Advances in Nanomaterials for Sustainable Gas Separation and Storage: Focus on Clathrate Hydrates.

ConspectusClathrate hydrates, also known as gas hydrates, are a type of inclusion compound formed in highly developed nanoporous lattice spaces created by water molecules, where gas molecules such as CO2, H2, CH4, and other low-molecular-weight liquid molecules are trapped. The nanoporous cage formed by water molecules serves as the "host", while the trapped gas or low-molecular-weight liquid molecules such as tetrahydrofuran act as "guests". Early on, clathrate hydrates drew attention as a potential replacement for conventional natural gas due to their natural gas hydrate form, which contains natural gases as guests and exists in permafrost or sea floors. Recently, based on the unique physicochemical properties of clathrate hydrates, efforts are being made to utilize synthetic clathrate hydrates in various separation processes such as post- and pre-combustion CO2 capture, H2 storage, natural gas storage and transportation, wastewater desalination, and more. While it is undeniable that clathrate hydrates are based on principles that are beneficial for the separation and storage of gas molecules, there are several challenges that must be addressed for their practical application. These challenges include (i) the limitation of gas storage capacity due to the confined size of nanoporous cages, (ii) the relatively high-pressure and low-temperature thermodynamic storage conditions typically required for clathrate hydrate formation, and (iii) slow formation kinetics and low gas hydrate conversion, which are also essential issues that need to be resolved for the meaningful implementation of clathrate hydrates. In this Account, we aim to introduce recent noteworthy research findings, including those from our research team, focusing on addressing these challenges. We explored the untapped potential of clathrate hydrates by bridging the gap between macroscopic and microscopic properties. This has led to breakthroughs in sustainable gas separation and storage applications. By revealing the hidden nature of these hydrates, we have effectively mitigated their inherent limitations, setting the stage for more feasible and efficient H2 storage solutions through the introduction of hydrogen-natural gas blends to clathrate hydrates. Additionally, we have demonstrated the tuning effect on all naturally formed hydrate structures, offering new insights into their underlying properties and macroscopic behavior. Furthermore, our research has proposed a highly efficient hydrate-based pre-combustion CO2 capture approach that leverages porous media with appropriate wettability and considers the implications of microstructure properties. This emphasizes the crucial connection between nano-structure and macroscopic properties, underscoring the significance of understanding their interplay for economic feasibility. We believe that our efforts to unveil the hidden nature of gas hydrates provide strategies to address challenges and lay the groundwork for practical applications.

Structural modification of salt-promoted MgO sorbents for intermediate temperature CO2 capture.

MgO-based sorbents are a promising option for CO2 capture at intermediate temperatures. MgO-based sorbents are often hybridized with alkali metal salts to promote the CO2 capture performance. However, MgO-based sorbents often suffer a rapid decrement of CO2 capture performance during multicycle carbonation-calcination reactions due to the reduction of active sites. In this study, we attempted to enhance the durability of MgO-based sorbents by modifying their morphology. A tubular-shaped MgO-based sorbent was synthesized using a carbon nanotube template. Various characterization experiments and evaluations were performed with the synthesized MgO-based materials. The MgO sample with modified structure exhibited a specific morphology consisting of elongated plate-like structures separated by empty spaces. This separation is expected to prevent MgO agglomeration and preserve the modified morphology during iterative CO2 capture reactions. The MgO with modified structure achieved higher cycling stability with four times slower performance decay than the control MgO, even though identical chemical compositions were applied.

Towards multi-omics characterization of tumor heterogeneity: a comprehensive review of statistical and machine learning approaches.

The multi-omics molecular characterization of cancer opened a new horizon for our understanding of cancer biology and therapeutic strategies. However, a tumor biopsy comprises diverse types of cells limited not only to cancerous cells but also to tumor microenvironmental cells and adjacent normal cells. This heterogeneity is a major confounding factor that hampers a robust and reproducible bioinformatic analysis for biomarker identification using multi-omics profiles. Besides, the heterogeneity itself has been recognized over the years for its significant prognostic values in some cancer types, thus offering another promising avenue for therapeutic intervention. A number of computational approaches to unravel such heterogeneity from high-throughput molecular profiles of a tumor sample have been proposed, but most of them rely on the data from an individual omics layer. Since the heterogeneity of cells is widely distributed across multi-omics layers, methods based on an individual layer can only partially characterize the heterogeneous admixture of cells. To help facilitate further development of the methodologies that synchronously account for several multi-omics profiles, we wrote a comprehensive review of diverse approaches to characterize tumor heterogeneity based on three different omics layers: genome, epigenome and transcriptome. As a result, this review can be useful for the analysis of multi-omics profiles produced by many large-scale consortia. Contact:sunkim.bioinfo@snu.ac.kr.

