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Tomographic Measurement of Dielectric Tensors
Dielectric tensor tomography allows the direct measurement of the 3D dielectric tensors of optically anisotropic structures A research team reported the direct measurement of dielectric tensors of anisotropic structures including the spatial variations of principal refractive indices and directors. The group also demonstrated quantitative tomographic measurements of various nematic liquid-crystal structures and their fast 3D nonequilibrium dynamics using a 3D label-free tomographic method. The method was described in Nature Materials. Light-matter interactions are described by the dielectric tensor. Despite their importance in basic science and applications, it has not been possible to measure 3D dielectric tensors directly. The main challenge was due to the vectorial nature of light scattering from a 3D anisotropic structure. Previous approaches only addressed 3D anisotropic information indirectly and were limited to two-dimensional, qualitative, strict sample conditions or assumptions. The research team developed a method enabling the tomographic reconstruction of 3D dielectric tensors without any preparation or assumptions. A sample is illuminated with a laser beam with various angles and circularly polarization states. Then, the light fields scattered from a sample are holographically measured and converted into vectorial diffraction components. Finally, by inversely solving a vectorial wave equation, the 3D dielectric tensor is reconstructed. Professor YongKeun Park said, “There were a greater number of unknowns in direct measuring than with the conventional approach. We applied our approach to measure additional holographic images by slightly tilting the incident angle.” He said that the slightly tilted illumination provides an additional orthogonal polarization, which makes the underdetermined problem become the determined problem. “Although scattered fields are dependent on the illumination angle, the Fourier differentiation theorem enables the extraction of the same dielectric tensor for the slightly tilted illumination,” Professor Park added. His team’s method was validated by reconstructing well-known liquid crystal (LC) structures, including the twisted nematic, hybrid aligned nematic, radial, and bipolar configurations. Furthermore, the research team demonstrated the experimental measurements of the non-equilibrium dynamics of annihilating, nucleating, and merging LC droplets, and the LC polymer network with repeating 3D topological defects. “This is the first experimental measurement of non-equilibrium dynamics and 3D topological defects in LC structures in a label-free manner. Our method enables the exploration of inaccessible nematic structures and interactions in non-equilibrium dynamics,” first author Dr. Seungwoo Shin explained. -PublicationSeungwoo Shin, Jonghee Eun, Sang Seok Lee, Changjae Lee, Herve Hugonnet, Dong Ki Yoon, Shin-Hyun Kim, Jongwoo Jeong, YongKeun Park, “Tomographic Measurement ofDielectric Tensors at Optical Frequency,” Nature Materials March 02, 2022 (https://doi.org/10/1038/s41563-022-01202-8) -ProfileProfessor YongKeun ParkBiomedical Optics Laboratory (http://bmol.kaist.ac.kr)Department of PhysicsCollege of Natural SciencesKAIST
Label-Free Multiplexed Microtomography of Endogenous Subcellular Dynamics Using Deep Learning
AI-based holographic microscopy allows molecular imaging without introducing exogenous labeling agents A research team upgraded the 3D microtomography observing dynamics of label-free live cells in multiplexed fluorescence imaging. The AI-powered 3D holotomographic microscopy extracts various molecular information from live unlabeled biological cells in real time without exogenous labeling or staining agents. Professor YongKeum Park’s team and the startup Tomocube encoded 3D refractive index tomograms using the refractive index as a means of measurement. Then they decoded the information with a deep learning-based model that infers multiple 3D fluorescence tomograms from the refractive index measurements of the corresponding subcellular targets, thereby achieving multiplexed micro tomography. This study was reported in Nature Cell Biology online on December 7, 2021. Fluorescence microscopy is the most widely used optical microscopy technique due to its high biochemical specificity. However, it needs to genetically manipulate or to stain cells with fluorescent labels in order to express fluorescent proteins. These labeling processes inevitably affect the intrinsic physiology of cells. It also has challenges in long-term measuring due to photobleaching and phototoxicity. The overlapped spectra of multiplexed fluorescence signals also hinder the viewing of various structures at the same time. More critically, it took several hours to observe the cells after preparing them. 3D holographic microscopy, also known as holotomography, is providing new ways to quantitatively image live cells without pretreatments such as staining. Holotomography can accurately and quickly measure the morphological and structural information of cells, but only provides limited biochemical and molecular information. The 'AI microscope' created in this process takes advantage of the features of both holographic microscopy and fluorescence microscopy. That is, a specific image from a fluorescence microscope can be obtained without a fluorescent label. Therefore, the microscope can observe many types of cellular structures in their natural state in 3D and at the same time as fast as one millisecond, and long-term measurements over several days are also possible. The Tomocube-KAIST team showed that fluorescence images can be directly and precisely predicted from holotomographic images in various cells and conditions. Using the quantitative relationship between the spatial distribution of the refractive index found by AI and the major structures in cells, it was possible to decipher the spatial distribution of the refractive index. And surprisingly, it confirmed that this relationship is constant regardless of cell type. Professor Park said, “We were able to develop a new concept microscope that combines the advantages of several microscopes with the multidisciplinary research of AI, optics, and biology. It will be immediately