Department+of+Chemical
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KAIST Presents a Breakthrough in Overcoming Drug Resistance in Cancer – Hope for Treating Intractable Diseases like Diabetes
<(From the left) Prof. Hyun Uk Kim, Ph.D candiate Hae Deok Jung, Ph.D candidate Jina Lim, Prof.Yoosik Kim from the Department of Chemical and Biomolecular Engineering>
One of the biggest obstacles in cancer treatment is drug resistance in cancer cells. Conventional efforts have focused on identifying new drug targets to eliminate these resistant cells, but such approaches can often lead to even stronger resistance. Now, researchers at KAIST have developed a computational framework to predict key metabolic genes that can re-sensitize resistant cancer cells to treatment. This technique holds promise not only for a variety of cancer therapies but also for treating metabolic diseases such as diabetes.
On the 7th of July, KAIST (President Kwang Hyung Lee) announced that a research team led by Professors Hyun Uk Kim and Yoosik Kim from the Department of Chemical and Biomolecular Engineering had developed a computational framework that predicts metabolic gene targets to re-sensitize drug-resistant breast cancer cells. This was achieved using a metabolic network model capable of simulating human metabolism.
Focusing on metabolic alterations—key characteristics in the formation of drug resistance—the researchers developed a metabolism-based approach to identify gene targets that could enhance drug responsiveness by regulating the metabolism of drug-resistant breast cancer cells.
< Computational framework that can identify metabolic gene targets to revert the metabolic state of the drug-resistant cells to that of the drug-sensitive parental cells>
The team first constructed cell-specific metabolic network models by integrating proteomic data obtained from two different types of drug-resistant MCF7 breast cancer cell lines: one resistant to doxorubicin and the other to paclitaxel. They then performed gene knockout simulations* on all of the metabolic genes and analyzed the results.
*Gene knockout simulation: A computational method to predict changes in a biological network by virtually removing specific genes.
As a result, they discovered that suppressing certain genes could make previously resistant cancer cells responsive to anticancer drugs again. Specifically, they identified GOT1 as a target in doxorubicin-resistant cells, GPI in paclitaxel-resistant cells, and SLC1A5 as a common target for both drugs.
The predictions were experimentally validated by suppressing proteins encoded by these genes, which led to the re-sensitization of the drug-resistant cancer cells.
Furthermore, consistent re-sensitization effects were also observed when the same proteins were inhibited in other types of breast cancer cells that had developed resistance to the same drugs.
Professor Yoosik Kim remarked, “Cellular metabolism plays a crucial role in various intractable diseases including infectious and degenerative conditions. This new technology, which predicts metabolic regulation switches, can serve as a foundational tool not only for treating drug-resistant breast cancer but also for a wide range of diseases that currently lack effective therapies.”
Professor Hyun Uk Kim, who led the study, emphasized, “The significance of this research lies in our ability to accurately predict key metabolic genes that can make resistant cancer cells responsive to treatment again—using only computer simulations and minimal experimental data. This framework can be widely applied to discover new therapeutic targets in various cancers and metabolic diseases.”
The study, in which Ph.D. candidates JinA Lim and Hae Deok Jung from KAIST participated as co-first authors, was published online on June 25 in Proceedings of the National Academy of Sciences (PNAS), a leading multidisciplinary journal that covers top-tier research in life sciences, physics, engineering, and social sciences.
※ Title: Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets ※ DOI: https://doi.org/10.1073/pnas.2425384122 ※ Authors: JinA Lim (KAIST, co-first author), Hae Deok Jung (KAIST, co-first author), Han Suk Ryu (Seoul National University Hospital, corresponding author), Yoosik Kim (KAIST, corresponding author), Hyun Uk Kim (KAIST, corresponding author), and five others.
This research was supported by the Ministry of Science and ICT through the National Research Foundation of Korea, and the Electronics and Telecommunications Research Institute (ETRI).
2025.07.08 View 184 -
Algorithm Identifies Optimal Pairs for Composing Metal-Organic Frameworks
The integration of metal-organic frameworks (MOFs) and other metal nanoparticles has increasingly led to the creation of new multifunctional materials. Many researchers have integrated MOFs with other classes of materials to produce new structures with synergetic properties.
Despite there being over 70,000 collections of synthesized MOFs that can be used as building blocks, the precise nature of the interaction and the bonding at the interface between the two materials still remains unknown. The question is how to sort out the right matching pairs out of 70,000 MOFs.
