Thin-Film Composite Membrane Compaction: Exploring the Interplay among Support Compressive Modulus, Structural Characteristics, and Overall Transport Efficiency.

Water scarcity has driven the demand for water production from unconventional sources and the reuse of industrial wastewater. Pressure-driven membranes, notably thin-film composite (TFC) membranes, stand as energy-efficient alternatives to the water scarcity challenge and various wastewater treatments. While pressure drives solvent movement, it concurrently triggers membrane compaction and flux deterioration. This necessitates a profound comprehension of the intricate interplay among compressive modulus, structural properties, and transport efficacy amid the compaction process. In this study, we present an all-encompassing compaction model for TFC membranes, applying authentic structural and mechanical variables, achieved by coupling viscoelasticity with Monte Carlo flux calculations based on the resistance-in-series model. Through validation against experimental data for multiple commercial membranes, we evaluated the influence of diverse physical parameters. We find that support polymers with a higher compressive modulus (lower compliance), supports with higher densities of "finger-like" pores, and "sponge-like" pores with optimum void fractions will be preferred to mitigate compaction. More importantly, we uncover a trade-off correlation between steady-state permeability and the modulus for identical support polymers displaying varying porosities. This model holds the potential as a valuable guide in shaping the design and optimization for further TFC applications and extending its utility to biological scaffolds and hydrogels with thin-film coatings in tissue engineering.

Recent Progress in All-Small-Molecule Organic Solar Cells.

Active layer material plays a critical role in promoting the performance of an organic solar cell (OSC). Small-molecule (SM) materials have the merits of well-defined chemical structures, few batch-to-batch variations, facile synthesis and purification procedures, and easily tuned properties. SM-donor and non-fullerene acceptor (NFA) innovations have recently produced all-small-molecule (ASM) devices with power conversion efficiencies that exceed 17% and approach those of their polymer-based counterparts, thereby demonstrating their great future commercialization potential. In this review, recent progress in both SM donors and NFAs to illustrate structure-property relationships and various morphology-regulation strategies are summarized. Finally, ASM-OSC challenges and outlook are discussed.

Understanding and Designing a High-Performance Ultrafiltration Membrane Using Machine Learning.

Ultrafiltration (UF) as one of the mainstream membrane-based technologies has been widely used in water and wastewater treatment. Increasing demand for clean and safe water requires the rational design of UF membranes with antifouling potential, while maintaining high water permeability and removal efficiency. This work employed a machine learning (ML) method to establish and understand the correlation of five membrane performance indices as well as three major performance-determining membrane properties with membrane fabrication conditions. The loading of additives, specifically nanomaterials (A_wt %), at loading amounts of >1.0 wt % was found to be the most significant feature affecting all of the membrane performance indices. The polymer content (P_wt %), molecular weight of the pore maker (M_Da), and pore maker content (M_wt %) also made considerable contributions to predicting membrane performance. Notably, M_Da was more important than M_wt % for predicting membrane performance. The feature analysis of ML models in terms of membrane properties (i.e., mean pore size, overall porosity, and contact angle) provided an unequivocal explanation of the effects of fabrication conditions on membrane performance. Our approach can provide practical aid in guiding the design of fit-for-purpose separation membranes through data-driven virtual experiments.

A Polymer Acceptor with Grafted Small Molecule Acceptor Unit for Efficient All Polymer Organic Solar Cells.

A polymer acceptor, named PX-1, is  designed and synthesized using a polymerization strategy with grafted small molecule acceptors. This design approach allows for the freedom of end groups while maintaining efficient terminal packing, enhancing π-π interactions, and facilitating charge transport. All-polymer organic solar cells based on PM6: PX-1 demonstrate a promising efficiency of 13.55%. The result presents an alternative pathway for the design of high-efficiency polymer acceptors through the careful regulation of small molecule acceptor monomers and linker units.

Total Organic Carbon as a Quantitative Index of Micro- and Nano-Plastic Pollution.

The global pollution of micro- and nano-plastics (MNPs) calls for monitoring methods. As diverse mixtures of various sizes, morphologies, and chemical compositions in the environment, MNPs are currently quantified based on mass or number concentrations. Here, we show total organic carbon (TOC) as an index for quantifying the pollution of total MNPs in environmental waters. Two parallel water samples are respectively filtered with a carbon-free glass fiber membrane. Then, one membrane with the collected particulate substances is treated by potassium peroxodisulfate oxidation and Fenton digestion in sequence for quantifying the sum of MNPs and particulate black carbon (PBC) as TOCMNP&PBC using a TOC analyzer, another membrane is treated by sulfonation and Fenton digestion for quantifying PBC as TOCPBC, and the TOC of MNPs is calculated by subtracting TOCPBC from TOCMNP&PBC. The feasibility of our method is demonstrated by determination of various MNPs of representative plastic types and sizes (0.5-100 µm) in tap, river, and sea water samples, with low detection limits (∼7 µg C L-1) and high spiked recoveries (83.7-114%). TOC is a powerful index for routine monitoring of MNP pollution.

