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Sir Martin Wood: the supercool thinker who founded Oxford Instruments

It all started in a garden shed in Northmoor Road, Oxford, in 1959. That was where Martin Wood and his wife Audrey set up a company to build superconducting magnets for use in scientific research. At the time, Wood was based in the Clarendon Laboratory at the University of Oxford, where the concept of a spin out was unheard of. But Oxford Instruments proved to be a staggering success and, in 1983, became the first Oxford spin out to be listed on the London Stock Exchange.

These days the company is a hugely profitable FTSE 250 business with global revenues of over £300m, most of which come from exports, and a market capitalization of £1.2bn. Historically best known for its magnetic resonance imaging (MRI) scanners, Oxford Instruments now builds, rents, sells and services a range of hi-tech tools across a wide range of applications. Its technology stretches from X-rays and plasma equipment to microscopy and nanoscience.

I got introduced to the company’s remarkable story by Jonathan Flint, a former president of the Institute of Physics who was chief executive of Oxford Instruments from 2005 until 2016. As he explained, Wood set up the firm while working as a senior research officer at the Clarendon lab (a position he held from 1955 to 1969). His job was to manage its high-magnetic-field facility, designing and making powerful electromagnets that his boss – the Hungarian émigré scientist Nicholas Kurti – and his colleagues wanted for their research.

Martin Wood’s electromagnets proved so popular that when students from the Clarendon left for other jobs, they would ask him to make magnets for their new labs

Wood found he could generate these electromagnets using superconducting materials operating at a few degrees above absolute zero. Indeed, they proved so popular that when students from the Clarendon left for other jobs, they would ask Wood to make magnets for their new labs. Realising this was an opportunity to go into business, he sought approval from Kurti, who fortunately gave his full backing to what was then regarded as a most unusual request.

Wood built the magnets in his garden shed, which years later moved to the grounds of his family’s new home in recognition of the pivotal role it played in the development of superconducting magnets. As noted in his obituary in the Guardian, starting a company was the realization of Wood’s long-held ambition to create a productive and rewarding working environment. Audrey covered the finance and people issues, while Martin concentrated on technical and customer aspects.

A different culture

As well as being pioneers in the commercialization of university research, Audrey and Martin Wood always adopted an unusually positive culture toward staff. It was a pioneering approach that many ex-Oxford Instruments people speak fondly of and carry forward in their professional lives. Flint himself told me how he was invited to the Woods’ home during the selection process for the top job at Oxford Instruments.

“The visit was completely unlike any executive selection I had been involved in before,” Flint recalls. “Martin and I had a wide-ranging discussion on topics from the natural world to the potential of the then embryonic field of quantum computing. By the end of the afternoon, I was enthralled by Martin as a person and quite forgot I was in a job interview.”

Claire Flint, a former group human-resources director at Oxford Instruments, has similarly positive recollections. “Sir Martin instinctively understood that engaging the whole workforce in shared endeavour was right for the people and the organization,” she says. “More than 50 years on, his ethos is still a core part of what makes the company commercially successful and a special place to be a part of.”

Oxford Instruments grew rapidly, becoming a global leader in designing and making superconducting magnets. Its products made it possible for people like the Nottingham University physicist (and future Nobel laureate) Peter Mansfield to image the body using MRI. Indeed, the company supplied superconducting magnets designed by Wood for the first whole-body MRI scanners in 1980.

As time went by, Martin and Audrey moved into philanthropy, supporting business start-ups, scientific innovation, young people and the natural environment

As time went by, Martin and Audrey moved into philanthropy, supporting business start-ups, scientific innovation, young people and the natural environment. Wood, however, kept a substantial shareholding in Oxford Instruments even after delegating the day-to-day running of the organization. And although the business was a financial success, it was always the science and people of Oxford Instruments that really interested him.

Nurturing minds

Aware of the challenges facing fledgling companies, in 1985 the Woods set up the Oxford Trust, buying an old builders’ yard in the city the following year. It became home to the Science and Technology Enterprise Project – the first innovation centre in the region and a catalyst for Oxfordshire’s now-flourishing ecosystem of innovation incubators and science parks. These days the trust runs the Wood Centre for Innovation and the Oxford Centre for Innovation, which provides work space for 40 science and tech start-ups.

