Computers Math

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.
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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.”
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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. 
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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

Some electronics can bend, twist and stretch in wearable displays, biomedical applications and soft robots. While these devices’ circuits have become increasingly pliable, the batteries and supercapacitors that power them are still rigid. Now, researchers in ACS’ Nano Letters report a flexible supercapacitor with electrodes made of wrinkled titanium carbide — a type of MXene nanomaterial — that maintained its ability to store and release electronic charges after repetitive stretching.
One major challenge stretchable electronics must overcome is the stiff and inflexible nature of their energy storage components, batteries and supercapacitors. Supercapacitors that use electrodes made from transitional metal carbides, carbonitrides or nitrides, called MXenes, have desirable electrical properties for portable flexible devices, such as rapid charging and discharging. And the way that 2D MXenes can form multi-layered nanosheets provides a large surface area for energy storage when they’re used in electrodes. However, previous researchers have had to incorporate polymers and other nanomaterials to keep these types of electrodes from breaking when bent, which decreases their electrical storage capacity. So, Desheng Kong and colleagues wanted to see if deforming a pristine titanium carbide MXene film into accordion-like ridges would maintain the electrode’s electrical properties while adding flexibility and stretchability to a supercapacitor.
The researchers disintegrated titanium aluminum carbide powder into flakes with hydrofluoric acid and captured the layers of pure titanium carbide nanosheets as a roughly textured film on a filter. Then they placed the film on a piece of pre-stretched acrylic elastomer that was 800% its relaxed size. When the researchers released the polymer, it shrank to its original state, and the adhered nanosheets crumpled into accordion-like wrinkles.
In initial experiments, the team found the best electrode was made from a 3 µm-thick film that could be repetitively stretched and relaxed without being damaged and without modifying its ability to store an electrical charge. The team used this material to fabricate a supercapacitor by sandwiching a polyvinyl(alcohol)-sulfuric acid gel electrolyte between a pair of the stretchable titanium carbide electrodes. The device had a high energy capacity comparable to MXene-based supercapacitors developed by other researchers, but it also had extreme stretchability up to 800% without the nanosheets cracking. It maintained approximately 90% of its energy storage capacity after being stretched 1,000 times, or after being bent or twisted. The researchers say their supercapacitor’s excellent energy storage and electrical stability is attractive for stretchable energy storage devices and wearable electronic systems.
The authors acknowledge funding from the Key Research and Development Program of Jiangsu Provincial Department of Science and Technology of China, China Postdoctoral Science Foundation and High-Level Entrepreneurial and Innovative Talents Program of Jiangsu Province.
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Materials provided by American Chemical Society. Note: Content may be edited for style and length. More

When stretched or deformed, shape memory polymers return to their original shapes after heat or light is applied. These materials show great promise for soft robotics, smart biomedical devices and deployable space structures, but until now they haven’t been able to store enough energy. Now, researchers reporting in ACS Central Science have developed a shape memory polymer that stores almost six times more energy than previous versions.
Shape memory polymers alternate between an original, undeformed state and a secondary, deformed state. The deformed state is created by stretching the polymer and is held in place by molecular changes, such as dynamic bonding networks or strain-induced crystallization, that are reversed with heat or light. The polymer then returns to its original state through the release of stored entropic energy. But it’s been challenging for scientists to make these polymers perform energy-intensive tasks. Zhenan Bao and colleagues wanted to develop a new type of shape memory polymer that stretches into a stable, highly elongated state, allowing it to release large amounts of energy when returning to its original state.
The researchers incorporated 4-,4′-methylene bisphenylurea units into a poly(propylene glycol) polymer backbone. In the polymer’s original state, polymer chains were tangled and disordered. Stretching caused the chains to align and form hydrogen bonds between urea groups, creating supermolecular structures that stabilized the highly elongated state. Heating caused the bonds to break and the polymer to contract to its initial, disordered state.
In tests, the polymer could be stretched up to five times its original length and store up to 17.9 J/g energy — almost six times more energy than previous shape memory polymers. The team demonstrated that the stretched material could use this energy to lift objects 5,000 times its own weight upon heating. They also made an artificial muscle by attaching the pre-stretched polymer to the upper and lower arm of a wooden mannequin. When heated, the material contracted, causing the mannequin to bend its arm at the elbow. In addition to its record-high energy density, the shape memory polymer is also inexpensive (raw materials cost about $11 per lb) and easy to make, the researchers say.
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Materials provided by American Chemical Society. Note: Content may be edited for style and length. More