Science
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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 View 13266 -
Coordination Chemistry and Alzheimer’s Disease
It has become evident recently that the interactions between copper and amyloid-b neurotoxically impact the brain of patients with Alzheimer’s disease. KAIST researchers have reported a new strategy to alter the neurotoxicity in Alzheimer’s disease by using a rationally designed chemical reagent.
This strategy, developed by Professor Mi Hee Lim from the Department of Chemistry, can modify the coordination sphere of copper bound to amyloid-b, effectively inhibiting copper’s binding to amyloid-b and altering its aggregation and toxicity. Their study was featured in PNAS last month.
The researchers developed a small molecule that is able to directly interact with the coordination sphere of copper–amyloid-b complexes followed by modifications via either covalent conjugation, oxidation, or both under aerobic conditions. The research team simply utilized copper–dioxygen chemistry to design a chemical reagent.
Answering how peptide modifications by a small molecule occur remains very challenging. The system includes transition metals and amyloidogenic proteins and is quite heterogeneous, since they are continuously being changed. It is critical to carefully check the multiple variables such as the presence of dioxygen and the type of transition metal ions and amyloidogenic proteins in order to identify the underlying mechanisms and target specificity of the chemical reagent.
The research team employed various biophysical and biochemical methods to determine the mechanisms for modifications on the coordination sphere of copper–Aꞵ complexes. Among them, peptide modifications were mainly analyzed using electrospray ionization-mass spectrometry.
Mass spectrometry (MS) has been applied to verify such peptide modifications by calculating the shift in exact mass. The research team also performed collision-induced dissociation (CID) of the target ion detected by MS to pinpoint which amino acid residue is specifically modified. The CID fragmentizes the amide bond located between the amino acid residues. This fragmental analysis allows us to identify the specific sites of peptide modifications.
The copper and amyloid-b complexes represent a pathological connection between metal ions and amyloid-b in Alzheimer’s disease. Recent findings indicate that copper and amyloid-b can directly contribute toward neurodegeneration by producing toxic amyloid-b oligomers and reactive oxygen species.
Professor Lim said, “This study illustrates the first experimental evidence that the 14th histidine residue in copper–amyloid-b complexes can be specifically modified through either covalent conjugation, oxidation, or both. Considering the neurotoxic implications of the interactions between copper and amyloid-b, such modifications at the coordination sphere of copper in amyloid-b could effectively alter its properties and toxicity.”
“This multidisciplinary study with an emphasis on approaches, reactivities, and mechanisms looks forward to opening a new way to develop candidates of anti-neurodegenerative diseases,” she added. The National Research Foundation of Korea funded this research.
2020.03.03 View 6708 -
Black Phosphorous Tunnel Field-Effect Transistor as an Alternative Ultra-low Power Switch
Researchers have reported a black phosphorus transistor that can be used as an alternative ultra-low power switch. A research team led by Professor Sungjae Cho in the KAIST Department of Physics developed a thickness-controlled black phosphorous tunnel field-effect transistor (TFET) that shows 10-times lower switching power consumption as well as 10,000-times lower standby power consumption than conventional complementary metal-oxide-semiconductor (CMOS) transistors.
The research team said they developed fast and low-power transistors that can replace conventional CMOS transistors. In particular, they solved problems that have degraded TFET operation speed and performance, paving the way to extend Moore’s Law.
In the study featured in Nature Nanotechnology last month, Professor Cho’s team reported a natural heterojunction TFET with spatially varying layer thickness in black phosphorous without interface problems. They achieved record-low average subthreshold swing values over 4-5 dec of current and record-high, on-state current, which allows the TFETs to operate as fast as conventional CMOS transistors with as much lower power consumption.
"We successfully developed the first transistor that achieved the essential criteria for fast, low-power switching. Our newly developed TFETs can replace CMOS transistors by solving a major issue regarding the performance degradation of TFETs,"Professor Cho said.
The continuous down-scaling of transistors has been the key to the successful development of current information technology. However, with Moore’s Law reaching its limits due to the increased power consumption, the development of new alternative transistor designs has emerged as an urgent need.
