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Quantum Laser Turns Energy Loss into Gain
A new laser that generates quantum particles can recycle lost energy for highly efficient, low threshold laser applications Scientists at KAIST have fabricated a laser system that generates highly interactive quantum particles at room temperature. Their findings, published in the journal Nature Photonics, could lead to a single microcavity laser system that requires lower threshold energy as its energy loss increases. The system, developed by KAIST physicist Yong-Hoon Cho and colleagues, involves shining light through a single hexagonal-shaped microcavity treated with a loss-modulated silicon nitride substrate. The system design leads to the generation of a polariton laser at room temperature, which is exciting because this usually requires cryogenic temperatures. The researchers found another unique and counter-intuitive feature of this design. Normally, energy is lost during laser operation. But in this system, as energy loss increased, the amount of energy needed to induce lasing decreased. Exploiting this phenomenon could lead to the development of high efficiency, low threshold lasers for future quantum optical devices. “This system applies a concept of quantum physics known as parity-time reversal symmetry,” explains Professor Cho. “This is an important platform that allows energy loss to be used as gain. It can be used to reduce laser threshold energy for classical optical devices and sensors, as well as quantum devices and controlling the direction of light.” The key is the design and materials. The hexagonal microcavity divides light particles into two different modes: one that passes through the upward-facing triangle of the hexagon and another that passes through its downward-facing triangle. Both modes of light particles have the same energy and path but don’t interact with each other. However, the light particles do interact with other particles called excitons, provided by the hexagonal microcavity, which is made of semiconductors. This interaction leads to the generation of new quantum particles called polaritons that then interact with each other to generate the polariton laser. By controlling the degree of loss between the microcavity and the semiconductor substrate, an intriguing phenomenon arises, with the threshold energy becoming smaller as energy loss increases. This research was supported by the Samsung Science and Technology Foundation and Korea’s National Research Foundation. -PublicationSong,H.G, Choi, M, Woo, K.Y. Yong-Hoon Cho Room-temperature polaritonic non-Hermitian system with single microcavityNature Photonics (https://doi.org/10.1038/s41566-021-00820-z) -ProfileProfessor Yong-Hoon ChoQuantum & Nanobio Photonics Laboratoryhttp://qnp.kaist.ac.kr/ Department of PhysicsKAIST
2021.07.07
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Defining the Hund Physics Landscape of Two-Orbital Systems
Researchers identify exotic metals in unexpected quantum systems Electrons are ubiquitous among atoms, subatomic tokens of energy that can independently change how a system behaves—but they also can change each other. An international research collaboration found that collectively measuring electrons revealed unique and unanticipated findings. The researchers published their results on May 17 in Physical Review Letters. “It is not feasible to obtain the solution just by tracing the behavior of each individual electron,” said paper author Myung Joon Han, professor of physics at KAIST. “Instead, one should describe or track all the entangled electrons at once. This requires a clever way of treating this entanglement.” Professor Han and the researchers used a recently developed “many-particle” theory to account for the entangled nature of electrons in solids, which approximates how electrons locally interact with one another to predict their global activity. Through this approach, the researchers examined systems with two orbitals — the space in which electrons can inhabit. They found that the electrons locked into parallel arrangements within atom sites in solids. This phenomenon, known as Hund’s coupling, results in a Hund’s metal. This metallic phase, which can give rise to such properties as superconductivity, was thought only to exist in three-orbital systems. “Our finding overturns a conventional viewpoint that at least three orbitals are needed for Hund’s metallicity to emerge,” Professor Han said, noting that two-orbital systems have not been a focus of attention for many physicists. “In addition to this finding of a Hund’s metal, we identified various metallic regimes that can naturally occur in generic, correlated electron materials.” The researchers found four different correlated metals. One stems from the proximity to a Mott insulator, a state of a solid material that should be conductive but actually prevents conduction due to how the electrons interact. The other three metals form as electrons align their magnetic moments — or phases of producing a magnetic field — at various distances