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An uncharged, water‐soluble per‐ethylene‐glycol pillar[5]arene derivative (1) was synthesized and its aggregation mode, host‐guest chemistry in water and extraction ability was explored. Compound 1 is a liquid at room temperature; in water, limited self‐aggregation occurred at high concentrations as deduced from diffusion NMR and dynamic light scattering. Compound 1 forms pseudo‐rotaxane‐like 1 : 1 host‐guest complexes with 1,ω‐di‐substituted alkanes with association constants on the order of 103–104 m −1. Interestingly, NMR experiments showed that the guest location relative to the host ring system differs among the different complexes. In proof‐of‐concept experiments, compound 1 was shown to extract structurally related organic compounds from benzene into water with significant selectivity. Compound 1, which is a liquid at room temperature and has only limited interactions with its side arms, can, in principle, be regarded as a complement to or as a kind of type I porous liquid., A liquid host based on a per‐ethylene‐glycol pillar[5]arene derivative (1) was prepared and its self‐aggregation, host‐guest chemistry in water and extraction capabilities were studied and evaluated. 1 forms pseudo‐rotaxane‐like complexes with 1,ω‐di‐substituted alkanes, showing Ka values in the range of 103–104 M−1. Host 1 can extract such alkanes with 6–7 fold selectivity and since the interaction with its rim side‐chains is weak, 1 can be regarded as a complement to or as a sort of type 1 porous liquid.

NMR has been instrumental in studies of both the structure and dynamics of molecular systems for decades, so it is not surprising that NMR has played a pivotal role in the study of host-guest complexes and supramolecular systems. In this mini-review, selected examples will be used to demonstrate the added value of using (multiparametric) NMR for studying macrocycle-based host-guest and supramolecular systems. We will restrict the discussion to synthetic host systems having a cavity that can engulf their guests thus restricting them into confined spaces. So discussion of selected examples of cavitands, cages, capsules and their complexes, aggregates and polymers as well as organic cages and porous liquids and other porous materials will be used to demonstrate the insights that have been gathered from the extracted NMR parameters when studying such systems emphasizing the information obtained from somewhat less routine NMR methods such as diffusion NMR, diffusion ordered spectroscopy (DOSY) and chemical exchange saturation transfer (CEST) and their variants. These selected examples demonstrate the impact that the results and findings from these NMR studies have had on our understanding of such systems and on the developments in various research fields.

Supramolecular systems in water are of paramount importance and those based on hydrogen bonds are both intriguing and scarce. Here, after studying the peculiar host-guest complexes formed between per-dimethylamino-pillar[5]arene (1) and the bis-sulfonates 2 a-c, we describe the formation of the first hydrogen-bond-based supramolecular pentagonal boxes (SPBs), which are stable in water. These pH-responsive SPBs are constructed from 1 as a body, benzene polycarboxylic acids 3 a,b as lid compounds, and 2 a-c as guests. We demonstrate that encapsulation of 2 a-c in pillar[5]arene 1 and in the highly stable water-soluble SPBs, that is, 1(3 a)2 and 1(3 b)2 , is both temperature and pH dependent and, quite interestingly, depends, on the nature of the lid compounds used for capping the boxes even at high pH. We also highlight the difference in the 1 H NMR characteristics of 2 b and 2 c in the cavity of 1 and the SPBs.

The observed induction time for seeded gypsum crystallization was investigated with respect to gypsum particle seed size and mass loading. The induction time was significantly shortened in the pres...

Tethered poly(acrylic acid) (PAA) chains, synthesized onto polysulfone (PSf) surfaces, were characterized with respect to surface topography and chain characteristics via AFM force spectroscopy. The tethered PAA chains were synthesized by surface activation with an impinging atmospheric pressure plasma stream (He, He/O2 and He/H2), followed by free-radical acrylic acid graft polymerization. The number average molecular weight of the tethered PAA chains was estimated to be of in the range of ∼13,000–35,000 with chain-chain separation of 1.5–2.4 nm. Deionized and high salinity water contact angles for the PAA-PSf surfaces were in the range of ∼ 29–38°, indicating hydrophilic surfaces, relative to 80° contact angle for the native hydrophobic PSf surface. In DI water the tethered PAA chains had significantly greater chain extension than in a high salinity aqueous environment. Ultrafiltration fouling stress tests with alginic acid in a high salinity water and post cleaning with non-saline water demonstrated permeability restoration of up to 90–100% for a PAA-PSf membrane relative to 50–70% for the native PSf membrane. The present study suggests the merit of exploring and optimizing surface modification of membranes for saline water filtration to reduce irreversible fouling and improve cleaning effectiveness using non-saline water.

