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Scientists have managed to draw at high resolution and speed, local patterns in organic semiconductor films used in optoelectronic and photonic applications. The new method enables the patterning of material characteristics and concomitant final properties, including molecular conformation, orientation, crystallinity and composition. The technique, published with open access in Nature Communications, has also been patented and industrial partners are sought for further co-development.

Bridging the gap between and the worldwide deployed silicon electronics requires new low cost and low energy consumption fabrication methods and technologies. This work represents a key enabling technology to accelerate the use of flexible and light-weight organic electronics and photonics to the level of silicon-based devices.

The microstructure and composition of organic semiconductors need to be tuned locally in order to optimize their properties, such as charge carrier mobility, electrical conductivity and light emission; and expand their functionalities for the practical upscaling of applications such as organic transistors (OFETs) and light emitting diodes (OLEDs), organic photovoltaics (OPV), organic thermoelectric generators (OTEGs), and organic photonic structures.

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Researchers at Tel Aviv University, led by Prof. Yaniv Assaf of the School of Neurobiology, Biochemistry and Biophysics and the Sagol School of Neuroscience and Prof. Yossi Yovel of the School of Zoology, the Sagol School of Neuroscience, and the Steinhardt Museum of Natural History, conducted a first-of-its-kind study designed to investigate brain connectivity in 130 mammalian species. The intriguing results, contradicting widespread conjectures, revealed that brain connectivity levels are equal in all mammals, including humans.

“We discovered that —namely the efficiency of information transfer through the —does not depend on either the size or structure of any specific ,” says Prof. Assaf. “In other words, the brains of all mammals, from tiny mice through humans to large bulls and dolphins, exhibit equal connectivity, and information travels with the same efficiency within them. We also found that the brain preserves this balance via a special compensation mechanism: when connectivity between the hemispheres is high, connectivity within each hemisphere is relatively low, and vice versa.”

Participants included researchers from the Kimron Veterinary Institute in Beit Dagan, the School of Computer Science at TAU and the Technion’s Faculty of Medicine. The paper was published in Nature Neuroscience on June 8.

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Carnegie Mellon today showed off new research into the world of robotic navigation. With help from the team at Facebook AI Research (FAIR), the university has designed a semantic navigation that helps robots navigate around by recognizing familiar objects.

The SemExp system, which beat out Samsung to take first place in a recent Habitat ObjectNav Challenge, utilizes machine learning to train the system to recognize objects. That goes beyond simple superficial traits, however. In the example given by CMU, the robot is able to distinguish an end table from a kitchen table, and thus extrapolate in which room it’s located. That should be more straightforward, however, with a fridge, which is both pretty distinct and is largely restricted to a singe room.

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The pandemic has accelerated demand for robots and automation. Robots have been regulated to marketing jobs, receptionist duties, and companionship for the elderly. But they’re really starting to come into their own and have practical use. Let’s take a look at how.

Supermarkets started to adopt robots to free up employees who previously spent time taking inventory to focus on disinfecting and sanitizing surfaces and processing deliveries to keep shelves stocked.

These retailers insist the robots are augmenting the work of employees, not replacing them. But as panic buying stops and sales decline in the recession, companies may no longer have a need for these workers.

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