The best way to stave off the worst effects of climate change is to reduce CO2 emissions around the world. And one way to do that, says Zhongwei Chen, a professor in the Department of Chemical Engineering at the University of Waterloo, is to capture the CO2 and convert it into other useful chemicals, such as methanol and methane for fuels.
Stopping emissions at the source, and further reducing future ones by replacing CO2-producing fuels with cleaner ones “…is a way to close the circle,” Chen says.
In order to turn CO2 into methanol, you need a catalyst to jump-start the electrochemical reaction. Traditionally, these catalysts have either been made out of precious metals like gold or palladium, or base metals like copper or tin. However, they are expensive and break down easily, hindering large-scale implementation.
“Right now we can’t meet industrial requirements,” says Chen. “So we are trying to design catalysts with better activity, selectivity, and durability.”
Chen and his team are focused on low-cost metal and metal-free catalysts. The metal-free catalysts, made from carbon, are cheaper and more durable but tend to have lower catalytic activity than metal ones. So the team tweaked the chemical composition and physical design of the catalyst to optimize its efficiency, combining the materials science of the catalyst design with the engineering of the electrode and reactor to improve the activity of the whole system.
“We want to make it as small as we can, but not too small to be a practical application,” says Chen. They combined nanometer-scale active sites within a micrometer-scale particle—like bubbles in a tiny sponge—to create a catalyst with a huge number of active sites in a particle that is easy and practical to fabricate.
The powerful light beams and expert technical teams at the Canadian Light Source (CLS) at the University of Saskatchewan were instrumental in helping to design an efficient catalyst, says Chen. “The advanced facilities at CLS are critical in helping us understand what was going on during the reaction, so we can continue to design and improve the next generation of catalysts.”
The paper is published in the journal ACS Catalysis.
More information: Zhen Zhang et al, Steering Carbon Hybridization State in Carbon-Based Metal-free Catalysts for Selective and Durable CO2 Electroreduction, ACS Catalysis (2022). DOI: 10.1021/acscatal.2c03055
A new study reveals a fresh way to control and track the motion of skyrmions—tiny, tornado-like magnetic swirls that could power future electronics. Using electric currents in a special magnetic material called Fe₃Sn₂, the team got these skyrmions to “vibrate” in specific ways, unlocking clues about how invisible spin currents flow through complex materials.
The discovery not only confirms what theory had predicted but also points to a powerful new method for detecting spin currents—a discovery that could one day lead to more efficient memory and sensing devices in future electronics. The findings are published in the journal Nature Communications.
Led by Assistant Prof. Amir Capua and Ph.D. Candidate Nirel Bernstein from the Institute of Applied Physics and Nano Center at Hebrew University in collaboration with Prof. Wenhong Wang and Dr. Hang Li from Tiangong University, the team explored how skyrmions behave in a special magnetic material called Fe₃Sn₂ (iron tin).
This material is already known to be promising for use in advanced technologies because it keeps skyrmions stable even at extreme temperatures—a key requirement for practical devices.
What are skyrmions—and why do they matter? Skyrmions are ultra-small, stable magnetic swirls that can exist in certain materials. Because they can be manipulated with very little energy, they are being studied as building blocks for future low-power memory and computing systems.
The team discovered that by sending electrical currents through Fe₃Sn₂, they could excite certain kinds of “resonances” in the skyrmions—essentially making them vibrate in very specific ways. These vibrations, or “modes,” were detected using advanced optical techniques that observe changes in real time.
Interestingly, only two types of motion were triggered: a “breathing” mode (expanding and contracting like lungs) and a rotating motion. This confirmed earlier scientific predictions and suggests that Fe₃Sn₂ behaves differently than other magnetic materials.
A new type of spin current detected The researchers also noticed something unexpected: The width of the resonance signal changed when they applied a steady current. Using computer simulations, they showed that this effect was caused by a “damping-like torque,” which indicates the presence of spin-polarized currents. Furthermore, they realized that the resonances of the magnetic swirls were excited due to “spin-orbit torque” rather than the more familiar “spin-transfer torque.”
“This gives us a deeper understanding of how spin currents interact with magnetic materials, especially in systems where the internal magnetic structure is frustrated or disordered,” said Assistant Prof. Capua.