MXene Composite Membranes with Enhanced Ion Transport and Regulated Ion Selectivity.

Two-dimensional (2D) material-based membranes are promising candidates for various separation applications. However, the further enhancement of membrane ion conductance is difficult, and the regulation of membrane ion selectivity remains a challenge. Here, we demonstrate the facile fabrication of MXene composite membranes by incorporating spacing agents that contain SO3H groups into the MXene interlayers. The synthesized membrane shows enhanced ion conductance and ion selectivity. Subsequently, the membranes are utilized for salinity gradient power (SGP) generation and lithium-ion (Li+) recovery. The membrane containing poly(sodium 4-styrenesulfonate) (PSS) as the spacing agent shows a much higher power density for SGP generation as compared to the pristine MXene membrane. Using artificial seawater and river water, the power density reaches 1.57 W/m2 with a testing area of 0.24 mm2. Also, the same membrane shows Li+/Na+ and Li+/K+ selectivities of 2.5 and 3.2, respectively. The incorporation of PSS increases both the size and charge density of the nanochannels inside the membrane, which is beneficial for ion conduction. In addition, the density functional theory (DFT) calculation shows that the binding energy between Li+ and the SO3H group is lower than other alkali ion metals, and this might be one major reason why the membrane possesses high Li+ selectivity. This study demonstrates that incorporating spacing agents into the 2D material matrix is a viable strategy to enhance the performance of the 2D material-based membranes. The results from this study can inspire new membrane designs for emerging applications including energy harvesting and monovalent ion recovery.

Capillary-Assisted Fabrication of Thin-Film Nanocomposite Membranes for Improved Solute-Solute Separation.

Efficient separation of harmful contaminants (e.g., per- and polyfluoroalkyl substances, PFASs) from valuable components (water and nutrients) is essential to the resource recovery from domestic wastewater for agricultural purposes. Such selective recovery requires precise separation at the angstrom scale. Although nanofiltration (NF) has the potential to achieve solute-solute separation, the state-of-the-art polyamide (PA) membranes are typically constrained by limited precision of solute-solute selectivity and their well-documented permeability-selectivity trade-off. Herein, we present a novel capillary-assisted interfacial polymerization (CAIP) approach to generate metal-organic framework (MOF)-PA nanocomposite membranes with reduced surface charges and more uniform pore sizes that favor solute selectivity by enhanced size exclusion. By uniquely regulating the PA-MOF interactions using the capillary force, CAIP results in effective exposure of MOF nanochannels on the membrane surface and a PA matrix with a high cross-linking gradient in the vertical direction, both of which contribute to an exceptional water permeance of ∼18.7 LMH/bar and an unprecedentedly high selectivity between nutrient ions and PFASs. Our CAIP approach breaks new ground for utilizing nanoparticles with nanochannels in fabricating the next-generation, fit-for-purpose NF membranes for improved solute-solute separations.

Revolutionizing Membrane Design Using Machine Learning-Bayesian Optimization.

Polymeric membrane design is a multidimensional process involving selection of membrane materials and optimization of fabrication conditions from an infinite candidate space. It is impossible to explore the entire space by trial-and-error experimentation. Here, we present a membrane design strategy utilizing machine learning-based Bayesian optimization to precisely identify the optimal combinations of unexplored monomers and their fabrication conditions from an infinite space. We developed ML models to accurately predict water permeability and salt rejection from membrane monomer types (represented by the Morgan fingerprint) and fabrication conditions. We applied Bayesian optimization on the built ML model to inversely identify sets of monomer/fabrication condition combinations with the potential to break the upper bound for water/salt selectivity and permeability. We fabricated eight membranes under the identified combinations and found that they exceeded the present upper bound. Our findings demonstrate that ML-based Bayesian optimization represents a paradigm shift for next-generation separation membrane design.

Forward Solute Transport in Forward Osmosis Using a Freestanding Graphene Oxide Membrane.