Reducing both switching and standby power consumption while further scaling transistors requires overcoming the thermionic limit of subthreshold swing, which is defined as the required voltage per ten-fold current increase in the subthreshold region. In order to reduce both the switching and standby power of CMOS circuits, it is critical to reduce the subthreshold swing of the transistors.
However, there is fundamental subthreshold swing limit of 60 mV/dec in CMOS transistors, which originates from thermal carrier injection. The International Roadmap for Devices and Systems has already predicted that new device geometries with new materials beyond CMOS will be required to address transistor scaling challenges in the near future. In particular, TFETs have been suggested as a major alternative to CMOS transistors, since the subthreshold swing in TFETs can be substantially reduced below the thermionic limit of 60 mV/dec. TFETs operate via quantum tunneling, which does not limit subthreshold swing as in thermal injection of CMOS transistors.
In particular, heterojunction TFETs hold significant promise for delivering both low subthreshold swing and high on-state current. High on-current is essential for the fast operation of transistors since charging a device to on state takes a longer time with lower currents. Unlike theoretical expectations, previously developed heterojunction TFETs show 100-100,000x lower on-state current (100-100,000x slower operation speeds) than CMOS transistors due to interface problems in the heterojunction. This low operation speed impedes the replacement of CMOS transistors with low-power TFETs.
Professor Cho said, “We have demonstrated for the first time, to the best of our knowledge, TFET optimization for both fast and ultra-low-power operations, which is essential to replace CMOS transistors for low-power applications.” He said he is very delighted to extend Moore’s Law, which may eventually affect almost every aspect of life and society. This study (https://doi.org/10.1038/s41565-019-0623-7) was supported by the National Research Foundation of Korea.
Publication:
Kim et al. (2020) Thickness-controlled black phosphorus tunnel field-effect transistor for low-power switches. Nature Nanotechnology. Available online at https://doi.org/10.1038/s41565-019-0623-7
Profile:
Professor Sungjae Cho
sungjae.cho@kaist.ac.kr
Department of Physics
http://qtak.kaist.ac.kr/
KAIST
Profile:
Seungho Kim, PhD Candidate
krksh21@kaist.ac.kr
Department of Physics
http://qtak.kaist.ac.kr/
KAIST
(END)
2020.02.21 View 10531 -
Rachmaninoff the most innovative of 18th and 19th century composers according to network science
Rachmaninoff, followed by Bach, Brahms and Mendelssohn, was the most innovative of the composers who worked during the Baroque, Classical and Romantic eras of music (1700 to 1900) according to a study published in the open access journal EPJ Data Science.
A team of researchers from KAIST (Korea Advanced Institute of Science and Technology), calculated novelty scores for 900 classical piano compositions written by 19 composers between approximately 1700 and 1900. The scores were based on how musical compositions differed from all prior pieces of piano music and how they differed from previous piano works by the same composer. The authors found that composers from the Romantic era (1820 to 1910) tended to have high novelty scores.
The authors from the Graduate School of Culture Technology at KAIST created a computer model which divided each composition into segments called ‘codewords’. Each ‘codeword’ consisted of all of the notes played together at a given time. Sequences of ‘codewords’ were then compared between compositions. The similarities between the sequences were used to create novelty scores for each composer and to determine the extent to which composers influenced each other.
Juyong Park, the corresponding author, said: “Our model allows us to calculate the degree of shared melodies and harmonies between past and future works and to observe the evolution of western musical styles by demonstrating how prominent composers may have influenced each other. The period of music we studied is widely credited for having produced many musical styles that are still influential today.”
The model distinguished each new musical period from the one before it by the rise of newly dominant and highly influential composers that indicated dramatic shifts in musical styles. The authors found that compositions from the Classical period (1750 to 1820) tended to have the lowest novelty scores. During this period Haydn and Mozart were highly influential but were later overtaken by Beethoven during the Classical-to-Romantic transitional period.
The most innovative composer, indicated by the highest combined novelty score, was Rachmaninoff. His work during the Romantic era was novel when compared to the compositions of the other 18 composers included in the study, and his later works were novel compared to his earlier works.
Lower novelty did not necessarily correlate with low influence. Beethoven was ranked in the lower half of novelty scores yet was the most influential composer during the Romantic period (1820 to 1910) and is widely considered one of the greatest composers of all time.