from the Mott insulator. Beyond identifying the metal phases, the researchers also suggested classification criteria to define each metal phase in other systems. “This research will help scientists better characterize and understand the deeper nature of so-called ‘strongly correlated materials,’ in which the standard theory of solids breaks down due to the presence of strong Coulomb interactions between electrons,” Professor Han said, referring to the force with which the electrons attract or repel each other. These interactions are not typically present in solid materials but appear in materials with metallic phases. The revelation of metals in two-orbital systems and the ability to determine whole system electron behavior could lead to even more discoveries, according to Professor Han. “This will ultimately enable us to manipulate and control a variety of electron correlation phenomena,” Professor Han said. Co-authors include Siheon Ryee from KAIST and Sangkook Choi from the Condensed Matter Physics and Materials Science Department, Brookhaven National Laboratory in the United States. Korea’s National Research Foundation and the U.S. Department of Energy’s (DOE) Office of Science, Basic Energy Sciences, supported this work. -PublicationSiheon Ryee, Myung Joon Han, and SangKook Choi, 2021.Hund Physics Landscape of Two-Orbital Systems, Physical Review Letters, DOI: 10.1103/PhysRevLett.126.206401 -ProfileProfessor Myung Joon HanDepartment of PhysicsCollege of Natural ScienceKAIST
2021.06.17
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Observing Individual Atoms in 3D Nanomaterials and Their Surfaces
Atoms are the basic building blocks for all materials. To tailor functional properties, it is essential to accurately determine their atomic structures. KAIST researchers observed the 3D atomic structure of a nanoparticle at the atom level via neural network-assisted atomic electron tomography. Using a platinum nanoparticle as a model system, a research team led by Professor Yongsoo Yang demonstrated that an atomicity-based deep learning approach can reliably identify the 3D surface atomic structure with a precision of 15 picometers (only about 1/3 of a hydrogen atom’s radius). The atomic displacement, strain, and facet analysis revealed that the surface atomic structure and strain are related to both the shape of the nanoparticle and the particle-substrate interface. Combined with quantum mechanical calculations such as density functional theory, the ability to precisely identify surface atomic structure will serve as a powerful key for understanding catalytic performance and oxidation effect. “We solved the problem of determining the 3D surface atomic structure of nanomaterials in a reliable manner. It has been difficult to accurately measure the surface atomic structures due to the ‘missing wedge problem’ in electron tomography, which arises from geometrical limitations, allowing only part of a full tomographic angular range to be measured. We resolved the problem using a deep learning-based approach,” explained Professor Yang. The missing wedge problem results in elongation and ringing artifacts, negatively affecting the accuracy of the atomic structure determined from the tomogram, especially for identifying the surface structures. The missing wedge problem has been the main roadblock for the precise determination of the 3D surface atomic structures of nanomaterials. The team used atomic electron tomography (AET), which is basically a very high-resolution CT scan for nanomaterials using transmission electron microscopes. AET allows individual atom level 3D atomic structural determination. “The main idea behind this deep learning-based approach is atomicity—the fact that all matter is composed of atoms. This means that true atomic resolution electron tomogram should only contain sharp 3D atomic potentials convolved with the electron beam profile,” said Professor Yang. “A deep neural network can be trained using simulated tomograms that suffer from missing wedges as inputs, and the ground truth 3D atomic volumes as targets. The trained deep learning network effectively augments the imperfect tomograms and removes the artifacts resulting from the missing wedge problem.” The precision of 3D atomic structure can be enhanced by nearly 70% by applying the deep learning-based augmentation. The accuracy of surface atom identification was also significantly improved. Structure-property relationships of functional nanomaterials, especially the ones that strongly depend on the surface structures, such as catalytic properties for fuel-cell applications, can now be revealed at one of the most fundamental scales: the atomic scale. Professor Yang concluded, “We would like to fully map out the 3D atomic structure with higher precision and better elemental specificity. And not being limited to atomic structures, we aim to measure the physical, chemical, and functional properties of nanomaterials at the 3D atomic scale by further advancing electron tomography techniques.” This research, reported at Nature Communications, was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research M3I3 Project. -Publication Juhyeok Lee, Chaehwa Jeong & Yongsoo Yang “Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography” Nature Communications -Profile Professor Yongsoo Yang Department of Physics Multi-Dimensional Atomic Imaging Lab (MDAIL) http://mdail.kaist.ac.kr KAIST