They also found signs that both real-space and momentum-space spin structures play a role in how electrons and spins move through the material, offering new clues about how to control electrical signals in future devices.
This research not only reveals new physics behind spin-torque effects but also opens up possibilities for using skyrmion resonances as highly sensitive detectors of spin currents—something that could benefit data storage, neuromorphic computing, and sensor technologies.
The study highlights how fundamental research in magnetism can lead to new tools for the electronics of tomorrow.
Ball-and-stick model of the dopamine molecule, a neurotransmitter that affects the brain’s reward and pleasure centers. Credit: Jynto/Wikipedia
Altered levels of the neurotransmitter dopamine are apparent in various conditions, such as Parkinson’s disease and depression.
In research published in ChemistrySelect, investigators describe a quick, sensitive, and simple test to determine dopamine levels in biological fluids. The method could help clinicians spot abnormal blood levels of dopamine in patients, potentially allowing for earlier disease detection.
The method relies on what are called carbon quantum dots, a type of carbon nanomaterial with photoluminescence properties, and ionic liquid, which is comprised of several mineral anions and organic cations existing in liquid form at room temperature.
“The proposed electrochemical sensor could be an exceptional step forward in dopamine detection and pave the way for the molecular diagnosis of neurological illnesses,” the authors wrote.
More information: Zahra Nazari et al, An Electrochemical Sensor Based on Carbon Quantum Dots and Ionic Liquids for Selective Detection of Dopamine, ChemistrySelect (2023). DOI: 10.1002/slct.202203630
University of Illinois Physics Professor Paul Kwiat and members of his research group have developed a new tool for precision measurement at the nanometer scale in scenarios where background noise and optical loss from the sample are present.
This new optical interferometry technology leverages the quantum properties of light—specifically, extreme color entanglement—to enable faster and more precise measurements than widely used classical and quantum techniques can achieve.
Colin Lualdi, Illinois Physics graduate student and lead author of the study, emphasizes, “By taking advantage of both quantum interference and quantum entanglement, we can make measurements that would otherwise be difficult with existing methods.”
Lualdi says this tool has ready applications in medical diagnostics, remote system monitoring, and material characterization. The quantum properties of the new technology give it many advantages over current high-precision measurement tools used in these fields. It has increased sensitivity in cases where background noise is present, for example, when trying to measure a distant target that reflects light faintly—making it capable of taking outdoor ranging measurements in broad daylight.
It is also better for measuring samples that transmit light poorly or are sensitive to light, such as metallic thin films or biological tissues. Unlike some of the alternatives for measuring delicate samples, this technology does not require placing a physical probe in close proximity or contact with the material being measured, allowing for more versatile measurement configurations. It also takes faster measurements than some classical and quantum technologies, which will allow researchers to study dynamic systems such as vibrating surfaces—difficult with current techniques.
This technology represents a rare example of an instrument’s quantum advantages enabling immediate applications across many fields.
Kwiat explains, “It is a practical application of some very fundamental quantum mechanical effects that have been known for quite a long time and underpin a lot of quantum information processing. Our measurement hits the quantum limit of how much information can be extracted from a system.”
This research is published in Science Advances.
Interferometry: Classical versus quantum Optical interferometry is today’s gold standard in precision measurement. It uses the interference properties of light described by classical physics to measure tiny distances. Here’s how it works: when two light waves meet and their peaks and troughs are aligned, they can add to each other, interfering constructively to produce a higher-amplitude resultant wave. If, on the other hand, the peaks of one wave are aligned with the troughs of another wave, they will cancel one another out, interfering destructively to produce a lower-amplitude resultant wave.
The classical optical interferometer setup comprises a laser that shines a beam of light through a beam splitter. One light wave travels down the vertical arm, and the other travels down the horizontal arm. A mirror at the end of each arm reflects the light waves, which travel back to meet at the beam splitter. The lengths of the vertical and horizontal arms are arranged such that the two waves interfere destructively, canceling each other out so that no interference signal is detected.
But if the length of one of the arms is made shorter, for example, when a material of some thickness is inserted into one of the arms, the waves will add to each other when they meet back up at the beam splitter, creating an interference signal. Changes in the interference signal are then used to calculate the thickness of the material.
