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Categories: Mathematics: Modeling, Physics: Optics

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Defects often limit the performance of devices such as light-emitting diodes (LEDs). The mechanisms by which defects annihilate charge carriers are well understood in materials that emit light at red or green wavelengths, but an explanation has been lacking for such loss in shorter-wavelength (blue or ultraviolet) emitters.

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Researchers have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data. The team introduced a self-supervised AI model nicknamed GedankenNet that learns from physics laws and thought experiments. Informed only by the laws of physics that universally govern the propagation of electromagnetic waves in space, the researchers taught their AI model to reconstruct microscopic images using only random artificial holograms -- synthesized solely from 'imagination' without relying on any real-world experiments, actual sample resemblances or real data.

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New study identifies concerning gaps between how human radiologists score the accuracy of AI-generated radiology reports and how automated systems score them. Researchers designed two novel scoring systems that outperform current automated systems that evaluate the accuracy of AI narrative reports. Reliable scoring systems that accurately gauge the performance of AI models are critical for ensuring that AI continues to improve and that clinicians can trust them.

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Deep learning methods have been used to augment existing energy-based physical models in 'do novo' or from-scratch computational protein design, resulting in a 10-fold increase in success rates verified in the lab for binding a designed protein with its target protein. The results will help scientists design better drugs against diseases like cancer and COVID-19.

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A research team recently developed a stable artificial photocatalytic system that is more efficient than natural photosynthesis. The new system mimics a natural chloroplast to convert carbon dioxide in water into methane, a valuable fuel, very efficiently using light. This is a promising discovery, which could contribute to the goal of carbon neutrality.

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New research has achieved a significant breakthrough in color switching for nanocrystals, unlocking exciting possibilities for a simple, energy efficient display design and for tunable light sources needed in numerous technologies. The discovery also has potential applications in sensitive sensors for various substances, including biological and neuroscience uses, as well as advancements in quantum communication technologies. This nanomaterial breakthrough holds the promise of inspiring exciting innovations in the future.

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New films inspired by butterfly wings circumvent the heating effect usually experienced by colored objects absorbing light on a hot day. The new films could be used on the outside of buildings, vehicles and equipment to reduce the energy needed for cooling while preserving vivid color properties.

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A new technique incorporates many different building blocks of cellular metamaterials into one unified graph-based representation. This can be used to make a user-friendly interface that can quickly and easily model metamaterials, edit the structures, and simulate their properties.

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The same fiber optic networks that provide internet can simultaneously act as earthquake sensors, as demonstrated in a new study.

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Engineers have developed HADAR, or heat-assisted detection and ranging.

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An interdisciplinary team of mathematicians, engineers, physicists, and medical scientists has uncovered an unexpected link between pure mathematics and genetics, that reveals key insights into the structure of neutral mutations and the evolution of organisms.

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Theoreticians report that they found no evidence of any universal topological signatures after performing the first ab initio investigation of high harmonic generation from topological insulators.

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Earth is rapidly warming and scientists are developing a variety of approaches to reduce the effects of climate change. An astronomer has proposed a novel approach -- a solar shield to reduce the amount of sunlight hitting Earth, combined with a tethered, captured asteroid as a counterweight. Engineering studies using this approach could start now to create a workable design that could mitigate climate change within decades.

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Bringing protons up to speed with strong laser pulses -- this still young concept promises many advantages over conventional accelerators. For instance, it seems possible to build much more compact facilities. Prototypes to date, however, in which laser pulses are fired at ultra-thin metal foils, show weaknesses -- especially in the frequency with which they can accelerate protons. An international working group has tested a new technique: In this approach, frozen hydrogen acts as a 'target' for the laser pulses.

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Scientists have trained a machine learning model in outer space, on board a satellite. This achievement could revolutionize the capabilities of remote-sensing satellites by enabling real-time monitoring and decision making for a range of applications.

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Researchers have developed a new technique that vastly improves readings of protein-to-ligand interactions through Raman spectroscopy.

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Researchers have developed a pioneering technological solution that counterfeiters have no response to.

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A new machine-learning technique can efficiently learn to control a robot, leading to better performance with fewer data.

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Enzymes play a key role in cellular metabolic processes. To enable the quantitative assessment of these processes, researchers need to know the so-called 'turnover number' (for short: kcat) of the enzymes. A team of bioinformaticians now describes a tool for predicting this parameter for various enzymes using AI methods.

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A team has combined economic theory with biology to understand how natural systems respond to change. The researchers noticed a similarity between consumers' shopping behavior and the behavior of metabolic systems, which convert food into energy in our bodies. The team focused on predicting how different metabolic systems might respond to environmental change by using an economic tool called the Slutsky equation. Their calculations indicated that very different metabolic systems actually share previously unknown universal properties, and can be understood using tools from other academic fields. Metabolic processes are used in drug development, bioengineering, food production and other industries, so being able to predict how such systems will respond to change can offer many benefits.