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The specific traits of a plant's roots determine the climatic conditions under which a particular plant prevails. A new study led by the University of Wyoming sheds light on this relationship -- and challenges the nature of ecological trade-offs.

Daniel Laughlin, an associate professor in the UW Department of Botany and director of the Global Vegetation Project, led the study, which included researchers from the German Centre for Integrative Biodiversity Research in Leipzig, Germany; Leipzig University; and Wageningen University & Research in Wageningen, Netherlands.

"We found that root traits can explain species distributions across the planet, which has never been attempted before at such a scale," Laughlin says. "We found that species with thick and dense roots were more likely to occur in warm climates, but species with thin and low density roots were more likely to occur in cold climates. This impacts their ability to acquire resources like nutrients and engage in symbiotic relationships with mycorrhizal fungi."

Laughlin is lead author of a paper, titled "Root Traits Explain Plant Species Distributions Along Climatic Gradients, Yet Challenge the Nature of Ecological Trade-Offs," that was published today (June 10) in Nature Ecology & Evolution. The online-only journal publishes, on a monthly basis, the best research from across ecology and evolutionary biology.

The paper includes contributors from more than 50 academic institutions, environmental agencies, institutes and laboratories.

Plant roots generally remain hidden below the ground, but their role for the distribution of plants should not be underestimated. Roots are essential for water and nutrient uptake, yet little is known about the influence of root traits on species distribution.

To investigate this relationship, an international team of researchers analyzed the root trait database, GRooT, and the vegetation database, known as sPlot. Each is the largest database of its kind. The work was facilitated by the German Centre for Integrative Biodiversity Research's synthesis center, sDiv, which supports collaboration of scientists from different countries and disciplines.

Researchers analyzed several plant root traits. These included the specific root length and root diameter, as well as the root tissue density and root nitrogen content. These root traits were compared to the environmental conditions under which these plants occur. Researchers found that, in forests, species with relatively thick fine roots and high root tissue density were more likely to occur in warm climates, while species with more delicate and longer fine roots and low root tissue density were found more often in cold climates -- a classic trade-off.

By contrast, forest species with large-diameter roots and high root tissue density were more commonly associated with dry climates, but species with the opposite trait values were not associated with wet climates. Instead, a diversity of root traits occurred in warm or wet climates.

Laughlin says the findings are important because roots are literally foundational to plant survival, yet scientists have neglected roots for too long.

"Understanding how root traits are related to climate gradients, like water and temperature, will determine how species respond and shift their distributions in response to climate change," he says.

Study Challenges Ecological Trade-Offs

Ecological theory is built on trade-offs, where trait differences among species evolved as adaptations to different environments. This prevailing view of trade-offs in ecological theory may have hindered the discovery of unidirectional benefits that could be widespread in nature. At the species level, particularly, discerning the difference between trade-offs and unidirectional benefits would advance the understanding of how individual traits affect community assembly, according to the study.

But plants can't cover all of the bases. For plants, this means that low trait values -- such as low specific root length in this study -- are associated with advantages under certain climate conditions. On the flip side, high trait values -- such as high specific root length -- confer benefits under opposing conditions.

However, certain root traits did not follow this general ecological theory. Rather, the certain root traits were associated with unidirectional benefits. Translated, this means there is a benefit for high trait values in certain environmental conditions, but no benefit of low trait values in other conditions.

"We were surprised at how common these unidirectional benefits were in roots compared to classic trade-offs," Laughlin says.

A classic trade-off would be when one species, such as cottonwoods, is highly adapted to wet riparian soil, but it simply dies in the dry prairie because it is not adapted to dry conditions. In contrast, some of the dry prairie grasses thrive in the dry soil, but may die in the wet riparian soil or else be overtopped by more productive species along the river, Laughlin says. This classic idea has pervaded ecological thought.

"We found something more nuanced, where a small set of traits enhanced occurrence of species in harsh climates that are dry and cold, but a large set of traits and species could tolerate benign climates that are warm and wet," he explains. "In other words, traits can be beneficial at one end of the climate gradient and neutral at the other end."

"This challenges our understanding of how traits drive species distributions, which we have been puzzled by as a scientific community," adds Alexandra Weigelt, a plant ecologist at Leipzig University and a member of the German Centre for Integrative Biodiversity Research, and last senior author of the paper.

This suggests that unidirectional benefits may be more widespread than previously thought, the study concludes. Unidirectional benefits were consistently associated with the more extreme cold and dry climates that are more resource-limited than warm and wet climates. By contrast, warm and wet climates were associated with a larger diversity of root traits, according to the study.

Laughlin admits there is still a lack of broad-scale empirical evidence to fully challenge the trade-off ecological theory, at least at this time. But this study expands on previous hints about the influence of unidirectional benefits.

"We believe that our work helps to understand the trait combinations that are possible in certain climate zones. This is important knowledge for ecosystem restoration in a changing world," says Liesje Mommer, a plant ecologist at Wageningen University & Research.

MORGANTOWN, W.Va. -- Imagine being woken up at 3 a.m. to navigate a corn maze, memorize 20 items on a shopping list or pass your driver's test.

According to a new analysis out of West Virginia University, that's often what it's like to be a rodent in a biomedical study. Mice and rats, which make up the vast majority of animal models, are nocturnal. Yet a survey of animal studies across eight behavioral neuroscience domains showed that most behavioral testing is conducted during the day, when the rodents would normally be at rest.

"There are these dramatic daily fluctuations--in metabolism, in immune function, in learning and memory, in perception--and by the large, they get ignored," said Randy Nelson, who led the study. "You just have to wonder: to what extent is that affecting the outcomes?"

Nelson chairs the School of Medicine's Department of Neuroscience and directs basic science research for the Rockefeller Neuroscience Institute.