An algorithmic study published in Nature Communications by a KAIST research team presents a clue for finding the perfect pairs. The team, led by Professor Ji-Han Kim from the Department of Chemical and Biomolecular Engineering, developed a joint computational and experimental approach to rationally design MOF@MOFs, a composite of MOFs where an MOF is grown on a different MOF.
Professor Kim’s team, in collaboration with UNIST, noted that the metal node of one MOF can coordinately bond with the linker of a different MOF and the precisely matched interface configurations at atomic and molecular levels can enhance the likelihood of synthesizing MOF@MOFs.
They screened thousands of MOFs and identified optimal MOF pairs that can seamlessly connect to one another by taking advantage of the fact that the metal node of one MOF can form coordination bonds with the linkers of the second MOF. Six pairs predicted from the computational algorithm successfully grew into single crystals.
This computational workflow can readily extend into other classes of materials and can lead to the rapid exploration of the composite MOFs arena for accelerated materials development. Even more, the workflow can enhance the likelihood of synthesizing MOF@MOFs in the form of large single crystals, and thereby demonstrated the utility of rationally designing the MOF@MOFs.
This study is the first algorithm for predicting the synthesis of composite MOFs, to the best of their knowledge. Professor Kim said, “The number of predicted pairs can increase even more with the more general 2D lattice matching, and it is worth investigating in the future.”
This study was supported by Samsung Research Funding & Incubation Center of Samsung Electronics.
(Figure: An example of a rationally synthesized MOF@MOFs (cubic HKUST-1@MOF-5 ))
2019.08.30 View 18473 -
Researchers Describe a Mechanism Inducing Self-Killing of Cancer Cells
(Professor Kim (left) and lead author Lee)
Researchers have described a new mechanism which induces the self-killing of cancer cells by perturbing ion homeostasis. A research team from the Department of Biochemical Engineering has developed helical polypeptide potassium ionophores that lead to the onset of programmed cell death. The ionophores increase the active oxygen concentration to stress endoplasmic reticulum to the point of cellular death.
The electrochemical gradient between extracellular and intracellular conditions plays an important role in cell growth and metabolism. When a cell’s ion homeostasis is disturbed, critical functions accelerating the activation of apoptosis are inhibited in the cell.
Although ionophores have been intensively used as an ion homeostasis disturber, the mechanisms of cell death have been unclear and the bio-applicability has been limited. In the study featured at Advanced Science, the team presented an alpha helical peptide-based anticancer agent that is capable of transporting potassium ions with water solubility. The cationic, hydrophilic, and potassium ionic groups were combined at the end of the peptide side chain to provide both ion transport and hydrophilic properties.
These peptide-based ionophores reduce the intracellular potassium concentration and at the same time increase the intracellular calcium concentration. Increased intracellular calcium concentrations produce intracellular reactive oxygen species, causing endoplasmic reticulum stress, and ultimately leading to apoptosis.
Anticancer effects were evaluated using tumor-bearing mice to confirm the therapeutic effect, even in animal models. It was found that tumor growth was strongly inhibited by endoplasmic stress-mediated apoptosis.
Lead author Dr. Dae-Yong Lee said, “A peptide-based ionophore is more effective than conventional chemotherapeutic agents because it induces apoptosis via elevated reactive oxygen species levels. Professor Yeu-Chun Kim said he expects this new mechanism to be widely used as a new chemotherapeutic strategy. This research was funded by the National Research Foundation.
2019.08.28 View 22594 -
Synthesizing Single-Crystalline Hexagonal Graphene Quantum Dots
(Figure: Uniformly ordered single-crystalline graphene quantum dots of various sizes synthesized through solution chemistry.)
A KAIST team has designed a novel strategy for synthesizing single-crystalline graphene quantum dots, which emit stable blue light. The research team confirmed that a display made of their synthesized graphene quantum dots successfully emitted blue light with stable electric pressure, reportedly resolving the long-standing challenges of blue light emission in manufactured displays. The study, led by Professor O Ok Park in the Department of Chemical and Biological Engineering, was featured online in Nano Letters on July 5.
Graphene has gained increased attention as a next-generation material for its heat and electrical conductivity as well as its transparency. However, single and multi-layered graphene have characteristics of a conductor so that it is difficult to apply into semiconductor. Only when downsized to the nanoscale, semiconductor’s distinct feature of bandgap will be exhibited to emit the light in the graphene. This illuminating featuring of dot is referred to as a graphene quantum dot.
