnetic field. However, many of the biological structures that respond to such fields apparently contain too little iron for the phenomenon to be explained by either ferromagnetism or ferrimagnetism. This suggests that the magnetic sensitivity of these structures is instead due to more subtle magnetic effects.
In an amino-acid chain called a peptide, for example, an external magnetic field induces a weak secondary field with the opposite direction, which pushes the peptide away. This effect, known as diamagnetism, has been attributed to the alignment of electrons in the peptide bonds between amino acids, or to electron currents flowing around cyclic structures called aromatic rings.
To investigate this phenomenon, Yang and colleagues prepared three different samples of a pentapeptide with the sequence AYFFF. A pentapeptide is a polymer consisting specifically of five amino acid units – in this case, one unit of alanine (A), one of tyrosine (Y) and three of phenylalanine (F).
In the first sample, the researchers dissolved the peptide in the organic solvent dimethyl sulfoxide (DMSO). In the second sample, they dispersed the powdered peptide in water. In the third sample, they also dispersed the powdered peptide in water, but then left it to stand for 16 hours. Over this 16-hour period, the peptides self-assembled into fibres more than 10 µm long.
AFM images of the self-assembled fibres of AYFFF aromatic peptides (left) and fibres of a control non-aromatic peptide IIIGK (right). (Courtesy: Haijun Yang, Feng Zhang and Haiping Fang)
The researchers weighed the samples, and then repeated the measurement in the presence of a magnetic field, which they applied by placing a permanent magnet above the apparatus. They assumed that any difference between measurements with and without the magnet was due to the diamagnetic interaction between the external magnetic field and the magnetic fields induced within the sample.
They found that the peptide dissolved in DMSO exhibited the weakest diamagnetic response, while the sample in which the peptide had been allowed to self-assemble exhibited the strongest. The strength of diamagnetism in the water-dispersed sample was somewhere between the two, which the researchers put down to the occurrence of a limited degree of self-assembly.
When the team performed the same experiment using a different pentapeptide – IIIGK, comprising isoleucine (I), glycine (G) and lysine (K) – they found only a weak diamagnetic response, even for the sample that had been left to self-assemble into fibril structures. Whereas tyrosine and phenylalanine in the AYFFF sequence incorporate aromatic rings in their structures, this is not the case for any of the components of the IIIGK peptide. Yang and colleagues therefore interpret their results as confirmation that the electron dynamics of the aromatic rings, rather than the peptide bonds, are responsible for strong diamagnetism in peptides.
Although the role of aromatic ring currents was not unexpected in itself, the researchers were surprised by how strong the diamagnetism was in the self-assembled peptide samples. They are still investigating the physics underlying the effect, but they do already have an idea of how such anomalously strong diamagnetism might arise.
“Each peptide molecule has an induced magnetic moment in the presence of an applied magnetic field,” says Haiping Fang, of the CAS and East China University of Science and Technology in Shanghai, who led the research. “Thermal forces randomize the orientation of these magnetic moments, weakening the diamagnetism. A group of aromatic peptides in the assembled state – with interactions between them – might reduce the effect of these thermal fluctuations, resulting in the strong diamagnetism.”
Whatever its origin, the researchers foresee several possible applications for the effect. “Peptides with various sequences could be easily assembled into different nanostructures under magnetic fields, widening fabrication strategies,” says Feng Zhang, a collaborator from Guangzhou Medical University. “Assembled peptides modified with biomarkers could also be used as biological tracers, enhancing the contrast between normal and abnormal tissues in magnetic resonance imaging. Or, in novel brain–computer interfaces, the assembled peptides’ strong diamagnetism could be used as a non-invasive sensor to detect weak variations in magnetic signals from brain activity.”
Simulated mountain and valley landscape created by buckling in graphene. Credit: Yuhang Jiang
An international team led by researchers at Rutgers University in the US has found a way to create “flat” electronic bands – that is, electron states in which there is no relationship between the electrons’ energy and velocity – in graphene simply by causing the material to buckle. This new strategy could be used to produce so-called “superlattice” systems that serve as platforms for exploring the collective behaviour of electrons in strongly interacting quantum systems. Such behaviour is known to be linked to high-temperature superconductivity, but a complete understanding is still lacking.
Flat bands are especially interesting for physicists because electrons become “dispersionless” in these bands – that is, their kinetic energy is suppressed. As the electrons slow down almost to a halt, their effective mass approaches infinity, leading to exotic topological phenomena as well as strongly correlated states of matter associated with high-temperature superconductivity, magnetism and other quantum properties of solids.