His findings appear in Neuroscience and Behavioral Reviews.

Nelson and his colleagues--RNI researchers Jacob Bumgarner, William Walker and Courtney DeVries--examined the 25 most frequently cited papers in each of eight categories of rodent behaviors: learning and memory, sensation and perception, attention, food intake, mating, maternal behavior, aggression and drug seeking.

For each study, they determined whether the behavioral testing was done during the day, at night, or both. They also identified which studies reported time-of-day information ambiguously or not at all.

Overall, only 20% of the studies reported nighttime testing. Seventeen percent reported daytime testing, and 7.5 percent reported both. The remainder of the studies either didn't mention when testing occurred (42%) or were ambiguous on that point (13.5%).

Even among the studies conducted at night, most didn't describe in detail how the authors protected the rodents' circadian rhythms. For example, at what times did the researchers observe the animals? Did they house the animals in the dark during the day? If so, how did they keep extraneous light from invading the room every time someone opened the door or turned on a hallway light? In most cases, it's impossible to tell from the methods section.

Yet recording this kind of information is crucial to a study's reproducibility. Without knowing how an experiment was run the first time, other scientists can't run it again to see if they get different results. And running experiments multiple times--under different conditions--is the basis of all scientific inquiry.

"We want to make sure everyone's conducting and reporting the best science they can do," Nelson said. "This is important because, in common with the NIH, we want to improve the rigor and reproducibility of science."

Failing to account for time of day doesn't just jeopardize an animal study's reproducibility. It can also make its results less applicable to humans.

Being diurnal, humans tend to be active when the sun is up and rest when it's down. That's the opposite of the nocturnal rodents that scientists common use in biomedical studies. If the scientists disregard this discrepancy, it can reduce the value of their data when they try to extrapolate their results to humans.

"If you're testing a mouse during the middle of its active period, which is during the dark, you can translate those data to a diurnal creature who's active during that time," Nelson said. "I think that's fine."

But in the light, a mouse's daytime behavior is less comparable to a person's.

"It's like waking you up at 3 in the morning and saying, 'OK, let's walk a tightrope,' and then you're no good at it," he said. "Well, what a surprise."

So, how can a diurnal, human researcher design and carry out a study of nocturnal rodents when their circadian rhythms naturally conflict?

One step she can take is to reverse the rodents' light/dark cycle by housing the animals in total darkness during the day and turning on the lights at night. This way, she and her colleagues get to observe the animals during their active phase--under simulated "nighttime" conditions--without driving to the lab at midnight.

When researchers check on the animals in the daytime, they can do so under dim red lighting instead of regular, white lighting. To complete the effect, windows can even be tinted with a red film. Rodents can't see red light, so it won't disrupt their circadian rhythms.

Some labs come equipped with red overhead lighting, but even if researchers can't access such a space, there are ways around the problem.

"You can use a miner's light with a little, red light in it," Nelson said. "That works really well."

Night-vision goggles are another option.

In any event, recording these measures--in detail--is key.

"The goal of this paper is to make sure that we raise consciousness about it in the same way that people raised consciousness about sex as a biological variable that's important," Nelson said. "Everybody knows it, but--as a group of biomedical researchers--we ignore it. And if you ignore it, then can you really translate those data on a nocturnal animal to a diurnal animal when you're testing at the wrong time of day?"

WASHINGTON, June 10, 2021 -- The demand for flexible wearable electronics has spiked with the dramatic growth of smart devices that can exchange data with other devices over the internet with embedded sensors, software, and other technologies. Researchers consequently have focused on exploring flexible energy storage devices, such as flexible supercapacitators (FSCs), that are lightweight and safe and easily integrate with other devices. FSCs have high power density and fast charge and discharge rates.

Printing electronics, manufacturing electronics devices and systems by using conventional printing techniques, has proved to be an economical, simple, and scalable strategy for fabricating FSCs. Traditional micromanufacturing techniques can be expensive and complex.

In Applied Physics Reviews, by AIP Publishing, researchers from Wuhan University and Hunan University provide a review of printed FSCs in terms of their ability to formulate functional inks, design printable electrodes, and integrate functions with other electronic devices.

Printed FSCs are generally manufactured by printing the functional inks on traditional organic and inorganic electrode materials on flexible substrates. Due to the thin film structure, these printed devices can be bent, stretched, and twisted to a certain radius without loss of electrochemical function.

In addition, the rigid current collector components of the supercapacitor can also be replaced by the flexible printed parts. Various printing techniques such as screen printing, inkjet printing, and 3D printing have been well established to fabricate the printed FSCs.

"The development of miniaturized, flexible, and planar high-performance electrochemical energy storage devices is an urgent requirement to promote the rapid development of portable electronic devices in daily life," said author Wu Wei. "We can imagine that in the future, we can use any printer in our lives and can print a supercapacitator to charge a mobile phone or smart wristband at any time."

The researchers found for printable ink formulations, two principles should be followed. First, when selecting ink components, it is vital to include fewer ineffective additives, better conductive binders, and excellent dispersion electrode materials. Second, the ink must have a suitable viscosity and a good rheology property to obtain excellent prints.

Printable functional materials, such as graphene and pseudocapacitive materials, are good core components of printed supercapacitators.

Since printed electronics offer the advantage of flexibility and low cost, they can be used to manufacture solar cells, flexible OLED displays, transistors, RFID tags, and other integrated smart devices. This opens up the possibility of many other applications, including smart textiles, intelligent packaging, and smart labels.

Researchers from Skoltech have designed and conducted experiments measuring gas permeability under various conditions for ice-containing sediments mimicking permafrost. Their results can be useful both in modeling and testing techniques for gas production from Arctic reservoirs and in tracing methane emission in high latitudes. The paper was published in the journal Energy&Fuels.