2021.05.12
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Deep-Learning and 3D Holographic Microscopy Beats Scientists at Analyzing Cancer Immunotherapy
Live tracking and analyzing of the dynamics of chimeric antigen receptor (CAR) T-cells targeting cancer cells can open new avenues for the development of cancer immunotherapy. However, imaging via conventional microscopy approaches can result in cellular damage, and assessments of cell-to-cell interactions are extremely difficult and labor-intensive. When researchers applied deep learning and 3D holographic microscopy to the task, however, they not only avoided these difficultues but found that AI was better at it than humans were. Artificial intelligence (AI) is helping researchers decipher images from a new holographic microscopy technique needed to investigate a key process in cancer immunotherapy “live” as it takes place. The AI transformed work that, if performed manually by scientists, would otherwise be incredibly labor-intensive and time-consuming into one that is not only effortless but done better than they could have done it themselves. The research, conducted by the team of Professor YongKeun Park from the Department of Physics, appeared in the journal eLife last December. A critical stage in the development of the human immune system’s ability to respond not just generally to any invader (such as pathogens or cancer cells) but specifically to that particular type of invader and remember it should it attempt to invade again is the formation of a junction between an immune cell called a T-cell and a cell that presents the antigen, or part of the invader that is causing the problem, to it. This process is like when a picture of a suspect is sent to a police car so that the officers can recognize the criminal they are trying to track down. The junction between the two cells, called the immunological synapse, or IS, is the key process in teaching the immune system how to recognize a specific type of invader. Since the formation of the IS junction is such a critical step for the initiation of an antigen-specific immune response, various techniques allowing researchers to observe the process as it happens have been used to study its dynamics. Most of these live imaging techniques rely on fluorescence microscopy, where genetic tweaking causes part of a protein from a cell to fluoresce, in turn allowing the subject to be tracked via fluorescence rather than via the reflected light used in many conventional microscopy techniques. However, fluorescence-based imaging can suffer from effects such as photo-bleaching and photo-toxicity, preventing the assessment of dynamic changes in the IS junction process over the long term. Fluorescence-based imaging still involves illumination, whereupon the fluorophores (chemical compounds that cause the fluorescence) emit light of a different color. Photo-bleaching or photo-toxicity occur when the subject is exposed to too much illumination, resulting in chemical alteration or cellular damage. One recent option that does away with fluorescent labelling and thereby avoids such problems is 3D holographic microscopy or holotomography (HT). In this technique, the refractive index (the way that light changes direction when encountering a substance with a different density—why a straw looks like it bends in a glass of water) is recorded in 3D as a hologram. Until now, HT has been used to study single cells, but never cell-cell interactions involved in immune responses. One of the main reasons is the difficulty of “segmentation,” or distinguishing the different parts of a cell and thus distinguishing between the interacting cells; in other words, deciphering which part belongs to which cell. Manual segmentation, or marking out the different parts manually, is one option, but it is difficult and time-consuming, especially in three dimensions. To overcome this problem, automatic segmentation has been developed in which simple computer algorithms perform the identification. “But these basic algorithms often make mistakes,” explained Professor YongKeun Park, “particularly with respect to adjoining segmentation, which of course is exactly what is occurring here in the immune response we’re most interested in.” So, the researchers applied a deep learning framework to the HT segmentation problem. Deep learning is a type of machine learning in which artificial neural networks based on the human brain recognize patterns in a way that is similar to how humans do this. Regular machine learning requires data as an input that has already been labelled. The AI “learns” by understanding the labeled data and then recognizes the concept that has been labelled when it is fed novel data. For