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    Sensing and controlling microscopic spin density in materials

    Electronic devices typically use the charge of electrons, but spin — their other degree of freedom — is starting to be exploited. Spin defects make crystalline materials highly useful for quantum-based devices such as ultrasensitive quantum sensors, quantum memory devices, or systems for simulating the physics of quantum effects. Varying the spin density in semiconductors can lead to new properties in a material — something researchers have long wanted to explore — but this density is usually fleeting and elusive, thus hard to measure and control locally.
    Now, a team of researchers at MIT and elsewhere has found a way to tune the spin density in diamond, changing it by a factor of two, by applying an external laser or microwave beam. The finding, reported this week in the journal PNAS, could open up many new possibilities for advanced quantum devices, the authors say. The paper is a collaboration between current and former students of professors Paola Cappellaro and Ju Li at MIT, and collaborators at Politecnico of Milano. The first author of the paper, Guoqing Wang PhD ’23, worked on his PhD thesis in Cappellaro’s lab and is now a postdoc at MIT.
    A specific type of spin defect known as a nitrogen vacancy (NV) center in diamond is one of the most widely studied systems for its potential use in a wide variety of quantum applications. The spin of NV centers is sensitive to any physical, electrical, or optical disturbance, making them potentially highly sensitive detectors. “Solid-state spin defects are one of the most promising quantum platforms,” Wang says, partly because they can work under ambient, room-temperature conditions. Many other quantum systems require ultracold or other specialized environments.
    “The nanoscale sensing capabilities of NV centers makes them promising for probing the dynamics in their spin environment, manifesting rich quantum many body physics yet to be understood,” Wang adds. “A major spin defect in the environment, called P1 center, can usually be 10 to 100 times more populous than the NV center and thus can have stronger interactions, making them ideal for studying many-body physics.”
    But to tune their interactions, scientists need to be able to change the spin density, something that had previously seldom been achieved. With this new approach, Wang says, “We can tune the spin density so it provides a potential knob to actually tune such a system. That’s the key novelty of our work.”
    Such a tunable system could provide more flexible ways of studying the quantum hydrodynamics, Wang says. More immediately, the new process can be applied to some existing nanoscale quantum-sensing devices as a way to improve their sensitivity.
    Li, who holds a joint appointment in MIT’s departments of Nuclear Science and Engineering and Materials Science and Engineering, explains that today’s computers and information processing systems are all based on the control and detection of electrical charges, but some innovative devices are beginning to make use of the property called spin. The semiconductor company Intel, for example, has been experimenting with new kinds of transistors that couple spin and charge, potentially opening a path to devices based on spintronics. More

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    Climate change puts children’s health at risk now and in the future

    Climate-related environmental disasters have not let up this summer. Heat waves are roasting the United States, Europe, China and North Africa (SN: 7/19/23), while wildfires are raging in Canada and Greece. Choking smoke from the Canadian fires has obscured skies throughout the United States (SN: 7/12/23).

    This is harmful to everyone, but especially children. The United Nations Children’s Fund calls climate change a child rights crisis. The organization estimates that 1 billion children worldwide – nearly half of all children – are at extremely high risk of the effects of climate change. This threatens the health of these children now and throughout their lives.

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    Children’s ongoing development from the fetal period through adolescence is one reason that they are particularly vulnerable to health harms from climate-related effects on the environment, says environmental health scientist Frederica Perera of Columbia University. She founded the Columbia Center for Children’s Environmental Health in 1998. Science News talked with Perera about climate change and children’s health and well-being, the disparities in terms of who is at highest risk and why these early harms endanger health throughout life. The interview has been edited for length and clarity.

    SN: How does climate change’s effects on the environment, such as heat waves and wildfire smoke, affect children’s health?

    Perera: When we speak of the effects of climate change and air pollution on children, we really need to include the fetal period as well as infancy and childhood and even adolescence, because the brain and other systems are developing all through those periods.

    There’s a multitude of health risks. Severe heat is contributing to preterm births, and it’s causing heat-related deaths and illnesses in infants and children. Children are also suffering from severe weather events: they’re suffering physical injury and also psychological trauma. Longer pollen seasons due to climate change are causing more allergy and asthma. Asthma attacks are increased from breathing forest fire smoke. There’s the issue of food insecurity and stunted growth due to drought in certain areas of the world. Infectious diseases [spread by insects and other vectors are] increasing as ticks and mosquitoes have extended their range.

