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Now showing items 1 - 16 of 32

  • Antibody Subclass Detection Using Graphene Nanopores

    Farimani, Amir Barati   Heiranian, Mohammad   Min, Kyoungmin   Aluru, Narayana R.  

    Solid-state nanopores are promising for label-free protein detection. The large thickness, ranging from several tens of nanometers to micrometers and larger, of solid-state nanopores prohibits atomic-scale scanning or interrogation of proteins. Here, a single-atom thick graphene nanopore is shown to be highly capable of sensing and discriminating between different subclasses of IgG antibodies despite their minor and subtle variation in atomic structure. Extensive molecular dynamics (MD) simulations, rigorous statistical analysis with a total aggregate simulation time of 2.7 mu s, supervised machine learning (ML), and classification techniques are employed to distinguish IgG2 from IgG3. The water flux and ionic current during IgG translocation reveal distinct clusters for IgG subclasses facilitating an additional recognition mechanism. In addition, the histogram of ionic current for each segment of lgG can provide high-resolution spatial detection. Our results show that nanoporous graphene can be used to detect and distinguish antibody subclasses with good accuracy.
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  • Accelerated discovery of potential ferroelectric perovskiteviaactive learning

    Min, Kyoungmin   Cho, Eunseog  

    Ferroelectric materials inherently exhibit great memory effect through piezo- and pyroelectricity, which enables their utilization in many state-of-the-art applications. Here, we demonstrate a novel material screening platform for identifying,viamachine learning and active learning, new inorganic ABO(3)-type perovskite materials that potentially possess ferroelectric properties. First, the machine learning model for predicting the band gap and formation energy is constructed based on the initial database. Then, an active learning process is implemented to demonstrate its practical applicability to an initial database of less than 10% of the entire chemical space of materials. The proposed platform demonstrates its reliability by identifying already known ferroelectric materials that satisfy the band gap and formation energy criteria. Furthermore, with an exploration of only approximately 30% of the total database, more than 90% of the materials found after the active learning process are satisfactory. This study validates that utilization of machine learning, with optimization, can greatly accelerate the discovery of novel materials.
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  • Capacitive Sensing of Intercalated H2O Molecules Using Graphene

    Olson, Eric J.   Ma, Rui   Sun, Tao   Ebrish, Mona A.   Haratipour, Nazila   Min, Kyoungmin   Aluru, Narayana R.   Koester, Steven J.  

    Understanding the interactions of ambient molecules with graphene and adjacent dielectrics is of fundamental importance for a range of graphene-based devices, particularly sensors, where such interactions could influence the operation of the device. It is well-known that water can be trapped underneath graphene and its host substrate; however, the electrical effect of water beneath graphene and the dynamics of how the interfacial water changes with different ambient conditions has not been quantified. Here, using a metal-oxide-graphene variable-capacitor (varactor) structure, we show that graphene can be used to capacitively sense the intercalation of water between graphene and HfO2 and that this process is reversible on a fast time scale. Atomic force microscopy is used to confirm the intercalation and quantify the displacement of graphene as a function of humidity. Density functional theory simulations are used to quantify the displacement of graphene induced by intercalated water and also explain the observed Dirac point shifts as being due to the combined effect of water and oxygen on the carrier concentration in the graphene. Finally, molecular dynamics simulations indicate that a likely mechanism for the intercalation involves adsorption and lateral diffusion of water molecules beneath the graphene.
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  • Crosslinking PMMA: Molecular dynamics investigation of the shear response

    Min, Kyoungmin   Silberstein, Meredith   Aluru, N. R.  

    Crosslinking can fundamentally change the mechanical properties of a linear glassy polymer. It has been experimentally observed that when lightly crosslinked, poly(methyl-methacrylate) (PMMA) has a characteristically more ductile response to mechanical loading than does linear PMMA despite having a higher glass transition temperature. Here, molecular dynamics (MD) simulations are used to investigate conformational and energetic differences between linear PMMA and lightly crosslinked PMMA under shear deformation. As consistent with experiments, crosslinked PMMA is found to have a reduced yield stress relative to linear PMMA. Using the probing capabilities of our explicit atom MD approach, it is observed that while the crosslinks have a minimal direct energy contribution to the total system, they can alter how the main chains conform to macroscopic loading. In crosslinked PMMA, the backbone aligns more with the direction of external loading, thereby reducing the force applied to (and associated deformation of) the polymer bonds. (c) 2013 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2014, 52, 444-449
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  • DNA base detection using a single-layer MoS2.

