Computers Math

An international team that includes Rutgers University-New Brunswick scientists has developed a new method to make and manipulate a widely studied class of high-temperature superconductors.
This technique should pave the way for the creation of unusual forms of superconductivity in previously unattainable materials.
When cooled to a critical temperature, superconductors can conduct electricity without resistance or energy loss. These materials have intrigued physicists for decades because they can achieve a state of perfect conductivity allowing an electric current to flow indefinitely. But most superconductors only exhibit this peculiarity at temperatures so low — a few degrees above absolute zero — which renders them impractical.
The new work, published in Science, describes experiments that grew out of theoretical calculations that included those by a Rutgers team led by Jedediah Pixley, an associate professor in the Department of Physics and Astronomy in the Rutgers School of Arts and Sciences.
The experiments confirmed predictions by Pixley and Pavel Volkov, who at the time was a postdoctoral fellow at the Rutgers Center for Materials Theory. These predictions, based on mathematical models Pixley and Volkov (now at the University of Connecticut) devised to represent the underlying quantum physical behavior, projected how cuprate superconductors would behave if they were placed in proximity in specific configurations and at varying angles.
Superconductors are already in use today. Since the 1970s, scientists have employed superconducting magnets to generate the powerful magnetic fields needed for the operation of magnetic resonance imaging (MRI) machines. Maglev trains using the technology were introduced in the 1980s. More recently, scientists have harnessed the power of superconducting magnets to guide electron beams in experimental devices such as synchrotrons and accelerators.
In the future, scientists envision a world where ultra-efficient electricity grids, ultrafast and energy-efficient computer chips, and even quantum computers are powered by new kinds of superconducting materials.

The new experiments that validated Pixley and Volkov’s ideas were conducted by a team at Harvard University led by professor and physicist Philip Kim.
“We took two cuprate superconductors — materials that already were interesting — and, in placing them together and twisting them in a precise way, made something else that was very interesting: another superconductor which could have lots of technological applications,” said Pixley, a condensed matter theorist.
Because of its unique properties, the new superconductor is a promising candidate for the world’s first high-temperature, superconducting diode, essentially a switch that controls the flow of electrical current, the researchers said.
Such a device could potentially fuel fledgling industries such as quantum computing, which rely on fleeting phenomena produced in materials like superconductors, they added.
Pixley, who joined the Rutgers faculty in 2017, earned his doctoral degree by studying the conditions involved in producing superconductivity in unconventional materials. The latest research extends the field of “twistronics,” which involves twisting flat layers of two-dimensional materials to produce physical effects at the subatomic level that are observable on the macroscopic scale.
To Pixley, the study enlarges the paradigm of what materials can exhibit superconducting properties when twisted. The work yields other insights, as well.

“At the same time, we have found that this leads to a novel type of ‘magnetic’ superconducting state that has been long sought after, showing definitively that different superconducting phases can be reached via a twist,” he said.
The experimentalists first split an extremely thin film of a superconductive cuprate — nicknamed “BSCCO” and made of bismuth strontium calcium copper oxide — into two layers. Then, maintaining frigid conditions, they stacked the layers at a 45-degree twist, like an ice cream sandwich with askew wafers, retaining superconductivity at the fragile interface.
Cuprates are copper oxides that, decades ago, upended the physics world by showing they become superconducting at much higher temperatures than theorists had thought possible. BSCCO is considered a high-temperature superconductor because it starts superconducting at about -288 Fahrenheit. That is very cold by practical standards, but astonishingly high among classical superconductors, which typically must be cooled to about -400 Fahrenheit.
The work opens the door to more experiments, Pixley said.
“It will be very exciting to extend these experiments to other configurations of superconductors — twisted monolayers and a few twisted multilayers of superconductors at small twist angles,” Pixley said.
Other researchers on the study included scientists from the University of British Columbia, Brookhaven National Laboratory, the Leibniz Institute for Solid State and Materials Research in Germany, Seoul National University in South Korea and the National Institute for Materials Science in Japan. More