Conventionally, single-crystalline graphene has been fabricated by chemical vapor deposition (CVD) on copper or nickel thin films, or by peeling graphite physically and chemically. However, graphene made via chemical vapor deposition is mainly used for large-surface transparent electrodes. Meanwhile, graphene made by chemical and physical peeling carries uneven size defects.
The research team explained that their graphene quantum dots exhibited a very stable single-phase reaction when they mixed amine and acetic acid with an aqueous solution of glucose. Then, they synthesized single-crystalline graphene quantum dots from the self-assembly of the reaction intermediate. In the course of fabrication, the team developed a new separation method at a low-temperature precipitation, which led to successfully creating a homogeneous nucleation of graphene quantum dots via a single-phase reaction.
Professor Park and his colleagues have developed solution phase synthesis technology that allows for the creation of the desired crystal size for single nanocrystals down to 100 nano meters. It is reportedly the first synthesis of the homogeneous nucleation of graphene through a single-phase reaction.
Professor Park said, "This solution method will significantly contribute to the grafting of graphene in various fields. The application of this new graphene will expand the scope of its applications such as for flexible displays and varistors.”
This research was a joint project with a team from Korea University under Professor Sang Hyuk Im from the Department of Chemical and Biological Engineering, and was supported by the National Research Foundation of Korea, the Nano-Material Technology Development Program from the Electronics and Telecommunications Research Institute (ETRI), KAIST EEWS, and the BK21+ project from the Korean government.
2019.08.02 View 36258 -
Deep Learning-Powered 'DeepEC' Helps Accurately Understand Enzyme Functions
(Figure: Overall scheme of DeepEC)
A deep learning-powered computational framework, ‘DeepEC,’ will allow the high-quality and high-throughput prediction of enzyme commission numbers, which is essential for the accurate understanding of enzyme functions.
A team of Dr. Jae Yong Ryu, Professor Hyun Uk Kim, and Distinguished Professor Sang Yup Lee at KAIST reported the computational framework powered by deep learning that predicts enzyme commission (EC) numbers with high precision in a high-throughput manner.
DeepEC takes a protein sequence as an input and accurately predicts EC numbers as an output. Enzymes are proteins that catalyze biochemical reactions and EC numbers consisting of four level numbers (i.e., a.b.c.d) indicate biochemical reactions. Thus, the identification of EC numbers is critical for accurately understanding enzyme functions and metabolism.
EC numbers are usually given to a protein sequence encoding an enzyme during a genome annotation procedure. Because of the importance of EC numbers, several EC number prediction tools have been developed, but they have room for further improvement with respect to computation time, precision, coverage, and the total size of the files needed for the EC number prediction.
DeepEC uses three convolutional neural networks (CNNs) as a major engine for the prediction of EC numbers, and also implements homology analysis for EC numbers if the three CNNs do not produce reliable EC numbers for a given protein sequence. DeepEC was developed by using a gold standard dataset covering 1,388,606 protein sequences and 4,669 EC numbers.
In particular, benchmarking studies of DeepEC and five other representative EC number prediction tools showed that DeepEC made the most precise and fastest predictions for EC numbers. DeepEC also required the smallest disk space for implementation, which makes it an ideal third-party software component.
Furthermore, DeepEC was the most sensitive in detecting enzymatic function loss as a result of mutations in domains/binding site residue of protein sequences; in this comparative analysis, all the domains or binding site residue were substituted with L-alanine residue in order to remove the protein function, which is known as the L-alanine scanning method.
This study was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 20, 2019, entitled “Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers.”
“DeepEC can be used as an independent tool and also as a third-party software component in combination with other computational platforms that examine metabolic reactions. DeepEC is freely available online,” said Professor Kim.
Distinguished Professor Lee said, “With DeepEC, it has become possible to process ever-increasing volumes of protein sequence data more efficiently and more accurately.”
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation of Korea. This work was also funded by the Bio & Medical Technology Development Program of the National Research Foundation of Korea funded by the Korean government, the Ministry of Science and ICT.