    Farimani, Amir Barati   Min, Kyoungmin   Aluru, Narayana R  

    Nanopore-based DNA sequencing has led to fast and high-resolution recognition and detection of DNA bases. Solid-state and biological nanopores have low signal-to-noise ratio (SNR) (< 10) and are generally too thick (> 5 nm) to be able to read at single-base resolution. A nanopore in graphene, a 2-D material with sub-nanometer thickness, has a SNR of 3 under DNA ionic current. In this report, using atomistic and quantum simulations, we find that a single-layer MoS2 is an extraordinary material (with a SNR > 15) for DNA sequencing by two competing technologies (i.e., nanopore and nanochannel). A MoS2 nanopore shows four distinct ionic current signals for single-nucleobase detection with low noise. In addition, a single-layer MoS2 shows a characteristic change/response in the total density of states for each base. The band gap of MoS2 is significantly changed compared to other nanomaterials (e.g., graphene, h-BN, and silicon nanowire) when bases are placed on top of the pristine MoS2 and armchair MoS2 nanoribbon, thus making MoS2 a promising material for base detection via transverse current tunneling measurement. MoS2 nanopore benefits from a craftable pore architecture (combination of Mo and S atoms at the edge) which can be engineered to obtain the optimum sequencing signals. =20
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  • Overview of the Oxygen Behavior in the Degradation of Li2MnO3 Cathode Material

    Cho, Eunseog   Kim, Kihong   Jung, Changhoon   Seo, Seung-Woo   Min, Kyoungmin   Lee, Hyo Sug   Park, Gyeong-Su   Shin, Jaikwang  

    The Li2MnO3 cathode material is vulnerable to complex degradation behaviors during the operation of battery although it has attracted much attention recently due to its potentially large capacity. In this study, we comprehensively examined the degradation process in Li2MnO3, using theoretical density functional computations as well as experimental techniques (in situ X-ray absorption near edge structure spectroscopy, X-ray diffraction, and Raman spectroscopy). Our study reveals that during the delithiation process, the Li ions mixed in the Mn layer are removed together with those in the Li layer, thereby inducing the release of oxygen atoms. The oxygen loss reaction is energetically favorable at the highly delithiated states, and it can reduce the plateau voltage in the charging curve. Such oxygen loss was observed during or even before the second cycle and furthermore it accelerates the phase transformation of the layered structure to a spinel one. Our results also suggest that oxygen release can be prevented when H ions are exchanged with Li ions during the charging process.
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  • Adhesion of Organic Molecules on Silica Surfaces:A Density Functional Theory Study

    McKenzie, Mathew E.   Goyal, Sushmit   Lee, Sung Hoon   Park, Hyun-Hang   Savoy, Elizabeth   Rammohan, Aravind R.   Mauro, John C.   Kim, Hyunbin   Min, Kyoungmin   Cho, Eunseog  

    Understanding the interface between organic and inorganic materials presents many challenges due to the complex chemistries involved. Modeling and experimental work have elucidated only a few facets of the physical and chemical nature of the adhesion between such surfaces. In this work, we use density functional theory to, understand the adhesion between five different inorganic crystal surfaces (two-dimensional silica, both sides of kaolinite, hydroxylated quartz, hydroxylated albite) with five different organic molecules (benzene, phenol, phthalimide, N-phenylmaleimide, diphenyl ether). In the analysis, we explore the binding motifs that constitute parts of a polyimide monomer and examine their interactions with increasingly complex crystal surfaces. Comparing these systems, we elucidate the key factors (such as electrostatic interactions, hydrogen bond formation, and cation effects) that affect adhesion of organics on inorganic surfaces. It is found that the presence of cations and the availability of the oxygen species, in either the organic or inorganic layers, allows for increased hydrogen bonding. The most significant contribution to adhesion is from the rearrangement of surface electrostatic interactions. These factors can be used to optimize adhesion by decomposing both the organic and inorganic materials into the constituent interactions and help design improved interfacial properties.
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  • Intrinsic origin of intra-granular cracking in Ni-rich layered oxide cathode material