Plasmonics are special optical phenomena that are understood as interactions between light and matter and possess diverse shapes, material compositions, and symmetry-related behavior. The design of such plasmonic structures at the nanoscale level can pave the way for optical materials that respond to the orientation of light (polarization), which is not easily achievable in bulk size and existing materials. In this regard, “shadow growth” is a technique that utilizes vacuum deposition to produce nanoparticles from a wide range of 2D and 3D shapes in nanoscale. Recent research progress in controlling this shadow effect has broadened the possibilities for the creation of different nanostructures.
Now, in twin studies led by Assistant Professor Hyeon-Ho Jeong from the Gwangju Institute of Science and Technology (GIST), Republic of Korea, researchers have comprehensively shed light on the recent advances in shadow growth techniques for hybrid plasmonic nanomaterials, including clock-inspired designs containing magnesium (Mg). The studies were published in Advanced Materials on 25 March 2022 (with Jang-Hwan Han and Doeun Kim as co-first authors and Professor Peer Fischer and Dr. Jeong as co-corresponding authors) and Advanced Optical Materials on 20 November 2023 (with Juhwan Kim and Jang-Hwan Han as co-first authors and Dr. Jeong as the corresponding author), respectively.
The shadow effect here refers to the presence of “dark” areas on a surface that are concealed by “seed” molecules, and hence, inaccessible for the deposition of vaporized materials, much like shadow areas where light cannot reach. Elaborating on this further, Dr. Jeong says, “Since these shadowed areas are the regions where the material cannot be deposited, an array of three-dimensional nanostructures can be formed. This formation depends on the size of the seed, spacing between the seeds, and the inclination of the substrate.” Adding further, Doeun Kim, a Ph.D. student, says, “Creation of unique nanostructures is influenced by the introduction of rotation during the process, based on rotation speed, time, and angle, ultimately forming three-dimensional nanostructures.”
In the first study (featured as a cover-page article), the team showcased the production of various nanostructures using a specific shadow growth technique known as glancing angle deposition. These structures exhibit tunable optical properties achieved through suitable modifications to their material, shape, and surrounding environment. Their review also emphasizes a broad range of potential applications, including nano- and micro-robots for wound healing and drug delivery in the human body, photonic devices, and chiral spectroscopy, among others.
For the subsequent study, the team created 3D rotamers (molecules with specific rotational arrangements) capable of both linear and circular polarization, as well as of storing a significant amount of information. This clock-inspired design involves placing two nanorods made of Mg at a certain modifiable angle, resembling the hour and minute hands of a clock. These nanostructures also hold promise for various applications, such as the secure verification of items like banknotes, anti-counterfeiting devices, and displays capable of transitioning to desired optical states, as needed.
Talking about these developments and envisioning the future of plasmonics, Dr. Jeong says, “These rotamers can have potential utilization in physically unclonable functions, an area currently under intensive research for ensuring robust security levels of hardware, such as PCs or servers.” Explaining further, Ph.D. student Juhwan Kim says, “In particular, the ability to selectively filter UV light sources and specific visible wavelengths depending on the polarization state can also be used in glasses and windows to protect eyes and skin by blocking UV rays from sunlight.” More

High-entropy alloys can withstand extreme heat and stress, making them suitable for a variety of specific applications. A new study at the X-ray synchrotron radiation source BESSY II has now provided deeper insights into the ordering processes and diffusion phenomena in these materials. The study involved teams from HZB, the Federal Institute for Materials Research and Testing, the University of Latvia and the University of Münster.
The team analysed samples of a so-called Cantor alloy, which consists of five 3D elements: chromium, manganese, iron, cobalt and nickel. The samples of crystalline structures (face-centred cubic, fcc) were annealed at two different temperatures and then shock frozen.
The study focussed on unravelling local atomic structures in single crystalline samples cooled from either a high-temperature (HT) state annealed at 1373 Kelvin or a low-temperature (LT) state annealed at 993 Kelvin. To analyse the local environments of the individual elements in the samples, the team used a well established method: element-specific multi-edge X-ray absorption spectroscopy (EXAFS). To interpret the measurement data in the most precise and unbiased manner, the team carried out a Reverse Monte Carlo (RMC) based analysis.
“In this way, we have been able to reveal, both qualitatively and quantitatively, the peculiarities of the characteristic local environments of each principal components of the alloy at the atomic scale,” explains Dr Alevtina Smekhova from HZB. In particular, the spectroscopic results also provide insights into the diffusion processes in HEAs. For example, it was directly demonstrated why the element manganese diffuses fastest in the HT samples, while the element nickel diffuses faster in the LT samples as it was found earlier from diffusion experiments.
“These results help us to better understand the relationship between the local atomic environment and the macroscopic properties in these alloys,” explains Smekhova. More