Permafrost, even though it sounds very stable and permanent, is actually quite diverse: depending on the composition of the frozen ground, pressure, temperature and so on, it can have varying properties, which are extremely important if you want to build something on permafrost, such as an oil and gas field. Permafrost is also very gassy: it may contain a lot of natural gas in the form of hydrates, and its permeability is an important parameter both for research and for many activities in the Arctic.

"Gas permeability affects migration and accumulation of natural gas in this frozen ground as well as atmospheric emissions. Knowledge of filtration properties of permafrost containing gas hydrates is also absolutely necessary for estimates of the possibility of extracting gas from hydrates," Evgeny Chuvilin, Leading Research Scientist at Skoltech and a coauthor of the paper, says.

Chuvilin and his colleagues decided to handle the poorly studied issue of gas permeability variations in ice- and hydrate-saturated sand samples during freezing and thawing and as gas hydrates form and dissociate. For that, the team had to design and build an experimental setup that would allow them to test various samples mimicking permafrost under various pressure and temperature conditions as well as clay content.

"The data we got can be used in testing methods of gas extraction in permafrost areas, including from hydrates, and in mapping areas with high permeability in permafrost for methane emissions studies in the Arctic," Chuvilin says.

Their study also showed a high probability of increasing permeability coupled with dissociation of gas hydrates in permafrost - a likely scenario given the current warming trend in the Arctic. "We don't necessarily have to wait for a complete thawing of permafrost - even a slight shift of temperature is enough to trigger dissociation. And increased gas permeability that will follow will create conditions for methane emissions into the atmosphere, causing a variety of environmental and technological impacts," Chuvilin notes.

ITHACA, N.Y. - Researchers from Cornell University's School of Applied and Engineering Physics and Samsung's Advanced Institute of Technology have created a first-of-its-kind metalens - a metamaterial lens - that can be focused using voltage instead of mechanically moving its components.

The proof of concept opens the door to a range of compact varifocal lenses for possible use in many imaging applications such as satellites, telescopes and microscopes, which traditionally focus light using curved lenses that adjust using mechanical parts. In some applications, moving traditional glass or plastic lenses to vary the focal distance is simply not practical due to space, weight or size considerations.

Metalenses are flat arrays of nano-antennas or resonators, less than a micron thick, that act as focusing devices. But until now, once a metalens was fabricated, its focal length was hard to change, according to Melissa Bosch, doctoral student and first author of a paper detailing the research in the American Chemical Society's journal Nano Letters.

The innovation, developed in the collaboration between Samsung and Cornell researchers, involved merging a metalens with the well-established technology of liquid crystals to tailor the local phase response of the metalens. This allowed the researchers to vary the focus of the metalens in a controlled way by varying the voltage applied across the device.

"This combination worked out as we hoped and predicted it would," said Bosch, who works in the lab of Gennady Shvets, professor of applied and engineering physics and senior author of the paper. "It resulted in an ultrathin, electrically tunable lens capable of continuous zoom and up to 20% total focal length shift."

Samsung researchers are hoping to develop the technology for use in augmented reality glasses, according to Bosch. She sees many other possible applications such as replacing the optical lenses on satellites, spacecraft, drones, night-vision goggles, endoscopes and other applications where saving space and weight are priorities.

Maxim Shcherbakov, postdoctoral associate in the Shvets lab and corresponding author of the paper, said that researchers have made progress in marrying liquid crystals to nanostructures for the past decade, but nobody had applied this idea to lenses. Now the group plans to continue the project and improve the prototype's capabilities.

"For instance," Shcherbakov said, "this lens works at a single wavelength, red, but it will be much more useful when it can work across the color spectrum - red, green, blue."

The Cornell research group is now developing a multiwavelength varifocal version of the metalens using the existing platform as a starting point.

"The optimization procedure for other wavelengths is very similar to that of red. In some ways, the hardest step is already finished, so now it is simply a matter of building on the work already done," Bosch said.

Thermotherapy or heat treatment can help in treating lesions and other tissue injuries. For example, chemotherapy or radiotherapy, when combined with thermotherapy, kills tumorous cells more effectively. Thermotherapy is considered a promising approach for treating internal lesions, but the advancement in the field depends on the availability of patient-friendly heat-inducing devices capable of rapidly increasing the temperature of target tissues.

Current clinical practices around thermotherapy majorly employ heat-generating devices that are probed inside the human body or are in contact with the skin. Receiving energy from external power sources and often operating through converging magnetic fields, these devices are usually large in size and static, limiting the movement of patients and also prolonging operational time.

An alternative option is small and flexible devices that can be implanted in the patient's body; however, such implantable devices must be flexible, body-compatible, heat resistant, and be powered wirelessly for heat generation--some of the criteria that are essential for their clinical use.

Recently, researchers at Tokyo Tech have innovated a heat-generating device that can revolutionize the field of thermotherapy by meeting all of the above criteria. Their innovation was reported in an article published in Advanced Functional Materials. Discussing their motivation, Associate Professor Toshinori Fujie, who led the study, explains ''One of the major obstacles in developing an implantable heating device is the requirement of incorporating electronic elements such capacitors in the circuit of the device itself. Such insertion takes away the flexibility required for internal implantation. To overcome this, we took the help of induction-heating, the same technology that is used in cooking heaters''. The working of such a device is based on the premise that the magnetic field generated by a coil with a high-frequency current induces current flow in a closely placed metal. Owing to its internal resistance, the metal then heats up automatically.

Developing such an induction heating device required ingenious design. First, the researchers printed the electronic wiring on a polyimide film with an 'ink' made of gold-nanoparticles. Next, a layer of poly (D, L-lactic acid) or PDLLA was coated above the printed film. In addition to heat-durability, the PDLLA layer is biodegradable and biocompatible, making it an excellent candidate for the base material of the device. Then, using tweezers, the researchers peeled off the PDLLA layer, causing it to come off the polyimide film. The result was a flexible device, conformably attaching to human skin, with electronic wirings printed on it.

