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Why Neutrons get a wider angle on DNA and RNA to advance 3-D models

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Why Neutrons get a wider angle on DNA and RNA to advance 3-D models

Oak Ridge National Laboratory (ORNL) to enable more precise computer simulation to acquire new information about the scientific DNA molecules and RNA molecules of the National Institute of Standards and Technology (NIST) and University of Maryland and interact with each other.

Are using neutron in Some from protein to viruses Solving three-dimensional structures of basic genetic material in the body will play an important role in the drug discovery and the development of important medical treatments.

Alexander Grechayev of NIST, who led the NIST team, said, “A better understanding of the structure and mobility of both RNA, RNA and RNA can help us to answer why and why drugs work and find out Help. ” Main talk at nuclear level “. The energy utility facility of the Ministry of Energy, located in OFNL, was researching the neutron dispersion in HFIR.

The team used HFIR’s BIO-SANS tool to operate a small, wide-angle neutron scattering, a technique that was previously not done on RNA in DNA samples and solutions due to limited experimental capacities.

“Until recently it was not possible to obtain a wide range of biomedical angles in the solution using the neutron scattering, and the OK ridge is the only place where you can do this kind of work,” Greeshche said.

The expansion of neutron dispersion capabilities in the solution is part of an evolved effort towards a more integrated approach to structural biology that connects crystalline studies, solution methods, and other experimental and computational techniques to increase the understanding of DNA and protein structures. .

Computer simulation of biomolecules was well informed by X-ray crystallography. The primary technique uses X-rays to determine the sequence of atoms in the “crystallized” sample for analysis.

To obtain high-quality data using this technique, generally diluted biological samples are concentrated in the solution and hardened in the crystal with a similar structure.

X-ray crystals work particularly well for solid biom with strong stable structures, but flexible biological molecules such as DNA and RNA, which adopt many “matches” or are less suitable for crystallization.

Within living cells, DNA and RNA can be transferred, change shape and can react differently to environmental effects such as pH or temperature, which is important to represent but it is difficult to describe.

Grazev said, “Pegas tightly closes the molecules tightly, limits their movements and want to see some structural information.”

In a solution, many techniques have been successfully implemented for DNA and RNA, including X-ray dispersion and NMR spectroscopy, which both produce significant data. However, there are significant differences between experimental scattering data and the best crystalline structures available for DNA and DNA.

The team switched to neutron to find out why.

“Rodrigo Acevedo of Maryland said,” Neutron interacts with biomolecules in different ways, so we can use them as an independent source of data.

While X-rays work well to identify heavy atoms such as carbon, oxygen, and phosphorus, neutrons are ideal for mild hydrogen atoms that are binding with DNA filaments for example. In addition, neutrons provide a benefit in biomolecules investigation because they are neither destructive nor harmful.

Using Bio-SNS tools in HFIR, researchers have been able to collect structural information in a solution that is not easily achieved by other experimental techniques.

The solution requires the use of high neutron flux and wide angle detectors to collect high-resolution dispersion patterns to detect atomic level structures of DNA and RNA.

Gresave says, neutron use is not uncommon for collecting structural information about biomolecules. In thin solutions, small organic molecular samples often produce noise dispersion patterns, making data analysis difficult.

Bio-SNS Tool Scientist, Volker Urban said, “HFIR’s Bio-SNS is one of the few neutron tools in the world which has the ability to catch small scattered and wide angles at the same time and combine global and local details. . ”

“We have been able to obtain some high-resolution data on the dispersion of neutrons, which have been collected not only on DNA and RNA, but also on broad biomolecules as well, from wide angles,” Greeshche said.

By combining new information gathered through the dispersion of neutron in the solution of X-ray dispersion and other data from MRI, the NIST-Maryland group expects to obtain a more comprehensive picture of DNA and RNA structures. RNA), in addition to the expansion of methods to identify particle structures with neutron-based technologies.

Why Freezing bubbles viral video inspired research now published

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Why Freezing bubbles viral video inspired research now published

Without hoping to do more than answer a video question on YouTube, Virginia Tech researchers may have changed the way people think about the cold.

Virginia Tech researcher Jonathan Boriko, assistant professor of mechanical engineering at the Engineering College, was a student who watched a video on YouTube to freeze the soap bubbles. Creating a stunning landscape of snow crystals floating around bubble engineers is a wonder why this event is so.

Researchers, Farzad Ahmadi and Sorb Nath, both graduate students in mechanical engineering and a university researcher in engineering and mechanical science, Christian Kennett, who graduated in 2019, did a literary research and found that nobody ever studied films or bubbles did not do. Freeze.

The results of the team’s investigation, which started as a simple “Why”, was published in the Nature Communications Journal, which shows the underlying physics behind the reasons for jumping into ice crystal bubbles and revolving around them. , Thus changing the concepts about the free process.