Dr. Park said: “While novelty is necessary in a creative work it cannot account for all the creative and artistic qualities that go into creating melodies and harmonies that spread to later generations of composers. That may be why being more novel did not necessarily result in composers being more influential.”
The authors suggest that their method could be applied to narrative or visual artworks by creating codewords from groups of words or colours and shapes. However, they caution that as only piano compositions were included in their analysis, it is unknown whether including all works by the 19 composers would have resulted in another composer being identified as the most original.
Profile: Prof. Juyong Park, PhD
juyongp@kaist.ac.kr
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr
Daejeon 34141, Korea
(END)
2020.01.31 View 4471 -
New Insights into How the Human Brain Solves Complex Decision-Making Problems
A new study on meta reinforcement learning algorithms helps us understand how the human brain learns to adapt to complexity and uncertainty when learning and making decisions. A research team, led by Professor Sang Wan Lee at KAIST jointly with John O’Doherty at Caltech, succeeded in discovering both a computational and neural mechanism for human meta reinforcement learning, opening up the possibility of porting key elements of human intelligence into artificial intelligence algorithms. This study provides a glimpse into how it might ultimately use computational models to reverse engineer human reinforcement learning.
This work was published on Dec 16, 2019 in the journal Nature Communications. The title of the paper is “Task complexity interacts with state-space uncertainty in the arbitration between model-based and model-free learning.”
Human reinforcement learning is an inherently complex and dynamic process, involving goal setting, strategy choice, action selection, strategy modification, cognitive resource allocation etc. This a very challenging problem for humans to solve owing to the rapidly changing and multifaced environment in which humans have to operate. To make matters worse, humans often need to often rapidly make important decisions even before getting the opportunity to collect a lot of information, unlike the case when using deep learning methods to model learning and decision-making in artificial intelligence applications.
In order to solve this problem, the research team used a technique called 'reinforcement learning theory-based experiment design' to optimize the three variables of the two-stage Markov decision task - goal, task complexity, and task uncertainty. This experimental design technique allowed the team not only to control confounding factors, but also to create a situation similar to that which occurs in actual human problem solving.
Secondly, the team used a technique called ‘model-based neuroimaging analysis.’ Based on the acquired behavior and fMRI data, more than 100 different types of meta reinforcement learning algorithms were pitted against each other to find a computational model that can explain both behavioral and neural data. Thirdly, for the sake of a more rigorous verification, the team applied an analytical method called ‘parameter recovery analysis,’ which involves high-precision behavioral profiling of both human subjects and computational models.
In this way, the team was able to accurately identify a computational model of meta reinforcement learning, ensuring not only that the model’s apparent behavior is similar to that of humans, but also that the model solves the problem in the same way as humans do.
The team found that people tended to increase planning-based reinforcement learning (called model-based control), in response to increasing task complexity. However, they resorted to a simpler, more resource efficient strategy called model-free control, when both uncertainty and task complexity were high. This suggests that both the task uncertainty and the task complexity interact during the meta control of reinforcement learning. Computational fMRI analyses revealed that task complexity interacts with neural representations of the reliability of the learning strategies in the inferior prefrontal cortex.
These findings significantly advance understanding of the nature of the computations being implemented in the inferior prefrontal cortex during meta reinforcement learning as well as providing insight into the more general question of how the brain resolves uncertainty and complexity in a dynamically changing environment. Identifying the key computational variables that drive prefrontal meta reinforcement learning, can also inform understanding of how this process might be vulnerable to break down in certain psychiatric disorders such as depression and OCD. Furthermore, gaining a computational understanding of how this process can sometimes lead to increased model-free control, can provide insights into how under some situations task performance might break down under conditions of high cognitive load.
Professor Lee said, “This study will be of enormous interest to researchers in both the artificial intelligence and human/computer interaction fields since this holds significant potential for applying core insights gleaned into how human intelligence works with AI algorithms.”
This work was funded by the National Institute on Drug Abuse, the National Research Foundation of Korea, the Ministry of Science and ICT, Samsung Research Funding Center of Samsung Electronics.