Once the device showed satisfactory electrical performance, mechanical strength, and heat generation capacity, the researchers assessed its clinical functionality by planting it on living tissue--the hepatic lobe of a beagle dog. The results were extremely promising. When a transmitter coil was placed directly on the device for one minute, the temperature of the liver tissue increased up to 7°C without any indication of tissue burning.

Assoc. Prof. Fujie highlights the feat of their research ''The flexibility, biocompatibility, and wireless-powered heating capacity of our device opens up the possibility of using thermotherapy in wide clinical scenarios including minimally invasive endoscopic surgery. Moreover, by adjusting the number and size of these devices, lesions of different sizes can be treated''.

What an incredible localized solution to revolutionize the medical field globally!

A research team, led by Professor Kyoung-Duck Park in the Department of Physics at UNIST has succeeded in investigating and controlling the physical properties of naturally-formed nanoscale wrinkles in two-dimensional (2D) semiconductors. This is thanks to their previously-developed hyperspectral adaptive tip-enhanced photoluminescence (a-TEPL) spectroscopy. This will be a major step forward in developing paper-thin, ultra-flexible displays.

Wrinkles are an inevitable structural deformation in 2D semiconductor materials, which gives rise to spatial heterogeneity in material properties, according to the research team. Such structural deformation has long been considered one of the top technical challenges in semiconductor manufacturing, as this would harm the uniformity in structural, electrical, and optical properties of semiconductors. Besides, because the size of these wrinkles is quite small, the accurate analysis of their structural, optical, and excitonic properties has been impossible with conventional spectroscopic tools. "Recent strain-engineering approaches have enabled to tune of some of these properties, yet there has been no attempt to control the induced strain of naturally-formed nanoscale wrinkles, while simultaneously investigating their modified nano-optical properties," noted the research team.

In this study, the research team presented a hyperspectral TEPL nano-imaging approach, combined with nano-optomechanical strain control, to investigate and control the nano-optical and -excitonic properties of naturally-formed wrinkles in a WSe2 ML. This approach allowed them to reveal the modified electronic properties and exciton behaviors at the wrinkle, associated with the induced uniaxial tensile strain at the apex. Based on this, the research team was able to exploit the wrinkle structure as a nanoscale strain-engineering platform. The precise atomic force tip control also enabled them to engineer the excitonic properties of TMD MLs at the nano-local regions in a fully reversible fashion, noted the research team.

The research team further presented a more systematic platform for dynamic nano-emission control of the wrinkle by demonstrating programmably-operational switching and modulation modes in time and space. "We envision that our approach gives access to potential applications in quantum-nanophotonic devices, such as bright nano-optical sources for light-emitting diodes, nano-optical switch/multiplexer for optical integrated circuits, and exciton condensate devices," said the research team.

Meanwhile, Professor Ki Kang Kim and Dr. Soo Ho Choi from Sungkyunkwan University, and Professor Hyun Seok Lee from Chungbuk National University participated in the production of 2D semiconductor materials used in the study. Professor Geunsik Lee and Dr. Yongchul Kim from the Department of Chemistry at UNIST also participated in the theoretical calculation of the findings.

The findings of this research have been published in the online version of Advanced Materials, ahead of print, on May 11, 2021. It has also been selected as the front cover of the April 2021 issue of the journal. Besides, the source technology of this nano-mechanical strain-engineering was granted an official patent.

Since energy storage devices are often used in a magnetic field environment, scientists have often explored how an external magnetic field affects the charge storage of nonmagnetic aqueous carbon-based supercapacitor systems.

Recently, an experiment designed by Prof. YAN Xingbin's group from the Lanzhou Institute of Chemical Physics (LICP) of the Chinese Academy of Sciences has revealed that applying an external magnetic field can induce capacitance change in aqueous acidic and alkaline electrolytes, but not in neutral electrolytes. The experiment also shows that the force field can explain the origin of the magnetic field effect.

This new discovery establishes a relationship between magnetic fields and supercapacitors, and provides insight into the transport behavior of ions in aqueous electrolytes.

Carbon-based supercapacitors are among the most prominent electrochemical energy storage devices because of their excellent power output and superior cycle life. During the charging/discharging process, the difference in electrical potential between the positive and negative electrodes generates a magnetic field based on Faraday's law of electromagnetic induction.

Moreover, supercapacitors are often used in electronic equipment that generates a magnetic field as well. However, whether the magnetic field affects the charge storage of supercapacitors was not yet clear before this experiment.

In this work, the researchers first reported that the external magnetic field indeed affects the charge storage of a nonmagnetic aqueous carbon-based supercapacitor system, thus overcoming the negligible effect of the magnetic field on nonmagnetic electrochemical systems.

According to the researchers, the direction and intensity of the magnetic field, concentration of electrolytes and voltammetry sweep all affect the capacitance change in acidic and alkaline electrolytes.

In addition, a quantitative relationship among the limiting current density at the electrode/electrolyte interface, the intensity of the magnetic field, and the concentration and viscosity of the electrolytes was identified, which provided a completely new insight into the charge transport behavior of supercapacitors.

"By establishing the relationship between magnetic fields and supercapacitors, we were able to deeply understand the transport behavior of ions in aqueous electrolytes. We expect to apply magnetic field-enhanced electrochemistry to other energy storage devices," said Prof. YAN.

The results were published online in Cell Reports Physical Science in an article entitled "Magnetic field induced capacitance change of aqueous carbon-based supercapacitors."