Spectroscopic Investigation of Entropic Canopy-Canopy Interactions of Nanoparticle Organic Hybrid Materials.

Nanoparticle organic hybrid materials (NOHMs) are self-suspended liquid-like nanoparticle-based functional materials consisting of a surface-functionalized inorganic nanocore and oligomeric or polymeric chains. They often exhibit complex intermolecular and intramolecular interactions among their constituents, resulting in versatile physicochemical characteristics that range from glassy solids to solvent-free nanoparticle fluids. A variety of applications involving NOHMs have been investigated thus far, including thermal management fluids, lubricants, magnetic fluids, nanocomposites, electrolytes, water treatment and biomass pretreatment chemicals, and CO2 capture solvents. In particular, NOHMs have recently been recognized as a promising CO2 capture and utilization medium. To capture CO2 more effectively, a variety of specific functional groups of strong chemical affinity to CO2 can be added to the polymeric canopy (enthalpic contribution), and various steric considerations induced by attractive/repulsive interactions among the nanocores and canopies can be introduced (entropic contribution). These occur while maintaining negligible vapor pressure and enhanced thermal stability. Here, we investigated the canopy dynamics of NOHMs with different-sized SiO2 nanocores, aiming to reveal the hidden nature of the entropic interaction occurring in NOHMs. Pulse-field gradient nuclear magnetic resonance spectroscopy (with 1H) was employed to investigate the canopy dynamics of the NOHMs synthesized using 7, 12, and 22 nm SiO2 particles, and these results were compared with those from a ternary mix of all three sizes of SiO2 nanocores. The self-diffusion coefficient and thermal diffusivity were also evaluated.

DeepFam: deep learning based alignment-free method for protein family modeling and prediction.

Motivation: A large number of newly sequenced proteins are generated by the next-generation sequencing technologies and the biochemical function assignment of the proteins is an important task. However, biological experiments are too expensive to characterize such a large number of protein sequences, thus protein function prediction is primarily done by computational modeling methods, such as profile Hidden Markov Model (pHMM) and k-mer based methods. Nevertheless, existing methods have some limitations; k-mer based methods are not accurate enough to assign protein functions and pHMM is not fast enough to handle large number of protein sequences from numerous genome projects. Therefore, a more accurate and faster protein function prediction method is needed. Results: In this paper, we introduce DeepFam, an alignment-free method that can extract functional information directly from sequences without the need of multiple sequence alignments. In extensive experiments using the Clusters of Orthologous Groups (COGs) and G protein-coupled receptor (GPCR) dataset, DeepFam achieved better performance in terms of accuracy and runtime for predicting functions of proteins compared to the state-of-the-art methods, both alignment-free and alignment-based methods. Additionally, we showed that DeepFam has a power of capturing conserved regions to model protein families. In fact, DeepFam was able to detect conserved regions documented in the Prosite database while predicting functions of proteins. Our deep learning method will be useful in characterizing functions of the ever increasing protein sequences. Availability and implementation: Codes are available at https://bhi-kimlab.github.io/DeepFam.

A 3D-printed flow distributor with uniform flow rate control for multi-stacked microfluidic systems.

In the scale-up of chemical production in a microfluidic system, it is challenging to prevent flow maldistribution from a single inlet into stacked multiple microchannel exits. In the present study, a compact flow distributor equipped with a fluidic damper is developed by computational fluid dynamics (CFD) along with experimental validation. A microfluidic flow distributor, which is equipped with an optimized fluidic damper and consists of 25 exit channels, is fabricated as an integrated body using a digital light processing (DLP) type 3D printer. The 3D printed flow distributor with a CFD-optimized fluidic damper is found to achieve a low maldistribution factor (MF) of 2.2% for the average flow rate over 25 exit channels while inducing only a minor increment (<6%) in the pressure drop. A generalized manual is proposed for the design of optimal flow distributors with different scale-up dimensions. Using the manual, an optimal flow distributor with 625 stacked microchannels with a MF of only 1.2% is successfully designed. It is expected that the design manual and the rapid printing platform will allow the efficient development of multi-channel stacked micro-devices such as those in drug delivery and energy conversion systems where equidistribution of fluid flow is highly demanded.

MIDAS: Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data.

