Aurelia Butler

Engineers have created intelligent 3D printers that can quickly detect and correct errors, even in previously unseen designs, or unfamiliar materials like ketchup and mayonnaise, by learning from the experiences of other machines.
The engineers, from the University of Cambridge, developed a machine learning algorithm that can detect and correct a wide variety of different errors in real time, and can be easily added to new or existing machines to enhance their capabilities. 3D printers using the algorithm could also learn how to print new materials by themselves. Details of their low-cost approach are reported in the journal Nature Communications.
3D printing has the potential to revolutionise the production of complex and customised parts, such as aircraft components, personalised medical implants, or even intricate sweets, and could also transform manufacturing supply chains. However, it is also vulnerable to production errors, from small-scale inaccuracies and mechanical weaknesses through to total build failures.
Currently, the way to prevent or correct these errors is for a skilled worker to observe the process. The worker must recognise an error (a challenge even for the trained eye), stop the print, remove the part, and adjust settings for a new part. If a new material or printer is used, the process takes more time as the worker learns the new setup. Even then, errors may be missed as workers cannot continuously observe multiple printers at the same time, especially for long prints.
“3D printing is challenging because there’s a lot that can go wrong, and so quite often 3D prints will fail,” said Dr Sebastian Pattinson from Cambridge’s Department of Engineering, the paper’s senior author. “When that happens, all of the material and time and energy that you used is lost.”
Engineers have been developing automated 3D printing monitoring, but existing systems can only detect a limited range of errors in one part, one material and one printing system. More

There’s still plenty of room at the bottom to generate piezoelectricity. Engineers at Rice University and their colleagues are showing the way.
A new study describes the discovery of piezoelectricity — the phenomenon by which mechanical energy turns into electrical energy — across phase boundaries of two-dimensional materials.
The work led by Rice materials scientists Pulickel Ajayan and Hanyu Zhu and their colleagues at Rice’s George R. Brown School of Engineering, the University of Southern California, the University of Houston, Wright-Patterson Air Force Base Research Laboratory and Pennsylvania State University appears in Advanced Materials.
The discovery could aid in the development of ever-smaller nanoelectromechanical systems, devices that could be used, for example, to power tiny actuators and implantable biosensors, and ultrasensitive temperature or pressure sensors.
The researchers show the atomically thin system of a metallic domain surrounding semiconducting islands creates a mechanical response in the material’s crystal lattice when subjected to an applied voltage.
The presence of piezoelectricity in 2D materials often depends on the number of layers, but synthesizing the materials with a precise number of layers has been a formidable challenge, said Rice research scientist Anand Puthirath, co-lead author of the paper. More

When early humans discovered how to harness fire, they were able to push back against the nightly darkness that enveloped them. With the invention and widespread adoption of electricity, it became easier to separate heat from light, work through the night, and illuminate train cars to highways. In recent years, old forms of electric light generation such as halogen lightbulbs have given way to more energy efficient alternatives, further cheapening the costs to brighten our homes, workplaces, and lives generally.
Unfortunately, however, white light generation by newer technologies such as light-emitting diodes (LEDs) is not straightforward and often relies on a category of materials called “rare-earth metals,” which are increasingly scarce. This has recently led scientists to look for ways to produce white light more sustainably. Researchers at Giessen University, the University of Marburg, and Karlsruhe Institute of Technology have recently uncovered a new class of material called a “cluster glass” that shows great potential for replacing LEDs in many applications.
“We are witnessing the birth of white-light generation technology that can replace current light sources. It brings all the requirements that our society asks for: availability of resources, sustainability, biocompatibility,” said Prof. Dr. Simone Sanna, Giessen University Professor and lead computational researcher on the project. “My colleagues from the experimental sciences, who observed this unexpected white light generation, asked for theoretical support. Cluster glass has an incredible optical response, but we don’t understand why. Computational methods can help to understand those mechanisms. This is exactly the challenge that theoreticians want to face.”
Sanna and his collaborators have turned to the power of high-performance computing (HPC), using the Hawk supercomputer at the High-Performance Computing Center Stuttgart (HLRS) to better understand cluster glass and how it might serve as a next-generation light source. They published their findings in Advanced Materials.
Clear-eyed view on cluster glass formation
If you are not a materials scientist or chemist, the word glass might just mean the clear, solid material in your windows or on your dinner table. Glass is actually a class of materials that are considered “amorphous solids;” that is, they lack an ordered crystalline lattice, often due to a rapid cooling process. At the atomic level, their constituent particles are in a suspended, disordered state. Unlike crystal materials, where particles are orderly and symmetrical across a long molecular distance, glasses’ disorder at the molecular level make them great for bending, fragmenting, or reflecting light. More