A fine-tuning challenge
Flat bands are, however, difficult to engineer, and researchers have only observed them in a handful of physical systems. An example is twisted bilayer graphene, which is created by placing two sheets of graphene on top of each other and slightly misaligning them. Under these conditions, the atoms in the graphene sheets form a quasi-periodic moiré pattern with a period that is determined by the relative twist between the sheets’ crystallographic axes, rather than the spacing between individual atoms.
The result is a “superlattice” in which the material’s unit cell (that is, the simple repetition of carbon atoms in its crystal structure) expands to a huge extent – as if the 2D crystal were being stretched 100 times in all directions. This stretching dramatically changes the material’s interactions and properties. Notably, it undergoes a transition from an insulator to a superconductor at a “magic” twist angle of 1.1° and a temperature of 1.7 K.
“Magic angle” graphene has been studied extensively since its discovery in 2018. However, because the “magic” effect disappears at slightly larger or smaller twists, very accurate fine-tuning of the material is required to achieve the desired electronic band structure.
Pseudo-magnetic fields
A team led by Eva Andrei of the Department of Physics and Astronomy at Rutgers has now developed an alternative means of producing flat electronic bands. She and her colleagues began by placing graphene on an atomically flat substrate of niobium diselenide or hexagonal boron nitride. Using scanning tunnelling microscope topography and computer simulations, they found that the graphene sheet buckled when cooled to 4 degrees above absolute zero. This buckling is driven by compressive strain within the graphene sample, which develops when ridges that formed during the sample’s fabrication collapse as it cools.
As the graphene buckles, a “mountain and valley” landscape forms that electrons in the material experience as pseudo-magnetic fields. “These fields are an electronic illusion, but they act as real magnetic fields,” Andrei explains. The result, she says, is a dramatic change in the material’s electronic properties – including the emergence of flat bands.
Unlike earlier realizations of a pseudo-magnetic fields that were mostly local in their extent, the buckling transition observed in this work produces a global change in the electronic structure of graphene, with a sequence of flat bands spread throughout the material.
According to the team, the new technique could thus become a general strategy for creating other superlattice systems and using them to explore interaction phenomena characteristic of flat bands.
The researchers, who report their work in Nature, say they would now like to develop ways of engineering buckled 2D materials with novel electronic and mechanical properties for use in applications such as nanorobotics and quantum computing.
Simulating chemical processes is one of the most promising applications of quantum computers, but problems with noise have prevented nascent quantum systems from outperforming conventional computers on such tasks. Now, researchers at Google have taken a major step towards this goal by using the most powerful quantum computer yet built to successfully implement a protocol for calculating the electronic structure of a molecule. The results may form a blueprint for complex, useful calculations on quantum computers affected by noise.
In October 2019, Google announced to great fanfare that its 53-qubit Sycamore computer had achieved quantum advantage. This means that a quantum computer can solve at least one problem much faster than any conventional supercomputer. However, Google researchers openly acknowledged that the problem Sycamore solved (sampling the outcome of a random quantum circuit) is easy for a quantum computer but difficult for a conventional supercomputer — and had little practical use.
What researchers would really like to do is use quantum computers to solve useful problems more effectively than possible with conventional computers: “Sycamore is extremely programmable and, in principle, you really can run any algorithm on it…In this sense, it’s a universal quantum computer,” explains team member Ryan Babbush of Google Research, “However, there’s a heavy caveat: there’s still noise affecting the device and as a result we’re still limited in the size of circuit we can implement.” Such noise, which results from classical sources such as thermal interference, can destroy the fragile superpositions crucial to quantum computation: “We can implement a completely universal circuit before the noise catches up and eventually destroys the computation,” says Babbush.
Hartree-Fock procedure
In the new research, the team used Sycamore to implement the Hartree-Fock procedure – a well-established method for calculating the electronic structure of molecular systems – and applied it to the isomerization of diazene. This is significantly more complex than previous simulations on quantum computers, increasing the maximum number of qubits used from six to 12.
Each successive qubit brings additional potential for noise: “You need to perform some type of error mitigation,” says Google Research’s Nick Rubin: “The extreme way – and this is something that the Google team is building towards – is to build an error corrected quantum computer, which involves turning a quantum computation into a digital quantum computation and correcting any errors that occur along the way”.
In the absence of this, however, Rubin developed a mathematical error mitigation technique that allowed noise to be identified and discarded. Using this technique and others, Rubin explains, the researchers could “lower the error rates of Sycamore through calibration and then apply algorithmic error mitigation to see the – in this case – chemistry at high fidelity.” Their results matched those from a conventional computer.
