Aurelia Butler

When scientists study unconventional superconductors — complex materials that conduct electricity with zero loss at relatively high temperatures — they often rely on simplified models to get an understanding of what’s going on.
Researchers know these quantum materials get their abilities from electrons that join forces to form a sort of electron soup. But modeling this process in all its complexity would take far more time and computing power than anyone can imagine having today. So for understanding one key class of unconventional superconductors — copper oxides, or cuprates — researchers created, for simplicity, a theoretical model in which the material exists in just one dimension, as a string of atoms. They made these one-dimensional cuprates in the lab and found that their behavior agreed with the theory pretty well.
Unfortunately, these 1D atomic chains lacked one thing: They could not be doped, a process where some atoms are replaced by others to change the number of electrons that are free to move around. Doping is one of several factors scientists can adjust to tweak the behavior of materials like these, and it’s a critical part of getting them to superconduct.
Now a study led by scientists at the Department of Energy’s SLAC National Accelerator Laboratory and Stanford and Clemson universities has synthesized the first 1D cuprate material that can be doped. Their analysis of the doped material suggests that the most prominent proposed model of how cuprates achieve superconductivity is missing a key ingredient: an unexpectedly strong attraction between neighboring electrons in the material’s atomic structure, or lattice. That attraction, they said, may be the result of interactions with natural lattice vibrations.
The team reported their findings today in Science.
“The inability to controllably dope one-dimensional cuprate systems has been a significant barrier to understanding these materials for more than two decades,” said Zhi-Xun Shen, a Stanford professor and investigator with the Stanford Institute for Materials and Energy Sciences (SIMES) at SLAC. More

A University of Texas at San Antonio (UTSA) researcher is part of a collaboration that has set a world record for innovation in quantum computing. The accomplishment comes from R. Tyler Sutherland, an assistant professor in the College of Sciences Department of Physics and Astronomy and the College of Engineering and Integrated Design’s Department of Electrical Engineering, who developed the theory behind the record setting experiment.
Sutherland and his team set the world record for the most accurate entangling gate ever demonstrated without lasers.
According to Sutherland, an entangling gate takes two qubits (quantum bits) and creates an operation on the secondary qubit that is conditioned on the state of the first qubit.
“For example, if the state of qubit A is 0, an entangling gate doesn’t do anything to qubit B, but if the state of qubit A is 1, then the gate flips the state of qubit B from 0 to 1 or 1 to 0,” he said. “The name comes from the fact that this can generate a quantum mechanical property called ‘entanglement’ between the qubits.”
Sutherland adds that making the entangling gates in your quantum computer “laser-free” enables more cost-effective and easier to use quantum computers. He says the price of an integrated circuit that performs a laser-free gate is negligible compared to the tens of thousands of dollars it costs for a laser that does the same thing.
“Laser-free gate methods do not have the drawbacks of photon scattering, energy, cost and calibration that are typically associated with using lasers,” said Sutherland. “This alternative gate method matches the accuracy of lasers by instead using microwaves, which are less expensive and easier to calibrate.”
This quantum computing accomplishment is detailed in a paper Sutherland co-authored titled, “High-fidelity laser-free universal control of trapped-ion qubits.” It was published in the scientific journal, Nature, on September 8.
Quantum computers have the potential to solve certain complex problems exponentially faster than classical supercomputers. One of the most promising uses for quantum computers is to simulate quantum mechanical processes themselves, chemical reactions for example, which could exponentially reduce the experimental trial and error required to solve difficult problems. These computers are being explored in many industries including science, engineering, finance and logistics.
“Broadly speaking, the goal of my research is to increase human control over quantum mechanics.” said Sutherland. “Giving people power over a different part of nature hands them a new toolkit. What they will eventually build with it is uncertain.”
That uncertainty, says Sutherland, is what excites him most.
Sutherland’s research background includes quantum optics, which studies how quantum mechanical systems emit light. He earned his Ph.D. at Purdue University and went on to Lawrence Livermore National Laboratory for his postdoc, where he began working on experimental applications for quantum computers.
He became a tenure-track assistant professor at UTSA last August as part of the university’s Quantum Computation and Quantum Information Cluster Hiring Initiative.
Story Source:
Materials provided by University of Texas at San Antonio. Original written by Bruce Forey. Note: Content may be edited for style and length. More