Classical interferometry has many successful applications. It has been used to detect gravitational waves—tiny ripples in the spacetime fabric that are less than the width of a proton. It is also used in medical diagnostic tools; for example, measuring retinal thickness to detect early signs of diseases. However, classical interferometers have limitations. They struggle to measure thin samples that transmit light poorly.
Background light can also leak in, weakening the interference signals and decreasing the sensitivity of the device in the same way an overexposed photo’s saturated light makes it hard to distinguish details.
Quantum two-photon interferometry addresses these shortcomings and adds new capabilities. In quantum physics, light is treated as discrete particles called photons. These particles maintain some wave-like qualities, including interference. In the quantum interferometer, a single photon is sent down each interferometer arm. Just like in the classical case, one goes through a sample, and one is a reference. They meet up, and their relative delay produces an interference signal at the detector.
Highly nondegenerate energy-entangled two-photon interferometer. Credit: Science Advances (2025). DOI: 10.1126/sciadv.adw4938 The quantum nature of this measurement overcomes the issue of measuring low-transmission materials—the strength of the interference signature is unchanged because the low-transmission loss affects both photons equally.
Lualdi explains, “As long as you detect two photons as a part of the interference measurement, the contrast of your interference signature will remain perfectly fine, which is a huge quantum advantage.”
Furthermore, the quantum interferometer’s sensitivity is much less impacted by background light. The measurement of the interference signal is taken in a narrow time window of the photons’ arrival, around 100 picoseconds. Nearly all background light can be filtered out because it does not arrive within that narrow window, meaning the quantum measurement remains highly sensitive.
Still, there are challenges to achieving nanometer sensitivity with quantum two-photon interferometry. Typically, to reach this level of precision, the measurement needs to run for hours or employ photons having a broad color bandwidth. In the same way that white light contains all the colors of the rainbow in its spectrum, photons can also have a particular color bandwidth. These broad-bandwidth photons are very difficult to work with in the lab, and hours-long measurements have limited applicability.
Extreme color entanglement is an advantage Quantum interferometry measurement capabilities can be increased by entangling the two photons. Entanglement is a quantum phenomenon in which the states of two particles are linked, regardless of the distance separating them. By entangling a property of the photons, in this case their color, the interferometer sensitivity increases. The Kwiat group has bypassed the technical issues stemming from the use of broad-bandwidth photons by employing two narrow-bandwidth entangled photons that have been prepared to have very different colors.
The greater the difference in the entangled photons’ colors, the greater the interferometer sensitivity. For example, entanglement between a strawberry-red photon and a raspberry-red photon (a wavelength difference of tens of nanometers) will produce a less sensitive interference signal than between a raspberry-red photon and a blueberry-blue photon. The latter is an example of extreme color entanglement.
“With entanglement, we only need to work with a little bit of blue and a little bit of red, instead of the whole span of colors between them,” explains Lualdi. The actual colors utilized, however, are invisible to the human eye, with wavelengths of 810 and 1,550 nanometers.
The team experimented with various light sources for generating extreme-color-entangled photons at the onset of this project. Their ultimate design enables a high entangled pair rate of hundreds of thousands per second, allowing faster measurements.
Having developed these advances, the team turned their attention to measuring real samples. The group collaborated with Illinois Electrical and Computer Engineering Professor Simeon Bogdanov and graduate student Swetapadma Sahoo to create a metallic thin film sample with low optical transmission—the type of sample that would show their technology’s advantages.
After measuring this sample with the new quantum interferometer, the researchers brought the sample to the Materials Research Laboratory for independent validation by atomic force microscopy. The results agreed. The new interferometer had made an accurate nanometer-scale measurement in a matter of seconds.
Future applications The new interferometric tool holds strong implications for applications across many fields. The Kwiat team is now focused on these potential applications and possible integrations with other measurement tools.
Kwiat elaborates, “We are trying to understand how we can further tailor this technology to be useful for other measurements… looking at thin films of biological samples, for example in microscopy, and being able to combine this with other sensing modalities, like atomic force microscopy.”
The lower light intensity of the Kwiat method—their source generates two photons at a time—opens exciting avenues for biological study. One could imagine imaging a sensitive biological tissue, such as the brain or retina, faster and over a larger area than current state-of-the-art techniques such as atomic force microscopy.