More complex simulations
Ironically, the structures predicted by the simple Hartree-Fock procedure for this molecule do not agree with measurements in the lab, but Babbush explains that the “notable deficiencies” of the Hartree-Fock procedure for structure prediction are irrelevant. “We certainly do want to build more complex simulations on top of it,” he says, “but even those will use the sub-routines we’ve developed here as a stepping stone.” Whether or not, with further improvements, it will prove possible to solve classically intractable problems in quantum chemistry on a so-called “noisy intermediate-scale quantum computer” (NISQ) using quantum error mitigation remains unknown: “Error mitigation will only take you so far,” says Babbush. “At some point all you’re going to be getting is noise, so it doesn’t matter whether you can tell whether it’s noise or not. To get past that point, you really need error correction.”
“This work pushes the needle in quantum computing for chemistry,” says quantum chemist and computer scientist Alán Aspuru-Guzik of the University of Toronto in Canada. “It shows in an honest way what quantum computers can do today in a device. Compare this to what they could do a couple of years ago, and the progress is extraordinary. It is also worth saying that there is still a large open space for hardware improvements and clever algorithmic tricks.”
“We’re in this era of NISQ,” says quantum information scientist Barry Sanders at Canada’s University of Calgary. “I appreciate what they’re doing now, which is to say ‘let’s forget about universal quantum computing and let’s just push our technology to answer relevant problems.”
The Moon is a dusty place, and this could be a real problem for future colonists. “Lunar dust sticks to all kinds of surfaces — spacesuits, solar panels, helmets — and it can damage equipment,” explains Xu Wang, who is a research associate in the Laboratory for Atmospheric and Space Physics at Colorado University Boulder.
To solve this problem, Wang and colleagues in Boulder developed an electron gun that could be used to disperse lunar dust. Why not simply use a feather duster? Moon dust is sticky because it acquires electric charge by being bombarded by radiation from the Sun. Firing electrons at the dust particles gives them even more charge, causing the particles to repel each other and disperse.
The team tested their lunar “dust buster” in a vacuum chamber using dust particles similar to those found on the Moon. “It literally jumps off,” says Benjamin Farr, who completed the work as an undergraduate student in physics at Boulder. You can read more about the research in CU Boulder Today.
Folks on Lina Island off the coast of British Columbia have been scratching their heads over a strange pattern of crushed seashells that has appeared on a local beach (see above figure). The white shells form a rectangular lattice on the beach and local councillor Billy Yovanovich says that the pattern is a natural phenomenon. However, government scientist Richard Thomson disagrees and says that the pattern was made by humans – possibly as a prank.
So, is this a practical joke, or an example of an emergent phenomenon driven by the action of waves and currents? I’m no expert, but I’m with Yovanovich. You can read more about these patterns on the CBC website.
In 1977 the Nobel laureate Leon Lederman published a tongue-in-cheek proposal to build a collider using existing subway tunnels in New York City. The city was suffering a financial crisis and Lederman reckoned physicists could acquire the tunnels for a knock-down price.
Hot political issue
Lederman’s proposal has inspired Caltech physicist David Hitlin to propose building another collider to address a hot political issue of today – building a wall on the US–Mexican border. In “The Very Big ILC”, Hitlin describes how long, straight sections of the border between the states of Sonora and Arizona could blocked by a huge linear particle collider.
Hitlin’s collider would be 300 km long and could achieve a centre-of-mass energy of 5 TeV. In contrast the proposed International Linear Collider in Japan is a mere 31 km long with an initial energy of 250 GeV. What’s more, with the addition of a bit or razor wire on top, Hitlin says the structure would meet Donald Trump’s specifications for a border wall.
And what would Hitlin call the facility? The TrumpILC, of course.
Big science, it seems, is often about the small details – and doubly so when it comes to the ultrahigh-vacuum (UHV) and extreme-high-vacuum (XHV) systems that play a core enabling role in large-scale research facilities such as the Large Hadron Collider (LHC) at CERN, the European Spallation Source (ESS) in Sweden, and the ITER nuclear fusion reactor in France.
Achieving and maintaining UHV/XHV conditions at scale – broadly the pressure regime from 10−7 mbar through 10−12 mbar and lower – is a complex engineering challenge that would simply not be possible without the online, real-time diagnostic capabilities of compact and robust quadrupole mass spectrometers known as residual gas analysers (RGAs).