Profile:
-Professor Hyun Uk Kim (ehukim@kaist.ac.kr)
https://sites.google.com/view/ehukim
Department of Chemical and Biomolecular Engineering
-Distinguished Professor Sang Yup Lee (leesy@kaist.ac.kr)
Department of Chemical and Biomolecular Engineering
http://mbel.kaist.ac.kr
2019.07.09 View 40494 -
Hydrogen-Natural Gas Hydrates Harvested by Natural Gas
A hydrogen-natural gas blend (HNGB) can be a game changer only if it can be stored safely and used as a sustainable clean energy resource. A recent study has suggested a new strategy for stably storing hydrogen, using natural gas as a stabilizer. The research proposed a practical gas phase modulator based synthesis of HNGB without generating chemical waste after dissociation for the immediate service.
The research team of Professor Jae Woo Lee from the Department of Chemical and Biomolecular Engineering in collaboration with the Gwangju Institute of Science and Technology (GIST) demonstrated that the natural gas modulator based synthesis leads to significantly reduced synthesis pressure simultaneously with the formation of hydrogen clusters in the confined nanoporous cages of clathrate hydrates. This approach minimizes the environmental impact and reduces operation costs since clathrate hydrates do not generate any chemical waste in both the synthesis and decomposition processes.
For the efficient storage and transportation of hydrogen, numerous materials have been investigated. Among others, clathrate hydrates offer distinct benefits. Clathrate hydrates are nanoporous inclusion compounds composed of a 3D network of polyhedral cages made of hydrogen-bonded ‘host’ water molecules and captured ‘guest’ gas or liquid molecules.
In this study, the research team used two gases, methane and ethane, which have lower equilibrium conditions compared to hydrogen as thermodynamic stabilizers. As a result, they succeeded in stably storing the hydrogen-natural gas compound in hydrates. According to the composition ratio of methane and ethane, structure I or II hydrates can be formed, both of which can stably store hydrogen-natural gas in low-pressure conditions.
The research team found that two hydrogen molecules are stored in small cages in tuned structure I hydrates, while up to three hydrogen molecules can be stored in both small and large cages in tuned structure II hydrates. Hydrates can store gas up to about 170-times its volume and the natural gas used as thermodynamic stabilizers in this study can also be used as an energy source.
The research team developed technology to produce hydrates from ice, produced hydrogen-natural gas hydrates by substitution, and successfully observed that the tuning phenomenon only occurs when hydrogen is involved in hydrate formation from the start for both structures of hydrates.
They expect that the findings can be applied to not only an energy-efficient gas storage material, but also a smart platform to utilize hydrogen natural gas blends, which can serve as a new alternative energy source with targeted hydrogen contents by designing synthetic pathways of mixed gas hydrates.
The research was published online in Energy Storage Materials on June 6, with the title ‘One-step formation of hydrogen clusters in clathrate hydrates stabilized via natural gas blending’.
Professor Lee said, “HNGB will utilize the existing natural gas infrastructure for transportation, so it is very likely that we can commercialize this hydrate system. We are investigating the kinetic performance through a follow-up strategy to increase the volume of gas storage.
This study was funded by the National Research Foundation of Korea and BK21 plus program.
(Figure1. Schematics showing the storage method for hydrogen in a natural gas hydrate using a substitution method and storage method directly from ice to a hydrogen-natural gas hydrate.)
(Figure 2. Artificially synthesized and dissociated hydrogen-natural gas hydrates. The Raman spectra of tuned sI and sII hydrate showing the hydrogen clusters in each cage.)
2019.06.21 View 43327 -
Efficiently Producing Fatty Acids and Biofuels from Glucose
Researchers have presented a new strategy for efficiently producing fatty acids and biofuels that can transform glucose and oleaginous microorganisms into microbial diesel fuel, with one-step direct fermentative production.
The newly developed strain, created by Distinguished Professor Sang Yup Lee and his team, showed the highest efficiency in producing fatty acids and biodiesels ever reported. It will be expected to serve as a new platform to sustainably produce a wide array of fatty acid-based products from glucose and other carbon substrates.
Fossil fuels, which have long been energy resources for our daily lives, are now facing serious challenges: depletion of their reserves and their role in global warming. The production of sustainable bio-based renewable energy has emerged as an essential alternative and many studies to replace fossil fuels are underway. One of the representative examples is biodiesel. Currently, it is mainly being produced through the transesterification of vegetable oils or animal fats.
The research team engineered oleaginous microorganisms, Rhodococcus opacus, to produce fatty acids and their derivatives that can be used as biodiesel from glucose, one of the most abundant and cheap sugars derived from non-edible biomass.