A graphene oxide membrane (GOM) has the potential to be used in forward osmosis (FO) because it has a high water permeability and low reverse salt flux. To explore suitable applications, we initiated the investigation of the forward solute transport through a freestanding GOM in FO. Both uncharged solutes (PEG 200 and PEG 1000) and charged solutes (NaCl, MgSO4, and MgCl2) were investigated, and the forward solute flux in FO was tested. The Donnan steric pore model (DSPM) was utilized to calculate the forward solute flux of the freestanding GOM in FO when discussing diffusion, convection, and electromigration. Our results showed that the freestanding GOM has a better separation performance for multivalent ions than the monovalent ions in the FO mode. We found an information gap between the calculated and experimental forward solute flux values, especially when charged solutes were used in the feed solution and the electrical double layer (EDL) was thick. We propose that the EDL inside the GOM has a screening effect on the forward ion transport during FO, even in the presence of relatively high water flux. According to our analysis, the forward solute transport for charged solutes is governed by steric exclusion and interfacial Donnan exclusion as well as EDL screening along the nanochannels inside the membrane. Our study provides guidance for the future use of the freestanding GOM during FO for water and wastewater treatment.

Fit-for-Purpose Design of Nanofiltration Membranes for Simultaneous Nutrient Recovery and Micropollutant Removal.

Domestic wastewater is a valuable reservoir of nutrients such as nitrogen and phosphorus. However, the presence of emerging micropollutants (EMPs) hinders its applications in resource recovery. In this study, we designed and fabricated a novel thin-film composite polyamide membrane, which enables highly selective nanofiltration (NF) that removes EMPs effectively while preserving valuable nutrients in the permeate. By incorporating polyethylenimine as an additional monomer to piperazine and surfactant sodium dodecyl sulfate in interfacial polymerization, we precisely tuned membrane pore size, pore size distribution, and surface charge. The resultant NF membrane achieved desirable solute-solute selectivity between EMPs (rejection rate > 75%) and nutrient N and P ions (rejection rate < 25%). By applying a modified Donnan steric pore model with dielectric exclusion, which takes membrane pore size distribution into consideration, we demonstrate the synergistic effect of membrane pore size, pore size distribution, and surface charge in regulating membrane solute-solute selectivity. Designing solute-solute selective NF membranes for fit-for-purpose wastewater treatment has great potential to improve the flexibility of membrane technologies that can convert wastewater streams to valuable water and nutrient resources.

Two-Dimensional Ti3C2Tx MXene/GO Hybrid Membranes for Highly Efficient Osmotic Power Generation.

Osmotic power has emerged as one of the promising candidates for clean and renewable energy. However, the advancement of present osmotic power-harvesting technologies, specifically pressure-retarded osmosis (PRO) in this work, is hindered by the unsatisfactory membrane transport properties. Herein, we demonstrate the freestanding transition-metal carbides and graphene oxide hybrid membranes as high-performance PRO membranes. Due to the elimination of internal concentration polarization, the freestanding hybrid membrane can achieve a record-high power density up to approximately 56.4 W m-2 with 2.0 M NaCl as the draw solution and river water (0.017 M) as the feed water at an applied hydraulic pressure difference of 9.66 bar. In addition, the hybrid membranes exhibit enhanced antifouling potential and antibacterial activity. The facile fabrication of the hybrid membranes shed light on a new membrane development platform for the highly anticipated osmotic power-harvesting technologies.

Study on the Transport Mechanism of a Freestanding Graphene Oxide Membrane for Forward Osmosis.

Graphene oxide membranes (GOMs) are promising separation technologies. In forward osmosis (FO), we found that the water flux from the feed solution to the draw solution can prevent ions from diffusing to the feed solution in a highly tortuous and porous GOM. In reverse osmosis (RO), we found that the salt rejection is low compared to that in commercially available RO membranes. While this prohibits the use of GOMs for RO and FO water desalination, we believe that such membranes could be used for other water treatment applications and energy production. To examine the transport mechanism, we characterized the physical and chemical properties of GOMs and derived mass transfer models to analyze water and salt transport inside freestanding GOMs. The experimental reverse salt flux was between the largest and smallest theoretical values, which corresponds to the lowest and highest tortuosity, respectively, in FO. Furthermore, the concentration profile for the reverse salt flux shortened as the NaCl draw concentration increased because the water flux increased and the electrical double layer (EDL) decreased with increasing NaCl in the draw solution. We provide insights into the transport mechanisms in GOMs and provide guidance for future exploration of GOMs in efficient water treatment and energy production processes.

Improving Ion Rejection of Conductive Nanofiltration Membrane through Electrically Enhanced Surface Charge Density.