Pathway based analysis of high throughput transcriptome data is a widely used approach to investigate biological mechanisms. Since a pathway consists of multiple functions, the recent approach is to determine condition specific sub-pathways or subpaths. However, there are several challenges. First, few existing methods utilize explicit gene expression information from RNA-seq. More importantly, subpath activity is usually an average of statistical scores, e.g., correlations, of edges in a candidate subpath, which fails to reflect gene expression quantity information. In addition, none of existing methods can handle multiple phenotypes. To address these technical problems, we designed and implemented an algorithm, MIDAS, that determines condition specific subpaths, each of which has different activities across multiple phenotypes. MIDAS utilizes gene expression quantity information fully and the network centrality information to determine condition specific subpaths. To test performance of our tool, we used TCGA breast cancer RNA-seq gene expression profiles with five molecular subtypes. 36 differentially activate subpaths were determined. The utility of our method, MIDAS, was demonstrated in four ways. All 36 subpaths are well supported by the literature information. Subsequently, we showed that these subpaths had a good discriminant power for five cancer subtype classification and also had a prognostic power in terms of survival analysis. Finally, in a performance comparison of MIDAS to a recent subpath prediction method, PATHOME, our method identified more subpaths and much more genes that are well supported by the literature information. AVAILABILITY: http://biohealth.snu.ac.kr/software/MIDAS/.

Measuring intratumor heterogeneity by network entropy using RNA-seq data.

Intratumor heterogeneity (ITH) is observed at different stages of tumor progression, metastasis and reouccurence, which can be important for clinical applications. We used RNA-sequencing data from tumor samples, and measured the level of ITH in terms of biological network states. To model complex relationships among genes, we used a protein interaction network to consider gene-gene dependency. ITH was measured by using an entropy-based distance metric between two networks, nJSD, with Jensen-Shannon Divergence (JSD). With nJSD, we defined transcriptome-based ITH (tITH). The effectiveness of tITH was extensively tested for the issues related with ITH using real biological data sets. Human cancer cell line data and single-cell sequencing data were investigated to verify our approach. Then, we analyzed TCGA pan-cancer 6,320 patients. Our result was in agreement with widely used genome-based ITH inference methods, while showed better performance at survival analysis. Analysis of mouse clonal evolution data further confirmed that our transcriptome-based ITH was consistent with genetic heterogeneity at different clonal evolution stages. Additionally, we found that cell cycle related pathways have significant contribution to increasing heterogeneity on the network during clonal evolution. We believe that the proposed transcriptome-based ITH is useful to characterize heterogeneity of a tumor sample at RNA level.

A Double-Side CMOS-CNT Biosensor Array With Padless Structure for Simple Bare-Die Measurements in a Medical Environment.

This paper presents a double-side CMOS-carbon nanotube (CNT) sensor array for simple bare-die measurements in a medical environment based on a 0.35 µm standard CMOS process. This scheme allows robust measurements due to its inherent back-side rectifying diodes with a high latch-up resistance. In particular, instead of using pads, only two contact metal structures: a wide ring structure around the sensor area on the front side and a plate structure at the backside are used for both power and single I/O line. The back-side rectification is made possible by creating VDD and VSS through the back-side and front-side, respectively. The single I/O line is conditioned such that it doubles as either the power source or the ground, depending on whether the chip is face down or face up. A modified universal asynchronous receiver/transmitter (UART) serial communication scheme with pulse based I/O signal transmission is developed to reduce the power degradation during the signaling intervals. In addition, communication errors and I/O power dissipation for the receiver path are minimized by using level sensitive switch control and double sampling difference amplifier. In order to implement these special functions, a controller chip with a special I/O protocol is designed. Using this controller chip, issuing commands and receiving data can both be performed on a single line and the results are flexibly measured through either the backside or the front side of the chip contacts. As a result, a stable operation of under 150 mW maximum power at 2 MHz data rate can be achieved. The double-side chips with 32 × 32 and 64 × 64 sensor arrays occupy areas of 1.9 × 2.3 mm(2) and 3.7 × 3.9 mm(2), respectively.

Tuning the dissolution kinetics of wollastonite via chelating agents for CO2 sequestration with integrated synthesis of precipitated calcium carbonates.