By using photons and electron spin qubits to control nuclear spins in a two-dimensional material, researchers at Purdue University have opened a new frontier in quantum science and technology, enabling applications like atomic-scale nuclear magnetic resonance spectroscopy, and to read and write quantum information with nuclear spins in 2D materials.
As published Monday (Aug. 15) in Nature Materials, the research team used electron spin qubits as atomic-scale sensors, and also to effect the first experimental control of nuclear spin qubits in ultrathin hexagonal boron nitride.
“This is the first work showing optical initialization and coherent control of nuclear spins in 2D materials,” said corresponding author Tongcang Li, a Purdue associate professor of physics and astronomy and electrical and computer engineering, and member of the Purdue Quantum Science and Engineering Institute.
“Now we can use light to initialize nuclear spins and with that control, we can write and read quantum information with nuclear spins in 2D materials. This method can have many different applications in quantum memory, quantum sensing, and quantum simulation.”
Quantum technology depends on the qubit, which is the quantum version of a classical computer bit. It is often built with an atom, subatomic particle, or photon instead of a silicon transistor. In an electron or nuclear spin qubit, the familiar binary “0” or “1” state of a classical computer bit is represented by spin, a property that is loosely analogous to magnetic polarity — meaning the spin is sensitive to an electromagnetic field. To perform any task, the spin must first be controlled and coherent, or durable.
The spin qubit can then be used as a sensor, probing, for example, the structure of a protein, or the temperature of a target with nanoscale resolution. Electrons trapped in the defects of 3D diamond crystals have produced imaging and sensing resolution in the 10-100 nanometer range. More

An international research team led by the University of Göttingen has detected novel quantum effects in high-precision studies of natural double-layer graphene and has interpreted them together with the University of Texas at Dallas using their theoretical work. This research provides new insights into the interaction of the charge carriers and the different phases, and contributes to the understanding of the processes involved. The LMU in Munich and the National Institute for Materials Science in Tsukuba, Japan, were also involved in the research. The results were published in Nature.
The novel material graphene, a wafer-thin layer of carbon atoms, was first discovered by a British research team in 2004. Among other unusual properties, graphene is known for its extraordinarily high electrical conductivity. If two individual graphene layers are twisted at a very specific angle to each other, the system even becomes superconducting, i.e. conducts electricity without any resistance, and exhibits other exciting quantum effects such as magnetism. However, the production of such twisted graphene double-layers has so far required increased technical effort.
This novel study used the naturally occurring form of double-layer graphene, where no complex fabrication is required. In a first step, the sample is isolated from a piece of graphite in the laboratory using a simple adhesive tape. To observe quantum mechanical effects, the Göttingen team then applied a high electric field perpendicular to the sample: the electronic structure of the system changes and a strong accumulation of charge carriers with similar energy occurs.
At temperatures just above absolute zero of minus 273.15 degrees Celsius, the electrons in the graphene can interact with each other — and a variety of complex quantum phases emerge completely unexpectedly. For example, the interactions cause the spins of the electrons to align, making the material magnetic without any further external influence. By changing the electric field, researchers can continuously change the strength of the interactions of the charge carriers in the double-layer graphene. Under specific conditions, the electrons can be so restricted in their freedom of movement that they form their own electron lattice and can no longer contribute to transporting charge due to their mutual repulsive interaction. The system is then electrically insulating.
“Future research can now focus on investigating further quantum states,” say Professor Thomas Weitz and PhD student Anna Seiler, Faculty of Physics at Göttingen University. “In order to access other applications, for example novel computer systems such as quantum computers, researchers would need to find how these results could be achieved at higher temperatures. However, a major advantage of the current system developed in our new research lies in the simplicity of the fabrication of the materials.”
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Materials provided by University of Göttingen. Note: Content may be edited for style and length. More