These workhorse instruments effectively “police” the UHV/XHV environment at a granular level – ensuring safe and reliable operation of large-scale research facilities by monitoring vacuum quality (detecting impurities at the sub-ppm level), providing in-situ leak detection and checking the integrity of vacuum seals and feed-throughs.
“We have RGAs deployed at all these big-science sites and more,” says Peter Hatton, managing director of Hiden. “Our instruments are used not only for routine UHV/XHV monitoring, but also to support the advanced research projects that underpin all large-scale science facilities – whether that’s surface analysis via secondary-ion mass spectrometry, UHV thermally programmed desorption studies or all manner of gas analysis applications.”
Peter Hatton: “We listen and learn from all of our customers.” (Courtesy: Hiden Analytical)
Hiden, for its part, has more than 35 years experience as a supplier of application-specific quadrupole mass spectrometers, including RGAs. As such, the company’s in-house manufacturing model combines state-of-the-art cleaning, metrology and assembly techniques with the firmware and software needed to give its analysers the sensitivity, stability and dynamic range for diverse research and industry applications.
“The collaborative nature of our business is a big differentiator,” Hatton explains. “We listen and learn from all our customers, who gain from having personal support from the engineers directly involved in the development, manufacture and test of their product.”
A case study in this regard is the National Synchrotron Light Source II (NSLS-II) at BNL in Upton, New York. Hiden was selected as a preferred supplier for NSLS-II in 2011 after extensive evaluation of its RGA product line for UHV/XHV applications – specifically the HAL 201 RC, which offers a minimum detectable partial pressure of 5×10−14 mbar. Since then, it’s been a productive relationship in terms of sales and product innovation. For starters, the scale and complexity of projects under way at NSLS-II necessitate a networked vacuum diagnostics capability and, all told, there are now more than 100 Hiden RGAs integrated with the laboratory’s central control systems via EPICS software drivers.
“Supplying projects like NSLS-II also requires full cognisance of some pretty harsh operating environments,” adds Hatton. “With this in mind, we have developed a ‘radiation-hard’ RGA (the HAL 101X) that can operate with no smart electronics within 100 m of the analyser location – a tough ask given that everything is micro-controlled these days.”
Collaboration equals innovation
In Europe, meanwhile, Hiden’s eagerness to learn from its customers is equally prominent – perhaps most notably CERN’s vacuum, surfaces and coatings group. With operational responsibility for the particle physics laboratory’s extensive vacuum infrastructure, this team of more than 60 scientists and engineers also manages a network of 200+ RGAs across the CERN site in Geneva – approximately a quarter of those analysers being supplied by Hiden.
There are three main applications for RGAs at CERN: commissioning of UHV/XHV systems in the laboratory’s particle accelerators and detectors – monitoring of possible contamination or leaks, for example, between experimental runs of the LHC; pass/fail acceptance testing of vacuum components and subsystems – collimators, magnets, pumps and the like – prior to deployment in the accelerators and detectors; and a range of offline R&D activities, including low-temperature UHV/XHV characterization and desorption studies of advanced engineering materials.
“What we appreciate from Hiden is their responsiveness – we always get a quick answer on any after-sales issues regarding hardware or software,” explains Sophie Meunier, senior vacuum engineer with responsibility for RGA technologies at CERN. “They know their products inside out,” she adds, “because they handle all aspects of the manufacturing and software development in-house.”
That forensic product know-how and attention to detail proved to be essential in addressing CERN’s stringent outgassing requirements for its UHV/XHV systems – and in particular the hydrogen outgassing rate of the RGA ion source (which must be less than 1×10−8 mbar·l/s two hours after switch-on). “The outgassing rate of the ion source is a critical success factor in RGAs destined for UHV/XHV applications,” explains Meunier. “In simple terms, we want to measure the partial pressure of our UHV/XHV systems – not the outgassing of the RGA ion source.”
Achieving this figure of merit – and delivering an ion-source solution that meets CERN’s RGA specifications for the long term – was very much a collaborative endeavour between customer and vendor. The joint testing and optimization effort addressed the ion-source components, enhanced source geometries and evaluation of materials compatible with vacuum-firing to 900 °C. All of which ultimately enabled Hiden to implement its own custom manufacturing set-up, pretreating RGAs with specialist cleaning, vacuum-firing and bakeout procedures prior to deployment at CERN.
