Ultrathin organosiloxane membrane for precision organic solvent nanofiltration.

Promising advances in membrane technology can lead to energy-saving and eco-friendly solutions in industrial sectors. This work demonstrates a highly selective membrane with ultrathin and highly interconnected organosiloxane polymer nanolayers by initiated chemical vapor deposition to effectively separate solutes within the molecular weight range of 150-300 g mol. We optimize the poly(1,3,5,7-tetravinyl-1,3,5,7-tetramethylcyclotetrasiloxane) membrane by adjusting both the thickness of the selective layer and the pore sizes of its support membranes.

Long short-term memory models of water quality in inland water environments.

Water quality is substantially influenced by a multitude of dynamic and interrelated variables, including climate conditions, landuse and seasonal changes. Deep learning models have demonstrated predictive power of water quality due to the superior ability to automatically learn complex patterns and relationships from variables. Long short-term memory (LSTM), one of deep learning models for water quality prediction, is a type of recurrent neural network that can account for longer-term traits of time-dependent data.

Tailoring the Stabilization and Pyrolysis Processes of Carbon Molecular Sieve Membrane Derived from Polyacrylonitrile for Ethylene/Ethane Separation.

For ethylene/ethane separation, a CMS (carbon molecular sieve) membrane was developed with a PAN (polyacrylonitrile) polymer precursor on an alumina support. To provide an excellent thermal property to PAN precursor prior to the pyrolysis, the stabilization as a pre-treatment process was carried out. Tuning the stabilization condition was very important to successfully preparing the CMS membrane derived from the PAN precursor.

Controlled Synthesis of Metal-Organic Frameworks in Scalable Open-Porous Contactor for Maximizing Carbon Capture Efficiency.

Metal-organic frameworks (MOFs) are a class of microporous materials that have been highlighted with fast and selective sorption of gas molecules; however, they are at least partially unstable in the scale-up process. Here, we report a rational shaping of MOFs in a scalable architecture of fiber sorbent. The long-standing stability challenge of MOFs was resolved by using stable metal oxide precursors that are subject to controlled surface oxide dissolution-growth chemistry during the Mg-based MOF synthesis.

A Review on Polymer Precursors of Carbon Molecular Sieve Membranes for Olefin/Paraffin Separation.

Carbon molecular sieve (CMS) membranes have been developed to replace or support energy-intensive cryogenic distillation for olefin/paraffin separation. Olefin and paraffin have similar molecular properties, but can be separated effectively by a CMS membrane with a rigid, slit-like pore structure. A variety of polymer precursors can give rise to different outcomes in terms of the structure and performance of CMS membranes.

Effect of hyperspectral image-based initial conditions on improving short-term algal simulation of hydrodynamic and water quality models.

Hydrodynamic and water quality modeling have provided valuable simulation results that have enhanced the understanding of the spatial and temporal distribution of algal blooms. Typical model simulations are performed with point-based observational data that are used to configure initial and boundary conditions, and for parameter calibration. However, the application of such conventional modeling approaches is limited due to cost, labor, and time constraints that preclude the retrieval of high-resolution spatial data.

Identification of influencing factors of A. catenella bloom using machine learning and numerical simulation.

Alexandrium catenella (A. catenella) is a notorious algal species known to cause paralytic shellfish poisoning (PSP) in Korean coastal waters. There have been numerous studies on its temporal and spatial blooms in Korea.

Designing a marine outfall to reduce microbial risk on a recreational beach: Field experiment and modeling.

A marine outfall can be a wastewater management system that discharges sewage and stormwater into the sea; hence, it is a source of microbial pollution on recreational beaches, including antibiotic resistant genes (ARGs), which lead to an increase in untreatable diseases. In this regard, a marine outfall must be efficiently located to mitigate these risks. This study aimed to 1) investigate the spatiotemporal variability of Escherichia coli (E.

Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil.

Heavy metal contamination in soil disturbs the chemical, biological, and physical soil conditions and adversely affects the health of living organisms. Visible and near-infrared spectroscopy (VNIRS) shows a potential feasibility for estimating heavy metal elements in soil. Moreover, deep learning models have been shown to successfully deal with complex multi-dimensional and multivariate nonlinear data.

Comparative Evaluation of Six Traditional Fermented Soybean Products in East Asia: A Metabolomics Approach.

Many ethnic fermented soybean products (FSPs) have long been consumed as seasoning and protein sources in East Asia. To evaluate the quality of various FSPs in East Asia, non-targeted metabolite profiling with multivariate analysis of six traditional FSPs (Natto; NT, Cheonggukjang; CG, Doenjang; DJ, Miso; MS, Doubanjiang; DB, Tianmianjiang; TM) was performed. Six FSPs could be clearly distinguished by principle component analysis (PCA) and partial least square-discriminant analysis (PLS-DA).

Untargeted and targeted metabolomics analyses of blackberries - Understanding postharvest red drupelet disorder.

Red drupelet is a postharvest disorder of blackberries with several drupelets turning back to red. This affects visual quality and thus marketability and consumers' acceptance. However, the cause of this disorder as well as metabolite changes during color reversion have not been fully understood.

Stability and pervaporation characteristics of PVA and its blend with PVAm membranes in a ternary feed mixture containing highly reactive epichlorohydrin.

In order to find an alternative for classical distillation in the recovery of ECH/IPA from azeotropic ECH/IPA/water (50/30/20 w/w, %) mixtures, a pervaporation process has been applied. Membranes from the crosslinking of poly(vinyl alcohol)/poly(vinyl amine) (PVA/PVAm) were prepared, and then the membrane stability and pervaporation efficiency of the crosslinked PVA/PVAm membranes were studied for highly reactive ECH systems containing a ternary feed mixture. From the Fourier-transform infrared (FT-IR) spectroscopy analysis, it was observed that all of the membranes were chemically stable for 15 days of immersion in a 50 : 30 : 20 ECH/IPA/water (w/w, %) feed mixture at 60 °C.

Ag-exchanged NaY zeolite introduced polyvinyl alcohol/polyacrylic acid mixed matrix membrane for pervaporation separation of water/isopropanol mixture.

Ag-exchanged NaY zeolite (Ag-NaZ) particles were prepared by ion exchange and introduced to a polyvinyl alcohol (PVA) membrane cross-linked with polyacrylic acid (PAA) for the pervaporation dehydration of an isopropanol (IPA) aqueous mixture. The Ag-exchanged NaY zeolite particles were characterized by FE-SEM, EDS, BET, and XRD studies. The prepared Ag-NaZ-loaded PVA/PAA composite membrane was characterized by FE-SEM, XRD, a swelling study, and contact angle measurements.

Evaluating physico-chemical influences on cyanobacterial blooms using hyperspectral images in inland water, Korea.

Understanding harmful algal blooms is imperative to protect aquatic ecosystems and human health. This study describes the spatial and temporal distributions of cyanobacterial blooms to identify the relations between blooms and environmental factors in the Baekje Reservoir. Two-year cyanobacterial cell data at one fixed station and four remotely sensed distributions of phycocyanin (PC) concentrations based on hyperspectral images (HSIs) were used to describe the relation between the spatial and temporal variations in the blooms and the affecting factors.