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Eun-Ah Kim Talks Electron Behavior

In CornellResearch's article by Caitlin Hayes, Eun-Ah Kim shares how she perceives and studies the secretive interactive behaviour of electrons.

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The Social Life of Electrons

Eun-Ah Kim and Yi Zhang's Research Highlighted in Viewpoint

Viewpoint: Neural Networks Identify Topological Phases

A new machine-learning algorithm based on a neural network can tell a topological phase of matter from a conventional one.

A detailed characterization of phases of matter is at the forefront of research in condensed-matter and statistical physics. Although physicists have made incredible progress in the characterization of a wide variety of phases, the identification of novel topological phases remains challenging. Now, Yi Zhang and Eun-Ah Kim from Cornell University, New York [1], have taken a big-data approach to tackling this problem. In their work, thousands of microscopic “images” or “snapshots” of a phase, created using a special topography procedure, are fed into a machine-learning algorithm that is trained to decide whether these images come from a topological or a conventional phase of matter—exactly as modern computer vision algorithms are designed to tell cats from dogs in a picture.

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Figure 1: Zhang and Kim’s machine-learning algorithm for identifying a topological phase of matter involves a procedure called quantum loop topography (QLT). The procedure builds a multidimensional image from several adjacent, triangular loops located at the pixels of snapshots of the phase’s electronic density (only one such snapshot is shown here). The QLT image is then fed into a neural network that is trained to determine whether the image corresponds to a topological phase or not.

Natasha Holmes wants Students to be Critically Thinking Good Citizens

Science is about experimentation, creativity, even play. The greatest breakthroughs have come from those who pushed the known limits to ask why, how, and ultimately what if. If this is how the best science is done, then why don’t we start giving students autonomy to explore and create in the lab early in their university training? If we do, Natasha G. Holmes, Physics, says that perhaps they’ll get a taste of what it means to be a scientist early enough that they’ll choose science as a career path.

Holmes studies the teaching and learning of physics, especially in lab courses, but her work is applicable more broadly across many disciplines. “In the lab students have their hands on the equipment,” she says. “I’m looking at what they are getting or not getting out of that experience and also digging into what the lab space is actually good for. As a loftier, long-term goal, how can we provide students with transferable skills that will make them critical thinkers and good citizens?”

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Eun-Ah Kim's group works toward devising next-gen superconductor

The experimental realization of ultrathin graphene – which earned two scientists from Cambridge the Nobel Prize in physics in 2010 – has ushered in a new age in materials research.

What started with graphene has evolved to include numerous related single-atom-thick materials, which have unusual properties due to their ultra-thinness. Among them are transition metal dichalcogenides (TMDs), materials that offer several key features not available in graphene and are emerging as next-generation semiconductors.

TMDs could realize topological superconductivity and thus provide a platform for quantum computing – the ultimate goal of a Cornell research group led by Eun-Ah Kim, associate professor of physics.

“Our proposal is very realistic – that’s why it’s exciting,” Kim said of her group’s research. “We have a theoretical strategy to materialize a topological superconductor … and that will be a step toward building a quantum computer. The history of superconductivity over the last 100 years has been led by accidental discoveries. We have a proposal that’s sitting on firm principles.

“Instead of hoping for a new material that has the properties you want,” she said, “let’s go after it with insight and design principle.”

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David Mermin to be first physicist to recieve the Dagmar and Vaclav Havel Foundation VIZE 97

Since 1999, The Dagmar and Václav Havel Foundation VIZE 97 has awarded its international Prize to significant thinkers whose work exceeds the traditional framework of scientific knowledge, contributes to the understanding of science as an integral part of general culture and is concerned with unconventional ways of asking fundamental questions about cognition, being and human existence.

This year David Mermin will be recognized with the Dagmar and Vaclav Havel Foundation VIZE 97 prize.David received a letter from the hormer Czech first lady, Dagmar Havlová informing him that he was chosen by the advisory body to be the 2017 recipient. The award is presented at a ceremony on October 5th, the birthday of President Václav Havel.

Notable laureates include Umberto Eco and Robert Reich, but there hasn't been a physicist selected until this year.

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The Electron Microscope Pixel Array Detector (EMPAD) Yields a Wealth of Information

The electron microscope, a powerful tool for science, just became even more powerful, with an improvement developed by Cornell physicists. Their electron microscope pixel array detector (EMPAD) yields not just an image, but a wealth of information about the electrons that create the image and, from that, more about the structure of the sample.

“We can extract local strains, tilts, rotations, polarity and even electric and magnetic fields,” explained David Muller, professor of applied and engineering physics, who developed the new device with Sol Gruner, professor of physics, and members of their research groups.

Cornell’s Center for Technology Licensing (CTL) has licensed the invention to FEI, a leading manufacturer of electron microscopes (a division of Thermo Fisher Scientific, which supplies products and services for the life sciences through several brands). FEI expects to complete the commercialization of the design and offer the detector for new and retrofitted electron microscopes this year.

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Fall 2017 Seminars will be Tuesdays 12:20-1:20