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Neuromorphic Memory Device Simulates Neurons and Synapses
Simultaneous emulation of neuronal and synaptic properties promotes the development of brain-like artificial intelligence Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic computing designed to rigorously mimic the human brain with semiconductor devices. Neuromorphic computing aims to realize artificial intelligence (AI) by mimicking the mechanisms of neurons and synapses that make up the human brain. Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses still remains a challenge. To address these issues, a research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices. Similar to commercial graphics cards, the artificial synaptic devices previously studied often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost efficiency. The human brain consists of a complex network of 100 billion neurons and 100 trillion synapses. The functions and structures of neurons and synapses can flexibly change according to the external stimuli, adapting to the surrounding environment. The research team developed a neuromorphic device in which short-term and long-term memories coexist using volatile and non-volatile memory devices that mimic the characteristics of neurons and synapses, respectively. A threshold switch device is used as volatile memory and phase-change memory is used as a non-volatile device. Two thin-film devices are integrated without intermediate electrodes, implementing the functional adaptability of neurons and synapses in the neuromorphic memory. Professor Keon Jae Lee explained, "Neurons and synapses interact with each other to establish cognitive functions such as memory and learning, so simulating both is an essential element for brain-inspired artificial intelligence. The developed neuromorphic memory device also mimics the retraining effect that allows quick learning of the forgotten information by implementing a positive feedback effect between neurons and synapses.” This result entitled “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse” was published in the May 19, 2022 issue of Nature Communications. -Publication:Sang Hyun Sung, Tae Jin Kim, Hyera Shin, Tae Hong Im, and Keon Jae Lee (2022) “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse,” Nature Communications May 19, 2022 (DOI: 10.1038/s41467-022-30432-2) -Profile:Professor Keon Jae Leehttp://fand.kaist.ac.kr Department of Materials Science and EngineeringKAIST
2022.05.20
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'Fingerprint' Machine Learning Technique Identifies Different Bacteria in Seconds
A synergistic combination of surface-enhanced Raman spectroscopy and deep learning serves as an effective platform for separation-free detection of bacteria in arbitrary media Bacterial identification can take hours and often longer, precious time when diagnosing infections and selecting appropriate treatments. There may be a quicker, more accurate process according to researchers at KAIST. By teaching a deep learning algorithm to identify the “fingerprint” spectra of the molecular components of various bacteria, the researchers could classify various bacteria in different media with accuracies of up to 98%. Their results were made available online on Jan. 18 in Biosensors and Bioelectronics, ahead of publication in the journal’s April issue. Bacteria-induced illnesses, those caused by direct bacterial infection or by exposure to bacterial toxins, can induce painful symptoms and even lead to death, so the rapid detection of bacteria is crucial to prevent the intake of contaminated foods and to diagnose infections from clinical samples, such as urine. “By using surface-enhanced Raman spectroscopy (SERS) analysis boosted with a newly proposed deep learning model, we demonstrated a markedly simple, fast, and effective route to classify the signals of two common bacteria and their resident media without any separation procedures,” said Professor Sungho Jo from the School of Computing. Raman spectroscopy sends light through a sample to see how it scatters. The results reveal structural information about the sample — the spectral fingerprint — allowing researchers to identify its molecules. The surface-enhanced version places sample cells on noble metal nanostructures that help amplify the sample’s signals. However, it is challenging to obtain consistent and clear spectra of bacteria due to numerous overlapping peak sources, such as proteins in cell walls. “Moreover, strong signals of surrounding media are also enhanced to overwhelm target signals, requiring time-consuming and tedious bacterial separation steps,” said Professor Yeon Sik Jung from the Department of Materials Science and Engineering. To parse through the noisy signals, the researchers implemented an artificial intelligence method called deep learning that can hierarchically extract certain features of the spectral information to classify data. They specifically designed their model, named the dual-branch wide-kernel network (DualWKNet), to efficiently learn the correlation between spectral features. Such an ability is critical for analyzing one-dimensional spectral data, according to Professor Jo. “Despite having interfering signals or noise from the media, which make the general shapes of different bacterial spectra and their residing media signals look similar, high classification accuracies of bacterial types and their media were achieved,” Professor Jo said, explaining that DualWKNet allowed the team to identify key peaks in each class that were almost indiscernible in individual spectra, enhancing the classification