Professor Lee’s team has already engineered Escherichia coli to produce short-chain hydrocarbons, which can be used as gasoline (published in Nature as the cover paper in 2013). However, the production efficiency of the short-chain hydrocarbons using E. coli (0.58 g/L) fell short of the levels required for commercialization.
To overcome these issues, the team employed oil-accumulating Rhodococcus opacus as a host strain in this study. First, the team optimized the cultivation conditions of Rhodococcus opacus to maximize the accumulation of oil (triacylglycerol), which serves as a precursor for the biosynthesis of fatty acids and their derivatives. Then, they systematically analyzed the metabolism of the strain and redesigned it to enable higher levels of fatty acids and two kinds of fatty acid-derived biodiesels (fatty acid ethyl esters and long-chain hydrocarbons) to be produced.
They found that the resulting strains produced 50.2, 21.3, and 5.2 g/L of fatty acids, fatty acid ethyl esters, and long-chain hydrocarbons, respectively. These are all the highest concentrations ever reported by microbial fermentations. It is expected that these strains can contribute to the future industrialization of microbial-based biodiesel production.
“This technology creates fatty acids and biodiesel with high efficiency by utilizing lignocellulose, one of the most abundant resources on the Earth, without depending on fossil fuels and vegetable or animal oils. This will provide new opportunities for oil and petroleum industries, which have long relied on fossil fuels, to turn to sustainable and eco-friendly biotechnologies,” said Professor Lee.
This paper titled “Engineering of an oleaginous bacterium for the production of fatty acids and fuels” was published in Nature Chemical Biology on June 17.
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea (NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557).
(Figure: Metabolic engineering for the production of free fatty acids (FFAs), fatty acid ethyl esters (FAEEs), and long-chain hydrocarbons (LCHCs) in Rhodococcus opacus PD630. Researchers have presented a new strategy for efficiently producing fatty acids and biofuels that can transform glucose and oleaginous microorganisms into microbial diesel fuel, with one-step direct fermentative production.)
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Source:
Hye Mi Kim, Tong Un Chae, So Young Choi, Won Jun Kim and Sang Yup Lee. Engineering of an oleaginous bacterium for the production of fatty acids and fuels. Nature Chemical Biology ( https://www.nature.com/nchembio/ ) DOI: 10.1038/s41589-019-0295-5
Profile
Dr. Sang Yup Lee
leesy@kaist.ac.kr
Distinguished Professor at the Department of Chemical and Biomolecular Engineering
KAIST
2019.06.19 View 52219 -
Novel Via-Hole-Less Multilevel Metal Interconnection Methods
Forming reliable multi-level metal interconnections is a key technology for integrating devices into organic integrated circuits (ICs). The conventional approach, called “via-hole,” locally removes the insulator and utilizes metal interconnects through the holes. Due to the high sensitivity of organic materials to chemical solvents, heat, and photo-radiation used in conventional “via-hole” methods, alternative printing methods or laser drilling methods have been developed. However, finding a reliable and practical metal interconnection for organic ICs is still challenging.
The research team of KAIST Professor Sung Gap Im and Postech Professor Kim Jae-Joon reported a new interconnection method that does not require via-hole formation, “via-hole-less metal interconnection,” in Nature Communications on June 3.
Metal electrodes in different layers can be isolated from each other by patterned dielectric layers, where they then can be interconnected to others in the open area where the dielectric layer is not present. See the images below. Vapor phase deposition and in-situ patterning of dielectric layer using iCVD (initiated chemical vapor deposition), used in the “via-hole-less” method, ensure a damage-free process for organic semiconductor materials and result in outstanding performance of the organic devices as multilevel metal interconnects are reliably formed. The team successfully demonstrated three-dimensional (3D) stacking of five organic transistors and integrated circuits using the proposed via-hole-less interconnect method. See the image below.
Vapor phase deposition and in-situ patterning of dielectric layer using iCVD (initiated chemical vapor deposition), used in the “via-hole-less” method, ensure a damage-free process for organic semiconductor materials and result in outstanding performance of the organic devices as multilevel metal interconnects are reliably formed. The team successfully demonstrated three-dimensional (3D) stacking of five organic transistors and integrated circuits using the proposed via-hole-less interconnect method. See the image below.
Professor Kim explained, “Our proposed via-hole-less interconnect method using a selectively patterned dielectric overcomes the limitations of the previous time-consuming, one-by-one via-hole formation process and provides reliable methods for creating metal interconnects in organic ICs. We expect the via-hole-less scheme to bring advances to organic IC technology.”