Depending on their location, cancer cells within a three-dimensional (3D) tumor structure can have different microenvironments. Cells in the core of the tumor receive less oxygen (hypoxia) and nutrients than those in the periphery. These varying conditions can drive differences in cell growth rates and drug sensitivities, highlighting the need to study 3D tumor models in lab settings. Until recently, conventional methods used to create such tumor spheroids were time-consuming, produced inconsistent results and involved high setup costs.
Investigators at Brigham and Women’s Hospital, a founding member of the Mass General Brigham healthcare system, developed a low-cost, high-throughput device that can reliably generate uniform tumor spheroids. The study describes how to assemble the ‘Do-It-Yourself (DIY)’ device from parts totaling less than $7, including a coin-vibrating motor commonly found in cell phones.
By vibrating a suspension of cancer cells flowing rapidly out of a fine nozzle, the team was able to create nearly 4000 equally sized droplets per minute. They found that cancer cells within the droplets aggregated to form tumor spheroids with hypoxic cores and exhibited proliferation markers typical of in vivo tumors.
The tumor spheroids also demonstrated clinically typical responses to chemotherapy, with cancer cells at the hypoxic core driving tumor survival and drug resistance. These findings, the authors suggest, could help overcome the limitations of traditional two-dimensional cancer cell cultures and provide insights for improved drug development.
“We developed a simple, DIY method for reliable preclinical testing of anti-cancer drugs,” said corresponding author Hae Lin Jang, PhD, of the Center for Engineered Therapeutics. “The cost of devices often acts as a barrier to cancer research. Low-cost, simple-to-operate systems like ours are essential to democratize cancer research and make science more accessible.”
First author Bumseok Namgung, PhD, of the Center for Engineered Therapeutics added, “Our simple and low-cost system facilitates the anti-cancer drug research by enabling high-throughput drug screening.” More

For over three decades, a highly accurate early diagnostic test for ovarian cancer has eluded physicians. Now, scientists in the Georgia Tech Integrated Cancer Research Center (ICRC) have combined machine learning with information on blood metabolites to develop a new test able to detect ovarian cancer with 93 percent accuracy among samples from the team’s study group.
John McDonald, professor emeritus in the School of Biological Sciences, founding director of the ICRC, and the study’s corresponding author, explains that the new test’s accuracy is better in detecting ovarian cancer than existing tests for women clinically classified as normal, with a particular improvement in detecting early-stage ovarian disease in that cohort.
The team’s results and methodologies are detailed in a new paper, “A Personalized Probabilistic Approach to Ovarian Cancer Diagnostics,” published in the March 2024 online issue of the medical journalGynecologic Oncology.Based on their computer models, the researchers have developed what they believe will be a more clinically useful approach to ovarian cancer diagnosis — whereby a patient’s individual metabolic profile can be used to assign a more accurate probability of the presence or absence of the disease.
“This personalized, probabilistic approach to cancer diagnostics is more clinically informative and accurate than traditional binary (yes/no) tests,” McDonald says. “It represents a promising new direction in the early detection of ovarian cancer, and perhaps other cancers as well.”
The study co-authors also include Dongjo Ban, a Bioinformatics Ph.D. student in McDonald’s lab; Research ScientistsStephen N. Housley,Lilya V. Matyunina, andL.DeEtte (Walker) McDonald; Regents’ ProfessorJeffrey Skolnick, who also serves as Mary and Maisie Gibson Chair in the School of Biological Sciences and Georgia Research Alliance Eminent Scholar in Computational Systems Biology; and two collaborating physicians: University of North Carolina Professor Victoria L. Bae-Jump and Ovarian Cancer Institute of Atlanta Founder and Chief Executive OfficerBenedict B. Benigno. Members of the research team are forming a startup to transfer and commercialize the technology, and plan to seek requisite trials and FDA approval for the test.
Silent killer
Ovarian cancer is often referred to as the silent killer because the disease is typically asymptomatic when it first arises — and is usually not detected until later stages of development, when it is difficult to treat.

McDonald explains that while the average five-year survival rate for late-stage ovarian cancer patients, even after treatment, is around 31 percent — but that if ovarian cancer is detected and treated early, the average five-year survival rate is more than 90 percent.
“Clearly, there is a tremendous need for an accurate early diagnostic test for this insidious disease,” McDonald says.
And although development of an early detection test for ovarian cancer has been vigorously pursued for more than three decades, the development of early, accurate diagnostic tests has proven elusive. Because cancer begins on the molecular level, McDonald explains, there are multiple possible pathways capable of leading to even the same cancer type.
“Because of this high-level molecular heterogeneity among patients, the identification of a single universal diagnostic biomarker of ovarian cancer has not been possible,” McDonald says. “For this reason, we opted to use a branch of artificial intelligence — machine learning — to develop an alternative probabilistic approach to the challenge of ovarian cancer diagnostics.”
Metabolic profiles
Georgia Tech co-author Dongjo Ban, whose thesis research contributed to the study, explains that “because end-point changes on the metabolic level are known to be reflective of underlying changes operating collectively on multiple molecular levels, we chose metabolic profiles as the backbone of our analysis.”
“The set of human metabolites is a collective measure of the health of cells,” adds co-author Jeffrey Skolnick, “and by not arbitrary choosing any subset in advance, one lets the artificial intelligence figure out which are the key players for a given individual.”