Research, development, and production of novel materials depend heavily on the availability of fast and at the same time accurate simulation methods. Machine learning, in which artificial intelligence (AI) autonomously acquires and applies new knowledge, will soon enable researchers to develop complex material systems in a purely virtual environment. How does this work, and which applications will benefit? In an article published in the Nature Materials journal, a researcher from Karlsruhe Institute of Technology (KIT) and his colleagues from Göttingen and Toronto explain it all. (DOI: 10.1038/s41563-020-0777-6)

Digitization and virtualization are becoming increasingly important in a wide range of scientific disciplines. One of these disciplines is materials science: research, development, and production of novel materials depend heavily on the availability of fast and at the same time accurate simulation methods. This, in turn, is beneficial for a wide range of different applications - from efficient energy storage systems, such as those indispensable for the use of renewable energies, to new medicines, for whose development an understanding of complex biological processes is required. AI and machine learning methods can take simulations in material sciences to the next level. "Compared to conventional simulation methods based on classical or quantum mechanical calculations, the use of neural networks specifically tailored to material simulations enables us to achieve a significant speed advantage," explains physicist and AI expert Professor Pascal Friederich, Head of the AiMat - Artificial Intelligence for Materials Sciences research group at KIT's Institute of Theoretical Informatics (ITI). "With faster simulation systems, scientists will be able to develop larger and more complex material systems in a purely virtual environment, and to understand and optimize them down to the atomic level."

High Precision from the Atom to the Material

In an article published in Nature Materials, Pascal Friederich, who is also associate group leader of the Nanomaterials by Information-Guided Design division at KIT's Institute of Nanotechnology (INT), presents, together with researchers from the University of Göttingen and the University of Toronto, an overview of the basic principles of machine learning used for simulations in material sciences. This also includes the data acquisition process and active learning methods. Machine learning algorithms not only enable artificial intelligence to process the input data, but also to find patterns and correlations in large data sets, learn from them, and make autonomous predictions and decisions. For simulations in materials science, it is important to achieve high accuracy over different time and size scales, ranging from the atom to the material, while limiting computational costs. In their article, the scientists also discuss various current applications, such as small organic molecules and large biomolecules, structurally disordered solid, liquid, and gaseous materials, as well as complex crystalline systems - for example, metal-organic frameworks that can be used for gas storage or for separation, for sensors or for catalysts.

Even More Speed with Hybrid Methods

To further extend the possibilities of material simulations in the future, the researchers from Karlsruhe, Göttingen, and Toronto suggest the development of hybrid methods: these combine machine learning (ML) and molecular mechanics (MM) methods. MM simulations use so-called force fields in order to calculate the forces acting on each individual particle and thus predict motions. As the potentials of the ML and MM methods are quite similar, a tight integration with variable transition areas is possible. These hybrid methods could significantly accelerate the simulation of large biomolecules or enzymatic reactions in the future, for example.

The movement of electrons can have a significantly greater influence on spintronic effects than previously assumed. This discovery was made by an international team of researchers led by physicists from the Martin Luther University Halle-Wittenberg (MLU). Until now, a calculation of these effects took, above all, the spin of electrons into consideration. The study was published in the journal "Physical Review Research" and offers a new approach in developing spintronic components.

Many technical devices are based on conventional semiconductor electronics. Charge currents are used to store and process information in these components. However, this electric current generates heat and energy is lost. To get around this problem, spintronics uses a fundamental property of electrons known as spin. "This is an intrinsic angular momentum, which can be imagined as a rotational movement of the electron around its own axis," explains Dr Annika Johansson, a physicist at MLU. The spin is linked to a magnetic moment that, in addition to the charge of the electrons, could be used in a new generation of fast and energy-efficient components.

Achieving this requires an efficient conversion between charge and spin currents. This conversion is made possible by the Edelstein effect: by applying an electric field, a charge current is generated in an originally non-magnetic material. In addition, the electron spins align, and the material becomes magnetic. "Previous papers on the Edelstein effect primarily focused on how electron spin contributes to magnetisation, but electrons can also carry an orbital moment that also contributes to magnetisation. If the spin is the intrinsic rotation of the electron, then the orbital moment is the motion around the nucleus of the atom," says Johansson. This is similar to the earth, which rotates both on its own axis and around the sun. Like spin, this orbital moment generates a magnetic moment.

In this latest study, the researchers used simulations to investigate the interface between two oxide materials commonly used in spintronics. "Although both materials are insulators, a metallic electron gas is present at their interface which is known for its efficient charge-to-spin conversion," says Johansson. The team also factored the orbital moment into the calculation of the Edelstein effect and found that its contribution to the Edelstein effect is at least one order of magnitude greater than that of spin. These findings could help to increase the efficiency of spintronic components.

Smithsonian Conservation Biology Institute scientists are one step closer to understanding why some corals can weather climate change better than others, and the secret could be in a specific protein that produces a natural sunscreen. As their name implies, Hawaiian blue rice corals sport a deep blue pigment, which is created by chromoprotein and filters out harmful ultraviolet (UV) radiation from the sun. Although UV damage may produce long-term impacts to reproduction in many coral species--including brown rice coral--it may not have the same effect on blue rice coral. The findings of this study were published June 9 in the paper "Reproductive plasticity of Hawaiian Montipora corals following thermal stress" in Scientific Reports.

"Having witnessed firsthand the devastating effects bleaching had on brown rice coral in 2014 and 2015, it is encouraging to see blue rice coral either recovered quickly after bleaching or was not affected by elevated ocean temperatures at all," said Mike Henley, Smithsonian Conservation Biology Institute scientist and the paper's lead author. "By studying blue rice corals' reproductive successes, we can better understand how other corals weather climate change and ocean warming."