example, AI trained on a thousand images of cats labelled “cat” should be able to recognize a cat the next time it encounters an image with a cat in it. Deep learning involves multiple layers of artificial neural networks attacking much larger, but unlabeled datasets, in which the AI develops its own ‘labels’ for concepts it encounters. In essence, the deep learning framework that KAIST researchers developed, called DeepIS, came up with its own concepts by which it distinguishes the different parts of the IS junction process. To validate this method, the research team applied it to the dynamics of a particular IS junction formed between chimeric antigen receptor (CAR) T-cells and target cancer cells. They then compared the results to what they would normally have done: the laborious process of performing the segmentation manually. They found not only that DeepIS was able to define areas within the IS with high accuracy, but that the technique was even able to capture information about the total distribution of proteins within the IS that may not have been easily measured using conventional techniques. “In addition to allowing us to avoid the drudgery of manual segmentation and the problems of photo-bleaching and photo-toxicity, we found that the AI actually did a better job,” Professor Park added. The next step will be to combine the technique with methods of measuring how much physical force is applied by different parts of the IS junction, such as holographic optical tweezers or traction force microscopy. -Profile Professor YongKeun Park Department of Physics Biomedical Optics Laboratory http://bmol.kaist.ac.kr KAIST
2021.02.24
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Drawing the Line to Answer Art’s Big Questions
- KAIST scientists show how statistical physics can reveal art trends across time and culture. - Algorithms have shown that the compositional structure of Western landscape paintings changed “suspiciously” smoothly between 1500 and 2000 AD, potentially indicating a selection bias by art curators or in art historical literature, physicists from the Korea Advanced Institute of Science and Technology (KAIST) and colleagues report in the Proceedings of the National Academy of Sciences (PNAS). KAIST statistical physicist Hawoong Jeong worked with statisticians, digital analysts and art historians in Korea, Estonia and the US to clarify whether computer algorithms could help resolve long-standing questions about design principles used in landscape paintings, such as the placement of the horizon and other primary features. “A foundational question among art historians is whether artwork contains organizing principles that transcend culture and time and, if yes, how these principles evolved over time,” explains Jeong. “We developed an information-theoretic approach that can capture compositional proportion in landscape paintings and found that the preferred compositional proportion systematically evolved over time.” Digital versions of almost 15,000 canonical landscape paintings from the Western renaissance in the 1500s to the more recent contemporary art period were run through a computer algorithm. The algorithm progressively divides artwork into horizontal and vertical lines depending on the amount of information in each subsequent partition. It allows scientists to evaluate how artists and various art styles compose landscape artwork, in terms of placement of a piece’s most important components, in addition to how high or low the landscape’s horizon is placed. The scientists started by analysing the first two partitioning lines identified by the algorithm in the paintings and found they could be categorized into four groups: an initial horizontal line followed by a second horizontal line (H-H); an initial horizontal line followed by a second vertical line (H-V); a vertical followed by horizontal line (V-H); or a vertical followed by a vertical line (V-V) (see image 1 and 2). They then looked at the categorizations over time. They found that before the mid-nineteenth century, H-V was the dominant composition type, followed by H-H, V-H, and V-V. The mid-nineteenth century then brought change, with the H-V composition style decreasing in popularity with a rise in the H-H composition style. The other two styles remained relatively stable. The scientists also looked at how the horizon line, which separates sky from land, changed over time. In the 16th century, the dominant horizon line of the painting was above the middle of the canvas, but it gradually descended to the lower middle of the canvas by the 17th century, where it remained until the mid-nineteenth century. After that, the horizon line began gradually rising again. Interestingly, the algorithm showed that these findings were similar across cultures and artistic periods, even through periods dominated by a diversity in art styles. This similarity may well be a function, then, of a bias in the dataset. “In recent decades, art historians have prioritized the argument that there is great diversity in the evolution of artistic expression