That customer-centric approach also informs Hiden’s software development. Consider the RGA user interface and data visualization. Meunier and her colleagues at CERN have a requirement for the laboratory’s RGAs to provide a read-out of ion current as the primary measurand (rather than pressure, which requires a conversion factor). “When we asked, Hiden delivered, incorporating our request into the latest version of its RGA software MASsoft Professional,” Meunier notes. What’s more, MASsoft provides additional flexibility for big-science end-users by allowing instrument control via USB 2.0, RS232 or Ethernet data protocols.
Hardware and software innovation notwithstanding, Hiden’s RGAs must also measure up against another unforgiving benchmark – reliability – if they are to enable big-science facilities to minimize vacuum downtime and ultimately reduce their operating costs. “Reliability and longevity are non-negotiable,” Hatton concludes. “That’s why, as well as a three-year warranty, all our products are supported by a lifetime application support guarantee. Worth noting also that we continue to support the first instruments that we manufactured over 35 years ago.”
Small details, it seems, really do go a long way in big science.
Academics are often derided for their lack of entrepreneurial skills. Partly that’s because the curricula and training for undergraduate and postgraduate degrees are generally designed for those continuing in academia. Most students, however, prefer to explore other, non-academic career paths, in which the learning curve can be steep. Even students who do PhDs with an industry focus, for example at the UK’s centres for doctoral training, will face unusual challenges.
With such limited exposure outside the academic bubble, what else can be done for students who are interested in what industry may have to offer? What opportunities are there for students to meet and talk with people from industry and other backgrounds? One exciting way to address such issues, I’ve discovered, is for institutions to run “hackathons”. These were traditionally software-based challenges in which small teams of computer programmers and software developers created software. Those kinds of hackathons are still going strong, but they are now beginning to be used elsewhere with broader remits.
These hackathons usually run non-stop over a couple of days and can bring together people from a variety of backgrounds including science, arts, business and design to form interdisciplinary teams. In exposing researchers to an entrepreneurial, commercial and business environment in a very short space of time, they allow scientists to apply the skills they have developed during their degree in a different environment. Hackathons also highlight the importance of teamwork, resilience and communication skills.
Late last year, a group of PhD students from the University of Manchester hosted the first Graphene Hackathon at the Graphene Engineering Innovation Centre. It was a 24-hour event where 10 interdisciplinary teams, each of between four and six people, designed, prototyped and pitched a commercial product using conductive graphene inks in front of a panel for the chance to win investment and cash prizes. The event required not only prototyping a technology that was worthy of investment but also developing business cases to outline the value of the products.
In developing the graphene-ink products, the teams faced some unexpected challenges including malfunctioning Raspberry Pis, screen-printing problems and flimsy final prototypes. During the event, industry experts such as strategy consultants, business development managers and patent attorneys were on hand to advise the teams as they worked throughout the night.
The hackathon was a fantastic way for participants to apply what they had learnt and put it into practice. I was involved with a team that created “BackUP” – an array of thin graphene strain sensors that can be printed onto a fabric seat cover for lorry, bus and truck drivers. It worked by monitoring the pressure on different parts of the seat in real time to indicate bad posture. If a driver was leaning on one side, for example, then it would send real-time feedback to remind them to improve their posture. The product, which came second in the competition, was designed to increase the comfort and wellbeing of drivers and reduce the number of days they are forced to take off work due to debilitating back pain.
Innovation and skills
Events like the Graphene Hackathon foster innovation by challenging participants in a competitive environment, boosting the likelihood of conceptualizing potentially disrupting technologies. For me, the experience highlighted the importance of a “fail-fast” approach that differs from the slower pace of academic research in which projects often run for months and even years. Fail-fast is often used as a mantra within start-ups as it highlights the importance of determining the long-term viability of a product or strategy. If something is predicted to fail, it’s important to turn to a new idea without wasting more precious time and resources.
Indeed, the experience allowed me to apply the skills I developed from my physics degree to a commercial setting and made me realize the importance of thinking about fundamental research with a broader horizon. PhD students are in a unique place to develop their research and find commercial avenues for its applications. Hackathons can help widen the perspectives of participants, especially scientists who are looking to start spin-out companies. The skills needed to build a successful business are not too dissimilar from the attributes needed to become a successful scientist as both stand on the foundations of perseverance, problem solving and presentation skills.
I believe hackathons could be run in many other areas of research such as energy harvesting from renewable resources, applications using recycled materials, and waste recovery. A hackathon that marries software and hardware is a particularly innovative way for early-career scientists who want to break out into industry-based roles to gain valuable first-hand experience in an emulated start-up environment. Here’s to more hacks in the future.