    Min, Kyoungmin   Cho, Eunseog  

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  • Intrinsic origin of intra-granular cracking in Ni-rich layered oxide cathode materials

    Min, Kyoungmin   Cho, Eunseog  

    Mechanical degradation phenomena in layered oxide cathode materials during electrochemical cycling have limited their long-term usage because they deteriorate the structural stability and result in a poor capacity retention rate. Among them, intra-granular cracking inside primary particles progressively degrades the performance of the cathode but comprehensive understanding of its intrinsic origin is still lacking. In this study, the mechanical properties of the primary particle in a Ni-rich layered oxide cathode material (LiNi0.8Co0.1Mn0.1O2) are investigated under tensile and compressive deformation towards both in-plane and out-of-plane directions within the density functional theory framework. The Young's modulus and maximum strength values indicate that the pristine structure is more vulnerable to tensile deformation than compression. In addition, delithiation significantly deteriorates the mechanical properties regardless of the direction of deformation. In particular, a substantial degree of anisotropy is observed, indicating that the mechanical properties in the out-of-plane direction are much weaker than those in the in-plane direction. Particular weakness in that direction is further confirmed using heterogeneously delithiated structures as well as by calculating the accumulated mechanical stress values inside during delithiation. A comparison of the mechanical properties of the structure with a lower Ni content (Ni =3D 33%) demonstrates that the Ni-rich material is slightly weaker and hence its intra-granular cracking could become accelerated during cycling.
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  • Interfacial adhesion behavior of polyimides on silica glass: A molecular dynamics study

    Min, Kyoungmin   Kim, Yaeji   Goyal, Sushmit   Lee, Sung Hoon   McKenzie, Matt   Park, Hyunhang   Savoy, Elizabeth S.   Rammohan, Aravind R.   Mauro, John C.   Kim, Hyunbin   Chae, Kyungchan   Lee, Hyo Sug   Shin, Jaikwang   Cho, Eunseog  

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  • Neural Network Interatomic Potential for Predicting the Formation of Planar Defect in Nanocrystal

    Min, Kyoungmin   Cho, Eunseog  

    Recent advances in the development of interatomic potential using neural networks have proven that its accuracy reaches that of first-principles calculations but with considerably reduced computational cost. In this study, we successfully implement a neural network to construct the interatomic potential of the ZnSe structure by training its potential energy surface results obtained from density functional theory (DFT) calculations. The developed potential is used for molecular dynamics simulations and its accuracy lies within an error of 6% on average from the DFT results for predicting the total energy on pristine and defective bulk structures, slab, and cluster structures of ZnSe. The prediction accuracy is also demonstrated considering the lattice constant and mechanical properties of the pristine bulk structure. To demonstrate its transferability further, a neural network potential is constructed to predict the formation energy of planar defects (stacking fault and twin boundary) in the slab and the nanocrystal structures, and it precisely reproduces the order of stability for each defect type. These results reveal that the neural-network-based interatomic potential can be used to revolutionize atomistic simulations by significantly saving the computation time while maintaining accuracy comparable to that of the DFT.
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  • Theoretical Prediction of Surface Stability and Morphology of LiNiO2 Cathode for Li Ion Batteries

    Cho, Eunseog   Seo, Seung-Woo   Min, Kyoungmin  

    Ni-rich layered oxides are considered to be a promising cathode material with high capacity, and their surface structure should be extensively explored to understand the complex associated phenomena. We investigated the surface stability and morphology of LiNiO2 as a representative of these materials by using density functional theory calculations. The results reveal that the Li-exposed surfaces have lower energies than the oxygen surfaces, irrespective of the facets, and the Ni-exposed ones are the least stable. The equilibrium morphology can vary from truncated trigonal bipyramid to truncated egg shape, according to the chemical potential, whose range is confined by the phase diagram. Moreover, the electrochemical window of stable facets is found to strongly depend on the surface elements rather than the facet directions. Contrary to the stable Li surfaces, oxygen exposure on the surface considerably lowers the Fermi level to the level of electrolyte, thereby accelerating oxidative decomposition of the electrolyte on the cathode surface.
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  • Computational approaches for investigating interfacial adhesion phenomena of polyimide on silica glass

    Min, Kyoungmin   Rammohan, Aravind R.   Lee, Hyo Sug   Shin, Jaikwang   Lee, Sung Hoon   Goyal, Sushmit   Park, Hyunhang   Mauro, John C.   Stewart, Ross   Botu, Venkatesh   Kim, Hyunbin   Cho, Eunseog  

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  • Effect of Nanoscale Roughness on Adhesion between Glassy Silica and Polyimides:A Molecular Dynamics Study

    Lee, Sung Hoon   Stewart, Ross J.   Park, Hyunhang   Goyal, Sushmit   Botu, Venkatesh   Kim, Hyunbin   Min, Kyoungmin   Cho, Eunseog   Rammohan, Aravind R.   Mauro, John C.  