Speaking shortly after Sir Martin’s death on 23 November 2021, Steve Burgess – chief executive of the Oxford Trust – paid tribute to Wood’s passion for innovation and physics, which saw him support new tech firms at a time when no-one else had the vision to do this. “With Audrey always at his side, the duo made an incredible impact on today’s entrepreneurial landscape and science education.”

Over the last 30 years, the Oxford Trust has supported hundreds of businesses including Quantum Dice, which last year won a business start-up award from the Institute of Physics. Sir Martin proved not only that high-technology start-ups can thrive in the UK, but also that they can grow into billion-pound businesses – without losing touch with the people and the science that made them possible.

Machine learning predicts when background noise impairs hearing

Machine learning algorithms could one day be used to improve speech recognition in hearing-impaired people, researchers in Germany have shown. Using a novel algorithm, Jana Roßbach and colleagues at Carl von Ossietzky University could accurately predict when people with both normal hearing, and those with different levels of hearing impairment would mishear over 50% of words in a variety of noisy environments – an important test of hearing-aid efficacy.

The lives of many hearing-impaired people have been significantly improved by hearing aid algorithms, which digitize and process sounds before delivering an amplified version into the ear. A key challenge still faced by this technology is improving the devices’ ability to differentiate between human speech and background noise – something that is done using digital signal-processing algorithms.

Researchers often use listening experiments to evaluate the ability of hearing aid algorithms to recognize speech. The aim of these tests is to determine the level of noise at which hearing aid users will recognize only half of the words spoken to them. However, this approach is expensive and time consuming and cannot easily be adapted to account for different acoustic environments, or for users with different levels of hearing loss.

Deep machine learning

In their study, Roßbach’s team used a human speech recognition model based on deep machine learning, which uses multiple layers to extract higher-level features from raw input data. When combined with conventional amplitude-enhancing algorithms, the model could be used to extract phonemes – these are the units of sound that form the building blocks of words.

To train their algorithm, the researchers used recordings of random basic sentences, produced by ten male and ten female speakers. They then masked this speech using eight possible noise signals, which included a simple constant noise and another person talking over the speaker. The team also degraded the recordings to different degrees, to mimic how they would sound to people with different levels of hearing impairment.

Noise threshold

Afterwards, Roßbach and colleagues played the masked recordings to participants with both normal hearing, and those with different degrees of age-related hearing loss. After asking the participants to write down the words they heard, they could then determine the threshold of noise that caused each listener to mishear over 50% of the words. As the team hoped, the responses of participants with different hearing abilities closely matched the predictions of the machine learning model, to within an error of just 2 dB.

Car passengers could soon listen to personalized audio using a new acoustic algorithm

Photograph of the acoustics testing system in a car

The researchers still face several challenges before their algorithm can be used to improve practical hearing aids. For now, the technology cannot be used to identify which words were spoken in the speech it interprets as being misheard. This means it cannot accurately reconstruct the correct phonemes within the amplified sounds produced by hearing aids.

In their future research, the researchers will adapt their technique to maximize the intelligibility of speech for any hearing-impaired person. If successful, their approach could eventually be implemented in hearing aids which are tailored to the needs of specific users.

The research is described in The Journal of the Acoustical Society of America.

Physics of cooking perfect pasta, plant-inspired actuator cracks bricks

For some reason physicists love pasta – and I don’t mean eating it, the physics of pasta is something that seems to fascinates scientist. So much so, that in 2014 two physicists at the UK’s University of Warwick invented a new type of pasta they called anelloni, which has a large ring shape. You can find a link to a recipe for anelloni and learn why it was inspired by polymer physics here: “A taste for anelloni”.

Anelloni is a fresh pasta, so it is easy to cook – just 3–5 min in boiling water is all it takes. With dry pasta, however, it can be much more difficult to gauge when pasta is ready. But the days of crunchy or gloopy pasta could soon be over thanks to a team of mechanical engineers at University of Illinois at Urbana-Champaign.