A flexible RO (FLERO) membrane desalination configuration employing a pressure intensifier and partial concentrate recycle was investigated with respect to operational flexibility and specific energy consumption (SEC). Decomposition of FLERO configuration and its operation into a membrane processing and concentrate recycle units allows fluid flow regulation at low pressure and adjustable product water recovery. Operational analysis, along with experimental evaluation using a small-scale spiral wound system, demonstrated a desalting capability over a wide range of both permeate recovery and source water salinity. Moreover, in the FLERO configuration a relatively low-pressure pump can be used, even for seawater desalination. However, the SEC for the FLERO configuration is higher, at the same recovery and permeate productivity, relative to conventional single-pass with energy recovery. Nonetheless, given its operational flexibility, in terms of handling both a wide range of source water salinity and recovery and source water salinity and need for low-pressure RO water feed pump. Given the above, FLERO should be ideal for small-scale applications, particularly in remote locations, and field evaluation is warranted to establish its long-term benefits. Large-scale FLERO applications would depend on the availability of suitable energy recovery devices of sufficient efficiency for large desalination capacity.

A deep cavitand binds long-chain trans,trans- and trans,cis-bis-formamide isomers in water solution giving a pair of caviplexes in a ca. 60:40 ratio. Both caviplexes display in/out guest exchange dynamics that are slow on the 1 H NMR chemical shift timescale, but fast on the EXSY timescale. We apply diffusion-ordered NMR spectroscopy (DOSY) to characterize the caviplexes. On the diffusion timescale, the guest in/out exchange processes feature intermediate dynamics allowing the assessment of their kinetic stabilities. We found that the trans,cis-bis-formamide isomers form kinetically more stable caviplexes than the trans,trans-counterparts. We also show that the kinetic stabilities of the bis-formamide caviplexes relate well with their relative thermodynamic stabilities. Fortunately, the tuning of the DOSY parameters allowed the observation of the exchange dynamics as slow processes on the experiment timescale.

Rationally designed two-component supramolecular organogels based on multiple chemical interactions between percarboxylato- and peramino-pillararenes are described. Mixing low concentration solutions (

The applicability of fouling indicators for real time performance assessment of UF feed pretreatment in RO seawater desalination was explored in a field study using an integrated seawater UF-RO desalination pilot plant. Fouling indictors were evaluated with respect to quantification of UF backwashability, unbackwashed fouling resistance and UF fouling rate. Feed water quality and coagulant dose demonstrated measurable impact on both UF fouling rate and effectiveness of foulant removal via UF backwash. Increased coagulant dose promoted higher rate of cake formation and in turn improved backwash efficiency. However, there was a maximum coagulant dose beyond which there was no further backwash improvement. Backwash effectiveness increased with higher backwash flux and duration, up to threshold upper limits, but declined as the filtration period increased above a threshold limit. Field tests during periods of temporally varying feed quality demonstrated that higher fouling rate (promoted by inline coagulation) resulted in more effective backwash and correspondingly lower progressive rise in post-backwash UF resistance. The study results suggest that real-time UF fouling indicators, based on UF filtration resistance metrics and backwash effectiveness, should be potentially useful for tracking UF performance and thus for deployment of UF feed-back control for optimal performance of UF feed pretreatment.

A machine learning approach to describing the dynamics of ultrafiltration performance in pretreatment of seawater reverse osmosis (RO) feedwater was explored via ensemble back propagation neural network (BPNN) model. The BPNN model was developed with Alopex evolutionary algorithm (AEA) optimization and AdaBoost strategy. The progression of ultrafiltration (UF) membrane resistance during both filtration and backwash, along with backwash efficiency were modeled via the ensemble BPNN-AEA approach relying on 422 days of operational data for an integrated SWRO UF-RO system. Model performance, for UF membrane resistance and backwash efficiency, evaluated over a wide range of operating conditions and coagulant dosing strategies, revealed excellent performance with a forecasting capability even for cases of temporally variable water quality. The performance level attained with the current machine learning modeling approach, which is particularly suited for handling the dynamics of UF operation, should prove useful for (a) determining UF performance deviation from intended baseline performance, (b) forecasting expected UF performance due to anticipated changes in water quality, and (c) providing a basis for model-based control of UF operation.

Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as quantitative structure-activity relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling but it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas outside of traditional QSAR boundaries including synthesis planning, nanotechnology, materials science, biomaterials, and clinical informatics. As modern research methods generate rapidly increasing amounts of data, the knowledge of robust data-driven modelling methods professed within the QSAR field can become essential for scientists working both within and outside of chemical research. We hope that this contribution highlighting the generalizable components of QSAR modeling will serve to address this challenge.

Power generation via pressure retarded osmosis (PRO) was explored based on a detailed two dimensional finite-element (2-D-FEM) PRO model. Using the numerical model, an approach is presented for determining the draw and feed crossflow velocities for maximizing peak power generation. The dependence of PRO power generation on channel dimensions, membrane transport parameters were then evaluated, followed by assessing the impact of frictional pressure losses and pumping and energy recovery device (ERD) efficiencies. Illustrative test cases are presented for three different draw/feed streams representing seawater/brackish water (SW/BW), seawater RO-brine/brackish water (SWB/BW), and Dead Sea water/Seawater RO-brine (DSW/SWB). The maximum peak power density attainable via PRO was for DSW/SWB (35.3 W/m2), followed by SWB/BW (7.29 W/m2) and SW/BW (3.53 W/m2) for the case of ideal pumps and ERD. For the optimistic Power generation from DSW/SWB PRO, high efficiency pumps (98%) and ERD (96%) would be required for peak power density to approach ~ 12 W/m2 and 1.6 W/m2 for the cases of DSW/SWB and SWB/BW, respectively, while net positive power generation is not expected for SW/BW. Higher permeability membranes could provide somewhat increased PRO performance; however, frictional pressure loses and less than ideal pumps and ERDs present a barrier for PRO as a viable approach for energy generation.