    The effect of nanoscale roughness on the adhesion between glassy silica and polyimides is examined by molecular dynamics simulation. Different silica surfaces, with varying degrees of roughness, were generated by cleaving bulk structures with a predefined surface and a desired average roughness, with different roughness periods and hydroxylation densities in an effort to study the influence of these surface characteristics on adhesion at the silica-polyimide interface. The calculated results reveal that average roughness R-a is the primary controlling factor within the considered conditions. Further, an energy decomposition analysis of the pulling process suggests that hydrogen bonding contributes to the adhesion on all the rough surfaces, while the Coulombic energy contribution becomes significant at higher R-a. From a structural analysis of the vacant volume and surface area, it is shown that the periodicity of roughness provides a rather interesting trend for the adhesion energy. Adhesion can increase with a reduction in period due to the corresponding surface area expansion; however, if vacant volumes exist at the interface, the level of adhesion can decrease. Competition between two opposing tendencies leads to the maximum adhesion, and hence, both R-a and period are key parameters to control the adhesion in nanoscale roughness.
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  • High-Performance and Industrially Feasible Ni-Rich Layered Cathode Materials by Integrating Coherent Interphase

    Min, Kyoungmin   Jung, Changhoon   Ko, Dong-Su   Kim, Kihong   Jang, Jaeduck   Park, Kwangjin   Cho, Eunseog  

    For developing the industrially feasible Ni-rich layered oxide cathode with extended cycle life, it is necessary to mitigate both the mechanical degradation due to intergranular cracking between primary particles and gas generation from the reaction between the electrolyte and residual Li in the cathode. To simultaneously resolve these two issues, we herein propose a simple but novel method to reinforce the primary particles in LiNi0.91Co0.06Mn0.03O2 by providing a Li-reactive material, whose spinel interphase is coherent with the surface of the cathode. The modified structure significantly outperforms analogous bare samples: they conserve more than 90% of the initial capacity after 50 cycles and also exhibit a greater rate capability. By tracking the same particle location during cycling, we confirmed that the current method significantly reduces crack generation because the provided coating material can penetrate inside the grain boundary of the secondary particle and help maintain the volume of the primary particle. Finally, first-principles calculations were implemented to determine the role of this spinel material, i.e., having intrinsically isotropic lattice parameters, superior mechanical properties, and only a small volume change during delithiation. We believe that the proposed method is straightforward and cost-effective; hence, it is directly applicable for the mass production of Ni-rich cathode material to enable its commercialization.
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  • Characterization of Mechanical Degradation in Perfluoropolyether Film for Its Application to Antifingerprint Coatings

    Min, Kyoungmin   Han, Jungim   Park, Byungha   Cho, Eunseog  

    Enhancing the mechanical durability of anti fingerprint films is critical for its industrial application on touch-screen devices to withstand friction damage from repeated rubbing in daily usage. Using reactive molecular dynamics simulations, we herein implement adhesion, mechanical, and deposition tests to investigate two durability-determining factors: intrachain and interchain strength, which affect the structural stability of the antifingerprint film (perfluoropolyether) on silica. From the intrachain perspective, it is found that the Si-C bond in the polymer chain is the weakest, and therefore prone to dissociation and potentially forming a C-O bond. This behavior is demonstrated consistently, regardless of the cross-linking density between polymer chains. For the interchain interaction, increasing the chain length enhances the mechanical properties of the film. Furthermore, the chain deposition test, mimicking the experimental coating process, demonstrates that placing shorter chains first to the surface of silica and then depositing longer chains is an ideal way to improve the interchain interaction in the film structure. The current study reveals a clear pathway to optimize the configuration of the polymer chain as well as its film structure to prolong the product life of the coated antifingerprint film.
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