Sameh Tawfick and colleagues studied how pasta swells, softens, and becomes sticky as it takes up water. They measured parameters such as expansion, bending rigidity, and water content and this allowed them to develop a theoretical model of the swelling dynamics of starchy materials. His team normally studies how deformable materials such as hairs interact with fluids, and they realized that pasta provided a good opportunity to further their knowledge. The fact that many of them were working at home during the pandemic also pointed them towards pasta.

Salt matters

One thing the team found is that the amount of salt added to the water had a significant impact on how long it took the pasta to cook. This could explain why some people struggle to produce perfect pasta despite following the instructions on the packet.

The team also made some important observations about how pasta changes as it cooks – observations that could be very useful for budding chefs.

To study how cooked noodles interact with each other, they observed what happens when pasta is lifted out of boiling water. They found that the liquid surface energy creates a meniscus that sticks noodles together. The is opposed by elastic resistance from bending the noodles, but aided by the adhesion energy from the surface tension of the liquid.

Stick test

Not surprisingly, the degree to which the pasta stuck together increased with cooking time. They conclude that by observing what percentage of two strands of spaghetti stick to each other, a chef could work out if their pasta is cooked to perfection (see figure).

The team also found that as spaghetti cooks its length expands 3.5 times more than its girth. This could explain why I always seem to not put enough water in the pan when I cook pasta. As a result, measuring the increase in length of a noodle as it is cooked would be another way of getting consistent results when making pasta.

You can find out more about their research in: “Swelling, softening, and elastocapillary adhesion of cooked pasta”, which is free to read in AIP Physics Of Fluids.

Super seedlings

We put a new patio in a few years ago and ever since we have been busy pulling out little plants that sprout up from the mortar between slabs. After a seed gets into a tiny gap in the mortar, the delicate-looking seedling manages to crack and move the much harder material so that the plant can grow.

Inspired by this annoying phenomenon, Hyeonuk Na and colleagues at Seoul National University have created a hydrogel actuator that can crack bricks. Plants can grow through mortar thanks to turgor pressure – which is osmosis-driven hydrostatic pressure confined within a plant cell’s walls. Na and colleagues wrapped a hydrogel in a stiff yet flexible semipermeable membrane. This membrane controlled and confined the osmotic swelling of the hydrogel. This resulted in an actuation force of about 730 N, which is 1000 times greater than that achieved by existing hydrogel actuators. This was enough force for the device to be used to break a brick.

You can read more about the actuator in Science.

Measuring gravity outdoors using a quantum gas, breakthroughs in materials processing and particle physics

In this episode of the Physics World Weekly podcast, four physicists at the University of Birmingham explain how they used two clouds of ultracold atoms as a portable gravity sensor. Their device was able to locate a small tunnel on the university campus and can be used outdoors – and impressive feat because the atoms were held in ultrahigh vacuum and millikelvin temperatures.

Also this week, Physics World editors chat about recent breakthroughs in physics including the first mass-produced silicon spin qubits and a surprisingly heavy W boson.

Quantum measurement splits information three ways

A strange feature of quantum systems is that observing them inherently changes their quantum state. More precisely, the act of measurement redistributes the information contained in a quantum system. Now, physicists in South Korea have refined this idea further, experimentally demonstrating a three-way information split in quantum measurements. The result could have applications in understanding information flow during measurements and optimizing protocols for quantum information processing.

Theorists had previously shown that during measurement, information encoded in a quantum state becomes split between the measurer, the measured state, and information that can be recovered. The measurer’s information is known as extracted information, since this is the information they gain by measuring the system. The information left in the measured state is known as transmitted (undisturbed) information. Finally, there is some chance of recovering the system’s original quantum state by performing a reverse operation on the measured system. The maximum probability of restoring the state is known as the reversible information.

The magnitudes of the three types of information vary depending on the type of quantum measurement being performed. For instance, a weaker measurement gives the measurer less information (less extracted information), leaving more of it in the measured state (more transmitted information) and making it less probable that the original state will be recovered (less reversible information). The best balance of the three will depend on the purpose of the measurement.

Pie chart showing extracted, transmitted and reversible information — No loss: In optimal measurements, all the quantum information is split between the extracted (G), transmitted (F) and reversible (R) information. (Courtesy: Seongjin Hong et al. Phys. Rev. Lett. 128, 050401. Reused with permission.)