applicable for new types of cells not included in the existing data and is expected to be widely applicable for various biological and medical research.” When comparing the molecular image information extracted by AI with the molecular image information physically obtained by fluorescence staining in 3D space, it showed a 97% or more conformity, which is a level that is difficult to distinguish with the naked eye. “Compared to the sub-60% accuracy of the fluorescence information extracted from the model developed by the Google AI team, it showed significantly higher performance,” Professor Park added. This work was supported by the KAIST Up program, the BK21+ program, Tomocube, the National Research Foundation of Korea, and the Ministry of Science and ICT, and the Ministry of Health & Welfare. -Publication Hyun-seok Min, Won-Do Heo, YongKeun Park, et al. “Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning,” Nature Cell Biology (doi.org/10.1038/s41556-021-00802-x) published online December 07 2021. -Profile Professor YongKeun Park Biomedical Optics Laboratory Department of Physics KAIST
Quantum Emitters: Beyond Crystal Clear to Single-Photon Pure
‘Nanoscale Focus Pinspot’ can quench only the background noise without changing the optical properties of the quantum emitter and the built-in photonic structure Photons, fundamental particles of light, are carrying these words to your eyes via the light from your computer screen or phone. Photons play a key role in the next-generation quantum information technology, such as quantum computing and communications. A quantum emitter, capable of producing a single, pure photon, is the crux of such technology but has many issues that have yet to be solved, according to KAIST researchers. A research team under Professor Yong-Hoon Cho has developed a technique that can isolate the desired quality emitter by reducing the noise surrounding the target with what they have dubbed a ‘nanoscale focus pinspot.’ They published their results on June 24 in ACS Nano. “The nanoscale focus pinspot is a structurally nondestructive technique under an extremely low dose ion beam and is generally applicable for various platforms to improve their single-photon purity while retaining the integrated photonic structures,” said lead author Yong-Hoon Cho from the Department of Physics at KAIST. To produce single photons from solid state materials, the researchers used wide-bandgap semiconductor quantum dots — fabricated nanoparticles with specialized potential properties, such as the ability to directly inject current into a small chip and to operate at room temperature for practical applications. By making a quantum dot in a photonic structure that propagates light, and then irradiating it with helium ions, researchers theorized that they could develop a quantum emitter that could reduce the unwanted noisy background and produce a single, pure photon on demand. Professor Cho explained, “Despite its high resolution and versatility, a focused ion beam typically suppresses the optical properties around the bombarded area due to the accelerated ion beam’s high momentum. We focused on the fact that, if the focused ion beam is well controlled, only the background noise can be selectively quenched with high spatial resolution without destroying the structure.” In other words, the researchers focused the ion beam on a mere pin prick, effectively cutting off the interactions around the quantum dot and removing the physical properties that could negatively interact with and degrade the photon purity emitted from the quantum dot. “It is the first developed technique that can quench the background noise without changing the optical properties of the quantum emitter and the built-in photonic structure,” Professor Cho asserted. Professor Cho compared it to stimulated emission depletion microscopy, a technique used to decrease the light around the area of focus, but leaving the focal point illuminated. The result is increased resolution of the desired visual target. “By adjusting the focused ion beam-irradiated region, we can select the target emitter with nanoscale resolution by quenching the surrounding emitter,” Professor Cho said. “This nanoscale selective-quenching technique can be applied to various material and structural platforms and further extended for applications such as optical memory and high-resolution micro displays.” Korea’s National Research Foundation and the Samsung Science and Technology Foundation supported this work. -PublicationMinho Choi, Seongmoon Jun, and Yong-Hoon Cho et al. ACS Nano‘Nanoscale Focus Pinspot for High-Purity Quantum Emitters via Focused-Ion-Beam-Induced Luminescence Quenching,’(https://pubs.acs.org/doi/10.1021/acsnano.1c00587) -ProfileProfessor Yong-Hoon ChoQuantum & Nanobio Photonics Laboratoryhttp://qnp.kaist.ac.kr/ Department of PhysicsKAIST
Professor Heung-Sun Sim the MSIT Scientist of July
Professor Heung-Sun Sim from the Department of Physics was selected as the Scientist of July by the Ministry of Science and ICT. Professor Sim was recognized for his research of the Kondo effect, which opened a novel way to engineer spin screening and entanglement by directly observing a quantum phenomenon known as a Kondo screening cloud. His research revealed that 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 phenomenon 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. The research was reported in Nature in March 2020. With this award, Professor Sim received 10 million KRW in prize money.
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
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
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
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
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 firstname.lastname@example.org https://www.kaist.ac.kr Department of Physics Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea (END)
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 email@example.com http://qtak.kaist.ac.kr Department of Physics Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea
‘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)
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 firstname.lastname@example.org 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
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