2019.06.18 View 45798 -
Engineered Microbial Production of Grape Flavoring
(Image 1: Engineered bacteria that produce grape flavoring.)
Researchers report a microbial method for producing an artificial grape flavor. Methyl anthranilate (MANT) is a common grape flavoring and odorant compound currently produced through a petroleum-based process that uses large volumes of toxic acid catalysts.
Professor Sang-Yup Lee’s team at the Department of Chemical and Biomolecular Engineering demonstrated production of MANT, a naturally occurring compound, via engineered bacteria. The authors engineered strains of Escherichia coli and Corynebacetrium glutamicum to produce MANT through a plant-based engineered metabolic pathway.
The authors tuned the bacterial metabolic pathway by optimizing the levels of AAMT1, the key enzyme in the process. To maximize production of MANT, the authors tested six strategies, including increasing the supply of a precursor compound and enhancing the availability of a co-substrate. The most productive strategy proved to be a two-phase extractive culture, in which MANT was extracted into a solvent. This strategy produced MANT on the scale of 4.47 to 5.74 grams per liter, a significant amount, considering that engineered microbes produce most natural products at a scale of milligrams or micrograms per liter.
According to the authors, the results suggest that MANT and other related molecules produced through industrial processes can be produced at scale by engineered microbes in a manner that would allow them to be marketed as natural one, instead of artificial one.
This study, featured at the Proceeding of the National Academy of Sciences of the USA on May 13, was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT.
(Image 2. Overview of the strategies applied for the microbial production of grape flavoring.)
2019.05.15 View 58078 -
Nanomaterials Mimicking Natural Enzymes with Superior Catalytic Activity and Selectivity for Detecting Acetylcholine
(Professor Jinwoo Lee from the Department of Chemical and Biomolecular Engineering)
A KAIST research team doped nitrogen and boron into graphene to selectively increase peroxidase-like activity and succeeded in synthesizing a peroxidase-mimicking nanozyme with a low cost and superior catalytic activity. These nanomaterials can be applied for early diagnosis of Alzheimer’s disease.
Enzymes are the main catalysts in our body and are widely used in bioassays. In particular, peroxidase, which oxidizes transparent colorimetric substrates to become a colored product in the presence of hydrogen peroxide, is the most common enzyme that is used in colorimetric bioassays.
However, natural enzymes consisting of proteins are unstable against temperature and pH, hard to synthesize, and costly. Nanozymes, on the other hand, do not consist of proteins, meaning the disadvantages of enzymes can be overcome with their robustness and high productivity. In contrast, most nanonzymes do not have selectivity; for example, peroxidase-mimicking nanozymes demonstrate oxidase-like activity that oxidizes colorimetric substrates in the absence of hydrogen peroxide, which keeps them away from precisely detecting the target materials, such as hydrogen peroxide.
Professor Jinwoo Lee from the Department of Chemical and Biomolecular Engineering and his team were able to synthesize a peroxidase-mimicking nanozyme with superior catalytic activity and selectivity toward hydrogen peroxide. Co-doping of nitrogen and boron into graphene, which has negligible peroxidase-like activity, selectively increased the peroxidase-like activity without oxidase-like activity to accurately mimic the nature peroxidase and has become a powerful candidate to replace the peroxidase.
The experimental results were also verified with computational chemistry. The nitrogen and boron co-doped graphene was also applied to the colorimetric detection of acetylcholine, which is an important neurotransmitter and successfully detected the acetylcholine even better than the nature peroxidase.
Professor Lee said, “We began to study nanozymes due to their potential for replacing existing enzymes. Through this study, we have secured core technologies to synthesize nanozymes that have high enzyme activity along with selectivity. We believe that they can be applied to effectively detect acetylcholine for quickly diagnosing Alzheimer’s disease.
This research, led by PhD Min Su Kim, was published in ACS Nano (10.1021/acsnano.8b09519) on March 25, 2019.
Figure 1. Comparison of the catalytic activities of various nanozymes and horseradish peroxidase (HRP) toward TMB and H₂O₂
Figure 2. Schematic illustration of NB-rGO Reactions in Bioassays
2019.04.30 View 38577 -
New LSB with Theoretical Capacity over 90%
(Professor Hee-Tak Kim and Hyunwon Chu)
A KAIST research team has developed a lithium sulfur battery (LSB) that realizes 92% of the theoretical capacity and an areal capacity of 4mAh/cm2.