With scientists beginning to more seriously consider constructing bases on celestial bodies such as the moon, the idea of space mining is growing in popularity.
After all, if someone from Los Angeles was moving to New York to build a house, it would be a lot easier to buy the building materials in New York rather than buy them in Los Angeles and lug them 2,800 miles. Considering the distance between Earth and the moon is about 85 times greater, and that getting there requires defying gravity, using the moon’s existing resources is an appealing idea.
A University of Arizona team, led by researchers in the College of Engineering, has received $500,000 in NASA funding for a new project to advance space-mining methods that use swarms of autonomous robots. As a Hispanic-Serving Institution, the university was eligible to receive funding through NASA’s Minority University Research and Education Project Space Technology Artemis Research Initiative.
“It’s really exciting to be at the forefront of a new field,” said Moe Momayez, interim head of the Department of Mining and Geological Engineering and the David & Edith Lowell Chair in Mining and Geological Engineering. “I remember watching TV shows as a kid, like ‘Space: 1999,’ which is all about bases on the moon. Here we are in 2021, and we’re talking about colonizing the moon.”
Blast Off!
According to the Giant Impact Hypothesis, Earth and the moon came from a common parent body, so scientists expect their chemical compositions to be relatively similar. Mining on the moon’s surface could turn up rare earth metals needed for technologies such as smartphones and medical equipment, titanium for use in titanium alloys, precious metals such as gold and platinum, and helium-3 — a stable helium isotope that could fuel nuclear power plants but is extremely rare on Earth. More

QUT researchers working on complicated problems in agriculture, ecology and medicine have developed a mathematical model to enable faster solutions.
Questions about intervention, how strong and how long, are just some of the judgment calls faced by doctors and scientists during everyday decision-making.
From crop production to chemotherapy, new research published in Journal of the Royal Society Interface, improves how to determine the ‘best’ intervention strategies.
Professor Matthew Simpson, PhD researcher Jesse Sharp and Professor Kevin Burrage from QUT’s Centre for Data Science and Australian Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) have developed the new mathematical method to faster simulate different scenarios to reach optimal solutions.
Mr Sharp, who is studying his PhD, said the method involved optimal control theory which could be described as a “science of trade-offs” between competing objectives.
“Using mathematical optimisation techniques help us to make smarter, more efficient resource allocation decisions,” he said. More

The need for more powerful electronic devices in today’s society is curtailed by our ability to produce highly conductive semiconductors that can withstand the harsh, high temperature fabrication processes of high-powered devices.
Gallium nitride (GaN)-on-diamond shows promise as a next-generation semiconductor material due to the wide band gap of both materials, allowing for high conductivity, and diamond’s high thermal conductivity, positioning it as a superior heat-spreading substrate. There have been attempts at creating a GaN-on-diamond structure by combining the two components with some form of transition or adhesion layer, but in both cases the additional layer significantly interfered with diamond’s thermal conductivity — defeating a key advantage of the GaN-diamond combination.
“There is thus a need for a technology that can directly integrate diamond and GaN,” states Jianbo Liang, Associate Professor of the Graduate School of Engineering, Osaka City University (OCU), and first author of the study, “However, due to large differences in their crystal structures and lattice constants, direct diamond growth on GaN and vice versa is impossible.”
Fusing the two elements together without any intermediate layers, known as Wafer direct bonding, is one way of getting around this mismatch. However, to create a sufficiently high bonding strength many direct bonding methods, the structure needs to be heated to extremely high degrees (typically 500 degrees Celsius) in something called a post-annealing process. This generally causes cracks in a bonded sample of dissimilar materials due to a thermal expansion mismatch — this time defeating any chance of the GaN-diamond structure surviving the extremely high temperatures that high-power devices go through during fabrication.
“In previous work, we used surface activated bonding (SAB) to successfully fabricate various interfaces with diamond at room temperature, all exhibiting a high thermal stability and an excellent practicality,” says research lead Professor Naoteru Shigekawa.
As reported this week in the journal ADVANCED MATERIALS, Liang, Shigekawa and their colleagues from Tohoku University, Saga University, and Adamant Namiki Precision Jewel. Co., Ltd, use the SAB method to successfully bond GaN and diamond, and demonstrate that the bonding is stable even when heated to 1,000 degrees Celsius.
SAB creates highly strong bonds between different materials at room temperature by atomically cleaning and activating the bonding surfaces to react when brought into contact with each other.
As the chemical properties of GaN is completely different from materials the research team has used in the past, after they used SAB to create the GaN-on-diamond material, they used a variety of techniques to test the stability the bonding site — or heterointerface. To characterize the residual stress in the GaN of the heterointerface they used micro-Raman spectroscopy, transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy shed light on the nanostructure and the atomic behavior of the heterointerface, electron energy-loss spectroscopy (EELS) showed the chemical bonding states of the carbon atoms at the heterointerface, and the thermal stability of the heterointerface was tested at 700 degrees Celsius in N2 gas ambient pressure, “which is required for GaN-based power device fabrication processes,” states Liang.
Results showed that at the heterointerface an intermediate layer of approximately 5.3 nm formed that was a mixture of amorphous carbon and diamond in which Ga and N atoms were distributed. As the team increased annealing temperatures, they noticed a decrease in the layer thickness, “due to a direct conversion of amorphous carbon into diamond,” as Shigekawa puts it. After annealing at 1,000 degrees Celsius, the layer decreased to 1.5nm, “suggesting the intermediate layer can be completely removed by optimizing the annealing process,” continues the professor. Although numbers for compressive strength of the heterointerface improved as annealing temperatures increased, they did not match those of GaN-on-diamond structures formed by crystal growth.
However, “as no peeling was observed at the heterointerface after annealing at 1000 degrees Celsius,” states Liang, “these results indicate that the GaN/diamond heterointerface can withstand harsh fabrications processes, with temperature rise in gallium nitride transistors being suppressed by a factor of four.” More