Types of measurements can be further distinguished by how the sum of the three types of information compares to the information in the quantum state. Whereas optimal measurements preserve the total information in the quantum state, such that it is entirely split between the three types, in non-optimal measurements some information is lost. This lost information can be due to noise in the experiment or inefficient estimates of the original quantum state. Yet sometimes it is inherent in the quantum measurement itself. Such inescapable information loss in non-optimal measurements could give insights into how the classical world appears to emerge from quantum measurements.

Preserving three-way information using photons

In their experimental study, which is published in Physical Review Letters, Seongjin Hong and colleagues at the Korea Institute of Science and Technology and the Korea Institute for Advanced Study showed how the information about a quantum state splits into these three parts. The researchers used photons to experimentally demonstrate information-preserving optimal measurements in which each photon could be in one of three possible states. They then used optical components to perform measurement and reversing operations on the photons, before characterizing their final states and demonstrating the quantitative balance between the three information types.

“The conditions for optimal measurements provide a useful guide for an optimal design of measurement-based quantum information processing protocols”, corresponding authors Seung-Woo Lee and Hyang-Tag Lim tell Physics World. For instance, to discriminate or estimate quantum states, the best strategy is to maximize information gained by the measurement and to minimize disturbance of the state. Alternatively, for tasks where it is important to reverse the measurement, such as quantum teleportation or quantum error correction, the reversibility should be maximized and information gain minimized.

Lee and Lim say the team is now planning further studies of information loss in quantum measurement. They hope to tease out how this loss relates to the transition between the classical and quantum worlds. The results could also have interesting links to the second law of thermodynamics, which describes how irreversibility emerges over time. “One of our inequalities implies that the disturbance in quantum measurement never decreases by any subsequent reversing operation,” Lee and Lim explain, adding that the implied increase in disturbance is “intuitively plausible by the second law of thermodynamics”.

LASER shines on in Munich

One of the world’s leading trade fairs to be devoted to all types of lasers and photonic technologies will once again fill the cavernous halls of Messe München in Germany. LASER World of PHOTONICS, which will take place on the rescheduled dates of 26–29 April 2022, will bring together more than 800 exhibitors to showcase the latest innovations in both industrial systems and scientific equipment.

Key industry sectors to be featured at the exhibition range from industrial manufacturing and quality control through to biophotonics and information processing. Parts of the main exhibition will be focused on sensors and measurement, and illumination and energy, while for the first time there will also be a dedicated World of QUANTUM event.

With the last event in the series taking place three years ago, there will be plenty of new innovations for delegates and exhibitors to discuss. A dedicated start-up pavilion will also enable newly formed companies to present their novel laser and photonics solutions to an international audience of industry insiders. Read on to find out more about some of the companies and product innovations that will be featured at the show.

Spectrometer combines speed with sensitivity

Ocean Insight will be debuting the all-new SR2 spectrometer, which combines high-speed spectral acquisition with best-in-class signal-to-noise ratio (SNR) performance. The Ocean SR2 spectrometer is ideally suited for applications such as laser characterization, plasma monitoring and absorbance measurements, which benefit from the excellent SNR (380:1) offered by the instrument. Combined with high speed – with integration times as low as 10 µs – the system can be used for many different applications without the trade-offs typical of comparable spectrometers.

The fully configurable spectrometer is produced using industry-leading manufacturing techniques, ensuring excellent thermal stability and minimal unit-to-unit variation. Pre-configured models are available with entrance-slit widths ranging from 5 to 200 µm, providing users with a range of options for optical resolution (FWHM) and signal throughput to meet the requirements of different experiments.

The Ocean SR2 spectrometer is compact and versatile, and is compatible with Ocean Insight’s range of light sources, accessories and software to enable users to configure their set-ups for different applications. Each SR2 instrument is supplied with OceanDirect, a powerful, cross-platform Software Developers Kit (SDK) that allows users to optimize spectrometer performance and access critical data for analysis. The software includes an Application Programming Interface (API) to offer maximum flexibility, while the SR2 is also compatible with OceanView, Ocean Insight’s powerful desktop spectroscopy application.