accuracies. “Ultimately, with the use of DualWKNet replacing the bacteria and media separation steps, our method dramatically reduces analysis time.” The researchers plan to use their platform to study more bacteria and media types, using the information to build a training data library of various bacterial types in additional media to reduce the collection and detection times for new samples. “We developed a meaningful universal platform for rapid bacterial detection with the collaboration between SERS and deep learning,” Professor Jo said. “We hope to extend the use of our deep learning-based SERS analysis platform to detect numerous types of bacteria in additional media that are important for food or clinical analysis, such as blood.” The National R&D Program, through a National Research Foundation of Korea grant funded by the Ministry of Science and ICT, supported this research. -PublicationEojin Rho, Minjoon Kim, Seunghee H. Cho, Bongjae Choi, Hyungjoon Park, Hanhwi Jang, Yeon Sik Jung, Sungho Jo, “Separation-free bacterial identification in arbitrary media via deepneural network-based SERS analysis,” Biosensors and Bioelectronics online January 18, 2022 (doi.org/10.1016/j.bios.2022.113991) -ProfileProfessor Yeon Sik JungDepartment of Materials Science and EngineeringKAIST Professor Sungho JoSchool of ComputingKAIST
2022.03.04
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Five Projects Ranked in the Top 100 for National R&D Excellence
Five KAIST research projects were selected as the 2021 Top 100 for National R&D Excellence by the Ministry of Science and ICT and the Korea Institute of Science & Technology Evaluation and Planning. The five projects are:-The development of E. coli that proliferates with only formic acid and carbon dioxide by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering -An original reverse aging technology that restores an old human skin cell into a younger one by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering-The development of next-generation high-efficiency perovskite-silicon tandem solar cells by Professor Byungha Shin from the Department of Materials Science and Engineering-Research on the effects of ultrafine dust in the atmosphere has on energy consumption by Professor Jiyong Eom from the School of Business and Technology Management-Research on a molecular trigger that controls the phase transformation of bio materials by Professor Myungchul Kim from the Department of Bio and Brain Engineering Started in 2006, an Evaluation Committee composed of experts in industries, universities, and research institutes has made the preliminary selections of the most outstanding research projects based on their significance as a scientific and technological development and their socioeconomic effects. The finalists went through an open public evaluation. The final 100 studies are from six fields: 18 from mechanics & materials, 26 from biology & marine sciences, 19 from ICT & electronics, 10 from interdisciplinary research, and nine from natural science and infrastructure. The selected 100 studies will receive a certificate and an award plaque from the minister of MSIT as well as additional points for business and institutional evaluations according to appropriate regulations, and the selected researchers will be strongly recommended as candidates for national meritorious awards. In particular, to help the 100 selected research projects become more accessible for the general public, their main contents will be provided in a free e-book ‘The Top 100 for National R&D Excellence of 2021’ that will be available from online booksellers.
2022.02.17
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New Chiral Nanostructures to Extend the Material Platform
Researchers observed a wide window of chiroptical activity from nanomaterials A research team transferred chirality from the molecular scale to a microscale to extend material platforms and applications. The optical activity from this novel chiral material encompasses to short-wave infrared region. This platform could serve as a powerful strategy for hierarchical chirality transfer through self-assembly, generating broad optical activity and providing immense applications including bio, telecommunication, and imaging technique. This is the first observation of such a wide window of chiroptical activity from nanomaterials. “We synthesized chiral copper sulfides using cysteine, as the stabilizer, and transferring the chirality from molecular to the microscale through self-assembly,” explained Professor Jihyeon Yeom from the Department of Materials Science and Engineering, who led the research. The result was reported in ACS Nano on September 14. Chiral nanomaterials provide a rich platform for versatile applications. Tuning the wavelength of polarization rotation maxima in the broad range is a promising candidate for infrared neural stimulation, imaging, and nanothermometry. However, the majority of previously developed chiral nanomaterials revealed the optical activity in a relatively shorter wavelength range, not in short-wave infrared. To achieve chiroptical activity in the short-wave infrared region, materials should be in sub-micrometer dimensions, which are compatible with the wavelength of short-wave infrared region light for strong light-matter interaction. They also should have the optical property of short-wave infrared region absorption while forming a structure with chirality. Professor Yeom’s team induced self-assembly of the chiral nanoparticles by controlling the attraction and repulsion forces between the building block nanoparticles. During this process, molecular chirality of cysteine