In addition, the lower light intensity allows for studying the behavior of photo-sensitive microorganisms, such as algae, in the dark. Current imaging methods require a bright spotlight to be shone on these organisms, making this kind of observation impossible.
The group is also currently exploring the technology’s capability to measure vibrations, which is much more difficult to do with existing technologies.
Lualdi says, “Compared to other quantum interferometers, our system measures faster and at a higher precision, and so now we have the opportunity to study time-varying signals, such as nanometer-scale vibrations, for example.”
Summary of the concept. Credit: Nature Food (2023). DOI: 10.1038/s43016-023-00750-9
Food waste and food-borne diseases are among the most critical problems urban populations face today. They contribute to greenhouse emissions tremendously and amplify economic and environmental costs. Since food spoilage remains the main reason for this waste, the circumstances of processing, transporting, and preserving food still need to be improved in line with current technological advancements.
Current monitoring processes are conducted in laboratories and use expensive chromatographic devices. These not only require too much time but also excessive resources and qualified personnel. So, present methods unfortunately prove to be inefficient in today’s circumstances.
New research published in Nature Food presents a significant alternative to this process: A new user-friendly, cost-effective, and up-to-date sensor that can be applied on food directly and replace lab-monitoring. The 2 x 2 cm miniature wireless device introduced in the paper offers real-time measurement, is battery-free and smartphone-compatible. It is expected to be highly effective especially in high-protein foods such as beef, chicken, and fish.
The research was led by Dr. Emin İstif (Molecular Biology and Genetics, Kadir Has University) and Asst. Prof. Levent Beker (Mechanical Engineering, Koç University) with the contribution of Prof. İskender Yılgör and Dr. Emel Yılgör (Chemistry, Koç University), Asst. Prof. Çağdaş Dağ (Molecular Biology and Genetics, Koç University) and Asst Prof. Hatice Ceylan Koydemir (Texas A&M University).
While existing solutions focus on the change in color of food, this new device, for the first time, offers a capacitive measurement method and thus utilizes near-field communication (NFC) technology with power-free and wireless communication. The authors indicate that this eliminates major disadvantages encountered in resistive devices such as moisture sensitivity and incorrect data due to distance.
The invention will not only provide companies the opportunity of reducing costs but also help consumers tremendously. Once widely commercialized, the device will enable continuous monitoring on shelves and allow users to control freshness right before buying a product or even before consumption at home. This opportunity of on-demand spoilage analysis via mobile phones will ultimately help preventing food waste and food-borne diseases.
With its cost-effectiveness and accessibility, the authors hope to contribute to the greater struggle against global warming and greenhouse emissions more effectively and quickly. The next steps will be to focus on increasing the potential for commercialization of the product in the near future.
More information: Emin Istif et al, Miniaturized wireless sensor enables real-time monitoring of food spoilage, Nature Food (2023). DOI: 10.1038/s43016-023-00750-9
Manuel Endres, professor of physics at Caltech, specializes in finely controlling single atoms using devices known as optical tweezers. He and his colleagues use the tweezers, made of laser light, to manipulate individual atoms within an array of atoms to study fundamental properties of quantum systems. Their experiments have led to, among other advances, new techniques for erasing errors in simple quantum machines; a new device that could lead to the world’s most precise clocks; and a record-breaking quantum system controlling more than 6,000 individual atoms.
One nagging factor in this line of work has been the normal jiggling motion of atoms, which make the systems harder to control. Now, reporting in the journal Science, the team has flipped the problem on its head and used this atomic motion to encode quantum information.
“We show that atomic motion, which is typically treated as a source of unwanted noise in quantum systems, can be turned into a strength,” says Adam Shaw, a co-lead author on the study along with Pascal Scholl and Ran Finkelstein.
Shaw was formerly a graduate student at Caltech during these experiments and is now a postdoctoral scholar at Stanford University. Scholl served as a postdoc at Caltech and is now working at the quantum computing company Pasqal. Finkelstein held the Troesh Postdoctoral Prize Fellowship at Caltech and is now a professor at Tel Aviv University.
Ultimately, the experiment not only encoded quantum information in the motion of the atoms but also led to a state known as hyper-entanglement. In basic entanglement, two particles remain connected even when separated by vast distances. When researchers measure the particles’ states, they observe this correlation: For example, if one particle is in a state known as spin up (in which the orientation of the angular momentum is pointing up), the other will always be spin down.
