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Categories: Mathematics: Modeling, Physics: Optics

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In organic solar cells, carbon-based polymers convert light into charges that are passed to an acceptor. Scientists have now calculated how this happens by combining molecular dynamics simulations with quantum calculations and have provided theoretical insights to interpret experimental data.

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Proteins are the heavy-lifters of biochemistry. These beefy molecules act as building blocks, receptors, processors, couriers and catalysts. Naturally, scientists have devoted a lot of research to understanding and manipulating proteins.

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Micron-sized 'bow ties,' self-assembled from nanoparticles, form a variety of different curling shapes that can be precisely controlled, a research team has shown.

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A researcher has solved a nearly 60-year-old game theory dilemma called the wall pursuit game, with implications for better reasoning about autonomous systems such as driver-less vehicles.

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In a world experiencing growing inequality and intolerance, tools borrowed from science and mathematics could be the key to understanding and preventing prejudice. Experts apply evolutionary game theory, which combines techniques from economics and biology, and complex system analysis to investigate the relationship between inequality and intolerance. They found that inequality boosts intolerance and that redistribution of wealth can prevent its infectious spread.

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Scientists succeeded in directly observing how LECs -- which are attracting attention as one of the post-organic LEDs -- change their electronic state over time during field emission by measuring their optical absorption via lamp light irradiation for the first time. This research method can be applied to all light-emitting devices, including not only LECs but also organic LEDs. This method is expected to reveal detailed electroluminescence processes and lead to the early detection of factors that reduce the efficiency of electroluminescence.

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Scientists have hypothesized for over six decades the possibility of observing a form of wave reflections known as temporal, or time, reflections. Researchers detail a breakthrough experiment in which they were able to observe time reflections of electromagnetic signals in a tailored metamaterial.

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Recently, a research team resolved the contradiction between spatial resolution and imaging speed in optical microscopy. They achieved high-speed super-resolution by developing an effective technique termed temporal compressive super-resolution microscopy (TCSRM). TCSRM merges enhanced temporal compressive microscopy with deep-learning-based super-resolution image reconstruction. Enhanced temporal compressive microscopy improves the imaging speed by reconstructing multiple images from one compressed image, and the deep-learning-based image reconstruction achieves the super-resolution effect without reduction in imaging speed. Their iterative image reconstruction algorithm contains motion estimation, merging estimation, scene correction, and super-resolution processing to extract the super-resolution image sequence from compressed and reference measurements.

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Fluorescence is a fascinating natural phenomenon. It is based on the fact that certain materials can absorb light of a certain wavelength and then emit light of a different wavelength. Fluorescent materials play an important role in our everyday lives, for example in modern screens. Due to the high demand for applications, science is constantly striving to produce new and easily accessible molecules with high fluorescence efficiency.

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In our modern society huge amounts of data are transmitted every day, mainly as short optical pulses propagating through glass fibers. With the steadily increasing density of such optical signals, their interaction grows, which can lead to data loss. Physicists are now investigating how to control large numbers of optical pulses as precisely as possible to reduce the effect of such interactions. To this end they have monitored an ensemble of optical pulses as they propagated through an optical fiber and have found that it follows fixed rules -- albeit mainly those of thermodynamics.

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Researchers have detected the existence of a charge density wave of electrons that acquires mass as it interacts with the background lattice ions of the material over long distances.

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Scientists have devised a way of fabricating a complex structure, previously found only in nature, to open up new ways for manipulating and controlling light.

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Researchers show that individual atoms can be caught and thrown using light. This is the first time an atom has been released from a trap -- or thrown -- and then caught by another trap. This technology could be used in quantum computing applications.

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Using a novel economic-epidemiological model, researchers examine the health and economic impacts that could have occurred if California took a 'business-as-usual' approach to the COVID-19 pandemic.

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Researchers are using glow-in-the-dark materials to enhance and improve rapid COVID-19 home tests.

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Trapped electrons traveling in circular loops at extreme speeds inside graphene quantum dots are highly sensitive to external magnetic fields and could be used as novel magnetic field sensors with unique capabilities, according to a new study.

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Researchers have succeeded in simultaneously cooling the motion of a tiny glass sphere in two dimensions to the quantum ground-state. This represents a crucial step towards a 3D ground-state cooling of a massive object and opens up new opportunities for the design of ultra-sensitive sensors.

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Materials scientists have uncovered a property of ferroelectric 2D materials that could be exploited in future devices.

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The ability to distinguish two chiral enantiomers is an essential analytical capability for chemical industries including pharmaceutical companies, flavor/odor engineering and forensic science. A new wave of chiral optical methods have shown significant improvements in chiral sensitivity, compared to their predecessors, leading to potential analytical advantages for chiral discrimination.

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A team of researchers has developed a machine learning model that draws from the contents of news articles to effectively predict locations that face risks of food insecurity. The model, which could be used to help prioritize the allocation of emergency food assistance across vulnerable regions, marks an improvement over existing measurements.