was transferred to the nanoscale chirality of nanoparticles, and then transferred to the micrometer scale chirality of nanoflowers with 1.5-2 2 μm dimensions formed by the self-assembly. “We will work to expand the wavelength range of chiroptical activity to the short-wave infrared region, thus reshaping our daily lives in the form of a bio-barcode that can store vast amount of information under the skin,” said Professor Yeom. This study was funded by the Ministry of Science and ICT, the Ministry of Health and Welfare, the Ministry of Food and Drug Safety, the National Research Foundation of Korea,the KAIST URP Program, the KAIST Creative Challenging Research Program, Samsung and POSCO Science Fellowship. -PublicationKi Hyun Park, Junyoung Kwon, Uichang Jeong, Ji-Young Kim, Nicholas A.Kotov, Jihyeon Yeom, “Broad Chrioptical Activity from Ultraviolet to Short-Wave Infrared by Chirality Transfer from Molecular to Micrometer Scale," September 14, 2021 ACS Nano (https://doi.org/10.1021/acsnano.1c05888) -ProfileProfessor Jihyeon YeomNovel Nanomaterials for New Platforms LaboratoryDepartment of Materials Science and EngineeringKAIST
2021.10.22
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Professor Il-Doo Kim Receives the Science Minister’s Award
Professor Il-Doo Kim from the Department of Materials Science and Engineering received the Science and ICT Minister’s Award in recognition of his commercialization and technology transfer achievements during the Day of IP celebration. Professor Kim, who has made over 222 patents application and registration home and abroad, has advanced toxic gas detection and breath gas sensor technology by arraying nanosensor fibers. His technological advances in micro-electro-mechanical systems (MEMS) helped to advance the commercialization of the MEMS-related sensor and improve its overall competitiveness. He founded the Il-Doo Kim Research Center in 2019 and focuses on the commercialization of nanofiber manufacturing through electrospinning and highly efficient nanofiber filters. For instance, he succeeded in manufacturing a nano-filter recyclable mask that maintains excellent filtering efficiency even after hand washing through the development of proprietary technology that aligns nanofibers with a diameter of 100~500 nanometers in orthogonal or unidirectional directions. Professor Kim also serves as an associate editor at ACS Nano. He said, “The importance of IP goes without saying. I look forward to the registration and application of more KAIST patents leading to commercialization, paving the way for national technological competitiveness.”
2021.09.15
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Biomimetic Resonant Acoustic Sensor Detecting Far-Distant Voices Accurately to Hit the Market
A KAIST research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering has developed a bioinspired flexible piezoelectric acoustic sensor with multi-resonant ultrathin piezoelectric membrane mimicking the basilar membrane of the human cochlea. The flexible acoustic sensor has been miniaturized for embedding into smartphones and the first commercial prototype is ready for accurate and far-distant voice detection. In 2018, Professor Lee presented the first concept of a flexible piezoelectric acoustic sensor, inspired by the fact that humans can accurately detect far-distant voices using a multi-resonant trapezoidal membrane with 20,000 hair cells. However, previous acoustic sensors could not be integrated into commercial products like smartphones and AI speakers due to their large device size. In this work, the research team fabricated a mobile-sized acoustic sensor by adopting ultrathin piezoelectric membranes with high sensitivity. Simulation studies proved that the ultrathin polymer underneath inorganic piezoelectric thin film can broaden the resonant bandwidth to cover the entire voice frequency range using seven channels. Based on this theory, the research team successfully demonstrated the miniaturized acoustic sensor mounted in commercial smartphones and AI speakers for machine learning-based biometric authentication and voice processing. (Please refer to the explanatory movie KAIST Flexible Piezoelectric Mobile Acoustic Sensor). The resonant mobile acoustic sensor has superior sensitivity and multi-channel signals compared to conventional condenser microphones with a single channel, and it has shown highly accurate and far-distant speaker identification with a small amount of voice training data. The error rate of speaker identification was significantly reduced by 56% (with 150 training datasets) and 75% (with 2,800 training datasets) compared to that of a MEMS condenser device. Professor Lee said, “Recently, Google has been targeting the ‘Wolverine Project’ on far-distant voice separation from multi-users for next-generation AI user interfaces. I expect that our multi-channel resonant acoustic sensor with abundant voice information is the best fit for this application. Currently, the mass production process is on the verge of completion, so we hope that this will be used in our daily lives very soon.” Professor Lee also established a startup company called Fronics Inc., located both in Korea and U.S. (branch office) to commercialize this flexible acoustic sensor and is seeking collaborations with global AI companies. These research results entitled “Biomimetic and Flexible Piezoelectric Mobile Acoustic Sensors with Multi-Resonant Ultrathin Structures for Machine Learning Biometrics” were published in Science Advances in 2021 (7, eabe5683). -Publication “Biomimetic and flexible piezoelectric mobile acoustic sensors with multiresonant ultrathin structures for machine learning biometrics,” Science Advances (DOI: 10.1126/sciadv.abe5683) -Profile Professor Keon Jae Lee Department of Materials Science and Engineering Flexible and Nanobio Device Lab http://fand.kaist.ac.kr/ KAIST