LSBs are gaining a great deal of attention as an alternative for lithium ion batteries (LIBs) because they have a theoretical energy density up to six to seven times higher than that of LIBs, and can be manufactured in a more cost-effective way.
However, LSBs face the obstacle of having a capacity reaching its theoretical maximum because they are prone to uncontrolled growth of lithium sulfide on the electrodes, which leads to blocking electron transfer.
To address the problem of electrode passivation, researchers introduced additional conductive agent into the electrode; however, it drastically lowered the energy density of LSBs, making it difficult to exceed 70% of the theoretical capacity.
Professor Hee-Tak Kim from the Department of Chemical and Biomolecular Engineering and his team replaced the lithium salt anions used in conventional LSB electrolytes with anions with a high donor number. The team successfully induced the three-dimensional growth of lithium sulfide on electrode surfaces and efficiently delayed the electrode passivation.
Based on this electrolyte design, the research team achieved 92% of the theoretical capacity with their high-capacity sulfur electrode (4mAh/cm2), which is equivalent to that of conventional LIB cathode. Furthermore, they were able to form a stable passivation film on the surface of the lithium anode and exhibited stable operation over 100 cycles.
This technology, which can be flexibly used with various types of sulfur electrodes, can mark a new milestone in the battery industry.
Professor Kim said, “We proposed a new physiochemical principle to overcome the limitations of conventional LSBs. I believe our achievement of obtaining 90% of the LBSs’ theoretical capacity without any capacity loss after 100 cycles will become a new milestone.”
This research, first-authored by Hyunwon Chu and Hyungjun Noh, was published in Nature Communications on January 14, 2019. It was also selected in the editor’s highlight for its outstanding achievements.
Figure 1. Lithium sulfur growth and its deposition mechanism for different sulfide growth behaviors
Figure 2. Capacity and cycle life characteristics of the LSBs
2019.02.11 View 8871 -
Hierarchical Porous Titanium Nitride Synthesized by Multiscale Phase Separation for LSBs
(from left: Professor Jinwoo Lee and PhD candidate Won-Gwang Lim)
A KAIST research team developed ultra-stable, high-rate lithium-sulfur batteries (LSBs) by using hierarchical porous titanium nitride as a sulfur host, and achieved superior cycle stability and high rate performance for LSBs.
The control of large amounts of energy is required for use in an electric vehicle or smart grid system. In this sense, the development of next-generation secondary batteries is in high demand. Theoretically, LSBs have an energy density seven times higher than commercial lithium ion batteries (LIBs). Also, their production cost can be reduced dramatically since sulfur can be obtained at a low price.
Despite these positive aspects, there have been several issues impeding the commercialization of LSBs, such as the low electric conductivity of sulfur, the dissolution of active materials during operation, and sluggish conversion reactions. These issues decrease the cycle stability and rate capability of batteries.
To tackle those issues, Professor Jinwoo Lee from the Department of Chemical and Biomolecular Engineering and his team synthesized a well-developed hierarchical macro/mesoporous titanium nitride as a host material for sulfur. The titanium nitride has a high chemical affinity for sulfur and high electrical conductivity. As a result, it prevents the dissolution of active materials and facilitates the charge transfer. Moreover, the synergistic effect of macropore and mesopore structures allows the stable accommodation of large amounts of sulfur and facilitates the electrolyte penetration.
Previously reported polar inorganic materials have a high affinity for sulfur, but it was challenging to control the porous architecture suitable to the sulfur host. This work breaks such limitations by developing a synthetic route to easily control the porous architecture of inorganic materials, which led to obtaining superior cycle stability and high rate capabilities.
Professor Lee said, “Some problems still remain in commercializing LSBs as next-generation batteries. Hence, there should be a continued research on this matter to solve the issues. Through this research, we secured a key technology for ultrastable, high-rate LSBs.”
This research was led by PhD candidate Won-Gwang Lim and collaborated on by Jeong Woo Han from POSTECH. It was chosen as the cover article of Advanced Materials on January 15, 2019.
Figure 1. Schematic illustration for the synthetic route of co-continuous h-TiN
Figure 2. The hierarchical multiscale porous structure is still retained without any collapse after the conversion to h-TiN. The good retention of the porous structure is attributed to the thick pore wall of the h-TiO₂derived from the block copolymer self-assembly
Figure 3. The cover page of Advanced Materials
2019.01.28 View 8222