In hyper-entanglement, two characteristics of a particle pair are correlated. As a simple analogy, this would be like a set of twins separated at birth having both the same names and same types of cars: The two traits are correlated between the twins.
In the new study, Endres and his team were able to hyper-entangle pairs of atoms such that their individual states of motion and their individual electronic states—their internal energy levels—were correlated among the atoms. What is more, this experimental demonstration implies that even more traits could be entangled at the same time.
“This allows us to encode more quantum information per atom,” Endres explains. “You get more entanglement with fewer resources.”
The experiment is the first demonstration of hyper-entanglement in massive particles, such as neutral atoms or ions (earlier demonstrations used photons).
Adam Shaw, Ivaylo Madjarov and Manuel Endres work on their laser-based apparatus at Caltech. Credit: Caltech For these experiments, the team cooled down an array of individual alkaline-earth neutral atoms confined inside optical tweezers. They demonstrated a novel form of cooling via “detection and subsequent active correction of thermal motional excitations,” says Endres, which he compares to James Clerk Maxwell’s famous 1867 thought experiment invoking a demon that measures and sorts particles in a chamber. “We essentially measure the motion of each atom and apply an operation depending on the outcome, atom-by-atom, similar to Maxwell’s demon.”
The method, which outperformed the best-known laser cooling techniques, caused the atoms to come to nearly a complete standstill.
From there, the researchers induced the atoms to oscillate like a swinging pendulum, but with an amplitude of approximately100 nanometers, which is much smaller than the width of a human hair. They were able to excite the atoms into two distinct oscillations simultaneously, causing the motion to be in a state of superposition. Superposition is a quantum state in which a particle exhibits opposite traits simultaneously, like a particle’s spin being both up and down at the same time.
“You can think of an atom moving in this superposition state like a kid on a swing who starts getting pushed by two parents on opposite sides, but simultaneously,” Endres says. “In our everyday world, this would certainly lead to a parental conflict; in the quantum world, we can remarkably make use of this.”
They then entangled the individual, swinging atoms to partner atoms, creating a correlated state of motion over several micrometers of distance. After the atoms were entangled, the team then hyper-entangled them in such a way that both the motion and the electronic states of the atoms were correlated.
“Basically, the goal here was to push the boundaries on how much we could control these atoms,” Endres says. “We are essentially building a toolbox: We knew how to control the electrons within an atom, and we now learned how to control the external motion of the atom as a whole. It’s like an atom toy that you have fully mastered.”
The findings could lead to new ways to perform quantum computing as well as quantum simulations designed to probe fundamental questions in physics. “Motional states could become a powerful resource for quantum technology, from computing to simulation to precision measurements,” Endres says.
Superimposition of structures of CpI in various states. Credit: Angewandte Chemie International Edition (2022). DOI: 10.1002/anie.202216903
In nature, enzymes termed hydrogenases are capable of producing molecular hydrogen (H2). Special types of these biocatalysts, so-called [FeFe]-hydrogenases, are extremely efficient and therefore of interest for biobased hydrogen production. Although scientists have learned a lot about how these enzymes work, many details remain to be completely understood.
A research team of the Photobiotechnology group at Ruhr University Bochum, Germany, headed by Dr. Jifu Duan and Professor Thomas Happe succeeded in filling a scientific gap. The researchers showed that external cyanide binds to the [FeFe] hydrogenases and inhibits hydrogen formation. In the process, they detected a structural change in the proton transport pathway, which helps to understand the coupling of electron and proton transport. They reported their findings in the journal Angewandte Chemie of December 4, 2022.
A sophisticated internal catalyst
To generate H2, these biocatalysts transfer electrons to protons, employing a sophisticated structure as internal catalyst. This so-called H-cluster contains electronically active iron ions that are bound to what most people know as toxins: carbon monoxide and cyanide.
However, although internal carbon monoxide and cyanide are crucial for the high activity of hydrogenases, additional external carbon monoxide binds to the H-cluster and prevents its H2 production. “Interestingly, cyanide is also a well-known inhibitor of iron-containing biocatalysts,” says Jifu Duan. “And yet, its effect on [FeFe]-hydrogenases has hardly been analyzed before.”