A coral's color is derived from a microscopic protozoa called zooxanthellae. This algae lives inside the coral tissue and serves as the main food source for shallow, reef-building corals, including brown rice coral and blue rice coral. They have a symbiotic relationship; the coral protects the zooxanthellae, and in turn zooxanthellae provide the coral with food. These algae also produce sunscreen for the coral. Corals are animals and cannot photosynthesize, but zooxanthellae can. The waste product of their photosynthesis are sugars that feed the coral.

When ocean temperatures warm, however, corals become stressed, and there is a breakdown in the symbiosis. Warm temperatures speed up the zooxanthellae's metabolism, causing it to produce a toxic compound. In response, the corals expel the algae and their sunscreen, leaving them open to harmful UV damage. Since these species get most of their coloring from the zooxanthellae, the expulsion causes the corals to "bleach," or appear lighter in appearance--changing from dark hue to a paler hue.

Bleaching affects some corals' ability to reproduce successfully. Upon expelling their zooxanthellae and, therefore, losing their UV protection, corals' DNA is at greater risk of being damaged. Specifically, changes in their sperm cells' mitochondria can affect their motility (ability to swim) for the long-term. If unable to successfully reproduce, corals cannot create novel offspring that may have genetic modifications that make them more resistant to warming and help them adapt to changing oceans.

Following the 2014 and 2015 bleaching events in Hawaii, the team observed that blue rice coral had exceptional reproductive vigor at 90% motility. Its brown-pigmented counterparts' motility, on the other hand, was only half this amount. This suggests that even if brown corals survive bleaching and look visually healthy, the damage caused by bleaching and UV exposure could have long-lasting impacts on their ability to successfully reproduce. A key factor in the blue rice coral's ability to reproduce successfully might be its sunscreen pigment, which the coral may retain even if it bleaches. By better understanding the role UV-protective pigments play in mitigating the adverse effects of climate change and warming oceans, scientists can piece together the picture of why some species are better equipped to survive and thrive in a changing environment than others.

From 1980 to 2016, grain production in Brazil increased more than fourfold, and the country now stands as the world's largest soybean exporter and the second largest exporter of corn. The two main drivers of this increase in food production were cropland expansion and double-cropping, harvesting two crops, such as corn and soybeans, from the same field in a single year.

While cropland expansion has long been recognized as one of the drivers behind the increase in Brazil's agricultural output, a new study published in Nature Food quantifies for the first time the impact that double-cropping also had on helping Brazil achieve its national grain boom.

Jing Gao, assistant professor of Geospatial Data Science in the University of Delaware's College of Earth, Ocean and Environment (CEOE) and Data Science Institute (DSI), was a co-author on the study that included collaborators from institutions in China and Brazil.

Gao contributed to the team efforts by examining agriculture census-related data gathered from the Brazilian Institute of Geography and Statistics (IBGE), and identifying spatial patterns and changes that occurred over time in three key agricultural regions with regards to food production: the Centre-West, Southeast-South, and Matopiba regions in Brazil.

"You don't know what is happening until you analyze data," said Gao. "This was the first time this unique dataset was analyzed from this angle to show how the system worked. Understanding how the boost in Brazil's grain productivity was achieved in the recent past provides insight for developing sustainable food production in the future."

These three regions covered 36% of Brazil's territory and accounted for 79% of the national soybean production and 85% of the country's corn production in 2016. The Centre-West area showed the biggest increases in production as well as cropland expansion. As such, the Centre-West displaced the Southeast-South as the dominant grain producer in the country, producing 46% of the nation's grain compared to 29% for the Southeast-South.

The increase in grain production in the Centre-West can be attributed to cropland expansion as well as double-cropping.

Contributions from double-cropping in the Centre-West increased from 19% to 33% from 2003 to 2016. While the increase in soybean production was largely due to cropland expansion -- soybean fields account for more than one-third of Brazil's cropland -- the increase in corn production could be linked to the practice of double-cropping. In the Centre-West, the agricultural area for second season corn -- or the corn grown after the first season soybean is harvested -- increased from 26.3% to 66.6% from 2003 to 2016, and in 2012, the second season corn crop surpassed the corn grown during the first season as the main source of corn nationwide.

Tao Lin, from the College of Biosystems Engineering and Food Science at Zhejiang University in China and the corresponding author of the paper, said that it was interesting to see the agricultural developments in these regions had different approaches to agricultural expansion and double-cropping.

"The Centre-West region has experienced a rapid cropland expansion in the last few decades, and after the new cropland was created, farmers then decided to also increase the double-cropping area a lot," said Lin. "Meanwhile, the contribution of double-cropping in the Southeast-South region is over 50%, which has had a much higher impact than cropland expansion in recent times, because there is not much arable land remaining for further expansion in this commercial agricultural region."

The researchers also found that the strongest driver behind this rapid increase in grain production has been the rising demand for corn and soybean exports from Brazil on a global scale.

It is important to understand how double-cropping has helped a country like Brazil, which plays a critical role in the global food supply chain, increase its agricultural productivity while limiting the conversion of natural land for agricultural use and possibly helping offset some of the negative environmental impacts that might result from cropland expansion.

From 2003 to 2016, double-cropping in Brazil offset the equivalent of about 76.7 million hectares of arable land for corn production, that is, more than twice the annual harvested area of corn in the United States.

While not every country is growing food in an area of the world that is conducive or even possible for double-cropping, for other grain-growing pantropical countries, double-cropping could be a solution to increase grain production without expanding cropland over natural landscapes.

The widely studied metallic asteroid known as 16 Psyche was long thought to be the exposed iron core of a small planet that failed to form during the earliest days of the solar system. But new University of Arizona-led research suggests that the asteroid might not be as metallic or dense as once thought, and hints at a much different origin story.