Find out more about Ocean Insights’ full range of spectrometers and measurement solutions at booth 421 in Hall A6.

Timing generator ensures precise synchronization

EKSMA Optics is expanding its electro-optics and laser electronics product group and production capacity, with a move at the end of 2021 to a new facility with even more cleanroom space. At LASER World of PHOTONICS the company will be showcasing its experience in the design of electro-optic devices, ranging from a comprehensive selection of Pockels cells to complete laser-pulse picking systems. EKSMA’s continuing innovation aims to integrate different technologies into easy-to-use modulation and control instruments for laser applications.

Keeping step: The TG10 timing generator from EKSMA Optics offers precise synchronization for laser systems and components. (Courtesy: EKSMA Optics)

One of the new additions is the timing generator TG10, designed to synchronize laser systems with other laser components such as detectors, laser-pulse pickers, and drivers for Pockels cells, laser diodes and flash lamps. The TG10 can create up to eight delayed output sequences precisely synchronized to its ultrastable internal or external clock. The TG10 also features a precise trigger output with an exceptionally low jitter of 3–5 ps, making it an ideal choice for high-speed acquisition systems such as streak-camera triggering.

EKSMA Optics will also present its uniLDD series of universal laser diode drivers, which are highly customizable and designed for easy OEM integration. At its core, the uniLDD is a DC input power converter that can supply a continuous current of up to 100 A or 360 A in pulsed, quasi-continuous wave mode, and it is compatible with single emitters, bars, stacked laser diodes and high-power VCSELs in constant current mode. These highly versatile devices are based on digital signal-processing technology and can be adapted for different laser diodes and modes of operation based on customers’ requirements.

See EKSMA Optics’ full range of electro-optics and laser electronics products at Hall H5, booth number 353.

Femtosecond fibre lasers open up ultrafast applications

The acquisition of VALO Innovations by HÜBNER Photonics at the end of 2021 has added short-pulse femtosecond fibre lasers to its already diverse technology portfolio, which includes compact single-frequency CW lasers, diode-laser modules and nanosecond pulsed lasers across the full UV, visible and near-IR spectrum.

The fibre-laser technology developed by VALO Innovations offer market-leading short-pulse performance, with pulse lengths of less than 50 fs and peak powers above 2 MW from a compact and stable turn-key system. Combined with computer-controlled compensation for dispersion and other nonlinear effects, these ultrashort and ultrafast femtosecond fibre lasers will help new applications in bioimaging, spectroscopy and optogenetics.

“Ultrafast lasers represent a natural complement to the HÜBNER Photonics portfolio and VALO Innovations provides the ideal vehicle to fast-track that ambition,” comments Oliver Prochnow, CEO of VALO Innovations. “For the VALO Innovations team, meanwhile, we are now positioned to develop and scale our femtosecond fibre-laser offering within an established innovation and manufacturing ecosystem.”

Key applications for VALO’s fibre-laser technology include multiphoton microscopy for studying complex and dynamic biological processes deep within living tissue, optogenetics for controlling the activity of neurons or other cells using light, and amplifier seeding – in which femtosecond pulses can increase the energy of selected laser pulses by several orders of magnitude. Integrating the short-pulse sources into multiphoton microscopy or spectroscopy systems can yield a significantly higher peak power, which Prochnow says enables “greater signal efficiency, enhanced penetration depth in tissue, better contrast and reduced photothermal damage”.

HÜBNER Photonics will be presenting its full technology portfolio at booth 421 in Hall B5.

Quantum approximate optimization algorithm can be implemented using Rydberg atoms

Quantum computers are often discussed as a technology of the future, but many devices exist already. Because there is no consensus on a single, universal quantum computer design, however, determining the best use for each existing device can be daunting. Recently, researchers at the University of Innsbruck in Austria started to address part of that question by proposing a new way to implement a quantum optimization algorithm by using extremely cold atoms. Their theoretical work could point towards an efficient way of using the strengths of existing quantum computation devices to tackle practical problems in logistics, the energy sector and finance in the near future.