rather than offering a relatively smoother consensus story in Western art,” Jeong says. “This study serves as a reminder that the available large-scale datasets might be perpetuating severe biases.” The scientists next aim to broaden their analyses to include more diverse artwork, as this particular dataset was ultimately Western and male biased. Future analyses should also consider diagonal compositions in paintings, they say. This work was supported by the National Research Foundation (NRF) of Korea. Publication: Lee, B, et al. (2020) Dissecting landscape art history with information theory. Proceedings of the National Academy of Sciences (PNAS), Vol. 117, No. 43, 26580-26590. Available online at https://doi.org/10.1073/pnas.2011927117 Profile: Hawoong Jeong, Ph.D. Professor hjeong@kaist.ac.kr https://www.kaist.ac.kr Department of Physics Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea (END)
2020.11.13
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Highly Efficient Charge-to-Spin Interconversion in Graphene Heterostructures
Researchers present a new route for designing a graphene-based active spintronic component KAIST physicists described a route to design the energy-efficient generation, manipulation and detection of spin currents using nonmagnetic two-dimensional materials. The research team, led by Professor Sungjae Cho, observed highly efficient charge-to-spin interconversion via the gate-tunable Rashba-Edelstien effect (REE) in graphene heterostructures. This research paves the way for the application of graphene as an active spintronic component for generating, controlling, and detecting spin current without ferromagnetic electrodes or magnetic fields. Graphene is a promising spintronic component owing to its long spin diffusion length. However, its small spin-orbit coupling limits the potential of graphene in spintronic applications since graphene cannot be used to generate, control, or detect spin current. “We successfully increased the spin-orbit coupling of graphene by stacking graphene on top of 2H-TaS2, which is one of the transition metal dichalcogenide materials with the largest spin-orbit coupling. Graphene now can be used to generate, control, and detect spin current,” Professor Cho said. The Rashba-Edelstein effect is a physical mechanism that enables charge current-to-spin current interconversion by spin-dependent band structure induced by the Rashba effect, a momentum-dependent splitting of spin bands in low-dimensional condensed matter systems. Professor Cho’s group demonstrated the gate-tunable Rashba-Edelstein effect in a multilayer graphene for the first time. The Rahsba-Edelstein effect allows the two-dimensional conduction electrons of graphene to be magnetized by an applied charge current and form a spin current. Furthermore, as the Fermi level of graphene, tuned by gate voltage, moves from the valence to conduction band, the spin current generated by graphene reversed its spin direction. This spin reversal is useful in the design of low-power-consumption transistors utilizing spins in that it provides the carrier “On” state with spin up holes (or spin down electrons) and the "Off" state with zero net spin polarization at so called “charge neutrality point” where numbers of electrons and holes are equal. “Our work is the first demonstration of charge-to-spin interconversion in a metallic TMD (transition-metal dichalcogenides) and graphene heterostructure with a spin polarization state controlled by a gate. We expect that the all-electrical spin-switching effect and the reversal of non-equilibrium spin polarization by the application of gate voltage is applicable for the energy-efficient generation and manipulation of spin currents using nonmagnetic van der Waals materials,” explained Professor Cho. This study (https://pubs.acs.org/doi/10.1021/acsnano.0c01037) was supported by the National Research Foundation of Korea. Publication: Lijun Li, Jin Zhang, Gyuho Myeong, Wongil Shin, Hongsik Lim, Boram Kim, Seungho Kim, Taehyeok Jin, Stuart Cavill, Beom Seo Kim, Changyoung Kim, Johannes Lischner, Aires Ferreira, and Sungjae Cho, Gate-Tunable Reversible Rashba−Edelstein Effect in a Few-Layer Graphene/2H-TaS2 Heterostructure at Room Temperature. ACS Nano 2020. Link to download the paper: https://pubs.acs.org/doi/10.1021/acsnano.0c01037 Profile: Professor Sungjae Cho, PhD sungjae.cho@kaist.ac.kr http://qtak.kaist.ac.kr Department of Physics Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea
2020.05.18
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‘OSK Rising Stars 30’ Recognizes Four KAISTians