Mass spectrometry can identify the presence of metabolites in the blood by detecting their mass and charge signatures. However, Ban says, the precise chemical makeup of a metabolite requires much more extensive characterization.
Ban explains that because the precise chemical composition of less than seven percent of the metabolites circulating in human blood have, thus far, been chemically characterized, it is currently impossible to accurately pinpoint the specific molecular processes contributing to an individual’s metabolic profile.
However, the research team recognized that, even without knowing the precise chemical make-up of each individual metabolite, the mere presence of different metabolites in the blood of different individuals, as detected by mass spectrometry, can be incorporated as features in the building of accurate machine learning-based predictive models (similar to the use of individual facial features in the building of facial pattern recognition algorithms).
“Thousands of metabolites are known to be circulating in the human bloodstream, and they can be readily and accurately detected by mass spectrometry and combined with machine learning to establish an accurate ovarian cancer diagnostic,” Ban says.
A new probabilistic approach
The researchers developed their integrative approach by combining metabolomic profiles and machine learning-based classifiers to establish a diagnostic test with 93 percent accuracy when tested on 564 women from Georgia, North Carolina, Philadelphia and Western Canada. 431 of the study participants were active ovarian cancer patients, and while the remaining 133 women in the study did not have ovarian cancer.
Further studies have been initiated to study the possibility that the test is able to detect very early-stage disease in women displaying no clinical symptoms, McDonald says.
McDonald anticipates a clinical future where a person with a metabolic profile that falls within a score range that makes cancer highly unlikely would only require yearly monitoring. But someone with a metabolic score that lies in a range where a majority (say, 90%) have previously been diagnosed with ovarian cancer would likely be monitored more frequently — or perhaps immediately referred for advanced screening. More

Rice University scientists have discovered a first-of-its-kind material, a 3D crystalline metal in which quantum correlations and the geometry of the crystal structure combine to frustrate the movement of electrons and lock them in place.
The find is detailed in a study published in Nature Physics. The paper also describes the theoretical design principle and experimental methodology that guided the research team to the material. One part copper, two parts vanadium and four parts sulfur, the alloy features a 3D pyrochlore lattice consisting of corner-sharing tetrahedra.
“We look for materials where there are potentially new states of matter or new exotic features that haven’t been discovered,” said study co-corresponding author Ming Yi, a Rice experimental physicist.
Quantum materials are a likely place to look, especially if they host strong electron interactions that give rise to quantum entanglement. Entanglement leads to strange electronic behaviors, including frustrating the movement of electrons to the point where they become locked in place.
“This quantum interference effect is analogous to waves rippling across the surface of a pond and meeting head-on,” Yi said. “The collision creates a standing wave that does not move. In the case of geometrically frustrated lattice materials, it’s the electronic wave functions that destructively interfere.”
Electron localization in metals and semimetals produces flat electronic bands, or flat bands. In recent years, physicists have found that the geometric arrangement of atoms in some 2D crystals, like Kagome lattices, can also produce flat bands. The new study provides empirical evidence of the effect in a 3D material.
Using an experimental technique called angle-resolved photoemission spectroscopy, or ARPES, Yi and study lead author Jianwei Huang, a postdoctoral researcher in her lab, detailed the band structure of the copper-vanadium-sulfur material and found it hosted a flat band that is unique in several ways.