The Innsbruck work centres on the quantum approximate optimization algorithm (QAOA), which recasts optimization in terms of minimizing the energy of a physical system of atoms. For example, instead of trying to find the best way to balance the electric grid, physicists can tackle the equivalent issue of determining the lowest energy assumed by some system of atoms that all interact with each other. Here, the details of the original problem are encoded into specific interatomic interactions.

Controlling those interactions, often between atoms that are far away from each other, is the big experimental challenge for this approach, explains Wolfgang Lechner, Innsbruck physicist and the co-author of a paper describing the new study. “In order to implement an optimization problem on a quantum simulation device one physically has to build these interactions, which is often nearly impossible,” he says. “The original motivation for our work was to reduce everything to local interaction. This opens a plethora of possibilities.”

Mathematical map

The new scheme proposed by Lechner and colleagues relies on a mathematical map that translates the optimization procedure onto an experiment in a way that requires exact calibration of interactions between nearby atoms only. In their study, they modelled how this could be implemented in a system of electrically neutral atoms caught in optical tweezers (held in place by laser beams) and Rydberg atoms, which are more energetic and larger than other atoms. Such a laboratory setup is readily available in many of the world’s research universities and even some commercial startups.

“There has been an outburst of platforms using Rydberg atoms for quantum computing in recent years,” notes Jiri Minar, a physicist at the University of Amsterdam in the Netherlands, who was not part of the study. Optical tweezers let physicists create arbitrary arrangements of atoms in space, he explains, and there are standard experimental procedures for controlling strong interactions between Rydberg atoms. In the Innsbruck team’s model, laser pulses lasting less than a microsecond are used to simultaneously set interactions between four quantum bits (qubits) made of these atoms. Minar says that this experimental simplicity is a big selling point for the practicality of the proposal.

“It’s a single [quantum logic] gate for controlling interactions where normally you would need a whole series of gates that are actually designed for some other tasks,” underlines Rick van Bijnen, physicist and team member at Innsbruck.

Just a few laser pulses

Loic Henriet, a physicist and chief technology officer at the French quantum information processor startup Pasqal comments, ”It’s a new way of implementing a four qubit gate, which is the thing required for implementing QAOA rather natively on Rydberg atoms. With only a few laser pulses, you’re able to do this thing rather efficiently”. Advances in experimentally implementing QAOA could have broad consequences since its applicability ranges from solving logistical problems to balancing financial portfolios, he says.

While the new study is theoretical, the Innsbruck team is keen on staying in lockstep with experiments. In anticipation of a proof-of-principle experiment, they have already numerically tested whether their scheme would work in the presence of noise, explains the paper’s lead author Clemens Dlaska. Since numerical simulations can only handle a small number of qubits, 20 as opposed to a few hundred, current promising results invite more explorations in the lab.

“Existing quantum devices can actually do things that we cannot compute with classical computers. The question is only can we harness this computational power that is apparently there,” van Bijnen says. “Maybe doing arbitrary computational problems is a bit much to ask, so we are now looking at whether we can match problems well to available quantum hardware.” Many current experiments involving Rydberg atoms would likely not require any radical changes in instrumentation that is already being used, he adds.

Lechner says that scientists from academic and commercial laboratories have been reaching out to his team since the study’s publication. This has encouraged the team keep working on mathematical models to make their proposal even more efficient. “We’re not just waiting for the experiments to get better,” says van Bijnen. The research is described in Physical Review Letters.

AI and infrared spectroscopy identify the age and species of mosquitoes

Researchers in the UK and Africa have developed a quick and cost-effective way to determine the age of malaria mosquitoes using mid-infrared spectroscopy. This is important for assessing the effectiveness of control interventions as only older mosquitoes can transmit the parasite. The scientists say that their approach could also help with other mosquito- and insect-borne diseases.

According to the World Health Organization, there were around 241 million cases of malaria globally in 2020, killing more than 620,000 people. The vast majority of these were in Africa, which was home to 95% of malaria cases and 96% of malaria deaths.