Figure 1 (modified from the figures of the original paper doi:10.1038/s41467-019-13632-1). Computations implemented in the inferior prefrontal cortex during meta reinforcement learning. (A) Computational model of human prefrontal meta reinforcement learning (left) and the brain areas whose neural activity patterns are explained by the latent variables of the model. (B) Examples of behavioral profiles. Shown on the left is choice bias for different goal types and on the right is choice optimality for task complexity and uncertainty. (C) Parameter recoverability analysis. Compared are the effect of task uncertainty (left) and task complexity (right) on choice optimality.
-Profile
Professor Sang Wan Lee
sangwan@kaist.ac.kr
Department of Bio and Brain Engineering
Director, KAIST Center for Neuroscience-inspired AI
KAIST Institute for Artificial Intelligence (http://aibrain.kaist.ac.kr)
KAIST Institute for Health, Science, and Technology
KAIST (https://www.kaist.ac.kr)
2020.01.31 View 5265 -
KAIST Vaccine for Tick-Borne Disease ‘SFTS’ Protects Against Lethal Infection
A KAIST research team reported the development of a DNA vaccine for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) which completely protects against lethal infection in ferrets. The team confirmed that ferrets immunized with DNA vaccines encoding all SFTSV proteins showed 100% survival rate without detectable viremia and did not develop any clinical symptoms. This study was published in Nature Communications on August 23.
Severe Fever with Thrombocytopenia Syndrome (SFTS) is a newly emerging tick-borne infectious disease. The disease causes fever, severe thrombocytopenia, leukocytopenia as well as vomiting and diarrhea. Severe cases end up with organ system failure often accompanied by hemorrhages, and its mortality rate stands at 10–20%.
The viral disease has been endemic to East Asia but the spread of the tick vector to North America increases the likelihood of potential outbreak beyond the Far East Asia. The World Health Organization (WHO) has also put SFTSV into the priority pathogen requiring urgent attention category. Currently, no vaccine has been available to prevent SFTS.
The research team led by Professor Su-Hyung Park noted that DNA vaccines induce broader immunity to multiple antigens than traditional ones. Moreover, DNA vaccines stimulate both T cell and antibody immunity, which make them suitable for vaccine development.
They constructed DNA vaccines that encode full-length Gn, Gc, N, NS, and RNA polymerase genes based on common sequences of 31 SFTSV strains isolated from patients. Their vaccine candidates induced both neutralizing antibody response and multifunctional SFTSV-specific T cell response in mice and ferrets.
To investigate the vaccine’s efficacy in vivo, the research team applied a recently developed ferret model that recapitulates fatal clinical symptoms in SFTSV infection in humans. Vaccinated ferrets were completely protected from lethal SFTSV challenge without SFTSV detection in their blood, whereas all control ferrets died within 10 days’ post-infection.
The KAIST team found that anti-envelope antibodies play an important role in protective immunity, suggesting that envelope glycoproteins of SFTSV may be the most effective antigens for inducing protective immunity. Moreover, the study revealed that T cell responses specific to non-envelope proteins of SFTSV also can contribute to protection against SFTSV infection.
Professor Park said, “This is the first study demonstrating complete protection against lethal SFTSV challenge using an immunocompetent, middle-sized animal model with clinical manifestations of SFTSV infection. We believe this study provides valuable insights into designing preventive vaccines for SFTSV.”
2020.01.31 View 4664 -
Professor Youngseok Ju Awarded the 13th ASAN Award for Young Medical Scientists
Professor Youngseok Ju from the Graduate School of Medical Science and Engineering was selected for the 13th ASAN Award for Young Medical Scientists under the age of 40. Professor Ju will receive 50 million won in prize money.
The ASAN Foundation established this Award in 2007 to encourage young medical scientists who accomplished outstanding achievements in basic and clinical medicine.
The winners are chosen based on a comprehensive assessment of consistency and originality, domestic and international impact, and contributions to medical development and fostering future generations.
Professor Ju is known for having identified the generation principle of cancer genome mutations. In particular, he is recognized for his contributions to the development of cancer prevention, diagnosis, and treatment, by having proven that some cases of lung cancer can occur from destructive changes in chromosomes in lung cells regardless of smoking.
The award ceremony will be held on March 19 in Seoul. The other award will be given to Professor Yong-Ho Lee from the Yonsei University College of Medicine.