“It turns out that both types of physics are important in this material,” Yi said. “The geometric frustration aspect was there, as theory had predicted. The pleasant surprise was that there were also correlation effects that produced the flat band at the Fermi level, where it can actively participate in determining the physical properties.”
In solid-state matter, electrons occupy quantum states that are divided in bands. These electronic bands can be imagined as rungs on a ladder, and electrostatic repulsion limits the number of electrons that can occupy each rung. Fermi level, an inherent property of materials and a crucial one for determining their band structure, refers to the energy level of the highest occupied position on the ladder.
Rice theoretical physicist and study co-corresponding author Qimiao Si, whose research group identified the copper-vanadium alloy and its pyrochlore crystal structure as being a possible host for combined frustration effects from geometry and strong electron interactions, likened the discovery to finding a new continent.
“It’s the very first work to really show not only this cooperation between geometric- and interaction-driven frustration, but also the next stage, which is getting electrons to be in the same space at the top of the (energy) ladder, where there’s a maximal chance of their reorganizing into interesting and potentially functional new phases,” Si said.
He said the predictive methodology or design principle that his research group used in the study may also prove useful to theorists who study quantum materials with other crystal lattice structures.
“The pyrochlore is not the only game in town,” Si said. “This is a new design principle that allows theorists to predictively identify materials in which flat bands arise due to strong electron correlations.”
Yi said there is also plenty of room for further experimental exploration of pyrochlore crystals.

“This is just the tip of the iceberg,” she said. “This is 3D, which is new, and just given how many surprising findings there have been on Kagome lattices, I’m envisioning that there could be equally or maybe even more exciting discoveries to be made in the pyrochlore materials.”
The research team included 10 Rice researchers from four laboratories. Physicist Pengcheng Dai’s research group produced the many samples needed for experimental verification, and Boris Yakobson’s research group in the Department of Materials Science and NanoEngineering performed first-principle calculations that quantified the flat-band effects produced by geometric frustration. ARPES experiments were conducted at Rice and at the SLAC National Accelerator Laboratory’s Stanford Synchrotron Radiation Lightsource in California and Brookhaven National Laboratory’s National Synchrotron Light Source II in New York, and the team included collaborators from SLAC, Brookhaven and the University of Washington.
The research used resources supported by a Department of Energy (DOE) contract to SLAC (DE-AC02-76SF00515) and was supported by grants from the Gordon and Betty Moore Foundation’s Emergent Phenomena in Quantum Systems Initiative (GBMF9470), the Robert A. Welch Foundation (C-2175, C-1411, C-1839), the DOE’s Office of Basic Energy Sciences (DE-SC0018197), the Air Force Office of Scientific Research (FA9550-21-1-0343, FA9550-21-1-0356), the National Science Foundation (2100741), the Office of Naval Research (ONR) (N00014-22-1-2753) and the ONR-managed Vannevar Bush Faculty Fellows program of the Department of Defense Basic Research Office (ONR-VB N00014-23-1-2870). More

Sensors that monitor infrastructure, such as bridges or buildings, or are used in medical devices, such as prostheses for the deaf, require a constant supply of power. The energy for this usually comes from batteries, which are replaced as soon as they are empty. This creates a huge waste problem. An EU study forecasts that in 2025, 78 million batteries will end up in the rubbish every day.
A new type of mechanical sensor, developed by researchers led by Marc Serra-​Garcia and ETH geophysics professor Johan Robertsson, could now provide a remedy. Its creators have already applied for a patent for their invention and have now presented the principle in the journal Advanced Functional Materials.
Certain sound waves cause the sensor to vibrate
“The sensor works purely mechanically and doesn’t require an external energy source. It simply utilises the vibrational energy contained in sound waves,” Robertsson says.
Whenever a certain word is spoken or a particular tone or noise is generated, the sound waves emitted — and only these — cause the sensor to vibrate. This energy is then sufficient to generate a tiny electrical pulse that switches on an electronic device that has been switched off.
The prototype that the researchers developed in Robertsson’s lab at the Switzerland Innovation Park Zurich in Dübendorf has already been patented. It can distinguish between the spoken words “three” and “four.” Because the word “four” has more sound energy that resonates with the sensor compared to the word “three,” it causes the sensor to vibrate, whereas “three” does not. That means the word “four” could switch on a device or trigger further processes. Nothing would happen with “three.”
Newer variants of the sensor should be able to distinguish between up to twelve different words, such as standard machine commands like “on,” “off,” “up” and “down.” Compared to the palm-​sized prototype, the new versions are also much smaller — about the size of a thumbnail — and the researchers are aiming to miniaturise them further.