“We started by freezing a bubble in the laboratory, using a frozen substrate,” Borico explained. “What we found was that the bubble would get frozen from the bottom to a certain point and then stopped.

We did not find the beautiful snowball effect which we saw in the video, but Verzad has created a brilliant model that can accurately predict That’s where the cold front will stop depending on the size of the bubble and the temperature of the air. ”

Because the bubble crust is subtle, the hot air temperature in the laboratory completely prevents the freezing of the bubbles from freezing. By going into the freezer room, the team tried to experiment again, believing that they found how floating ice crystals were formed.

“We have not seen it in the refrigerator,” he said. “But we tried again to store bubbles on ice instead of dried substrate, and this is where we saw what we were seeing.”

By using temperatures below 20 degrees Celsius and using ice layer, the bubble was filled with swirling crystals soon, which prevented a full freeze of the bubble and opened the researcher’s eyes.

Ahmadi said, “When the bubble gets deposited on the snowy substrate, the bubble starts to freeze, which causes heat.” “Bottom of the bubble, in this case, the rest gets warmer than the bubbles, there is heat from the cold.”

Molecular energy is released when water molecules are merged together in a solid, closed grid, resulting in approximately 14 degrees in temperature – minus 20 on the top of the bubble and 6 degree in frozen base.

Ahmadi said, “The temperature above and below is not the surface tension.” “Stress causes colds to flow from winter.”

This flow is known as the Marangoni flow. When it is in the freezing bubble, the flow tears the ice crystals down the bubble and the liquid rotates around the crust where it grows up to the maximum bubble.

“In the past, we thought that with the speed at which we can grow faster on the freeze front, depending on that, some can freeze”.

“We know that the flow of Marigans due to the freeze will create hundreds of additional free fronts from the ice crystals removed from the bottom, so we realized that not only is the movement growing rapidly, but the situation like ours In, you can manipulate hundreds of fronts, freeze very fast to freeze some. ”

It took a video on YouTube, and the fridge was kept at a negative temperature of 20 degrees Celsius, and some engineering students eventually had cold tolerance to find out why frozen soap bubbles appear in a snowball .

The trick is a famous winter scientific experiment when the temperature drops below freezing: go out, bubbling a soap bubble, gently pinch it on some ice or ice, and until the snowball becomes sensitive, the crystal is around the film. Keep on moving. It is visually stunning – but until recently, people did not know why the bubbles were frozen in this special, attractive way.

Generally, when a drop of water or a pond gets accumulated, it starts to freeze in the coldest place, where it encounters ice or other snow.

In the fresh snow the adjacent water gets accumulated, which makes a beautifully organized progress through the pool, which is called freezing point. But when a bubble accumulates in a very cold room, then all these demands come out quickly from the window.

It grows naturally, gets frozen from the bottom, where the snow touches upward, but then, suddenly, hundreds of frozen fronts appear on the surface of the bubble.

“It’s like a spin crystal you see in a snowball game,” says Jonathan Boriko, co-author of a new article on the impact of the globe, which has now been published in Nature Communications magazine. That’s why we call it snowball effect.

How perfect quantum portal emerges at exotic interface

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How perfect quantum portal emerges at exotic interface

Researchers at the University of Maryland have discovered the most direct evidence of a quantitative dispute so far that allows molecules to stop an obstacle, as if it was not there.

The result, which appeared in the June 20, 2019 issue of nature, has enabled engineers to design more compatible components for quantum computers, quantum sensors and other devices.

The new experiment is a note of the Klein tunnel, which is a special case of a normal quantum event. In the quantum world, tunnels allow particles such as electrons to pass through an obstacle, even if they do not actually have enough energy to climb. The long hurdle usually makes it more difficult and leaves less particles.

The clay tunnel occurs when the barrier becomes completely transparent, opening a door that can pass without regard to the height of the particle barrier. Scientists and engineers of the UNM Center for Nanophysics and Advanced Materials (CNAM), the Joint Quantum Institute (JQI) and Center for Intensive Material Theory (CMTC) have made the most measurements so far with appointments in the UMD UMD department.

Ichiro Tekuchi, professor of materials science and engineering (MSE) and author of the new study at UMD, says, “The Klein Tunnel was originally relatively effective, it was predicted for almost a hundred years ago.” “Until recently, however, you can not inspect it.”

It was almost impossible to gather evidence of the Klein tunnel, where the world’s first high-energy quantum particle was predicted to be close to the speed of light for the first time.

But in the last few decades, scientists have found that some rules that control the fast-moving quantum particles also apply to relatively slow moving particles near the surface of some unusual substances.