Scientists are interested in 16 Psyche because if its presumed origins are true, it would provide an opportunity to study an exposed planetary core up close. NASA is scheduled to launch its Psyche mission in 2022 and arrive at the asteroid in 2026.

UArizona undergraduate student David Cantillo is lead author of a new paper published in The Planetary Science Journal that proposes 16 Psyche is 82.5% metal, 7% low-iron pyroxene and 10.5% carbonaceous chondrite that was likely delivered by impacts from other asteroids. Cantillo and his collaborators estimate that 16 Psyche's bulk density - also known as porosity, which refers to how much empty space is found within its body - is around 35%.

These estimates differ from past analyses of 16 Psyche's composition that led researchers to estimate it could contain as much as 95% metal and be much denser.

"That drop in metallic content and bulk density is interesting because it shows that 16 Psyche is more modified than previously thought," Cantillo said.

Rather than being an intact exposed core of an early planet, it might actually be closer to a rubble pile, similar to another thoroughly studied asteroid -- Bennu. UArizona leads the science mission team for NASA's OSIRIS-REx mission, which retrieved a sample from Bennu's surface that is now making its way back to Earth.

"Psyche as a rubble pile would be very unexpected, but our data continues to show low-density estimates despite its high metallic content," Cantillo said.

Asteroid 16 Psyche is about the size of Massachusetts, and scientists estimate it contains about 1% of all asteroid belt material. First spotted by an Italian astronomer in 1852, it was the 16th asteroid ever discovered.

"Having a lower metallic content than once thought means that the asteroid could have been exposed to collisions with asteroids containing the more common carbonaceous chondrites, which deposited a surface layer that we are observing," Cantillo said. This was also observed on asteroid Vesta by the NASA Dawn spacecraft.

Asteroid 16 Psyche has been estimated to been worth $10,000 quadrillion (that's $10,000 followed by 15 more zeroes), but the new findings could slightly devalue the iron-rich asteroid.

"This is the first paper to set some specific constraints on its surface content. Earlier estimates were a good start, but this refines those numbers a bit more," Cantillo said.

The other well-studied asteroid, Bennu, contains a lot of carbonaceous chondrite material and has porosity of over 50%, which is a classic characteristic of a rubble pile.

Such high porosity is common for relatively small and low-mass objects such as Bennu - which is only as large as the Empire State Building - because a weak gravitational field prevents the object's rocks and boulders from being packed together too tightly. But for an object the size of 16 Psyche to be so porous is unexpected.

"The opportunity to study an exposed core of a planetesimal is extremely rare, which is why they're sending the spacecraft mission there," Cantillo said, "but our work shows that 16 Psyche is a lot more interesting than expected."

Past estimates of 16 Psyche's composition were done by analyzing the sunlight reflected off its surface. The pattern of light matched that of other metallic objects. Cantillo and his collaborators instead recreated 16 Psyche's regolith - or loose rocky surface material - by mixing different materials in a lab and analyzing light patterns until they matched telescope observations of the asteroid. There are only a few labs in the world practicing this technique, including the UArizona Lunar and Planetary Laboratory and the Johns Hopkins Applied Physics Laboratory in Maryland, where Cantillo worked while in high school.

"I've always been interested in space," said Cantillo, who is also president of the UArizona Astronomy Club. "I knew that astronomy studies would be heavy on computers and observation, but I like to do more hands-on kind of work, so I wanted to connect my studies to geology somehow. I'm majoring geology and minoring in planetary science and math."

"David's paper is an example of the cutting-edge research work done by our undergraduate students," said study co-author Vishnu Reddy, an associate professor of planetary sciences who heads up the lab in which Cantillo works. "It is also a fine example of the collaborative effort between undergraduates, graduate students, postdoctoral fellows and staff in my lab."

The researchers also believe the carbonaceous material on 16 Psyche's surface is rich in water, so they will next work to merge data from ground-based telescopes and spacecraft missions to other asteroids to help determine the amount of water present.

Today, solar energy provides 2% of U.S. power. However, by 2050, renewables are predicted to be the most used energy source (surpassing petroleum and other liquids, natural gas, and coal) and solar will overtake wind as the leading source of renewable power. To reach that point, and to make solar power more affordable, solar technologies still require a number of breakthroughs. One is the ability to more efficiently transform photons of light from the Sun into useable energy.

Organic photovoltaics max out at 15% to 20% efficiency — substantial, but a limit on solar energy's potential. Lehigh University engineer Ganesh Balasubramanian, like many others, wondered if there were ways to improve the design of solar cells to make them more efficient?

Balasubramanian, an associate professor of Mechanical Engineering and Mechanics, studies the basic physics of the materials at the heart of solar energy conversion — the organic polymers passing electrons from molecule to molecule so they can be stored and harnessed — as well as the manufacturing processes that produce commercial solar cells.

Architecture of the OPV bulk-heterojunction structure and the design scope. [Credit: Ganesh Balasubramanian, Joydeep Munshi, Lehigh University]

Using the Frontera supercomputer at the Texas Advanced Computing Center (TACC) — one of the most powerful on the planet — Balasubramanian and his graduate student Joydeep Munshi have been running molecular models of organic solar cell production processes, and designing a framework to determine the optimal engineering choices. They described the computational effort and associated findings in the May issue of IEEE Computing in Science and Engineering.

"When engineers make solar cells, they mix two organic molecules in a solvent and evaporate the solvent to create a mixture which helps with the exciton conversion and electron transport," Balasubramanian said. "We mimicked how these cells are created, in particular the bulk heterojunction — the absorption layer of a solar cell. Basically, we're trying to understand how structure changes correlate with the efficiency of the solar conversion?"

Balasubramanian uses what he calls ‘physics-informed machine learning'. His research combines coarse-grained simulation — using approximate molecular models that represent the organic materials — and machine learning. Balasubramanian believes the combination helps prevent artificial intelligence from coming up with unrealistic solutions.