    SN: What are some of the physiological reasons that children are at higher risk than adults from the effects of climate change?

    Perera: First, there’s the very rapid and complex developmental programming during the fetal period, infancy and childhood, which is vulnerable to disruption by toxic pollutants, climate-related shocks and stressors. A second point is that infants and children don’t have the same fully functioning biologic defense mechanisms that operate in adults to protect them against toxic exposures.

    [In terms of heat,] children have less ability to control core body temperature during severe heat waves. The young are dependent on us adults for hydration and for care when there are early indications of heat-related illness.

    With respect to air pollution and smoke from forest fires, children are especially vulnerable because of increased exposure. They often spend more time outdoors. [Children have a larger lung surface area and so] breathe more air [per kilogram of] body weight [than adults]. [Children’s noses are less efficient at filtering inhaled] particles, so a higher proportion of these particles penetrates deeply into the lungs. Their narrow airways are more prone to effects of inflammation, and that results in constriction and difficulty breathing.

    SN: How does climate change affect children’s mental health?

    Perera: Climate change is affecting mental health both directly and indirectly. Children who experience severe storms and floods and wildfires show elevated rates of symptoms of depression and also of post-traumatic stress disorder.

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    But even if children haven’t directly experienced such a disaster, they’re being affected by climate anxiety. In a survey that covered 10 countries, more than 50 percent [of teens and young people] said they felt very worried or extremely worried about climate change, and this anxiety was negatively affecting their daily lives.

    SN: What disparities exist in terms of which children are at greatest risk from climate-related effects on the environment?

    Perera: All children are vulnerable, but certain children are hurt first and worst, as we say. This is true globally [in terms of low-income countries compared with high-income countries], and also here in the United States, where communities of color and communities of low income have disproportionately higher exposure to air pollution as well as to severe heat and extreme weather events. If you take the United States, for example, polluting sources like major highways, bus and truck depots, industrial plants and power plants are disproportionately located in and near communities of color and communities of low income. Discriminatory policies like redlining have created urban heat islands.

    We see that disproportionate exposure combined with poverty and racism are contributing to the disparities in disease rates. In the U.S., asthma prevalence and infant mortality in Black children are twice the rates seen in white children. The preterm birth rate is 50 percent higher [among Black women compared with white women].

    SN: What do these early health harms to children mean for their lives ahead?

    Perera: We know that there are long-term effects of these early harms and damages. Respiratory conditions frequently persist. Children with severe or persistent asthma are at increased risk of permanent air flow obstruction and chronic obstructive pulmonary disease. Reduced intellectual functioning associated with air pollution, and also malnutrition prenatally or in early life, affects the ability to learn, and that affects the ability to earn and contribute to society. Stress and trauma from shocks of climate change and other adverse events that are experienced at a young age can affect mental health throughout life.

    We should be thinking about the long-term implications of these early health harms from climate change and air pollution. When we look then at policies and other interventions to eliminate fossil fuel emissions, we see enormous health and associated economic benefits. Children will be the greatest beneficiaries. More

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    Robots cause company profits to fall — at least at first

    Researchers have found that robots can have a ‘U-shaped’ effect on profits: causing profit margins to fall at first, before eventually rising again.
    The researchers, from the University of Cambridge, studied industry data from the UK and 24 other European countries between 1995 and 2017, and found that at low levels of adoption, robots have a negative effect on profit margins. But at higher levels of adoption, robots can help increase profits.
    According to the researchers, this U-shaped phenomenon is due to the relationship between reducing costs, developing new processes and innovating new products. While many companies first adopt robotic technologies to decrease costs, this ‘process innovation’ can be easily copied by competitors, so at low levels of robot adoption, companies are focused on their competitors rather than on developing new products. However, as levels of adoption increase and robots are fully integrated into a company’s processes, the technologies can be used to increase revenue by innovating new products.
    In other words, firms using robots are likely to focus initially on streamlining their processes before shifting their emphasis to product innovation, which gives them greater market power via the ability to differentiate from their competitors. The results are reported in the journal IEEE Transactions on Engineering Management.
    Robots have been widely used in industry since the 1980s, especially in sectors where they can carry out physically demanding, repetitive tasks, such as automotive assembly. In the decades since, the rate of robot adoption has increased dramatically and consistently worldwide, and the development of precise, electrically controlled robots makes them particularly useful for high-value manufacturing applications requiring greater precision, such as electronics.
    While robots have been shown to reliably raise labour productivity at an industry or country level, what has been less studied is how robots affect profit margins at a similar macro scale.
    “If you look at how the introduction of computers affected productivity, you actually see a slowdown in productivity growth in the 1970s and early 1980s, before productivity starts to rise again, which it did until the financial crisis of 2008,” said co-author Professor Chander Velu from Cambridge’s Institute for Manufacturing. “It’s interesting that a tool meant to increase productivity had the opposite effect, at least at first. We wanted to know whether there is a similar pattern with robotics.”
    “We wanted to know whether companies were using robots to improve processes within the firm, rather than improve the whole business model,” said co-author Dr Philip Chen. “Profit margin can be a useful way to analyse this.” More