2020.01.31 View 3649 -
Scientists Discover the Mechanism of DNA High-Order Structure Formation
(Molecular structures of Abo1 in different energy states (left), Demonstration of an Abo1-assisted histone loading onto DNA by the DNA curtain assay. )
The genetic material of our cells—DNA—exists in a high-order structure called “chromatin”. Chromatin consists of DNA wrapped around histone proteins and efficiently packs DNA into a small volume. Moreover, using a spool and thread analogy, chromatin allows DNA to be locally wound or unwound, thus enabling genes to be enclosed or exposed. The misregulation of chromatin structures results in aberrant gene expression and can ultimately lead to developmental disorders or cancers. Despite the importance of DNA high-order structures, the complexity of the underlying machinery has circumvented molecular dissection.
For the first time, molecular biologists have uncovered how one particular mechanism uses energy to ensure proper histone placement onto DNA to form chromatin. They published their results on Dec. 17 in Nature Communications.
The study focused on proteins called histone chaperones. Histone chaperones are responsible for adding and removing specific histones at specific times during the DNA packaging process. The wrong histone at the wrong time and place could result in the misregulation of gene expression or aberrant DNA replication. Thus, histone chaperones are key players in the assembly and disassembly of chromatin.
“In order to carefully control the assembly and disassembly of chromatin units, histone chaperones act as molecular escorts that prevent histone aggregation and undesired interactions,” said Professor Ji-Joon Song in the Department of Biological Sciences at KAIST. “We set out to understand how a unique histone chaperone uses chemical energy to assemble or disassemble chromatin.”
Song and his team looked to Abo1, the only known histone chaperone that utilizes cellular energy (ATP). While Abo1 is found in yeast, it has an analogous partner in other organisms, including humans, called ATAD2. Both use ATP, which is produced through a cellular process where enzymes break down a molecule’s phosphate bond. ATP energy is typically used to power other cellular processes, but it is a rare partner for histone chaperones.
“This was an interesting problem in the field because all other histone chaperones studied to date do not use ATP,” Song said.
By imaging Abo1 with a single-molecule fluorescence imaging technique known as the DNA curtain assay, the researchers could examine the protein interactions at the single-molecule level. The technique allows scientists to arrange the DNA molecules and proteins on a single layer of a microfluidic chamber and examine the layer with fluorescence microscopy.
The researchers found through real-time observation that Abo1 is ring-shaped and changes its structure to accommodate a specific histone and deposit it on DNA. Moreover, they found that the accommodating structural changes are powered by ADP.
“We discovered a mechanism by which Abo1 accommodates histone substrates, ultimately allowing it to function as a unique energy-dependent histone chaperone,” Song said. “We also found that despite looking like a protein disassembly machine, Abo1 actually loads histone substrates onto DNA to facilitate chromatin assembly.”
The researchers plan to continue exploring how energy-dependent histone chaperones bind and release histones, with the ultimate goal of developing therapeutics that can target cancer-causing misbehavior by Abo1’s analogous human counterpart, ATAD2.
-Profile
Professor Ji-Joon Song
Department of Biological Sciences KI for the BioCentury (https://kis.kaist.ac.kr/index.php?mid=KIB_O) KAIST
2020.01.07 View 8798 -
Gallium-Based Solvating Agent Efficiently Analyzes Optically Active Alcohols
A KAIST research team has developed a gallium-based metal complex enabling the rapid chiral analysis of alcohols. A team working under Professor Hyunwoo Kim reported the efficient new alcohol analysis method using nuclear magnetic resonance (NMR) spectroscopy in iScience.
Enantiopure chiral alcohols are ubiquitous in nature and widely utilized as pharmaceuticals. This importance of chirality in synthetic and medicinal chemistry has advanced the search for rapid and facile methods to determine the enantiomeric purities of compounds. To date, chiral analysis has been performed using high-performance liquid chromatography (HPLC) with chiral columns.
Along with the HPLC technique, chiral analysis using NMR spectroscopy has gained tremendous attention as an alternative to traditionally employed chromatographic methods due to its simplicity and rapid detection for real-time measurement. However, this method carries drawbacks such as line-broadening, narrow substrate scope, and poor resolution. Thus, compared with popular methods of chromatographic analysis, NMR spectroscopy is infrequently used for chiral analysis.