Malaria is transmitted by female Anopheles mosquitoes. Strangely, the average lifespan of these mosquitoes is shorter than the time it takes for the Plasmodium parasites that cause malaria to develop. This means that only a small proportion of mosquitoes live long enough to pass on the disease. Because of this, malaria control interventions such as insecticidal nets tend to target adult mosquito survival. An accurate and reliable method of determining the age of the insects would help assess the impact of such vector controls. The current way to do this involves dissecting mosquitoes’ ovaries. This is expensive, slow and hard to do at scale.

In recent years, there has been some success using infrared spectroscopy to determine the age of mosquitoes. This technique provides information regarding the chemical composition of the insect’s cuticle (its protective exoskeleton), which varies with species and age, based on the light signature returned when it is illuminated with infrared light. But while this approach is accurate for laboratory-reared populations that are genetically similar, spectroscopy has struggled with ageing genetically diverse wild mosquito populations.

Now Francesco Baldini, a medical entomologist at the University of Glasgow, and his colleagues have combined mid-infrared spectroscopy with deep learning to develop a rapid, cost-effective way to identify the species and age of three species of malaria carrying mosquito. They report their results in Nature Communications.

“With this infrared technology, we have developed a tool which could be adopted within current mosquito control plans, has the potential to be scaled up for use across different areas, and would greatly help in testing new products and solutions against diseases transmitted by mosquitoes,” Baldini says.

The researchers used data from more than 40,000 female mosquitoes of different ages from three malaria-transmitting species. The insects came from diverse genetic backgrounds and were reared both in different laboratories and semi-wild conditions in East and West Africa to capture genetic and environmental variations. The artificial intelligence (AI) model was initially trained using mid-infrared spectroscopy data from the genetically varying lab-reared mosquitoes. The team then retrained it using an additional sample of mosquitoes from the semi-wild populations. The resulting model was able to predict the age and species of mosquitoes reared in semi-wild conditions from their mid-infrared signatures with more than 95% accuracy.

To further test the effectiveness of this “transfer-learning” approach, the researchers collected wild mosquitoes in Burkina Faso and Tanzania. They then dissected and age-assessed a sample of these and used them to retrain the AI model that was previously trained on the lab-reared mosquito populations. When tested on more of the wild mosquitoes, this deep-learning mid-infrared spectroscopy system returned similar results to traditional dissection techniques.

Baldini says that the technique requires mosquitoes to be collected, killed and then scanned in a laboratory. Mosquitoes are already routinely collected in many areas to check species and malaria infection rates. “The [spectroscopy] procedure takes approximately 10 seconds per mosquito instead of several hours and is essentially free after the upfront cost of the hardware,” he explains.

“We envision this approach could also be applied to other vectors and vector-borne diseases, from filariasis and chikungunya, to sleeping sickness and Zika; and could be used to evaluate the attempts to limit the expansion of invasive mosquito species across Europe and the United States,” says Baldini.

In the future, it may even be possible to scan flying mosquitoes. Baldini notes that this will probably be easier using near-infrared spectroscopy, rather than mid-infrared. “We are working on the development of this type of device,” he adds.

Carbon nanotubes could stabilize energy-rich nitrogen chains

From TNT to nitro-glycerine, nitrogen-rich compounds are known for packing an explosive punch. When these materials explode, bonds between atoms in the compounds are broken, which gives a chance for two nitrogen atoms to form very strong triple bonds with each other. This releases an enormous amount of chemical energy due to the high strength of the triple bond, which is almost six times stronger than its single-bond counterpart. In fact, the strength of nitrogen-nitrogen triple bonds is one of the reasons that the stable nitrogen gas dominates Earth’s atmosphere.

This chemical property of nitrogen is encouraging scientists to develop new nitrogen-rich compounds for use as high energy-density materials that can be used as explosives or propellants. Polymeric nitrogen exists in the form of chains and tubes of linked nitrogen atoms with a high number of single or double bonds that can break and form triple bonds, releasing a large amount of energy and no dangerous by-products.

Several types of these polymers have been made at high temperatures and pressures, but they have been notoriously difficult to stabilize at ambient conditions. However, the electrochemical pressure inside the confined walls of carbon nanotubes may be the key to realizing these structures under more practical conditions. In a paper, published in Chinese Physics Letters, a team of scientists led by Jian Sun at Nanjing University provide a theoretical map to the process and the resulting compounds.

