Post Scientist

  Two-dimensional (2D) semiconductors are semiconducting materials with thicknesses on the atomic scale, which have exceptional electronic properties. In the future, these materials could have the potential to replace silicon in the development of numerous electronic and optoelectronic devices. Despite their advantages, the use of 2D semiconductors has so far been limited, partially due to their low carrier mobility at room temperature. This is caused by a strong scattering of phonons (i.e., quasiparticles associated with collective atomic vibrations) in the materials' lattices. Researchers at the Agency for Science, Technology and Research (A*STAR) in Singapore and The Hong Kong Polytechnic University in Hong Kong, China have recently devised a design strategy that could help to overcome this limitation...

  University at Buffalo scientists have discovered a convergent mechanism that may be responsible for how two top-ranked genetic risk factors for autism spectrum disorder/intellectual disability (ASD/ID) lead to these neurodevelopmental disorders. While ASD is distinct from ID, a significant proportion—approximately 31%—of people with ASD also exhibit ID. Neither condition is well-understood at the molecular level. "Given the vast number of genes known to be involved in ASD/ID and the many potential mechanisms contributing to the disorders, it is exciting to find a shared process between two different genes at the molecular level that could be underlying the behavioral changes ," said Megan Conrow-Graham, Ph.D., first author and an MD/Ph.D. candidate in the Jacobs School of Medic...

  U.S. new vehicle sales tumbled more than 21% in the second quarter compared with a year ago as the global semiconductor shortage continued to cause production problems for the industry. Yet demand still outstripped supply from April through June, even with $5 per gallon gasoline, high inflation and rising interest rates. The low supply has raised prices to record levels, knocking many consumers out of the new- vehicle market. Edmunds.com said that automakers sold 3.49 million vehicles during the quarter, nearly 933,000 fewer than the same period last year. J.D. Power estimates that the average sales price of a new vehicle for the first six months of the year hit nearly $45,000, a record that is 17.5% higher than a year ago. Edmunds.com reported that 12.7% of consumers who financed a new vehicle in Ju...

  Although most fundamental mathematical equations that describe electronic structures are long known, they are too complex to be solved in practice. This has hampered progress in physics, chemistry and the material sciences. Thanks to modern high-performance computing clusters and the establishment of the simulation method density functional theory (DFT), researchers were able to change this situation. However, even with these tools the modeled processes are in many cases still drastically simplified. Now, physicists at the Center for Advanced Systems Understanding (CASUS) and the Institute of Radiation Physics at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) succeeded in significantly improving the DFT method. This opens up new possibilities for experiments with ultra-high intensity lasers, as the group explains in the Journal of Chemical Theory and Computation . ...

  It may seem like technology advances year after year, as if by magic. But behind every incremental improvement and breakthrough revolution is a team of scientists and engineers hard at work.  UC Santa Barbara Professor Ben Mazin is developing precision optical sensors for telescopes and observatories. In a paper published in Physical Review Letters , he and his team improved the spectra resolution of their superconducting sensor, a major step in their ultimate goal: analyzing the composition of exoplanets. "We were able to roughly double the spectral resolving power of our detectors," said first author Nicholas Zobrist, a doctoral student in the Mazin Lab. "This is the largest energy resolution increase we've ever seen," added Mazin. "It opens up a whole new pathway to science goals that we couldn't achieve before." The Mazin lab works with a type of sensor called an MKID. Most light detectors—like the CMOS sensor in a phone camera—...

Babies can help unlock the next generation of artificial intelligence (AI), according to Trinity College neuroscientists and colleagues who have just published new guiding principles for improving AI. The research, published today  in the journal Nature Machine Intelligence , examines the neuroscience and psychology of infant learning and distills three principles to guide the next generation of AI, which will help overcome the most pressing limitations of machine learning. Dr Lorijn Zaadnoordijk, Marie Skłodowska-Curie Research Fellow at Trinity College explained: "Artificial intelligence (AI) has made tremendous progress in the last decade, giving us smart speakers, autopilots in cars, ever-smarter apps, and enhanced medical diagnosis. These exciting developments in AI have been achieved thanks to machine learning which uses enormous datasets to train artificial neural network models. However, progress is stalling in many areas because the data...