A component of computer processors that connects different parts of the chip can be exploited by malicious agents who seek to steal secret information from programs running on the computer, MIT researchers have found.
Modern computer processors contain many computing units, called cores, which share the same hardware resources. The on-chip interconnect is the component that enables these cores to communicate with each other. But when programs on multiple cores run simultaneously, there is a chance they can delay one another when they use the interconnect to send data across the chip at the same time.
By monitoring and measuring these delays, a malicious agent could conduct what is known as a “side-channel attack” and reconstruct secret information that is stored in a program, such as a cryptographic key or password.
MIT researchers reverse-engineered the on-chip interconnect to study how this kind of attack would be possible. Drawing on their discoveries, they built an analytical model of how traffic flows between the cores on a processor, which they used to design and launch surprisingly effective side-channel attacks. Then they developed two mitigation strategies that enable a user to improve security without making any physical changes to the computer chip.
“A lot of current side-channel defenses are ad hoc — we see a little bit of leakage here and we patch it. We hope our approach with this analytical model pushes more systematic and robust defenses that eliminate whole classes of attacks at the same time,” says co-lead author Miles Dai, MEng ’21.
Dai wrote the paper with co-lead author Riccardo Paccagnella, a graduate student at the University of Illinois at Urbana-Champaign; Miguel Gomez-Garcia ’22; John McCalpin, a research scientist at Texas Advanced Computing Center; and senior author Mengjia Yan, the Homer A. Burnell Career Development Assistant Professor of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). The research is being presented at the USENIX Security Conference. More

Researchers have created a mathematical model to predict genetic resistance to antimalarial drugs in Africa to manage one of the biggest threats to global malarial control.
Malaria is a life-threatening disease caused by parasites and spread to humans through infected mosquitos. It is preventable and curable, yet resistance to current antimalarial drugs is causing avoidable loss of life. The World Health Organisation estimated there were 241 million cases of malaria worldwide in 2020, with more than 600,000 deaths.
In research published today in PLOS Computational Biology, an international research team used data from the WorldWide Antimalarial Resistance Network (WWARN), a global, scientifically independent collaboration, to map the prevalence of genetic markers that indicate resistance to Plasmodium falciparum — the parasite that causes malaria.
Lead author Associate Professor Jennifer Flegg from the University of Melbourne said malaria has devastating impacts on lower-income countries and effective treatment is key to elimination.
“The antimalarial drug sulfadoxine-pyrimethamine (SP) is commonly used in various preventative malaria treatment programs in Africa, particularly for infants, young children and during pregnancy. But we know its efficacy as a treatment is threatened in areas where resistance to SP is high,” Associate Professor Flegg said.
“The statistical mapping tool we have developed is critical for health organisations to understand the spread of antimalarial resistance. The model takes in the data that is available and fills in the gaps by making continuous predictions in space and time. More

They say timing is everything, and that couldn’t be more true for cell cycle progression and differentiation. Now, researchers from Japan have found that the circadian clock is crucial for proper plant development.
In a study published in Cell Reports, researchers at Nara Institute of Science and Technology (NAIST) have revealed that the circadian clock plays a guiding role in plant cell differentiation.
The circadian clock is involved in both cell-cycle progression and cell fate transitions. The involvement of circadian clocks in the process of differentiation has been shown in many multicellular organisms; however, how plant circadian clocks regulate cell differentiation remains unclear.
“Elucidating how the circadian clock is involved in cell differentiation is important to understand the basis of cell fate determination,” explains Motomu Endo, senior author of the study. “However, this has been difficult to investigate in plants because it is challenging to isolate single plants’ cells, and existing analytical methods rely on “pseudo-time” analysis that does not accurately reflect normal circadian rhythms.”
To address these challenges, the researchers used tiny glass tubes to isolate individual cells from developing plants and analyzed the expression of various genes related to circadian rhythms and cell differentiation in each cell. They then developed a new algorithm called PeakMatch to reconstruct actual-time gene expression patterns from the single-cell datasets.
“Using this powerful approach, we were able to show that the expression profile of clock genes is changed prior to cell differentiation,” states Endo. “Specifically, in early differentiating cells, the induction of the clock gene LUX ARRYTHMO directly targets genes involved in cell-cycle progression to regulate cell differentiation.”
Further investigation showed that large-scale changes in the circadian clock profile in undifferentiated cells induce the expression of the clock gene LUX, which directly triggers cell differentiation.
“Taken together, our results show that the plant circadian clock plays a guiding role in cell differentiation,” says Endo. “Importantly, our study also provides an approach for time-series analysis at single-cell resolution.”
Because the development of circadian rhythms during cell differentiation is observed in animals as well as in plants, the finding that clock genes directly regulate cell fate determination and cell division may help understand how cell differentiation is controlled in multicellular organisms. The newly developed PeakMatch algorithm can also be applied to all kinds of single-cell transcriptomes in other organisms.
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Materials provided by Nara Institute of Science and Technology. Note: Content may be edited for style and length. More