Carbon mineralization has recently received much attention as one of the most promising options for CO2 sequestration. The engineered weathering of silicate minerals as a means of permanent carbon storage has unique advantages such as the abundance of naturally occurring calcium and magnesium-bearing minerals and the formation of environmentally-benign and geologically stable solids via a thermodynamically favored carbonation reaction. However, several challenges need to be overcome to successfully deploy carbon mineralization on a large scale. In particular, the acceleration of the rate-limiting mineral dissolution step along with process optimization is essential to ensure the economic feasibility of the proposed carbon storage technology. In this study, the effect of various types of chelating agents on the dissolution rate of calcium-bearing silicate mineral, wollastonite, was explored to accelerate its weathering rate. It was found that chelating agents such as acetic acid and gluconic acid significantly improved the dissolution kinetics of wollastonite even at a much diluted concentration of 0.006 M by complexing with calcium in the mineral matrix. Calcium extracted from wollastonite was then reacted with a carbonate solution to form precipitated calcium carbonate (PCC), while tuning the particle size and the morphological structure of PCC to mimic commercially available PCC-based filler materials.

Investigation of CO2 capture mechanisms of liquid-like nanoparticle organic hybrid materials via structural characterization.

Nanoparticle organic hybrid materials (NOHMs) have been recently developed that comprise an oligomeric or polymeric canopy tethered to surface-modified nanoparticles via ionic or covalent bonds. It has already been shown that the tunable nature of the grafted polymeric canopy allows for enhanced CO(2) capture capacity and selectivity via the enthalpic intermolecular interactions between CO(2) and the task-specific functional groups, such as amines. Interestingly, for the same amount of CO(2) loading NOHMs have also exhibited significantly different swelling behavior compared to that of the corresponding polymers, indicating a potential structural effect during CO(2) capture. If the frustrated canopy species favor spontaneous ordering due to steric and/or entropic effects, the inorganic cores of NOHMs could be organized into unusual structural arrangements. Likewise, the introduction of small gaseous molecules such as CO(2) could reduce the free energy of the frustrated canopy. This entropic effect, the result of unique structural nature, could allow NOHMs to capture CO(2) more effectively. In order to isolate the entropic effect, NOHMs were synthesized without the task-specific functional groups. The relationship between their structural conformation and the underlying mechanisms for the CO(2) absorption behavior were investigated by employing NMR and ATR FT-IR spectroscopies. The results provide fundamental information needed for evaluating and developing novel liquid-like CO(2) capture materials and give useful insights for designing and synthesizing NOHMs for more effective CO(2) capture.

Magnetic transition and long-time relaxation behavior induced by selective injection of guest molecules into clathrate hydrates.

Magnetic molecules physisorbed into low-dimensional nanostructures of microporous materials such as graphite and metal-organic frameworks have been verified to exhibit an unusual magnetic behavior. We demonstrate that the selective injection of both magnetic and nonmagnetic guest molecules into the water-ice cages of clathrate hydrates to form a 3D superstructure with tetrahedral and diamond-like sublattices can modify the inherent magnetism.

Effect of interlayer ions on methane hydrate formation in clay sediments.

Natural methane hydrates occurring in marine clay sediments exhibit heterogeneous phase behavior with high complexity, particularly in the negatively charged interlayer region. To date, the real clay interlayer effect on natural methane hydrate formation and stability remains still much unanswered, even though a few computer simulation and model studies are reported. We first examined the chemical shift difference of 27Al, 29Si, and 23Na between dry clay and clay containing intercalated methane hydrates (MH) in the interlayer. We also measured the solid-state 13C MAS NMR spectra of MH in Na-montmorillonite (MMT) and Ca-montmorillonite (MMT) to reveal abnormal methane popularity established in the course of intercalation and further performed cryo-TEM and XRD analyses to identify the morphology and layered structure of the intercalated methane hydrate. The present findings strongly suggest that the real methane amount contained in natural MH deposits should be reevaluated under consideration of the compositional, structural, and physical characteristics of clay-rich sediments. Furthermore, the intercalated methane hydrate structure should be seriously considered for developing the in situ production technologies of the deep-ocean methane hydrate.

Spectroscopic observation of critical guest concentration appearing in tert-butyl alcohol clathrate hydrate.

The tert-butyl alcohol (TBA) is the most hydrophobic of the simple alcohol and by itself does not form a clathrate hydrate with water. A genuine clathrate hydrate is synthesized by exposing a gaseous guest to solid TBA + H2O powders. Here, we examine three consecutive spectroscopic approaches of (1) the occurrence of a "free" OH stretching band (nu(OH)) signal of TBA molecules representing an absence of hydrogen bonding between the host water and guest TBA, (2) a tuning effect for creating fresh cages via the rearrangement of the host-water lattice, and finally (3) the existence of a critical guest concentration (CGC) that appears only when the TBA concentration is dilute. The present findings from this simple three-step approach can be extended to other alcoholic guest species with the specific modifications to provide the new insights into inclusion chemistry.