In principle, a chiral solvating agent is additionally required for the NMR measurement of chiral alcohols to obtain two distinct signals. However, NMR analysis of chiral alcohols has been challenging due to weak binding interactions with chiral solvating agents. To overcome the intrinsic difficulty of relatively weak molecular interactions that are common for alcohols, many researchers have used multifunctional alcohols to enhance interactions with solvating agents.
Instead, the KAIST team successfully varied the physical properties of metal complexes to induce stronger interactions with alcohols rather than the strategy of using multifunctional analytes, in the hopes of developing a universal chiral solvating agent for alcohols. Compared to the current method of chiral analysis used in the pharmaceutical industry, alcohols that do not possess chromophores can also be directly analyzed with the gallium complexes.
Professor Kim said that this method could be a complementary chiral analysis technique at the industry level in the near future. He added that since the developed gallium complex can determine enantiomeric excess within minutes, it can be further utilized to monitor asymmetric synthesis. This feature will benefit a large number of researchers in the organic chemistry community, as well as the pharmaceutical industry.
(Figure: Schematic view of the in-situ direct 1H NMR chiral analysis.)
-Profile:
Professor Hyunwoo Kim
Department of Chemistry
KAIST
http://mdos.kaist.ac.kr
hwk34@kaist.ac.kr
For more on this article,
please go to https://doi.org/10.1016/j.isci2019.07051
2019.11.14 View 10107 -
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 View 15760 -
A Single, Master Switch for Sugar Levels?
When a fly eats sugar, a single brain cell sends simultaneous messages to stimulate one hormone and inhibit another to control glucose levels in the body. Further research into this control system with remarkable precision could shed light on the neural mechanisms of diabetes and obesity in humans .
A single neuron appears to monitor and control sugar levels in the fly body, according to research published this week in Nature. This new insight into the mechanisms in the fly brain that maintain a balance of two key hormones controlling glucose levels, insulin and glucagon, can provide a framework for understanding diabetes and obesity in humans.
Neurons that sense and respond to glucose were identified more than 50 years ago, but what they do in our body has remained unclear. Researchers at the Korea Advanced Institute of Science and Technology (KAIST) and New York University School of Medicine have now found a single “glucose-sensing neuron” that appears to be the master controller in Drosophila, the vinegar fly, for maintaining an ideal glucose balance, called homeostasis.
Professor Greg Seong-Bae Suh, Dr. Yangkyun Oh and colleagues identified a key neuron that is excited by glucose, which they called CN neuron. This CN neuron has a unique shape – it has an axon (which is used to transmit information to downstream cells) that is bifurcated. One branch projects to insulin-producing cells, and sends a signal triggering the secretion of the insulin equivalent in flies. The other branch projects to glucagon-producing cells and sends a signal inhibiting the secretion of the glucagon equivalent.
When flies consume food, the levels of glucose in their body increase; this excites the CN neuron, which fires the simultaneous signals to stimulate insulin and inhibit glucagon secretion, thereby maintaining the appropriate balance between the hormones and sugar in the blood. The researchers were able to see this happening in the brain in real time by using a combination of cutting-edge fluorescent calcium imaging technology, as well as measuring hormone and sugar levels and applying highly sophisticated molecular genetic techniques.
When flies were not fed, however, the researchers observed a reduction in the activity of CN neuron, a reduction in insulin secretion and an increase in glucagon secretion. These findings indicate that these key hormones are under the direct control of the glucose-sensing neuron. Furthermore, when they silenced the CN neuron rendering dysfunctional CN neuron in flies, these animals experienced an imbalance, resulting in hyperglycemia – high levels of sugars in the blood, similar to what is observed in diabetes in humans. This further suggests that the CN neuron is critical to maintaining glucose homeostasis in animals.
While further research is required to investigate this process in humans, Suh notes this is a significant step forward in the fields of both neurobiology and endocrinology.
“This work lays the foundation for translational research to better understand how this delicate regulatory process is affected by diabetes, obesity, excessive nutrition and diets high in sugar,” Suh said.
Profile: Greg Seong-Bae Suh
seongbaesuh@kaist.ac.kr
Professor Department of Biological Sciences
KAIST
(Figure: A single glucose-excited CN neuron extends bifurcated axonal branches,
one of which innervates insulin producing cells and stimulates their activity an the other axonal branch projects to glucagon producing cells and inhibits their activity.)
