By reworking a theory first proposed by physicists in the 1920s, the researchers discovered a new way to predict important characteristics of a new material before it's been created. The new formula allows computers to model the properties of a material up to 100,000 times faster than previously possible and vastly expands the range of properties scientists can study.
"The equation scientists were using before was inefficient and consumed huge amounts of computing power, so we were limited to modeling only a few hundred atoms of a perfect material," said Emily Carter, the engineering professor who led the project.
"But most materials aren't perfect," said Carter, the Arthur W. Marks '19 Professor of Mechanical and Aerospace Engineering and Applied and Computational Mathematics. "Important properties are actually determined by the flaws, but to understand those you need to look at thousands or tens of thousands of atoms so the defects are included. Using this new equation, we've been able to model up to a million atoms, so we get closer to the real properties of a substance."
By offering a panoramic view of how substances behave in the real world, the theory gives scientists a tool for developing materials that can be used for designing new technologies. Car frames made from lighter, strong metal alloys, for instance, might make vehicles more energy efficient, and smaller, faster electronic devices might be produced using nanowires with diameters tens of thousands of times smaller than that of a human hair.
thinkahol * on 11 Jul 11Listen up, Facebook and Twitter groupies: how easily can social pressure affect your memory? Very easily, researchers at the Weizmann Institute and University College London have proved, and they think they even know what part of the brain is responsible. The participants conformed to the group on these "planted" responses, giving incorrect answers nearly 70% of the time. Volunteers watched a documentary film in small groups. Three days later, they returned to the lab individually to take a memory test, answering questions about the film. They were also asked how confident they were in their answers. They were later invited back to the lab to retake the test. This time, the subjects were also given supposed answers of the others in their film-viewing group (along with social-media-style photos) while being scanned in a functional MRI (fMRI) that revealed their brain activity. Is most of what you know false? Planted among these were false answers to questions the volunteers had previously answered correctly and confidently. The participants conformed to the group on these "planted" responses, giving incorrect answers nearly 70% of the time. To determine if their memory of the film had actually undergone a change, the researchers invited the subjects back to the lab later to take the memory test once again, telling them that the answers they had previously been fed were not those of their fellow film watchers, but random computer generations. Some of the responses reverted back to the original, correct ones, but get this: despite finding out the scientists messed with their minds, close to half of their responses remained erroneous, implying that the subjects were relying on false memories implanted in the earlier session. An analysis of the fMRI data showed a strong co-activation and connectivity between two brain areas: the hippocampus and the amygdala. Social reinforcement could act on the amygdala to persuade our brains to replace a strong memory wi