The Bochum-based research team closed this scientific gap. The researchers showed that external cyanide binds to and inhibits [FeFe]-hydrogenases. In collaboration with Professor Eckhard Hofmann, head of the protein crystallography group at RUB, the team obtained the structure of H2-producing biocatalysts to which external cyanide was bound.
“The high-resolution structure in combination with spectroscopic analyses tells us that the external cyanide directly binds to the H-cluster, similar to other inhibitors studied so far,” says Jifu Duan. “This explains why the hydrogenase is inactive after cyanide treatment.”
Coincidental capture of a transient state
When the researchers took a detailed look into the structure of the cyanide-poisoned hydrogenase, they found a surprise. They observed structural changes in the proton transport pathway that is required to guide the protons that will become H2 to the H-cluster.
“This conformation has been suggested to be vital for efficient proton shuttling, but it had never been observed structurally. Coincidently, the cyanide binding helped us to capture such a transient state,” says Jifu Duan.
“These findings are important for researchers to understand the coupling of electron and proton transport which is not only relevant for H2-generating enzymes, but many additional biocatalysts,” concludes Thomas Happe.
More information: Jifu Duan et al, Cyanide Binding to [FeFe]‐Hydrogenase Stabilizes the Alternative Configuration of the Proton Transfer Pathway, Angewandte Chemie International Edition (2022). DOI: 10.1002/anie.202216903
When two-dimensional electron systems are subjected to magnetic fields at low temperatures, they can exhibit interesting states of matter, such as fractional quantum Hall liquids. These are exotic states of matter characterized by fractionalized excitations and the emergence of interesting topological phenomena.
Researchers at Cavendish Laboratory and Massachusetts Institute of Technology (MIT) set out to better understand these fascinating states using machine learning, specifically employing a newly developed attention-based fermionic neural network (FNN).
The method they developed, outlined in a paper published in Physical Review Letters, was trained to find the lowest-energy quantum state (i.e., ground state) of fractional quantum Hall liquids.
“AI has transformed many areas of society and science, but we are yet to see an AI breakthrough in quantum physics,” Liang Fu, co-author of the paper, told Phys.org.
“Solving quantum many-body problems is known to be extremely difficult, because a quantum system can be in a superposition of exponentially many states: literally, everything everywhere all at once! So, we wanted to find out whether AI has the power to conquer the quantum world.”
The main objective of the recent research by Fu and his colleagues was to assess the potential of advanced machine learning tools for solving complex quantum problems. Working towards this goal, the researchers developed a new FNN and tried to use it to uncover the hidden patterns of electrons in topological quantum liquids.
“Our recent paper was inspired by the rapid development of AI, in particular the FNN, to tackle quantum chemistry problems,” said Yi Teng, co-author of the paper. “We wanted to demonstrate that this neural network based variational approach can also be applied to complex condensed matter systems, proven challenging for traditional numerical methods.”
Fractional quantum Hall liquids are intricate states of matter known to emerge in 2D electron systems when a strong magnetic field is applied to them. The computational method developed by Fu, Teng and Dai can capture rich physical phenomena, successfully uncovering microscopic features of fermionic quantum Hall liquids and competing states.
“The fractional quantum Hall liquid hosts emergent particles—-neither bosons nor fermions—-that carry a quantized fraction of electron’s charge,” explained Fu. “While great success in this venerable field came from the best human minds, there remain long-standing open questions that require numerically accurate solutions beyond the capability of traditional methods. So, we gave AI a shot.”
This study is among the first to demonstrate the potential of AI and machine learning for studying fractional phases of matter. Using their FNN, Fu, Teng and Dai generated a variational ansatz, which is a flexible mathematical structure that can be optimized to estimate a system’s ground state.
“We then used Monte-Carlo sampling to minimize the total energy in search of ground state,” said Teng. “We also performed extensive benchmarks and found neural networks consistently outperform traditional methods. The biggest advantage of our method is that no human biases are put in by hand, and the neural network captures all possible states of electrons without truncating the Hilbert space.”
The team’s demonstration highlights the promise of FNNs for the study and estimation of states that can be difficult to predict theoretically. As part of their study, the researchers successfully used their FNN to accurately predict the transition of a 2D electron system from liquid to crystal.