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    Quantum discovery: Materials can host D-wave effects with F-wave behaviors

    Rice University physicists have shown that immutable topological states, which are highly sought for quantum computing, can be entangled with other, manipulable quantum states in some materials.
    “The surprising thing we found is that in a particular kind of crystal lattice, where electrons become stuck, the strongly coupled behavior of electrons in d atomic orbitals actually act like the f orbital systems of some heavy fermions,” said Qimiao Si, co-author of a study about the research in Science Advances.
    The unexpected find provides a bridge between subfields of condensed matter physics that have focused on dissimilar emergent properties of quantum materials. In topological materials, for example, patterns of quantum entanglement produce “protected,” immutable states that could be used for quantum computing and spintronics. In strongly correlated materials, the entanglement of billions upon billions of electrons gives rise to behaviors like unconventional superconductivity and the continual magnetic fluctuations in quantum spin liquids.
    In the study, Si and co-author Haoyu Hu, a former graduate student in his research group, built and tested a quantum model to explore electron coupling in a “frustrated” lattice arrangement like those found in metals and semimetals that feature “flat bands,” states where electrons become stuck and strongly correlated effects are amplified.
    The research is part of an ongoing effort by Si, who won a  Vannevar Bush Faculty Fellowship from the Defense Department in July to pursue the validation of a theoretical framework for controlling topological states of matter.
    In the study, Si and Hu showed that electrons from d atomic orbitals could become part of larger, molecular orbitals that are shared by several atoms in the lattice. The research also showed that electrons in molecular orbitals could become entangled with other frustrated electrons, producing strongly correlated effects that were very familiar to Si, who has spent years studying heavy fermion materials.
    “These are completely d-electron systems,” Si said. “In the d-electron world, it’s like you have a highway with multiple lanes. In the f-electron world, you can think of electrons moving in two tiers. One is like the d-electron highway, and the other is like a dirt road, where movement is very slow.”
    Si said f-electron systems host very clean examples of strongly correlated physics, but they aren’t practical for everyday use. More

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    Robotic grippers offer unprecedented combo of strength and delicacy

    Researchers at North Carolina State University have developed a robotic gripping device that is gentle enough to pick up a drop of water, strong enough to pick up a 6.4 kilogram (14.1 pound) weight, dexterous enough to fold a cloth, and precise enough to pick up microfilms that are 20 times thinner than a human hair. In addition to possible manufacturing applications, the researchers also integrated the device with technology that allows the gripper to be controlled by the electrical signals produced by muscles in the forearm, demonstrating its potential for use with robotic prosthetics.
    “It is difficult to develop a single, soft gripper that is capable of handling ultrasoft, ultrathin, and heavy objects, due to tradeoffs between strength, precision and gentleness,” says Jie Yin, corresponding author of a paper on the work and an associate professor of mechanical and aerospace engineering at NC State. “Our design achieves an excellent balance of these characteristics.”
    The design for the new grippers builds on an earlier generation of flexible, robotic grippers that drew on the art of kirigami, which involves both cutting and folding two-dimensional sheets of material to form three-dimensional shapes.
    “Our new grippers also use kirigami, but are substantially different, as we learned a great deal from the previous design,” says Yaoye Hong, co-author of the paper and a recent Ph.D. graduate from NC State. “We’ve been able to improve the fundamental structure itself, as well as the trajectory of the grippers — meaning the path at which the grippers approach an object when grabbing it.”
    The new design is able to achieve high degrees of strength and gentleness because of how it distributes force throughout the structure of the gripper.
    “The strength of robotic grippers is generally measured in payload-to-weight ratio,” Yin says. “Our grippers weigh 0.4 grams and can lift up to 6.4 kilograms. That’s a payload-to-weight ratio of about 16,000. That is 2.5 times higher than the previous record for payload-to-weight ratio, which was 6,400. Combined with its characteristics of gentleness and precision, the strength of the grippers suggests a wide variety of applications.”
    Another benefit of the new technology is that its attractive characteristics are driven primarily by its structural design, rather than by the materials used to fabricate the grippers. More