Such a substance – is used by researchers in a new study – Samarium (SmB6), a substance which is permanently isolated at low temperature.

In a natural insulator such as wood, rubber or air, the electrons are closed, unable to move even after the voltage is applied. Thus, electrons can not be made a current in the insulator, while spinning their companions freely in a metal wire.

Occasional insulators like SmB6 behave like composite materials. At sufficiently low temperatures, the interior of SMB6 is isolated, but the surface is metallic and gives electrons freedom of motion.

Apart from this, in the direction in which the electrons move, it is close enough to be called a spin which can be indicated above or below. For example, the electrons on the right always rotate upwards, and the electrons on the left will rotate downward.

The metal surface of SLB 6 was not enough to monitor the Klein tunnel. It has been learned that Tekuchi and his colleagues need to convert the SmB6 surface into a superconductor – a material that can connect the power supply without resistance.

To convert SmB6 to SuperConductor, place a thin layer of it on a layer of Y3-hexaboride. When the entire group was cooled down to a few degrees of absolute zero, then YB6 became a super conductor, and due to its proximity, the surface of SmB6 metal also became a super conductor.

Professor of Physics at UMD University and director of CNAM and co-author of the paper, JohnPier Paglione, said that it was “a piece of opportunity” that SMB6 and its interferon counterpart share the same crystalline structure.

“The multi-disciplinary team, which we have, is the key to success. Our experts in topographical physics, thin-film synthesis, spectroscopy and theoretical understanding have already brought us to this point,” says Baglioni.

Performance of a combination of the right control mixture for the Klein tunnel. By making the tip of a small metal in contact with the top of SmB6, the team measured the transfer of electrons from the side in the supervisor. They have fully observed dual action – a measure of how the change is done through the current change in the voltage change through the content.

“When we first saw the double, I could not believe it,” said Cushy. “After all, this is an extraordinary observation, so Lee Senghoon Lee and postdoctoral scientist Geohang Zhang asked me to come back and experiment.”

When Tekuchi and his experimental colleagues convinced that the measurements were accurate, they initially did not understand the multiplexing source.

So they started looking for explanations. UQ Victor Galitsky, a fellow JQI, professor of physics and member of CMTC, suggested that Klein could join the tunnel.

“First, it was just an intuition,” says Galitskiy. “But over time, we are more confident that the scenario of Klein can actually be the reason behind these comments.”

How Researchers improve semiconductor laser on silicon

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How Researchers improve semiconductor laser on silicon

Electrical engineering researchers have enhanced the promising new semiconductor laser operating temperature on the silicon substrate, making it one step in a potential commercial application.

The development of a “pump” laser made of implanted germanium tin on silicon pumps can be highly accurate processing speed for computer chips, sensors, cameras and other electronic devices – at very low costs.

Shui-King Fisher, associate professor of electrical engineering, said, “In a relatively short period – about two years – we have progressed from 110 kelvin to record temperature of 270,000.”

“Now we are very close to working at room temperature and moving towards the application of materials, which can increase processing speed with very little power consumption.”

U, led by a multi-institutional team of researchers on the development of laser injector light, similar to electric injection. The enhanced laser covers a wide range of wavelengths of 2 to 3 micrometers and uses a low laser threshold, while it can work at 270 kW, or about 26 fahrenheit.

“Improvement is based on a simple but accurate foundation,” PhD candidate for microelectronics program, the leading author of paper and member of the UK research group Yin Zhou said. “With mature development technology, we can achieve high quality alloy with up to 20 percent tin content, which is the key to achieving current achievement.”

Germanium tin uses an effective emission of light, a gain that standard silicon semiconductor can not do for computer chips.

U and other researchers focused on germanium tin on silicon substrate to create an electronic chip for optoelectronics, which could transmit the data much faster than current chips. In 2016, U and his colleagues reported the creation of the first generation of lasers that were pumped.

The broad wavelength range means more data transfer capacity, and less laser thresholds and high operating temperatures make it easy to consume less power, reduce costs and simplify design.

Easily integrated into electronic circuits, such as in computer chips and sensors, germanium tin can be the reason for the development of low-cost, lightweight, compact and energy-efficient electronic components in the form of a semiconductor that transmits light and the use of information We do.

U, led by a multi-institutional team of researchers on the development of laser injector light, similar to electric injection. The enhanced laser covers a wide range of wavelengths of 2 to 3 micrometers and uses a low laser threshold, while it can work at 270 kW, or about 26 fahrenheit. (Calvin is the standard unit for temperature measurement in physics.)

“Improvement is based on a simple but accurate foundation,” PhD candidate for microelectronics program, the leading author of paper and member of the UK research group Yin Zhou said. “With mature development technology, we can achieve high quality alloy with up to 20 percent tin content, which is the key to achieving current achievement.”