“We demonstrate that an unbiased neural network can be used to solve different phases (fractional quantum Hall liquid and Wigner crystal in our case) in a unified manner with unprecedented accuracy,” said Teng. “This shows the capacity and versality of the NN-based variational method in quantum condensed matter physics.”
In the future, the model developed by Fu, Teng and Dai could be improved further and used to predict the quantum phase diagram of various 2D electron systems. In addition, it could inspire the development of other FNN-based models for quantum research and could potentially contribute to the discovery of new quantum states of matter.
“For me, this project was a mind-blowing experience,” said Fu. “I am now fully convinced of the transformative power of AI for quantum science, offering a vast opportunity.
“Looking ahead, I also believe that solving challenging quantum problems provides an objective benchmark for different large language model architectures. Think of it: no training data is involved in such test, and the ranking is objectively determined by the variational energy. The best of all is the reward—AI solving the quantum phase diagram of real materials and discovering new quantum states of matter.”
As part of their future studies, the researchers plan to use their FNN-based method to study a wide range of other quantum systems. For instance, they would like to use it to gather new insights into non-Abelian states, unconventional superconductivity and quantum spin liquids.
“Going forward, I’m also excited to both use AI to solve challenging physics problems, and to use challenging physics problems to learn more about AI,” added David Dai, co-author of the paper.
Re-using gold from electronic waste prevents it from being lost to landfill, and using this reclaimed gold for drug manufacture reduces the need to mine new materials. Current catalysts are often made of rare metals, which are extracted using expensive, energy-intensive and damaging mining processes.
The method for extracting gold was developed by researchers at the University of Cagliari in Italy and the process for using the recovered gold was developed by researchers at Imperial College London. The study is published in ACS Sustainable Chemistry & Engineering.
Waste electrical and electronic equipment (WEEE) is typically sent to landfill, as separating and extracting the components requires a lot of energy and harsh chemicals, undermining its economic viability. However, WEEE contains a wealth of metals that could be used in a range of new products.
Finding ways to recover and use these metals in a low-cost, low-energy and non-toxic way is therefore crucial for making our use of electronic goods more sustainable.
Lead researcher Professor James Wilton-Ely, from the Department of Chemistry at Imperial, said, “It is shocking that most of our electronic waste goes to landfill and this is the opposite of what we should be doing to curate our precious elemental resources. Our approach aims to reduce the waste already within our communities and make it a valuable resource for new catalysts, thereby also reducing our dependence on environmentally damaging mining practices.”
“We are currently paying to get rid of electronic waste, but processes like ours can help reframe this ‘waste’ as a resource. Even SIM cards, which we routinely discard, have a value and can be used to reduce reliance on mining and this approach has the potential to improve the sustainability of processes such as drug manufacture.”
Professors Angela Serpe and Paola Deplano, from the University of Cagliari, developed a low-cost way to extract gold and other valued metals from electronic waste such as printed circuit boards (PCBs), SIM cards and printer cartridges under mild conditions. This patented process involves selective steps for the sustainable leaching and recovery of base metals like nickel, then copper, silver and, finally, gold, using green and safe reagents.
However, the gold produced from this process is part of a molecular compound and so cannot be re-used again for electronics without investing a lot more energy to obtain the gold metal. Seeking a use for this compound of recovered gold, the team of Professor Wilton-Ely and his colleague, Professor Chris Braddock, investigated whether it could be applied as a catalyst in the manufacture of useful compounds, including pharmaceutical intermediates.
Catalysts are used to increase the rate of a chemical reaction while remaining unchanged and are used in most processes to produce materials. The team tested the gold compound in a number of reactions commonly used in pharmaceutical manufacture, for example for making anti-inflammatory and pain-relief drugs.
They found that the gold compound performed as well, or better, than the currently used catalysts, and is also reusable, further improving its sustainability.
The researchers suggest that making it economically viable to recover gold from electronic waste could create spin-off uses for other components recovered in the process. For example, in the process, copper and nickel are also separated out, as is the plastic itself, with all these components potentially being used in new products.
Sean McCarthy, the Ph.D. student leading the research in the lab at Imperial, said, “By weight, a computer contains far more precious metals than mined ore, providing a concentrated source of these metals in an ‘urban mine’.”