Spectroscopic observation of atomic hydrogen radicals entrapped in icy hydrogen hydrate.

A hydrogen molecule entrapped in the cages of icy hydrogen hydrate is confined in host water framework and thus behaves unlike pure solid or liquid hydrogen. The gamma-irradiated hydrogen radicals are for the first time observed from ESR and solid-state MAS 1H NMR spectra to stably exist in the icy hydrate channels without any collapse of the host framework, confirming the chemical shift consistency of ionized hydrogen derivatives. We discuss the confined icy hydrate channels, which can act as potential storage sites for simultaneously imprisoning both molecular and ionized hydrogen and further as icy nanoreactors.

Thermal expansivity of tetrahydrofuran clathrate hydrate with diatomic guest molecules.

The guest dynamics and thermal behavior occurring in the cages of clathrate hydrates appear to be too complex to be clearly understood through various structural and spectroscopic approaches, even for the well-known structures of sI, sII, and sH. Neutron diffraction studies have recently been carried out to clarify the special role of guests in expanding the host water lattices and have contributed to revealing the influence factors on thermal expansivity. Through this letter we attempt to address three noteworthy features occurring in guest inclusion: (1) the effect of guest dimension on host water lattice expansion; (2) the effect of thermal history on host water lattice expansion; and (3) the effect of coherent/incoherent scattering cross sections on guest thermal patterns. The diatomic guests of H 2, D 2, N 2, and O 2 have been selected for study, and their size and mass dependence on the degree of lattice expansion have been examined, and four sII clathrate hydrates with tetrahydrofuran (THF) have been synthesized in order to determine their neutron powder diffraction patterns. After thermal cycling, the THF + H 2 clathrate hydrate is observed to exhibit an irreversible plastic deformation-like pattern, implying that the expanded lattices fail to recover the original state by contraction. The host-water cage dimension after degassing the guest molecules remains as it was expanded, and thus host-guest as well as guest-guest interactions will be altered if guest uptake reoccurs.

Sequestering carbon dioxide into complex structures of naturally occurring gas hydrates.

Large amounts of CH4 in the form of solid hydrates are stored on continental margins and in permafrost regions. If these CH4 hydrates could be converted into CO2 hydrates, they would serve double duty as CH4 sources and CO2 storage sites. We explore here the swapping phenomenon occurring in structure I (sI) and structure II (sII) CH4 hydrate deposits through spectroscopic analyses and its potential application to CO2 sequestration at the preliminary phase. The present 85% CH4 recovery rate in sI CH4 hydrate achieved by the direct use of binary N2+CO2 guests is surprising when compared with the rate of 64% for a pure CO2 guest attained in the previous approach. The direct use of a mixture of N2+CO2 eliminates the requirement of a CO2 separation/purification process. In addition, the simultaneously occurring dual mechanism of CO2 sequestration and CH4 recovery is expected to provide the physicochemical background required for developing a promising large-scale approach with economic feasibility. In the case of sII CH4 hydrates, we observe a spontaneous structure transition of sII to sI during the replacement and a cage-specific distribution of guest molecules. A significant change of the lattice dimension caused by structure transformation induces a relative number of small cage sites to reduce, resulting in the considerable increase of CH4 recovery rate. The mutually interactive pattern of targeted guest-cage conjugates possesses important implications for the diverse hydrate-based inclusion phenomena as illustrated in the swapping process between CO2 stream and complex CH4 hydrate structure.

Effects of oleamide on choline acetyltransferase and cognitive activities.

We screened 50 Korean traditional natural plants to measure the activation effect on choline acetyltransferase and attenuation of scopolamine-induced amnesia. The methanolic extracts from Zizyphus jujuba among the tested 50 plants, showed the highest activatory effect (34.1%) on choline acetyltransferase in vitro. By sequential fractionation of Zizyphus jujuba, the active component was finally identified as cis-9-octadecenoamide (oleamide). After isolation, oleamide showed a 65% activation effect. Administration of oleamide (0.32%) to mice significantly reversed the scopolamine-induced memory and/or cognitive impairment in the passive avoidance test and Y-maze test. Injection of scopolamine to mice impaired performance on the passive avoidance test (31% decrease in step-through latency), and on the Y-maze test (16% decrease in alternation behavior). In contrast, mice treated with oleamide before scopolamine injection were protected from these changes (12-25% decrease in step-through latency; 1-10% decrease in alternation behavior). These results suggest that oleamide should be a useful chemo-preventive agent against Alzheimer's disease.