Researchers in Vietnam have developed a transparent nanostructure with anti-icing properties that could keep objects such as aircraft wings and wind turbines ice-free in cold, damp conditions. The material, which is inspired by the structure of moth eyes, consists of a quartz substrate coated with a monolayer of nano-sized polystyrene beads. The ensemble is then covered with a flat, insulating layer of paraffin.
On cold days and at high altitudes, water vapour in the air transforms directly into solid ice, forming a thin coating on exposed surfaces. This coating reduces the lift of aircraft wings, blocks moving parts in ships and turbines, and sometimes causes serious motor vehicle accidents as well as damage to infrastructure such as electricity transmission systems.
There are two main approaches to improving the anti-icing properties of surfaces in these conditions. The first, active approach is to remove the ice using an external source of energy, such as heat. The second, passive approach uses physiochemical methods to modify the surface – with superhydrophobic materials, for example – so that it repels water.
SLIPs: an advanced anti-icing strategy
More recently, a new variant of the passive strategy has emerged: applying a coating to icing-prone objects that forms a defect-free liquid interface with the ice. Such coatings are known as slippery liquid-infused porous surfaces (SLIPs), and one way of making them is to cover a porous structure with a low-surface-tension lubricant that is immiscible in water, resists humidity and self-heals after ice treatment.
While the SLIPS studied to date have produced some good anti-icing results, none of them can prevent icing permanently because their lubricant layer degrades through evaporation and during de-icing. Physicists Nguyen Ba Duc of Tan Trao University and Nguyen Thanh Binh of Thai Nguyen University of Education sought to avoid this problem by creating a SLIP based on a nanostructure that mimics the structure of moth eyes, which are inherently ice-phobic.
In their experiments, Ba Duc and Thanh Binh used a plasma etching process to deposit polystyrene nanobeads onto a quartz substrate. This process produced a uniform structure of protrusions shaped like truncated cones with heights of 500 nm and top diameters of around 70 nm, as revealed in scanning electron microscopy measurements. The researchers then added paraffin wax to an n-hexane solution and coated the top of their nanostructure with the mixture. As a control experiment, they also applied the same thickness of paraffin wax/n-hexane coating to a bare quartz substrate.
Measuring adhesion forces
Next, the researchers attached their samples to a thermoelectric cooling module and gently placed a 5 μl droplet of deionized water onto the sample surface. After cooling the system down to -20°C, they used a load cell to measure how strongly an ice drop adhered to the freezing surface. They did this by moving the cell at a speed of 50 μm/s, which slowly pushed the ice droplet sideways until it detached completely. The force exerted on the cell could then be computed, and the researchers took the maximum force recorded to be the droplet’s adhesive strength.
Ba Duc and Thanh Binh also used a high-speed camera to record the icing process and determine the time it took for the entire water droplet to freeze solid. Another camera monitored changes to the interface between the water droplet and the surface. Finally, the researchers performed a “freezing rain” test in which they sprayed cold water droplets (maintained at temperatures of 0.5°C) ranging from 5 μl to 50 μl in size onto surfaces at 0°C, -5°C, -10°C and -15°C.
The results for the nanostructured surface confirmed its outstanding anti-icing performance relative to the control surface. The researchers also say that the hydrophobic nature of the paraffin layer proved key to the performance of the new structure in both the static (water droplet) and dynamic (freezing rain) experiments.
Delayed heat transfer
The researchers chose paraffin as their coating material because it is water-repellent and has a low thermal conductivity. When the paraffin coats the top of the nanostructured quartz substrate, the substrate becomes isolated from its environment, preventing heat from being transferred away. Air pockets trapped inside the nanostructure contribute to delayed heat transfer too, Ba Duc and Thanh Binh explain, adding that this extra insulation also increases the freezing time of any attached water droplets.
As well as anti-icing applications in industry and transport, the superhydrophobic nanostructured coated paraffin material might be suitable for applications such as eye glasses, Ba Duc says. This is because it is highly transparent and has anti-reflective properties, just like moth eyes. The researchers also report that the material is mechanically stable, and the paraffin-coated layer can easily be recovered after tests simply by heating it.
The new anti-icing structure is detailed in AIP Advances.
Task Group 233 provides new guidance for CT performance assessment and addresses the challenges inherent in established CT imaging quality metrics. The Mercury 4.0 Phantom, designed by Dr Ehsan Samei at Duke University and commercialized by Gammex, now Sun Nuclear Corporation, assists with evaluations outlined in TG-233.