Carbon nanotube nano reactors

When graphene sheets of a single layer of bonded carbon atoms are rolled up, they can form cylindrical molecules with a diameter on the order of nanometres, called carbon nanotubes. Like test tubes, high-strength and high-stability nanotubes can be used as containers for chemical reactions, as they are larger than simple molecules. But nanotubes are not just passive vessels, their small dimensions provide confinement effects that can help stabilize a reaction and even control it. Previously, scientists studied pre-made polymeric nitrogen molecules in nanotubes, yet most have not been fabricated directly in the tubes.

In their recent work, Sun and colleagues use a new computational approach to search and characterize potential polymeric nitrogen structures, like in the conceptual figure above. Modelling the potential inside simplified carbon nanotubes of different diameters, the software looks for possible polymerized structures using a machine learning approach called Magus. Then, the properties and stability of the structures were investigated using molecular dynamics simulations.

Their technique predicted that stable chains and tubes of nitrogen atoms can form in two previously known structures as well as three completely new ones. Both the pressure acting on the nitrogen chains and the confining potentials inside the carbon nanotubes of different sizes highly affect the type of nitrogen structure formed, and consequently its properties.

Polymer predictions

Not only did the researchers predict the existence and stability of different polymeric nitrogen structures, but they also describe their expected properties. Theoretical studies of their vibrational properties suggest the nitrogen structures are likely to be mechanically stable, with the stability being strongly dependent on the size of the nanotubes.

Simulations using models more closely resembling actual carbon nanotubes show that the carbon tubes might sometimes deform to having an elliptical cross-section, further stabilizing the nitrogen chains. Simulations of some of the polymeric nitrogen structures at room temperature suggest that they can be stabilized in bamboo-like nanotube structures. The electronic properties of the structures inside the nanotubes are predicted to range from semiconductors to more metal-like behaviour.

Importantly, the energy density of the polymeric nitrogen is expected to be almost twice that of TNT, suggesting their potency as propellants or explosives.

From theory to experiment

While the research provides an understanding of how confined structures could be used to stabilize nanomaterials, creating these structures in the lab will be a tough task. Using short nanotubes with sodium azides as precursors under laser heating and a mixture of argon and nitrogen might do the trick. Still, the realization of these structures remains a challenge to be faced by experimental chemists.

Next-generation measurement systems: future challenges and opportunities

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In this webinar, experts explore the possibilities of signal processing in response to the future challenges and opportunities of advanced measurement systems.

The speakers will cover a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and impact of current and future developments per research field.

If you would like to delve a little deeper, read our latest Roadmap on signal processing for next generation measurement systems.

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Left to right: Dimitris Iakovidis, Andrew Yacoot, Manus Henry, Silvano Donati and Jianghui Geng

Dimitris K Iakovidis is editor of the Roadmap on signal processing for next-generation measurement systems. He is professor at the University of Thessaly, Greece, and the director of its Biomedical Imaging Laboratory. His research focuses particularly on digital signal processing and medical decision support systems.

Andrew Yacoot is editor-in-chief of Measurement Science and Technology. He leads the dimensional nanometrology work at NPL and chairs the BIPMs Consultative Committee for Length’s Working Group on Dimensional Nanometrology.

Manus Henry is director of the Advanced Instrumentation Group at the Department of Engineering Science, University of Oxford, UK, and professor of flow management, Coventry University, UK. His interests include self-validating sensors and systems, particularly in flow measurement and enabled through signal processing.

Silvano Donati is an emeritus professor at the University of Pavia, Italy, with a wealth of experience in the application of laser diodes to optical techniques, particularly in the area of interferometry and noise limits. He is the inventor of self-mixing interferometry.

Jianghui Geng is a professor and director of the Satellite Navigation and Positioning Technology Research Center of Wuhan University, China. He is particularly interested in the challenges presented by multi-constellation and multi-frequency GNSS signal processing.

About this journal

Measurement Science and Technology was the world’s first scientific instrumentation and measurement journal. It covers all aspects of the theory, practice and application of measurement, instrumentation and sensing across science and engineering.

Editor-in-chief: Andrew Yacoot, National Physical Laboratory, Teddington, UK.

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