"A lot of research uses machine learning on raw data," Balasubramanian said. "But more and more, there's an interest in using physics-educated machine learning. That's where I think lies the most benefit. Machine learning per se is simply mathematics. There's not a lot of real physics involved in it."

Writing in Computational Materials Science in February 2021, Balasubramanian and Munshi along with Wei Chen (Northwestern University), and TeYu Chien (University of Wyoming) described results from a set of virtual experiments on Frontera testing the effects of various design changes. These included altering the proportion of donor and receptor molecules in the bulk heterojunctions, and the temperature and amount of time spent in annealing — a cooling and hardening process that contributes to the stability of the product.

They harnessed the data to train a class of machine learning algorithms known as support vector machines to identify parameters in the materials and production process that would generate the most energy conversion efficiency, while maintaining structural strength and stability. Coupling these methods together, Balasubramanian's team was able to reduce the time required to reach an optimal process by 40%.

"At the end of the day, molecular dynamics is the physical engine. That's what captures the fundamental physics," he said. "Machine learning looks at numbers and patterns, and evolutionary algorithms facilitate the simulations."

Trade-Offs and Limitations

Like many industrial processes, there are trade-offs involved in tweaking any facet of the manufacturing process. Faster cooling may help increase power efficiency, but it may make the material brittle and prone-to-break, for instance. Balasubramanian and his team employed a multi-objective optimization algorithm that balances the benefits and drawbacks of each change to derive the overall optimal manufacturing process.

Flowchart describing steps in a typical coupled Cuckoo Search-Coarse Grained Molecular Dynamics (CS-CGMD) algorithm. The dashed box represents the augmented machine learned exploration of the regions of interest to supplement ill-performed nests with newer alternatives during each CS optimization generation. [Credit: Ganesh Balasubramanian, Joydeep Munshi, Lehigh University]

"When you try to optimize one particular variable, you are looking at the problem linearly," he said. "But most of these efforts have multi-pronged challenges that you're trying to solve simultaneously. There are trade-offs that you need to make, and synergistic roles that you must capture, to come to the right design."

Balasubramanian's simulations matched experimental results. They determined that the make-up of the heterojunction and the annealing temperature/timing have the largest effects on overall efficiency. They also found what proportion of the materials in the heterojunction is best for efficiency.

"There are certain conditions identified in literature which people claim are the best conditions for efficiency for those select molecules and processing behavior," he said. "Our simulation were able to validate those and show that other possible criteria would not give you the same performance. We were able to realize the truth, but from the virtual world."

With an award of more time on Frontera in 2021-22, Balasubramanian will add further layers to the machine learning system to make it more robust. He plans to add experimental data, as well as other modalities of computer models, such as electronic structure calculations.

"Heterogeneity in the data will improve the results," he said. "We plan to do first principle simulations of materials and then feed that data into the machine learning model, as well as data from coarse-grained simulations."

Balasubramanian believes that current organic photovoltaics may be reaching the limits of their efficiency. "There's a wall that's hard to penetrate and that's the material," he said. "These molecules we've used can only go so far. The next thing to try is to use our framework with other molecules and advanced materials."

His team mined the literature to understand the features that increase solar efficiency and then trained a machine learning model to identify potential new molecules with ideal charge transport behaviors. They published their research in the Journal of Chemical Information and Modeling. Future work on Frontera will use Balasubramanian's framework to explore and computationally test these alternative materials, assuming they can be produced.

"Once established, we can take realistic molecules that are made in the lab and put them in the framework we've created," he said. "If we discover new materials that perform well, it will reduce the cost of solar power generation devices and help Mother Earth."

Balasubramanian's research harnesses the two things that computer simulations are critical for, he says. "One is to understand the science that we cannot study with the tools that we have in the real world. And the other is to expedite the science – streamline what we really have to do, which reduces our cost and time to make things and physically test them."

Small pieces of plastic are everywhere, stretching from urban environments to pristine wilderness. Left to their own devices, it can take hundreds of years for them to degrade completely. Catalysts activated by sunlight could speed up the process, but getting these compounds to interact with microplastics is difficult. In a proof-of-concept study, researchers reporting in ACS Applied Materials & Interfaces developed self-propelled microrobots that can swim, attach to plastics and break them down.

While plastic products are omnipresent indoors, plastic waste and broken bits now litter the outdoors, too. The smallest of these - microplastics less than 5 mm in size - are hard to pick up and remove. In addition, they can adsorb heavy metals and pollutants, potentially harming humans or animals if accidently consumed. So, previous researchers proposed a low-energy way to get rid of plastics in the environment by using catalysts that use sunlight to produce highly reactive compounds that break down these types of polymers. However, getting the catalysts and tiny plastic pieces in contact with each other is challenging and usually requires pretreatments or bulky mechanical stirrers, which aren't easily scaled-up. Martin Pumera and colleagues wanted to create a sunlight-propelled catalyst that moves toward and latches onto microparticles and dismantles them.

To transform a catalytic material into light-driven microrobots, the researchers made star-shaped particles of bismuth vanadate and then evenly coated the 4-8 μm-wide structures with magnetic iron oxide. The microrobots could swim down a maze of channels and interact with microplastic pieces along their entire lengths. The researchers found that under visible light, microrobots strongly glommed on to four common types of plastics. The team then illuminated pieces of the four plastics covered with the microrobot catalyst for seven days in a dilute hydrogen peroxide solution. They observed that the plastic lost 3% of its weight and that the surface texture for all types changed from smooth to pitted, and small molecules and components of the plastics were found in the left-over solution. The researchers say the self-propelled microrobot catalysts pave the way toward systems that can capture and degrade microplastics in hard-to-reach-locations.