Nanofiltration (NF) is considered a promising candidate for brackish and seawater desalination. NF exhibits high multivalent ion rejection, but the rejection rate for monovalent ions is relatively low. Besides, great challenges remain for conventional NF membranes to achieve high ion rejection without sacrificing water flux. This work presents an effective strategy for improving the ion rejection of conductive NF membrane without decreasing the permeability through electrically assisted enhancement of surface charge density. When external voltage is increased from 0 to 2.5 V, the surface charge density of the membrane increases from 11.9 to 73.0 mC m-2, which is 6.1× higher than that without external voltage. Correspondingly, the rejection rate for Na2SO4 increases from 81.6 to 93.0% and that for NaCl improves from 53.9 to 82.4%; meanwhile, the membrane retains high permeabilities of 14.0 L m-2 h-1 bar-1 for Na2SO4 filtration and 14.5 L m-2 h-1 bar-1 for NaCl filtration. The Donnan steric pore model analysis suggests that the Donnan potential difference between the membrane and bulk solution is increased under electrical assistance, leading to increased ion transfer resistance for improved ion rejection. This work provides new insight into the development of advanced NF technologies for desalination and water treatment.

Enhanced Ionic Conductivity and Power Generation Using Ion-Exchange Resin Beads in a Reverse-Electrodialysis Stack.

Reverse electrodialysis (RED) is a promising technique for harvesting energy by mixing seawater with river water. The energy production is usually limited by ionic conductivity in dilute compartments of a RED system. Novel tests were conducted in this research, which used ion-exchange resin beads (IERB) to replace nonconductive spacer fabrics in RED compartments with dilute NaCl solution in a modified stack containing Fumasep FKS and Fumasep FAS membranes. We compared the conductivity of an IERB packed bed with that of an inert glass-beads-packed bed as a control to confirm IERB's effectiveness. When applied in a RED system, IERB decreased the stack resistance by up to 40%. The maximum gross power density improved by 83% in the RED stack compared to that in a regular RED stack at 1.3 cm/s average linear flow velocity. IERB-filled stack resistance was modeled. The model results fit well with experimental data, thereby confirming the effectiveness of the new approach presented here. The net power density is also estimated based on the measured pressure drop and pumping energy model. Both gross and net power density was improved by over 75% at higher flow rate. A net power density of 0.44 W/m(2) was achieved at a cell thickness of 500 µm. To the best of our knowledge, this research is the first to study the impact of IERB on power generation and establishes a new approach to improving the power performance of a RED system.

Removal of total cyanide in coking wastewater during a coagulation process: significance of organic polymers.

Whether a cationic organic polymer can remove more total cyanide (TCN) than a non-ionic organic polymer during the same flocculation system has not been reported previously. In this study, the effects of organic polymers with different charge density on the removal mechanisms of TCN in coking wastewater are investigated by polyferric sulfate (PFS) with a cationic organic polymer (PFS-C) or a non-ionic polymer (PFS-N). The coagulation experiments results show that residual concentrations of TCN (Fe(CN)6(3-)) after PFS-C flocculation (TCN < 0.2 mg/L) are much lower than that after PFS-N precipitation. This can be attributed to the different TCN removal mechanisms of the individual organic polymers. To investigate the roles of organic polymers, physical and structural characteristics of the flocs are analyzed by FT-IR, XPS, TEM and XRD. Owing to the presence of N+ in PFS-C, Fe(CN)6(3-) and negative flocs (Fe(CN)6(3-) adsorbed on ferric hydroxides) can be removed via charge neutralization and electrostatic patch flocculation by the cationic organic polymer. However, non-ionic N in PFS-N barely reacts with cyanides through sweeping or bridging, which indicates that the non-ionic polymer has little influence on TCN removal.

Surface-coating-dependent dissolution, aggregation, and reactive oxygen species (ROS) generation of silver nanoparticles under different irradiation conditions.