2021.06.14
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Professor Byungha Shin Named Scientist of the Month
Professor Byungha Shin from the Department of Materials Science and Engineering won the Scientist of the Month Award presented by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF) on May 4. Professor Shin was recognized for his research in the field of next-generation perovskite solar cells and received 10 million won in prize money. To achieve ‘carbon neutrality,’ which many countries across the globe including Korea hope to realize, the efficiency of converting renewable energies to electricity must be improved. Solar cells convert solar energy to electricity. Since single solar cells show lower efficiency, the development of ‘tandem solar cells’ that connect two or more cells together has been popular in recent years. However, although ‘perovskite’ received attention as a next-generation material for tandem solar cells, it is sensitive to the external environment including light and moisture, making it difficult to maintain stability. Professor Shin discovered that, theoretically, adding certain anion additives to perovskite solar cells would allow the control of the electrical and structural properties of the two-dimensional stabilization layer that forms inside the film. He confirmed this through high-resolution transmission electron microscopy. Controlling the amount of anions in the additives allowed the preservation of over 80% of the initial stability even after 1000 hours of continuous exposure to sunlight. Based on this discovery, Professor Shin combined silicon with solar cells to create a tandem solar cell with 26.7% energy convergence efficiency. Considering that the highest-efficiency tandem solar cell in existence showed 29.5% efficiency, this figure is quite high. Professor Shin’s perovskite solar cell is also combinable with the CIGS (Cu(In,Ga)Se2) thin-film solar cell composed of copper (Cu), indium (In), gallium (Ga), and selenium (Se2). Professor Shin’s research results were published in the online edition of the journal Science in April of last year. “This research is meaningful for having suggested a direction for solar cell material stabilization using additives,” said Professor Shin. “I look forward to this technique being applied to a wide range of photoelectrical devices including solar cells, LEDs, and photodetectors,” he added. (END)
2021.05.07
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Streamlining the Process of Materials Discovery
The materials platform M3I3 reduces the time for materials discovery by reverse engineering future materials using multiscale/multimodal imaging and machine learning of the processing-structure-properties relationship Developing new materials and novel processes has continued to change the world. The M3I3 Initiative at KAIST has led to new insights into advancing materials development by implementing breakthroughs in materials imaging that have created a paradigm shift in the discovery of materials. The Initiative features the multiscale modeling and imaging of structure and property relationships and materials hierarchies combined with the latest material-processing data. The research team led by Professor Seungbum Hong analyzed the materials research projects reported by leading global institutes and research groups, and derived a quantitative model using machine learning with a scientific interpretation. This process embodies the research goal of the M3I3: Materials and Molecular Modeling, Imaging, Informatics and Integration. The researchers discussed the role of multiscale materials and molecular imaging combined with machine learning and also presented a future outlook for developments and the major challenges of M3I3. By building this model, the research team envisions creating desired sets of properties for materials and obtaining the optimum processing recipes to synthesize them. “The development of various microscopy and diffraction tools with the ability to map the structure, property, and performance of materials at multiscale levels and in real time enabled us to think that materials imaging could radically accelerate materials discovery and development,” says Professor Hong. “We plan to build an M3I3 repository of searchable structural and property maps using FAIR (Findable, Accessible, Interoperable, and Reusable) principles to standardize best practices as well as streamline the training of early career researchers.” One of the examples that shows the power of structure-property imaging at the nanoscale is the development of future materials for emerging nonvolatile memory devices. Specifically, the research team focused on microscopy using photons, electrons, and physical probes on the multiscale structural hierarchy, as well as structure-property relationships to enhance the performance of memory devices. “M3I3 is an algorithm for performing the reverse engineering of future materials. Reverse engineering starts by analyzing the structure and composition of cutting-edge materials or products. Once the research team determines the performance of our targeted future materials, we need to know the candidate structures and compositions for producing the future materials.” The research team has built a data-driven experimental design based on traditional NCM (nickel, cobalt, and manganese) cathode materials. With this, the research team expanded their future direction for achieving even higher discharge capacity, which can be realized via Li-rich cathodes. However, one of the major challenges was the limitation of available data that describes the Li-rich cathode properties. To mitigate this problem, the researchers proposed two solutions: First, they should build a machine-learning-guided data generator for data augmentation. Second, they would use a machine-learning method based on ‘transfer learning.’ Since the NCM cathode database shares a common feature with a Li-rich cathode, one could consider repurposing the NCM trained model for assisting the Li-rich prediction. With the pretrained model and transfer learning, the team expects to achieve outstanding predictions for Li-rich cathodes even with the small data set. With advances in experimental imaging and the availability of well-resolved information and big data, along with significant advances in high-performance computing and a worldwide thrust toward a general, collaborative, integrative, and on-demand research platform, there is a clear confluence in the required capabilities of advancing the M3I3 Initiative. Professor Hong said, “Once we succeed in using the inverse “property−structure−processing” solver to develop cathode, anode, electrolyte, and membrane materials for high energy density Li-ion batteries, we will expand our scope of materials to battery/fuel cells, aerospace, automobiles, food, medicine, and cosmetic materials.” The review was published in ACS Nano in March. This study was conducted through collaborations with Dr. Chi Hao Liow, Professor Jong Min Yuk, Professor Hye Ryung Byon, Professor Yongsoo Yang, Professor EunAe Cho, Professor Pyuck-Pa Choi, and Professor Hyuck Mo Lee at KAIST, Professor Joshua C. Agar at Lehigh University, Dr. Sergei V. Kalinin at Oak Ridge National Laboratory, Professor Peter W. Voorhees at Northwestern University, and Professor Peter Littlewood at the University of Chicago (Article title: Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration).This work was supported by the KAIST Global Singularity Research Program for 2019 and 2020. Publication: “Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics and Integration,” S. Hong, C. H. Liow, J. M. Yuk, H. R. Byon, Y. Yang, E. Cho, J. Yeom, G. Park, H. Kang, S. Kim, Y. Shim, M. Na, C. Jeong, G. Hwang, H. Kim, H. Kim, S. Eom, S. Cho, H. Jun, Y. Lee, A. Baucour, K. Bang, M. Kim, S. Yun, J. Ryu, Y. Han, A. Jetybayeva, P.-P. Choi, J. C. Agar, S. V. Kalinin, P. W. Voorhees, P. Littlewood, and H. M. Lee, ACS Nano 15, 3, 3971–3995 (2021) https://doi.org/10.1021/acsnano.1c00211 Profile: Seungbum Hong, PhD Associate Professor seungbum@kaist.ac.kr http://mii.kaist.ac.kr Department of Materials Science and Engineering KAIST (END)
2021.04.05
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ACS Nano Special Edition Highlights Innovations at KAIST
- The collective intelligence and technological innovation of KAIST was highlighted with case studies including the Post-COVID-19 New Deal R&D Initiative Project. - KAIST’s innovative academic achievements and R&D efforts for addressing the world’s greatest challenges such as the COVID-19 pandemic were featured in ACS Nano as part of its special virtual issue commemorating the 50th anniversary of KAIST. The issue consisted of 14 review articles contributed by KAIST faculty from five departments, including two from Professor Il-Doo Kim from the Department of Materials Science and Engineering, who serves as an associate editor of the ACS Nano. ACS Nano, the leading international journal in nanoscience and nanotechnology, published a special virtual issue last month, titled ‘Celebrating 50 Years of KAIST: Collective Intelligence and Innovation for Confronting Contemporary Issues.’ This special virtual issue introduced KAIST’s vision of becoming a ‘global value-creative leading university’ and its progress toward this vision over the last 50 years. The issue explained how KAIST has served as the main hub for advanced scientific research and technological innovation in South Korea since its establishment in 1971, and how its faculty and over 69,000 graduates played a key role in propelling the nation’s rapid industrialization and economic development. The issue also emphasized the need for KAIST to enhance global cooperation and the exchange of ideas in the years to come, especially during the post-COVID era intertwined with the Fourth Industrial Revolution (4IR). In this regard, the issue cited the first ‘KAIST Emerging Materials e-Symposium (EMS)’, which was held online for five days in September of last year with a global audience of over 10,000 participating live via Zoom and YouTube, as a successful example of what academic collaboration could look like in the post-COVID and 4IR eras. In addition, the “Science & Technology New Deal Project for COVID-19 Response,” a project conducted by KAIST with support from the Ministry of Science and ICT (MSIT) of South Korea, was also introduced as another excellent case of KAIST’s collective intelligence and technological innovation. The issue highlighted some key achievements from this project for overcoming the pandemic-driven crisis, such as: reusable anti-virus filters, negative-pressure ambulances for integrated patient transport and hospitalization, and movable and expandable negative-pressure ward modules. “We hold our expectations high for the outstanding achievements and progress KAIST will have made by its centennial,” said Professor Kim on the background of curating the 14 review articles contributed by KAIST faculty from the fields of Materials Science and Engineering (MSE), Chemical and