Last season, Kansas City Chiefs quarterback Patrick Mahomes boasted a 66.3 pass-completion percentage.
But Mahomes’ impressive stat pales compared with the accuracy of MAHOMES, or Metal Activity Heuristic of Metalloprotein and Enzymatic Sites, a machine-learning model developed at the University of Kansas — and named in the quarterback’s honor — that could lead to more effective, eco-friendly and cheaper drug therapies and other industrial products.
Instead of targeting wide receivers, MAHOMES differentiates between enzymatic and non-enzymatic metals in proteins with a precision rate of 92.2%. A team at KU recently published results on this machine-learning approach to differentiating enzymes in Nature Communications.
“Enzymes are super interesting proteins that do all the chemistry — an enzyme does a chemical reaction on something to transform it from one thing to another thing,” said corresponding author Joanna Slusky, associate professor of molecular biosciences and computational biology at KU. “Everything that you bring into your body, your body breaks it down and makes it into new things, and that process of breaking down and making into new things — all of that is due to enzymes.”
Slusky and graduate student collaborators in her lab, Ryan Feehan (the Chiefs fan who named MAHOMES) and Meghan Franklin of KU’s Center for Computational Biology, sought to use computers to distinguished between metalloproteins, which don’t perform chemical reactions, and metalloenzymes, which facilitate chemical reactions with amazing power and efficiency.
The problem is metalloproteins and metalloenzymes are in many ways identical. More

Soft robots driven by pressurized fluids could explore new frontiers and interact with delicate objects in ways that traditional rigid robots can’t. But building entirely soft robots remains a challenge because many of the components required to power these devices are, themselves, rigid. 
Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed electrically-driven soft valves to control hydraulic soft actuators. These valves could be used in assistive and therapeutic devices, bio-inspired soft robots, soft grippers, surgical robots, and more.
The research was published in the Proceedings of the National Academy of Sciences (PNAS).  
“Today’s rigid regulation systems considerably limit the adaptability and mobility of fluid-driven soft robots,” said Robert J. Wood, the Harry Lewis and Marlyn McGrath Professor of Engineering and Applied Sciences at SEAS and senior author of the paper. “Here, we have developed soft and lightweight valves to control soft hydraulic actuators that open up possibilities for soft on-board controls for future fluidic soft robots.”
Soft valves aren’t new but so far none have achieved the pressure or flow rates required by many existing hydraulic actuators. To overcome those limitations, the team developed new electrically powered dynamic dielectric elastomer actuators (DEAs). These soft actuators have ultra-high power density, are lightweight, and can run for hundreds of thousands of cycles. The team combined these new dielectric elastomer actuators with a soft channel, resulting in a soft valve for fluidic control. 
“These soft valves have a fast response time and are able to control fluidic pressure and flow rates that match the needs of hydraulic actuators,” said Siyi Xu, a graduate student at SEAS and first author of the paper. “These valves give us fast, powerful control of macro-and small-scale hydraulic actuators with internal volume ranging from hundreds of microliters to tens of milliliters.” 
Using the DEA soft valves, the researchers demonstrated control of hydraulic actuators of different volumes and achieved independent control of multiple actuators powered by a single pressure source. 
“This compact and light-weight DEA valve is capable of unprecedented electrical control of hydraulic actuators, showing the potential for future on-board motion control of soft fluid-driven robots,” said Xu. 
The research was co-authored by Yufeng Chen, Nak-Seung Patrick Hyun, and Kaitlyn Becker. It was supported by the National Science Foundation and the National Robotic Initiative under award CMMI-1830291. 
Story Source:
Materials provided by Harvard John A. Paulson School of Engineering and Applied Sciences. Original written by Leah Burrows. Note: Content may be edited for style and length. More