Germanium tin uses an effective emission of light, a gain that standard silicon semiconductor can not do for computer chips.

U and other researchers focused on germanium tin on silicon substrate to create an electronic chip for optoelectronics, which could transmit the data much faster than current chips. In 2016, U and his colleagues reported the creation of the first generation of lasers that were pumped.

The broad wavelength range means more data transfer capacity, and less laser thresholds and high operating temperatures make it easy to consume less power, reduce costs and simplify design.

Easily integrated into electronic circuits, such as in computer chips and sensors, germanium tin can be the reason for the development of low-cost, lightweight, compact and energy-efficient electronic components in the form of a semiconductor that transmits light and the use of information We do.

The development of a “pump” laser made from implanted germanium tin on silicon pumps can be rapid processing of computer chips, sensors, cameras and other electronic devices – at a very low cost.

Choi Cheng, associate professor of electrical engineering, said, “In a relatively short period – about two years – we have progressed from 110 kelvin to record temperature of 270,000.”

“Now we are very close to working at room temperature and moving towards the application of materials, which can increase processing speed with very little power consumption.”

Top Machine learning unlocks mysteries of quantum physics

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Top Machine learning unlocks mysteries of quantum physics

Understanding the complex behavior of electrons has led to the discovery of those who have changed society, such as the revolution of computing was possible by the invention of the transistor.

Today, through technological advances, electron behavior can be studied very deeply in the past, which can achieve scientific successes such as changing world like PC. However, the data generated by these devices is so complex that humans can not understand them.

A team led by Cornell has developed a method of using machine learning to analyze data from tunnel microscopy (STM) – a technique that provides images without scale for electronic movements on the surfaces of materials in various energies. Produces information that is otherwise inaccessible.

Physics professor On-Kim said, “Some of these images were taken over two decades ago material considered to be important and mysterious.” “You wonder about the kind of secrets buried in those images, we would like to open these secrets.”

Kim is a senior author of the book “Automated Learning in Quantitative Imaging Experiments” published in Nature on June 19.

The first two authors are Yi Zhang, who is a former postdoctoral researcher at Kim’s laboratory and is now in Peking University in China, and Andrei Meisroos, a post-graduate researcher at Kim’s Laboratory, who is now in France at Paris-Sood University.

Co-authors Jesse Sims Davis, Professor James Gilbert White, is a prestigious professor of physics at Cornell University, who is an innovator in STM-based studies.

Research gave a new insight into how the electrons interact – and showed how automated learning can be used to run further discoveries in automatic quantum physics.

At the sub-atomic level, a sample will contain millions of trillion electrons which interact with each other and surrounding infrastructure.

The behavior of electrons is partly determined by the tension between two competing directions: the speed, which is related to kinetic energy, and being separate from each other, is associated with the disgusting energy of the conversation.

In this study, Kim and his colleagues began to find out which of these tendencies were more important in superconducting materials at high temperatures.

Using STM, electrons are used to spend between vacuum between the tip of the microscope and the sample surface, which provides detailed information about the behavior of the electrons.

“The problem is that when you take such data and record it, you get the data that looks like a picture, but it is not a natural picture, such as an apple or a pear,” Kim said.

The data generated by the device was more like a model, and was nearly 10,000 times more complex than the conventional measurement curve. “We do not have a good tool to study such data sets.”

To explain this data, researchers followed an ideal environment and added factors that would cause change in electron behavior. Then he trained an artificial neural network – a kind of artificial intelligence that can learn a specific work inspired by the brain’s working methods – to identify situations related to different theories.

When researchers enter experimental data in the neural network, then identify any theory that is similar to the actual data.

Kim said that this method has confirmed the hypothesis that the negative energy of interaction in the behavior of electrons was more effective.

With better understanding of the number of electrons who interact with different materials in different situations, new discoveries will develop, which will lead to further exploration.

“The material that caused the initial transistor revolution, was really simple material, and now we have the ability to design a lot more complex materials,” Kim said. “If these powerful tools can reveal important aspects that lead to a desirable asset, then we will be able to create content with that specialty.”

Using STM, electrons are used to spend between vacuum between the tip of the microscope and the sample surface, which provides detailed information about the behavior of the electrons.

“The problem is that when you take such data and record it, you get the data that looks like a picture, but it is not a natural picture, such as an apple or a pear,” Kim said. The data generated by the device was more like a model, and was nearly 10,000 times more complex than the conventional measurement curve. “We do not have a good tool to study such data sets.”

To explain this data, researchers followed an ideal environment and added factors that would cause change in electron behavior. Then he trained an artificial neural network – a kind of artificial intelligence that can learn a specific work inspired by the brain’s working methods – to identify situations related to different theories.