Professor Serpe said, “Research like ours aims to contribute to the cost-effective and sustainable recovery of metals by building a bridge between the supply of precious metals from scrap and industrial demand, bypassing the use of virgin raw materials.”
The teams are working to extend this approach to the recovery and re-use of the palladium content of end-of-life automotive catalytic converters. This is particularly pressing as palladium is widely used in catalysis and is even more expensive than gold.
More information: Sean McCarthy et al, Homogeneous Gold Catalysis Using Complexes Recovered from Waste Electronic Equipment, ACS Sustainable Chemistry & Engineering (2022). DOI: 10.1021/acssuschemeng.2c04092
Experimental and simulated (a) 1D- and (b-c) 2D-SAXS patterns of the 12 wt% PBPEO solution by temperature-quenching from disordered states to the crystallization temperatures noted. The left panels of the 2D-SAXS are experimental, and the right panels are simulated patterns. Credit: Soft Matter (2023). DOI: 10.1039/D3SM00199G
When most people think of crystals, they picture suncatchers that act as rainbow prisms or the semi-transparent stones that some believe hold healing powers. However, to scientists and engineers, crystals are a form of materials in which their constituents—atoms, molecules, or nanoparticles—are arranged regularly in space. In other words, crystals are defined by the regular arrangement of their constituents. Common examples are diamonds, table salt, or sugar cubes.
However, in research just published in Soft Matter, a team led by Rensselaer Polytechnic Institute’s Sangwoo Lee, associate professor in the Department of Chemical and Biological Engineering, discovered that crystal structures are not necessarily always regularly arranged. The discovery advances the field of materials science and has unrealized implications for the materials used for semiconductors, solar panels, and electric vehicle technologies.
One of the most common and important classes of crystal structures is the close-packed structures of regular spheres constructed by stacking layers of spheres in a honeycomb arrangement. There are many ways to stack the layers to construct close-packed structures, and how nature selects specific stacking is an important question in materials and physics research. In the close-packing construction, there is a very unusual structure with irregularly spaced constituents known as the random stacking of two-dimensional hexagonal layers (RHCP). This structure was first observed from cobalt metal in 1942, but it has been regarded as a transitional and energetically unpreferred state.
Lee’s research group collected X-ray scattering data from soft model nanoparticles made of polymers and realized that the scattering data contains important results about RHCP but is very complicated. Then, Patrick Underhill, professor in Rensselaer’s Department of Chemical and Biological Engineering, enabled the analysis of the scattering data using the supercomputer system, Artificial Intelligence Multiprocessing Optimized System (AiMOS), at the Center for Computational Innovations.
“What we found is that the RHCP structure is, very likely, a stable structure, and this is the reason that RHCP has been widely observed in many materials and naturally occurring crystal systems,” said Lee. “This finding challenges the classical definition of crystals.”
The study provides insights into the phenomenon known as polytypism, which enables the formation of RHCP and other close-packed structures. A representative material with polytypism is silicon carbide, widely used for high-voltage electronics in electric vehicles and as hard materials for body armor. Lee’s team’s findings indicate that those polytypic materials may have continuous structural transitions, including the non-classical random arrangements with new useful properties.
“The problem of how soft particles pack seems straightforward, but even the most basic questions are challenging to answer,” said Kevin Dorfman of the University of Minnesota-Twin Cities, who is unaffiliated with this research. “This paper provides compelling evidence for a continuous transition between face-centered cubic (FCC) and hexagonal close-packed (HCP) lattices, which implies a stable random hexagonal close-packed phase between them, and thus makes an important breakthrough in materials science.”
“I am particularly pleased with this discovery, which shows the power of advanced computation to make an important breakthrough in materials science by decoding the molecular level structures in soft materials,” said Shekhar Garde, dean of Rensselaer’s School of Engineering. “Lee and Underhill’s work at Rensselaer also promises to open up opportunities for many technological applications for these new materials.”
Lee and Underhill were joined in research by Rensselaer’s Juhong Ahn, Liwen Chen of the University of Shanghai for Science and Technology, and Guillaume Freychet and Mikhail Zhernenkov of Brookhaven National Laboratory.
More information: Juhong Ahn et al, Continuous transition of colloidal crystals through stable random orders, Soft Matter (2023). DOI: 10.1039/D3SM00199G