Four KAISTians were selected as star researchers to brighten the future of optics in commemoration of the 30th anniversary of the Optical Society of Korea (OSK). As ‘OSK Rising Stars 30’, the OSK named 27 domestic researchers under the age of 40 who have made significant contributions and will continue contributing to the development of Korea’s optics academia and industry. Professor YongKeun Park from the Department of Physics was selected in recognition of his contributions to the field of biomedical optics. Professor Park focuses on developing novel optical methods for understanding, diagnosing, and treating human diseases, based on light scattering, light manipulation, and interferometry. As a member of numerous international optics societies including the OSA and the SPIE and a co-founder of two start-up companies, Professor Park continues to broaden his boundaries as a leading opticist and entrepreneur. Professor Jonghwa Shin from the Department of Materials Science and Engineering was recognized for blazing a trail in the field of broadband metamaterials. Professor Shin’s research on the broadband enhancement of the electric permittivity and refractive index of metamaterials has great potential in both academia and industry. Professor Hongki Yoo from the Department of Mechanical Engineering is expected to create a significant ripple effect in the diagnosis of cardiovascular disorders through the development of new optical imaging techniques and applications. Finally, Dr. Sejeong Kim, a KAIST graduate and a Chancellor’s postdoctoral research fellow at the University of Technology Sydney (UTS), was acknowledged for her optical device research utilizing two-dimensional materials. Dr. Kim’s research at UTS now focuses on the introduction of micro/nano cavities for new materials. (END)
2020.03.16
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Scientists Observe the Elusive Kondo Screening Cloud
Scientists ended a 50-year quest by directly observing a quantum phenomenon An international research group of Professor Heung-Sun Sim has ended a 50-year quest by directly observing a quantum phenomenon known as a Kondo screening cloud. This research, published in Nature on March 11, opens a novel way to engineer spin screening and entanglement. According to the research, the cloud can mediate interactions between distant spins confined in quantum dots, which is a necessary protocol for semiconductor spin-based quantum information processing. This spin-spin interaction mediated by the Kondo cloud is unique since both its strength and sign (two spins favor either parallel or anti-parallel configuration) are electrically tunable, while conventional schemes cannot reverse the sign. This phenomenon, which is important for many physical phenomena such as dilute magnetic impurities and spin glasses, is essentially a cloud that masks magnetic impurities in a material. It was known to exist but its spatial extension had never been observed, creating controversy over whether such an extension actually existed. Magnetism arises from a property of electrons known as spin, meaning that they have angular momentum aligned in one of either two directions, conventionally known as up and down. However, due to a phenomenon known as the Kondo effect, the spins of conduction electrons—the electrons that flow freely in a material—become entangled with a localized magnetic impurity, and effectively screen it. The strength of this spin coupling, calibrated as a temperature, is known as the Kondo temperature. The size of the cloud is another important parameter for a material containing multiple magnetic impurities because the spins in the cloud couple with one another and mediate the coupling between magnetic impurities when the clouds overlap. This happens in various materials such as Kondo lattices, spin glasses, and high temperature superconductors. Although the Kondo effect for a single magnetic impurity is now a text-book subject in many-body physics, detection of its key object, the Kondo cloud and its length, has remained elusive despite many attempts during the past five decades. Experiments using nuclear magnetic resonance or scanning tunneling microscopy, two common methods for understanding the structure of matter, have either shown no signature of the cloud, or demonstrated a signature only at a very short distance, less than 1 nanometer, so much shorter than the predicted cloud size, which was in the micron range. In the present study, the authors observed a Kondo screening cloud formed by an impurity defined as a localized electron spin in a quantum dot—a type of “artificial atom”—coupled to quasi-one-dimensional conduction electrons, and then used an interferometer to measure changes in the Kondo temperature, allowing them to investigate the presence of a cloud at the interferometer end. Essentially, they slightly perturbed the conduction electrons at a location away from the quantum dot using an electrostatic gate. The wave of conducting electrons scattered by this perturbation returned back to the quantum dot and interfered with itself. This is similar to how a wave on a water surface being scattered by a wall forms a stripe pattern. The Kondo cloud is a quantum mechanical object which acts to preserve the wave nature of electrons inside the cloud. Even though there is no direct electrostatic influence of the perturbation on the quantum dot, this interference modifies the Kondo signature measured by electron conductance through the quantum dot if the perturbation is present inside