Biomolecular Engineering (CBE), Nuclear and Quantum Engineering (NQE), Electrical Engineering (EE), and Chemistry (Chem). Review articles discussing emerging materials and their properties covered photonic carbon dots (Professor Chan Beum Park, MSE), single-atom and ensemble catalysts (Professor Hyunjoo Lee, CBE), and metal/metal oxide electrocatalysts (Professor Sung-Yoon Chung, MSE). Review articles discussing materials processing covered 2D layered materials synthesis based on interlayer engineering (Professor Kibum Kang, MSE), eco-friendly methods for solar cell production (Professor Bumjoon J. Kim, CBE), an ex-solution process for the synthesis of highly stable catalysts (Professor WooChul Jung, MSE), and 3D light-patterning synthesis of ordered nanostructures (Professor Seokwoo Jeon, MSE, and Professor Dongchan Jang, NQE). Review articles discussing advanced analysis techniques covered operando materials analyses (Professor Jeong Yeong Park, Chem), graphene liquid cell transmission electron microscopy (Professor Jong Min Yuk, MSE), and multiscale modeling and visualization of materials systems (Professor Seungbum Hong, MSE). Review articles discussing practical state-of-the-art devices covered chemiresistive hydrogen sensors (Professor Il-Doo Kim, MSE), patient-friendly diagnostics and implantable treatment devices (Professor Steve Park, MSE), triboelectric nanogenerators (Professor Yang-Kyu Choi, EE), and next-generation lithium-air batteries (Professor Hye Ryung Byon, Chem, and Professor Il-Doo Kim, MSE). In addition to Professor Il-Doo Kim, post-doctoral researcher Dr. Jaewan Ahn from the KAIST Applied Science Research Institute, Dean of the College of Engineering at KAIST Professor Choongsik Bae, and ACS Nano Editor-in-Chief Professor Paul S. Weiss from the University of California, Los Angeles also contributed to the publication of this ACS Nano special virtual issue. The issue can be viewed and downloaded from the ACS Nano website at https://doi.org/10.1021/acsnano.1c01101. Image credit: KAIST Image usage restrictions: News organizations may use or redistribute this image,with proper attribution, as part of news coverage of this paper only. Publication: Ahn, J., et al. (2021) Celebrating 50 Years of KAIST: Collective Intelligence and Innovation for Confronting Contemporary Issues. ACS Nano 15(3): 1895-1907. Available online at https://doi.org/10.1021/acsnano.1c01101 Profile: Il-Doo Kim, Ph.D Chair Professor idkim@kaist.ac.kr http://advnano.kaist.ac.kr Advanced Nanomaterials and Energy Lab. Department of Materials Science and Engineering Membrane Innovation Center for Anti-Virus and Air-Quality Control https://kaist.ac.kr/ Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea (END)
2021.03.05
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Highly Deformable Piezoelectric Nanotruss for Tactile Electronics
With the importance of non-contact environments growing due to COVID-19, tactile electronic devices using haptic technology are gaining traction as new mediums of communication. Haptic technology is being applied in a wide array of fields such as robotics or interactive displays. haptic gloves are being used for augmented information communication technology. Efficient piezoelectric materials that can convert various mechanical stimuli into electrical signals and vice versa are a prerequisite for advancing high-performing haptic technology. A research team led by Professor Seungbum Hong confirmed the potential of tactile devices by developing ceramic piezoelectric materials that are three times more deformable. For the fabrication of highly deformable nanomaterials, the research team built a zinc oxide hollow nanostructure using proximity field nanopatterning and atomic layered deposition. The piezoelectric coefficient was measured to be approximately 9.2 pm/V and the nanopillar compression test showed an elastic strain limit of approximately 10%, which is more than three times greater than that of the bulk zinc oxide one. Piezoelectric ceramics have a high piezoelectric coefficient with a low elastic strain limit, whereas the opposite is true for piezoelectric polymers. Therefore, it has been very challenging to obtain good performance in both high piezoelectric coefficients as well as high elastic strain limits. To break the elastic limit of piezoelectric ceramics, the research team introduced a 3D truss-like hollow nanostructure with nanometer-scale thin walls. According to the Griffith criterion, the fracture strength of a material is inversely proportional to the square root of the preexisting flaw size. However, a large flaw is less likely to occur in a small structure, which, in turn, enhances the strength of the material. Therefore, implementing the form of a 3D truss-like hollow nanostructure with nanometer-scale thin walls can extend the elastic limit of the material. Furthermore, a monolithic 3D structure can withstand large strains in all directions while simultaneously preventing the loss from the bottleneck. Previously, the fracture property of piezoelectric ceramic materials was difficult to control, owing to the large variance in crack sizes. However, the research team structurally limited the crack sizes to manage the fracture properties. Professor Hong’s results demonstrate the potential for the development of highly deformable ceramic piezoelectric materials by improving the elastic limit using a 3D hollow nanostructure. Since zinc oxide has a relatively low piezoelectric coefficient compared to other piezoelectric ceramic materials, applying the proposed structure to such components promised better results in terms of the piezoelectric activity. “With