Dissolution, aggregation, and reactive oxygen species (ROS) generation are three major processes that silver nanoparticles (AgNPs) undergo in aqueous environments. In this study, the effects of AgNP surface coatings on these three processes were systematically evaluated under three irradiation conditions (UV-365, UV-254, and xenon lamp) to advance knowledge on the environmental fate and photochemical kinetics of AgNPs. The AgNPs used were (a) bare-AgNPs, (b) electrostatically stabilized citrate-AgNPs, and (c) sterically stabilized polyvinylpyrrolidone-AgNPs (PVP-AgNPs), and the light exposures greatly promoted the three processes. Both the 5-h released Ag(+) concentrations and the 2.5-h aggregation rate followed the order UV-365 > xenon lamp > UV-254 for all three types of AgNPs. For all irradiation conditions, the 5-h released Ag(+) concentration was highest for bare-AgNPs, followed by PVP-AgNPs and citrate-AgNPs; the 2.5-h aggregation rate was highest for bare-AgNPs, followed by citrate-AgNPs and PVP-AgNPs, which indicated that surface coating significantly determines the process kinetics of AgNPs. Under UV-365 irradiation, the bare-AgNPs generated superoxide and hydroxyl radicals, but the citrate-AgNPs yielded only superoxide radical, and the PVP-AgNPs did not generate any ROS. This study highlights the different fates and kinetic behaviors of AgNPs during photochemical interactions, providing important insight into the environmental implications of AgNP release.

Genetic and physical fine mapping of the novel brown midrib gene bm6 in maize (Zea mays L.) to a 180 kb region on chromosome 2.

Brown midrib mutants in maize are known to be associated with reduced lignin content and increased cell wall digestibility, which leads to better forage quality and higher efficiency of cellulosic biomass conversion into ethanol. Four well known brown midrib (bm) mutants, named bm1-4, were identified several decades ago. Additional recessive brown midrib mutants have been identified by allelism tests and designated as bm5 and bm6. In this study, we determined that bm6 increases cell wall digestibility and decreases plant height. bm6 was confirmed onto the short arm of chromosome 2 by a small mapping set with 181 plants from a F(2) segregating population, derived from crossing B73 and a bm6 mutant line. Subsequently, 960 brown midrib individuals were selected from the same but larger F(2) population for genetic and physical mapping. With newly developed markers in the target region, the bm6 gene was assigned to a 180 kb interval flanked by markers SSR_308337 and SSR_488638. In this region, ten gene models are predicted in the maize B73 sequence. Analysis of these ten genes as well as genes in the syntenic rice region revealed that four of them are promising candidate genes for bm6. Our study will facilitate isolation of the underlying gene of bm6 and advance our understanding of brown midrib gene functions.

Commenting on the effects of surface treated- and non-surface treated TiO(2) in the Caco-2 cell model.

In a recent work published in Particle and Fibre Toxicology by Fisichella and coworkers investigating surface-modified TiO2 nanoparticle exposure in a model human intestinal epithelium (Caco-2), albeit degraded to mimic conditions in the gut and exposure to natural sunlight, purportedly resulted in no toxic effects. The authors (Fisichella et al.) claim to have confirmed the results of a 2010 report by Koeneman et al. However, the study by Koeneman and colleagues revealed significant effects of unmodified TiO2 nanoparticles. These contradicting data warrant further investigation into the possible effects of aluminum hydroxide, as these nanoparticles appear to have resulted in an abnormal apical surface in Caco-2 cells.

Polymorphisms in monolignol biosynthetic genes are associated with biomass yield and agronomic traits in European maize (Zea mays L.).

BACKGROUND: Reduced lignin content leads to higher cell wall digestibility and, therefore, better forage quality and increased conversion of lignocellulosic biomass into ethanol. However, reduced lignin content might lead to weaker stalks, lodging, and reduced biomass yield. Genes encoding enzymes involved in cell wall lignification have been shown to influence both cell wall digestibility and yield traits. RESULTS: In this study, associations between monolignol biosynthetic genes and plant height (PHT), days to silking (DTS), dry matter content (DMC), and dry matter yield (DMY) were identified by using a panel of 39 European elite maize lines. In total, 10 associations were detected between polymorphisms or tight linkage disequilibrium (LD) groups within the COMT, CCoAOMT2, 4CL1, 4CL2, F5H, and PAL genomic fragments, respectively, and the above mentioned traits. The phenotypic variation explained by these polymorphisms or tight LD groups ranged from 6% to 25.8% in our line collection. Only 4CL1 and F5H were found to have polymorphisms associated with both yield and forage quality related characters. However, no pleiotropic polymorphisms affecting both digestibility of neutral detergent fiber (DNDF), and PHT or DMY were discovered, even under less stringent statistical conditions. CONCLUSION: Due to absence of pleiotropic polymorphisms affecting both forage yield and quality traits, identification of optimal monolignol biosynthetic gene haplotype(s) combining beneficial quantitative trait polymorphism (QTP) alleles for both quality and yield traits appears possible within monolignol biosynthetic genes. This is beneficial to maximize forage and bioethanol yield per unit land area.