the cloud. In the study, the researchers found that the length as well as the shape of the cloud is universally scaled by the inverse of the Kondo temperature, and that the cloud’s size and shape were in good agreement with theoretical calculations. Professor Sim at the Department of Physics proposed the method for detecting the Kondo cloud in the co-research with the RIKEN Center for Emergent Matter Science, the City University of Hong Kong, the University of Tokyo, and Ruhr University Bochum in Germany. Professor Sim said, “The observed spin cloud is a micrometer-size object that has quantum mechanical wave nature and entanglement. This is why the spin cloud has not been observed despite a long search. It is remarkable in a fundamental and technical point of view that such a large quantum object can now be created, controlled, and detected. Dr. Michihisa Yamamoto of the RIKEN Center for Emergent Matter Science also said, “It is very satisfying to have been able to obtain real space image of the Kondo cloud, as it is a real breakthrough for understanding various systems containing multiple magnetic impurities. The size of the Kondo cloud in semiconductors was found to be much larger than the typical size of semiconductor devices.” Publication: Borzenets et al. (2020) Observation of the Kondo screening cloud. Nature, 579. pp.210-213. Available online at https://doi.org/10.1038/s41586-020-2058-6 Profile: Heung-Sun Sim, PhD Professor hssim@kaist.ac.kr https://qet.kaist.ac.kr/ Quantum Electron Correlation & Transport Theory Group (QECT Lab) https://qc.kaist.ac.kr/index.php/group1/ Center for Quantum Coherence In COndensed Matter Department of Physics https://www.kaist.ac.kr Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea
2020.03.13
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Ultrafast Quantum Motion in a Nanoscale Trap Detected
< Professor Heung-Sun Sim (left) and Co-author Dr. Sungguen Ryu (right) > KAIST researchers have reported the detection of a picosecond electron motion in a silicon transistor. This study has presented a new protocol for measuring ultrafast electronic dynamics in an effective time-resolved fashion of picosecond resolution. The detection was made in collaboration with Nippon Telegraph and Telephone Corp. (NTT) in Japan and National Physical Laboratory (NPL) in the UK and is the first report to the best of our knowledge. When an electron is captured in a nanoscale trap in solids, its quantum mechanical wave function can exhibit spatial oscillation at sub-terahertz frequencies. Time-resolved detection of such picosecond dynamics of quantum waves is important, as the detection provides a way of understanding the quantum behavior of electrons in nano-electronics. It also applies to quantum information technologies such as the ultrafast quantum-bit operation of quantum computing and high-sensitivity electromagnetic-field sensing. However, detecting picosecond dynamics has been a challenge since the sub-terahertz scale is far beyond the latest bandwidth measurement tools. A KAIST team led by Professor Heung-Sun Sim developed a theory of ultrafast electron dynamics in a nanoscale trap, and proposed a scheme for detecting the dynamics, which utilizes a quantum-mechanical resonant state formed beside the trap. The coupling between the electron dynamics and the resonant state is switched on and off at a picosecond so that information on the dynamics is read out on the electric current being generated when the coupling is switched on. NTT realized, together with NPL, the detection scheme and applied it to electron motions in a nanoscale trap formed in a silicon transistor. A single electron was captured in the trap by controlling electrostatic gates, and a resonant state was formed in the potential barrier of the trap. The switching on and off of the coupling between the electron and the resonant state was achieved by aligning the resonance energy with the energy of the electron within a picosecond. An electric current from the trap through the resonant state to an electrode was measured at only a few Kelvin degrees, unveiling the spatial quantum-coherent oscillation of the electron with 250 GHz frequency inside the trap. Professor Sim said, “This work suggests a scheme of detecting picosecond electron motions in submicron scales by utilizing quantum resonance. It will be useful in dynamical control of quantum mechanical electron waves for various purposes in nano-electronics, quantum sensing, and quantum information”. This work was published online at Nature Nanotechnology on November 4. It was partly supported by the Korea National Research Foundation through the SRC Center for Quantum Coherence in Condensed Matter. For more on the NTT news release this article, please visit https://www.ntt.co.jp/news2019/1911e/191105a.html -ProfileProfessor Heung-Sun Sim Department of PhysicsDirector, SRC Center for Quantum Coherence in Condensed Matterhttps://qet.kaist.ac.kr KAIST -Publication:Gento Yamahata, Sungguen Ryu, Nathan Johnson, H.-S. Sim, Akira Fujiwara, and Masaya Kataoka. 2019. Picosecond coherent electron motion in a silicon single-electron source. Nature Nanotechnology (Online Publication). 6 pages. https://doi.org/10.1038/s41565-019-0563-2