the advent of the non-contact era, the importance of emotional communication is increasing. Through the development of novel tactile interaction technologies, in addition to the current visual and auditory communication, mankind will enter a new era where they can communicate with anyone using all five senses regardless of location as if they are with them in person,” Professor Hong said. “While additional research must be conducted to realize the application of the proposed designs for haptic enhancement devices, this study holds high value in that it resolves one of the most challenging issues in the use of piezoelectric ceramics, specifically opening new possibilities for their application by overcoming their mechanical constraints. The research was reported in Nano Energy and supported by the Ministry of Science and ICT, the Korea Research Foundation, and the KAIST Global Singularity Research Project. -Profile: Professor Seungbum Hong seungbum@kaist.ac.kr http://mii.kaist.ac.kr/ Department of Materials Science and Engineering KAIST
2021.02.02
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Extremely Stable Perovskite Nanoparticles Films for Next-Generation Displays
Researchers have reported an extremely stable cross-linked perovskite nanoparticle that maintains a high photoluminescence quantum yield (PLQY) for 1.5 years in air and harsh liquid environments. This stable material’s design strategies, which addressed one of the most critical problems limiting their practical application, provide a breakthrough for the commercialization of perovskite nanoparticles in next-generation displays and bio-related applications. According to the research team led by Professor Byeong-Soo Bae, their development can survive in severe environments such as water, various polar solvents, and high temperature with high humidity without additional encapsulation. This development is expected to enable perovskite nanoparticles to be applied to high color purity display applications as a practical color converting material. This result was published as the inside front cover article in Advanced Materials. Perovskites, which consist of organics, metals, and halogen elements, have emerged as key elements in various optoelectronic applications. The power conversion efficiency of photovoltaic cells based on perovskites light absorbers has been rapidly increased. Perovskites are also great promise as a light emitter in display applications because of their low material cost, facile wavelength tunability, high (PLQY), very narrow emission band width, and wider color gamut than inorganic semiconducting nanocrystals and organic emitters. Thanks to these advantages, perovskites have been identified as a key color-converting material for next-generation high color-purity displays. In particular, perovskites are the only luminescence material that meets Rec. 2020 which is a new color standard in display industry. However, perovskites are very unstable against heat, moisture, and light, which makes them almost impossible to use in practical applications. To solve these problems, many researchers have attempted to physically prevent perovskites from coming into contact with water molecules by passivating the perovskite grain and nanoparticle surfaces with organic ligands or inorganic shell materials, or by fabricating perovskite-polymer nanocomposites. These methods require complex processes and have limited stability in ambient air and water. Furthermore, stable perovskite nanoparticles in the various chemical environments and high temperatures with high humidity have not been reported yet. The research team in collaboration with Seoul National University develops siloxane-encapsulated perovskite nanoparticle composite films. Here, perovskite nanoparticles are chemically crosslinked with thermally stable siloxane molecules, thereby significantly improving the stability of the perovskite nanoparticles without the need for any additional protecting layer. Siloxane-encapsulated perovskite nanoparticle composite films exhibited a high PLQY (> 70%) value, which can be maintained over 600 days in water, various chemicals (alcohol, strong acidic and basic solutions), and high temperatures with high humidity (85℃/85%). The research team investigated the mechanisms impacting the chemical crosslinking and water molecule-induced stabilization of perovskite nanoparticles through various photo-physical analysis and density-functional theory calculation. The research team confirmed that displays based on their siloxane-perovskite nanoparticle composite films exhibited higher PLQY and a wider color gamut than those of Cd-based quantum dots and demonstrated perfect color converting properties on commercial mobile phone screens. Unlike what was commonly believed in the halide perovskite field, the composite films showed excellent bio-compatibility because the siloxane matrix prevents the toxicity of Pb in perovskite nanoparticle. By using this technology, the instability of perovskite materials, which is the biggest challenge for practical applications, is greatly improved through simple encapsulation method. “Perovskite nanoparticle is the only photoluminescent material that can meet the next generation display color standard. Nevertheless, there has been reluctant to commercialize it due to its moisture vulnerability. The newly developed siloxane encapsulation technology will trigger more research on perovskite nanoparticles as color conversion materials and will accelerate early commercialization,” Professor Bae said. This work was supported by the Wearable Platform Materials Technology Center (WMC) of the Engineering Research Center (ERC) Project, and the Leadership Research Program funded by the National Research Foundation of Korea. -Publication: Junho Jang, Young-Hoon Kim, Sunjoon Park, Dongsuk Yoo, Hyunjin Cho, Jinhyeong Jang, Han Beom Jeong, Hyunhwan Lee, Jong Min Yuk, Chan Beum Park, Duk Young Jeon, Yong-Hyun Kim, Byeong-Soo Bae, and Tae-Woo Lee. “Extremely Stable Luminescent Crosslinked Perovskite Nanoparticles under Harsh Environments over 1.5 Years” Advanced Materials, 2020, 2005255. https://doi.org/10.1002/adma.202005255. Link to download the full-text paper: https://onlinelibrary.wiley.com/doi/10.1002/adma.202005255 -Profile: Prof. Byeong-Soo Bae (Corresponding author) bsbae@kaist.ac.kr Lab. of Optical Materials & Coating Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology (KAIST)