2019.10.24 View 16258 -
Image Analysis to Automatically Quantify Gender Bias in Movies
Many commercial films worldwide continue to express womanhood in a stereotypical manner, a recent study using image analysis showed. A KAIST research team developed a novel image analysis method for automatically quantifying the degree of gender bias in films.
The ‘Bechdel Test’ has been the most representative and general method of evaluating gender bias in films. This test indicates the degree of gender bias in a film by measuring how active the presence of women is in a film. A film passes the Bechdel Test if the film (1) has at least two female characters, (2) who talk to each other, and (3) their conversation is not related to the male characters.
However, the Bechdel Test has fundamental limitations regarding the accuracy and practicality of the evaluation. Firstly, the Bechdel Test requires considerable human resources, as it is performed subjectively by a person. More importantly, the Bechdel Test analyzes only a single aspect of the film, the dialogues between characters in the script, and provides only a dichotomous result of passing the test, neglecting the fact that a film is a visual art form reflecting multi-layered and complicated gender bias phenomena. It is also difficult to fully represent today’s various discourse on gender bias, which is much more diverse than in 1985 when the Bechdel Test was first presented.
Inspired by these limitations, a KAIST research team led by Professor Byungjoo Lee from the Graduate School of Culture Technology proposed an advanced system that uses computer vision technology to automatically analyzes the visual information of each frame of the film. This allows the system to more accurately and practically evaluate the degree to which female and male characters are discriminatingly depicted in a film in quantitative terms, and further enables the revealing of gender bias that conventional analysis methods could not yet detect.
Professor Lee and his researchers Ji Yoon Jang and Sangyoon Lee analyzed 40 films from Hollywood and South Korea released between 2017 and 2018. They downsampled the films from 24 to 3 frames per second, and used Microsoft’s Face API facial recognition technology and object detection technology YOLO9000 to verify the details of the characters and their surrounding objects in the scenes.
Using the new system, the team computed eight quantitative indices that describe the representation of a particular gender in the films. They are: emotional diversity, spatial staticity, spatial occupancy, temporal occupancy, mean age, intellectual image, emphasis on appearance, and type and frequency of surrounding objects.
Figure 1. System Diagram
Figure 2. 40 Hollywood and Korean Films Analyzed in the Study
According to the emotional diversity index, the depicted women were found to be more prone to expressing passive emotions, such as sadness, fear, and surprise. In contrast, male characters in the same films were more likely to demonstrate active emotions, such as anger and hatred.
Figure 3. Difference in Emotional Diversity between Female and Male Characters
The type and frequency of surrounding objects index revealed that female characters and automobiles were tracked together only 55.7 % as much as that of male characters, while they were more likely to appear with furniture and in a household, with 123.9% probability.
In cases of temporal occupancy and mean age, female characters appeared less frequently in films than males at the rate of 56%, and were on average younger in 79.1% of the cases. These two indices were especially conspicuous in Korean films.
Professor Lee said, “Our research confirmed that many commercial films depict women from a stereotypical perspective. I hope this result promotes public awareness of the importance of taking prudence when filmmakers create characters in films.”
This study was supported by KAIST College of Liberal Arts and Convergence Science as part of the Venture Research Program for Master’s and PhD Students, and will be presented at the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) on November 11 to be held in Austin, Texas.
Publication:
Ji Yoon Jang, Sangyoon Lee, and Byungjoo Lee. 2019. Quantification of Gender Representation Bias in Commercial Films based on Image Analysis. In Proceedings of the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW). ACM, New York, NY, USA, Article 198, 29 pages. https://doi.org/10.1145/3359300
Link to download the full-text paper:
https://files.cargocollective.com/611692/cscw198-jangA--1-.pdf
Profile: Prof. Byungjoo Lee, MD, PhD
byungjoo.lee@kaist.ac.kr
http://kiml.org/
Assistant Professor
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
Profile: Ji Yoon Jang, M.S.
yoone3422@kaist.ac.kr
Interactive Media Lab
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
Profile: Sangyoon Lee, M.S. Candidate
sl2820@kaist.ac.kr
Interactive Media Lab
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
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2019.10.17 View 22696