2019.11.05
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Dr. Sejeong Kim Recognized as Excellent Young Scientist
(Dr. Sejeong Kim) Dr. Sejeong Kim, a postdoctoral research associate in the School of Mathematical and Physical Sciences at the University of Technology Sydney was honored to receive the Excellence Award for a Young Scientist by the Korea Federation of Women’s Science & Technology Association (KOFWST). The award ceremony will be held on October 31 in Seoul. KOFWST recognizes ten promising young female scientists and engineers every year who show significant potential, passion, and remarkable achievement in their work. The awardees are selected among those who finished their degree within the previous five years. Dr. Kim earned her Ph.D. in physics at KAIST in 2014 and was selected as the winner in the field of physics in recognition of her outstanding research activities in photonics. Dr. Kim conducted various research activities in the field of photonics and was published in high impact journals including Nano Letters and Advanced materials. In July, she developed the first photonic cavity from van der Waals materials and published the study in Nature Communications titled “Photonic Crystal Cavities from Hexagonal Boron Nitride.” At UTS, she carries out research activities supervised by Professor Igor Aharonovich and has engaged in many science outreach activities.
2018.10.18
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Professor YongKeun Park Wins the 2018 Fumio Okano Award
(Professor Park) Professor YongKeun Park from the Department of Physics won the 2018 Fumio Okano Award in recognition of his contributions to 3D display technology development during the annual conference of the International Society for Optics and Photonics (SPIE) held last month in Orlando, Florida in the US. The Fumio Okano Best 3D Paper Prize is presented annually in memory of Dr. Fumio Okano, a pioneer and innovator of 3D displays who passed away in 2013, for his contributions to the field of 3D TVs and displays. The award is sponsored by NHK-ES. Professor Park and his team are developing novel technology for measuring and visualizing 3D images by applying random light scattering. He has published numerous papers on 3D holographic camera technology and 3000x enhanced performance of 3D holographic displays in renowned international journals such as Nature Photonics, Nature Communications, and Science Advances. His technology has drawn international attention from renowned media outlets including Newsweek and Forbes. He has established two startups to commercialize his technology. Tomocube specializes in 3D imaging microscopes using holotomographic technology and the company exports their products to several countries including the US and Japan. The.Wave.Talk is exploring technology for examining pre-existing bacteria anywhere and anytime. Professor Park’s innovations have already been recognized in and out of KAIST. In February, he was selected as the KAISTian of the Year for his outstanding research, commercialization, and startups. He was also decorated with the National Science Award in April by the Ministry of Science and ICT and the Hong Jin-Ki Innovation Award later in May by the Yumin Cultural Foundation. Professor Park said, “3D holography is emerging as a significant technology with growing potential and positive impacts on our daily lives. However, the current technology lags far behind the levels displayed in SF movies. We will do our utmost to reach this level with more commercialization."
2018.05.31
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Park Chosen for Principality of Monaco/ITER Postdoctoral Fellowship
(Jaesun Park in the Integrated Master's and Doctoral Degree Program ) Jaesun Park from the Department of Physics, was selected as a Principality of Monaco/ITER Postdoctoral Fellowship recipient. This program was established by the Principality of Monaco and an international organization, ITER, in January 2008 to support postdoctoral researchers who will be working for ITER. It is a relatively competitive program because it chooses only five people every two years. The selected postdoctoral researchers will be working for ITER for two years while conducting research projects with outstanding researchers in the field of nuclear fusion. ITER, one of the most ambitious energy projects, was launched in 1985 with the purpose of carrying out joint research on nuclear fusion energy. Currently, about 800 people are working for this organization. Seven ITER member countries (i.e. Korea, the European Union, the United States, China, Japan, Russia, and India) are sharing the expenses and engaging in mega-scale science projects. Korea shares 9.1% (20 billion Euro) of the total construction costs of ITER experimental devices. Park will begin his duties in early 2019.
2018.05.04
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