2020.12.29
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Chemical Scissors Snip 2D Transition Metal Dichalcogenides into Nanoribbon
New ‘nanoribbon’ catalyst should slash cost of hydrogen production for clean fuels Researchers have identified a potential catalyst alternative – and an innovative way to produce them using chemical ‘scissors’ – that could make hydrogen production more economical. The research team led by Professor Sang Ouk Kim at the Department of Materials Science and Engineering published their work in Nature Communications. Hydrogen is likely to play a key role in the clean transition away from fossil fuels and other processes that produce greenhouse gas emissions. There is a raft of transportation sectors such as long-haul shipping and aviation that are difficult to electrify and so will require cleanly produced hydrogen as a fuel or as a feedstock for other carbon-neutral synthetic fuels. Likewise, fertilizer production and the steel sector are unlikely to be “de-carbonized” without cheap and clean hydrogen. The problem is that the cheapest methods by far of producing hydrogen gas is currently from natural gas, a process that itself produces the greenhouse gas carbon dioxide–which defeats the purpose. Alternative techniques of hydrogen production, such as electrolysis using an electric current between two electrodes plunged into water to overcome the chemical bonds holding water together, thereby splitting it into its constituent elements, oxygen and hydrogen are very well established. But one of the factors contributing to the high cost, beyond being extremely energy-intensive, is the need for the very expensive precious and relatively rare metal platinum. The platinum is used as a catalyst–a substance that kicks off or speeds up a chemical reaction–in the hydrogen production process. As a result, researchers have long been on the hunt for a substitution for platinum -- another catalyst that is abundant in the earth and thus much cheaper. Transition metal dichalcogenides, or TMDs, in a nanomaterial form, have for some time been considered a good candidate as a catalyst replacement for platinum. These are substances composed of one atom of a transition metal (the elements in the middle part of the periodic table) and two atoms of a chalcogen element (the elements in the third-to-last column in the periodic table, specifically sulfur, selenium and tellurium). What makes TMDs a good bet as a platinum replacement is not just that they are much more abundant, but also their electrons are structured in a way that gives the electrodes a boost. In addition, a TMD that is a nanomaterial is essentially a two-dimensional super-thin sheet only a few atoms thick, just like graphene. The ultrathin nature of a 2-D TMD nanosheet allows for a great many more TMD molecules to be exposed during the catalysis process than would be the case in a block of the stuff, thus kicking off and speeding up the hydrogen-making chemical reaction that much more. However, even here the TMD molecules are only reactive at the four edges of a nanosheet. In the flat interior, not much is going on. In order to increase the chemical reaction rate in the production of hydrogen, the nanosheet would need to be cut into very thin – almost one-dimensional strips, thereby creating many edges. In response, the research team developed what are in essence a pair of chemical scissors that can snip TMD into tiny strips. “Up to now, the only substances that anyone has been able to turn into these ‘nano-ribbons’ are graphene and phosphorene,” said Sang Professor Kim, one of the researchers involved in devising the process. “But they’re both made up of just one element, so it’s pretty straightforward. Figuring out how to do it for TMD, which is made of two elements was going to be much harder.” The ‘scissors’ involve a two-step process involving first inserting lithium ions into the layered structure of the TMD sheets, and then using ultrasound to cause a spontaneous ‘unzipping’ in straight lines. “It works sort of like how when you split a plank of plywood: it breaks easily in one direction along the grain,” Professor Kim continued. “It’s actually really simple.” The researchers then tried it with various types of TMDs, including those made of molybdenum, selenium, sulfur, tellurium and tungsten. All worked just as well, with a catalytic efficiency as effective as platinum’s. Because of the simplicity of the procedure, this method should be able to be used not just in the large-scale production of TMD nanoribbons, but also to make similar nanoribbons from other multi-elemental 2D materials for purposes beyond just hydrogen production. -ProfileProfessor Sang Ouk KimSoft Nanomaterials Laboratory (http://snml.kaist.ac.kr)Department of Materials Science and EngineeringKAIST
2020.10.29
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