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    AniFaceDrawing: Delivering generative AI-powered high-quality anime portraits for beginners

    Anime, the Japanese art of animation, comprises hand-drawn sketches in an abstract form with unique characteristics and exaggerations of real-life subjects. While generative artificial intelligence (AI) has found use in the content creation such as anime portraits, its use to augment human creativity, and guide freehand drawings proves challenging. The primary challenge lies with the generation of suitable reference images corresponding with the incomplete and abstract strokes made during the freehand drawing process. This is particularly true when the strokes created during the drawing process are incomplete and offer insufficient information for generative AI to predict the final shape of the drawing.
    To tackle this problem, a research team from Japan Advanced Institute of Science and Technology (JAIST) and Waseda University in Japan, sought to develop a novel generative AI tool that offers progressive drawing assistance and helps generate anime portraits from freehand sketches. The tool is based on a sketch-to-image (S2I) deep learning framework that matches raw sketches with latent vectors of the generative model. It employs a two-stage training strategy through the pre-trained Style Generative Adversarial Network (StyleGAN) — a state-of-the-art generative model that uses adversarial networks to generate new images.
    The team, led by Dr. Zhengyu Huang from JAIST, including Associate Professor Haoran Xie and Professor Kazunori Miyata, and Lecturer Tsukasa Fukusato from Waseda University proposed a novel “stroke-level disentanglement,” a strategy that associates input strokes of a freehand sketch with edge-related attributes, in the latent structural code of StyleGAN. This approach allows users to manipulate the attribute parameters, thereby having greater autonomy over the properties of generated images. Dr. Huang says, “We introduced an unsupervised training strategy for stroke-level disentanglement in StyleGAN, which enables the automatic matching of rough sketches with sparse strokes to the corresponding local parts in anime portraits, all without the need for semantic labels.”
    This study will be presented at ACM SIGGRAPH 2023, the premier conference for computer graphics and interactive techniques and the only CORE ranking A* conference in the research fields worldwide.
    Regarding the development of the tool, Prof. Xie adds, “We first trained an image encoder using a pre-trained StyleGAN model as a teacher encoder. In the second stage, we simulated the drawing process of generated images without additional data to train the sketch encoder for incomplete progressive sketches. This helped us generate high-quality portrait images that align with the disentangled representations of teacher encoder.”
    To further highlight the effectiveness and usability of AniFaceDrawing in aiding users with anime portrait creation, the team conducted a user study. They invited 15 graduate students to draw digital freehand anime-style portraits using the AniFaceDrawing tool, with the option to switch between rough and detailed guidance modes for line art. While the former provided prompts for specific facial parts, the latter provided prompts for the full-face portrait based on the user’s drawing progress. Participants could pin the generated guidance once it matched their expectations, and further refine their input sketch. This tool also allowed participants to select a reference image to generate a color portrait of their input sketch. Next, they evaluated the tool for user satisfaction and guidance matching through a survey.
    The team noted that the system consistently provided high-quality facial guidance and effectively supported the creation of anime-style portraits, by not only enhancing user sketches, but also by generating desirable corresponding colored images. Prof. Fukusato remarks, “Our system could successfully transform the user’s rough sketches into high-quality anime portraits. The user study indicated that even novices could make reasonable sketches with the help of the system and end up with high-quality color art drawings.”
    “Our generative AI framework enables users, regardless of their skill level and experience, to create professional anime portraits even from incomplete drawings. Our approach consistently produces high-quality image generation results throughout the creation process, regardless of the drawing order or how poor the initial sketches are,” summarizes Prof. Miyata.
    In the long run, these findings can help democratize AI technology and assist users with creative tasks, thereby augmenting their creative capacity without technological barriers. More

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    New method simplifies the construction process for complex materials