Metamaterial without problematic substances
The sensor is what is known as a metamaterial: it’s not the material used that gives the sensor its special properties, but rather the structure. “Our sensor consists purely of silicone and contains neither toxic heavy metals nor any rare earths, as conventional electronic sensors do,” Serra-​Garcia says.
The sensor comprises dozens of identical or similarly structured plates that are connected to each other via tiny bars. These connecting bars act like springs. The researchers used computer modelling and algorithms to develop the special design of these microstructured plates and work out how to attach them to each other. It is the springs that determine whether or not a particular sound source sets the sensor in motion.
Monitoring infrastructure
Potential use cases for these battery-​free sensors include earthquake or building monitoring. They could, for example, register when a building develops a crack that has the right sound or wave energy.
There is also interest in battery-​free sensors for monitoring decommissioned oil wells. Gas can escape from leaks in boreholes, producing a characteristic hissing sound. Such a mechanical sensor could detect this hissing and trigger an alarm without constantly consuming electricity — making it far cheaper and requiring much less maintenance.
Sensor for medical implants
Serra-​Garcia also sees applications in medical devices, such as cochlear implants. These prostheses for the deaf require a permanent power supply for signal processing from batteries. Their power supply is located behind the ear, where there is no room for large battery packs. That means the wearers of such devices must replace the batteries every twelve hours. The novel sensors could also be used for the continuous measurement of eye pressure. “There isn’t enough space in the eye for a sensor with a battery,” he says.
“There’s a great deal of interest in zero-​energy sensors in industry, too,” Serra-​Garcia adds. He no longer works at ETH but at AMOLF, a public research institute in the Netherlands, where he and his team are refining the mechanical sensors. Their aim is to launch a solid prototype by 2027. “If we haven’t managed to attract anyone’s interest by then, we might found our own start-​up.” More

Global warming continues to pose a threat to human society and the ecological systems, and carbon dioxide accounts for the largest proportion of the greenhouse gases that dominate climate warming. To combat climate change and move towards the goal of carbon neutrality, researchers from The Hong Kong Polytechnic University (PolyU) have developed a durable, highly selective and energy-efficient carbon dioxide (CO2) electroreduction system that can convert CO2 into ethylene for industrial purposes to provide an effective solution for reducing CO2 emissions. This research was recently published in Nature Energy and won a Gold Medal at the 48th International Exhibition of Inventions Geneva in Switzerland.
Ethylene (C2H4) is one of the most in-demand chemicals globally and is mainly used in the manufacture of polymers such as polyethylene, which, in turn, can be used to make plastics and chemical fibres commonly used in daily life. However, it is still mostly obtained from petrochemical sources and the production process involves the creation of a very significant carbon footprint.
Led by Prof. Daniel LAU, Chair Professor of Nanomaterials and Head of the Department of Applied Physics, the research team adopted the method of electrocatalytic CO2 reduction — using green electricity to convert carbon dioxide into ethylene, providing a more environmentally friendly alternative and stable ethylene production. The research team is working to promote this emerging technology to bring it closer to mass production, closing the carbon loop and ultimately achieving carbon neutrality.
Prof. Lau’s innovation is to dispense with the alkali-metal electrolyte and use pure water as a metal-free anolyte to prevent carbonate formation and salt deposition. The research team denotes their design the APMA system, where A stands for anion-exchange membrane (AEM), P represents the proton-exchange membrane (PEM), and MA indicates the resulting membrane assembly.
When an alkali-metal-free cell stack containing the APMA and a copper electrocatalyst was constructed, it produced ethylene with a high specificity of 50%. It was also able to operate for over 1,000 hours at an industrial-level current of 10A — a very significant increase in lifespan over existing systems, meaning the system can be easily expanded to an industrial scale.
Further tests showed that the formation of carbonates and salts was suppressed, while there was no loss of CO2 or electrolyte. This is crucial, as previous cells using bipolar membranes instead of APMA suffered from electrolyte loss due to the diffusion of alkali-metal ions from the anolyte. The formation of hydrogen in competition with ethylene, another problem affecting earlier systems that used acidic cathode environments, was also minimised.
Another key feature of the process is the specialised electrocatalyst. Copper is used to catalyse a wide range of reactions across the chemical industry. However, the specific catalyst used by the research team took advantage of some distinctive features. The millions of nano-scale copper spheres had richly textured surfaces, with steps, stacking faults and grain boundaries. These “defects” — relative to an ideal metal structure — provided a favourable environment for the reaction to proceed.
Prof. Lau said, “We will work on further improvements to enhance the product selectivity and seek for collaboration opportunities with the industry. It is clear that this APMA cell design underpins a transition to green production of ethylene and other valuable chemicals and can contribute to reducing carbon emissions and achieving the goal of carbon neutrality.”
This innovative PolyU project was a collaboration with researchers from the University of Oxford, the National Synchrotron Radiation Research Centre of Taiwan and Jiangsu University. More