The spiral is pervasive throughout the universe -- from the smallest DNA molecule to ferns and sunflowers, and from fingerprints to galaxies themselves. In science the ubiquity of this structure is associated with parsimony -- that things will organize themselves in the simplest or most economical way. Researchers from the University of Pittsburgh and Princeton University unexpectedly discovered that this principle also applies to some non-biological systems that convert chemical energy into mechanical action -- allowing two-dimensional polymer sheets to rise and rotate in spiral helices without the application of external power. This self-assembly into coherent three-dimensional structures represents the group's latest contribution in the field of soft robotics and chemo-mechanical systems. The research was published this month in Proceedings of the National Academy of Sciences ( PNAS ) Nexus. Lead author is Raj Kumar Manna with Oleg E. Shklyaev...

Researchers from the University of Tsukuba have developed a mathematical model of motor learning that reflects the motor learning process in the human brain. Their findings suggest that motor exploration -- that is, increased variability in movements -- is important when learning a new task. These results may lead to improved motor rehabilitation in patients after injury or disease. Even seemingly simple movements are very complex to perform, and the way we learn how to perform new movements remains unclear. Researchers from Japan have recently proposed a new model of motor learning that combines a number of different theories. A study published this month in Neural Networks revealed that their model can simulate motor learning in humans surprisingly well, paving the way for a greater understanding of how our brains work. For even a relatively simple task, such as to reach out and pick up an object, there are a huge number of potential combinations o...

Just like us, robots can't see through walls. Sometimes they need a little help to get where they're going. Engineers at Rice University have developed a method that allows humans to help robots "see" their environments and carry out tasks. The strategy called Bayesian Learning IN the Dark -- BLIND, for short -- is a novel solution to the long-standing problem of motion planning for robots that work in environments where not everything is clearly visible all the time. The peer-reviewed study led by computer scientists Lydia Kavraki and Vaibhav Unhelkar and co-lead authors Carlos Quintero-Peña and Constantinos Chamzas of Rice's George R. Brown School of Engineering was presented at the Institute of Electrical and Electronics Engineers' International Conference on Robotics and Automation in late May. The algorithm developed primarily by Quintero-Peña and Chamzas, both graduate students working with Kavraki, keeps a human in the ...

 Microplastics are found nearly everywhere on Earth and can be harmful to animals if they're ingested. But it's hard to remove such tiny particles from the environment, especially once they settle into nooks and crannies at the bottom of waterways. Now, researchers in ACS' Nano Letters have created a light-activated fish robot that "swims" around quickly, picking up and removing microplastics from the environment. Because microplastics can fall into cracks and crevices, they've been hard to remove from aquatic environments. One solution that's been proposed is using small, flexible and self-propelled robots to reach these pollutants and clean them up. But the traditional materials used for soft robots are hydrogels and elastomers, and they can be damaged easily in aquatic environments. Another material called mother-of-pearl, also known as nacre, is strong and flexible, and is found on the inside surface of clam shells. ...

Chaos in natural populations appears to be much more common than previously recognized, according to a new analysis by scientists at UC Santa Cruz and NOAA Fisheries. "Knowing whether these fluctuations are regular, chaotic, or random has major implications for how well, and how far into the future, we can predict population sizes and how they will respond to management interventions," said Tanya Rogers, a NOAA Fisheries ecologist and research fellow at UCSC's Institute of Marine Sciences. Rogers is first author of the new study, published June 27 in Nature Ecology & Evolution . Her coauthors are Bethany Johnson, a UCSC graduate student in applied mathematics, and Stephan Munch, a NOAA Fisheries ecologist and adjunct professor at UCSC in the Departments of Applied Mathematics and Ecology and Evolutionary Biology. The researchers found evidence of chaotic dynamics in over 30 percent of the populations they analyzed in an ecological database. Previous meta...