    Engineers are constantly searching for materials with novel, desirable property combinations. For example, an ultra-strong, lightweight material could be used to make airplanes and cars more fuel-efficient, or a material that is porous and biomechanically friendly could be useful for bone implants.
    Cellular metamaterials — artificial structures composed of units, or cells, that repeat in various patterns — can help achieve these goals. But it is difficult to know which cellular structure will lead to the desired properties. Even if one focuses on structures made of smaller building blocks like interconnected beams or thin plates, there are an infinite number of possible arrangements to consider. So, engineers can manually explore only a small fraction of all the cellular metamaterials that are hypothetically possible.
    Researchers from MIT and the Institute of Science and Technology Austria have developed a computational technique that makes it easier for a user to quickly design a metamaterial cell from any of those smaller building blocks, and then evaluate the resulting metamaterial’s properties.
    Their approach, like a specialized CAD (computer-aided design) system for metamaterials, allows an engineer to quickly model even very complex metamaterials and experiment with designs that may have otherwise taken days to develop. The user-friendly interface also enables the user to explore the entire space of potential metamaterial shapes, since all building blocks are at their disposal.
    “We came up with a representation that can cover all of the different shapes engineers have traditionally shown interest in. Because you can build them all the same way, that means you can switch between them more fluidly,” says MIT electrical engineering and computer science graduate student Liane Makatura, co-lead author of a paper on this technique.
    Makatura wrote the paper with co-lead author Bohan Wang, an MIT postdoc; Yi-Lu Chen, a graduate student at the Institute of Science and Technology Austria (ISTA); Bolei Deng, an MIT postdoc; Chris Wojtan and Bernd Bickel, professors at ISTA; and senior author Wojciech Matusik, a professor of electrical engineering and computer science at MIT who leads the Computational Design and Fabrication Group within the MIT Computer Science and Artificial Intelligence Laboratory. The research will be presented at SIGGRAPH.
    A unified method
    When a scientist develops a cellular metamaterial, she typically begins by choosing a representation that will be used to describe her potential designs. This choice determines the set of shapes that will be available for exploration. More

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    Calculations reveal high-resolution view of quarks inside protons

    A collaboration of nuclear theorists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory, Argonne National Laboratory, Temple University, Adam Mickiewicz University of Poland, and the University of Bonn, Germany, has used supercomputers to predict the spatial distributions of charges, momentum, and other properties of “up” and “down” quarks within protons. The results, just published in Physical Review D, revealed key differences in the characteristics of the up and down quarks.
    “This work is the first to leverage a new theoretical approach to obtain a high-resolution map of quarks within a proton,” said Swagato Mukherjee of Brookhaven Lab’s nuclear theory group and a coauthor on the paper. “Our calculations show that the up quark is more symmetrically distributed and spread over a smaller distance than the down quark. These differences imply that up and down quarks may make different contributions to the fundamental properties and structure of the proton, including its internal energy and spin.”
    Coauthor Martha Constantinou of Temple University noted, “Our calculations provide input for interpreting data from nuclear physics experiments exploring how quarks and the gluons that hold them together are distributed within the proton, giving rise to the proton’s overall properties.”
    Such experiments are already taking place at the Continuous Electron Beam Accelerator Facility (CEBAF), a DOE Office of Science user facility at Thomas Jefferson National Accelerator Facility. Higher resolution versions are planned for the future Electron-Ion Collider (EIC) at Brookhaven Lab. In these experiments, high-energy electrons emit virtual particles of light that scatter off and change the overall momentum of a proton without breaking it apart. The way the momentum of the proton changes in response to these scatterings reveals details about the quarks and gluons — the inner components of the proton — sort of like an x-ray imaging technique for the building blocks of bulk matter.
    New theoretical approach to GPD
    Specifically, the scatterings give scientists access to the Generalized Parton Distribution (GPD) of the proton — parton being the collective name for quarks and gluons. If you picture the proton as a bag filled with marbles representing quarks and gluons, the GPD provides a description of how the energy-momentum and other characteristics of these marbles are distributed within the bag — for example, when the bag is shaken and the marbles move around. It can be compared to a map that indicates the likelihood of finding a marble with a specific energy-momentum at a particular position inside the bag. Knowing the distribution of these quark and gluon characteristics allows scientists to understand the inner workings of the proton, which may lead to new ways to apply that knowledge.
    “To obtain a detailed map, we need to analyze many scattering interactions, involving various values of momentum change of the proton,” said Shohini Bhattacharya, a research associate in Brookhaven’s nuclear theory group and the RIKEN BNL Research Center (RBRC). More