Real-time self-adaptive approach to in-line UF coagulant dosing was developed and field demonstrated for integrated UF-RO seawater desalination. A novel coagulant dose controller was designed and successfully implemented in a pilot UF-RO seawater desalination plant. The coagulant controller, which tracks the UF resistance during filtration and backwash, adjusts coagulant dose to the UF feed with the objective of reducing the incremental cycle-to-cycle UF post-backwash (PB) resistance change (i.e., Δn). Real-time tracking the above UF resistance metrics, as well as the rate of change of Δn with coagulant dose, enabled the controller to quantify the progression of both irreversible fouling and UF backwash effectiveness. The above information was then utilized by the controller to make the appropriate coagulant adjustment. Field tests of the proposed self-adaptive coagulant dosing approach demonstrated measurable coagulant dose reduction while maintaining robust UF operation even during periods of both mild and severe water quality degradation. The approach to real-time coagulant dose control developed in the present work should be suitable for both seawater and brackish water UF treatment and has the potential of providing both effective UF operation as well as reduction in coagulant use.

© 2016 American Chemical Society. Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations - where observing outcomes is difficult - versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test end points, duration, and study conditions - including ENM test concentrations - that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.

Angular double-pulsed-field gradient (d-PFG) MR methodology is increasingly used to non-invasively obtain pore sizes in opaque chemical and biological systems. In such MR experiments, the angular dependency of the signal at zero mixing time, through modeling, can be used to extract the pore size. In many systems not only the pore sizes but also their directions are of importance. Before applying d-PFG NMR to complex systems, it is of value to challenge the ability of the methodology to extract these microstructural parameters in samples where the ground truth is known. In the present study we explored whether modeling of the signal in angular d-PFG NMR experiments at zero mixing time, can simultaneously provide the size and the direction of tilted compartments with little prior knowledge. We showed that the angular d-PFG MR methodology enables simultaneous extraction of the pore size and the direction of mono-dispersed phantoms and of phantoms where the restricted compartments have different pore sizes. However, we found that in phantoms with two or more pore sizes, only averaged pore sizes were extracted for large azimuthal and polar angles.

A novel design for a reverse osmosis (RO) desalination system directly integrated with an ultrafiltration (UF) pre-treatment unit was developed. The integration involves direct RO feed from the UF filtrate and UF backwash using the RO concentrate. This alignment reduces overall plant footprint, while the use of RO concentrate for UF backwash allows 100% UF recovery and implementation of flexible backwash strategies. The present system design utilizes a control scheme, whereby RO productivity can be prescribed independently of the UF system which self-adjusts to provide the RO system with its required feed flow rate at the specified RO pump inlet pressure. UF backwash, achieved via direct RO concentrate flow from the RO system provided a continuous flow for sequential UF backwash which was additionally integrated with pulse backwash using a hydraulic accumulator. Seawater desalination field studies with a UF–RO pilot system of 12,000 gal/day permeate production capacity successfully demonstrated the advantage of RO concentrate UF backwash that was triggered based on a membrane resistance threshold. The above self-adaptive UF backwash strategy significantly extended the projected UF operation period (by a factor of nine) to the threshold of required chemical cleaning.

A web-based resource for meta-analysis of nanomaterials toxicity is developed whereby the utility of Bayesian networks (BNs) is illustrated for exploring the cellular toxicity of Cd-containing quantum dots (QDs). BN models are developed based on a dataset compiled from 517 publications comprising 3028 cell viability data samples and 837 IC50 values. BN QD toxicity (BN-QDTox) models are developed using both continuous (i.e., numerical) and categorical attributes. Using these models, the most relevant attributes identified for correlating IC50 are: QD diameter, exposure time, surface ligand, shell, assay type, surface modification, and surface charge, with the addition of QD concentration for the cell viability analysis. Data exploration via BN models further enables identification of possible association rules for QDs cellular toxicity. The BN models as web-based applications can be used for rapid intelligent query of the available body of evidence for a given nanomaterial and can be readily updated as the body of knowledge expands.

We describe the preparation of the first water-soluble pH-responsive supramolecular hexagonal boxes (SHBs) based on multiple charge-assisted hydrogen bonds between peramino-pillar[6]arenes 2 with the molecular "lid" mellitic acid (1 a). The interaction between 2 and 1 a, as well as the other "lids" pyromellitic and trimesic acids (1 b and 1 c, respecively) were studied by a combination of experimental and computational methods. Interestingly, the addition of 1 a to the complexes of the protonated form of pillar[6]arene 2, that is, 3, with bis-sulfonate 4 a or 4 b, immediately led to guest escape along with the formation of closed 1 a2 2 supramolecular boxes. Moreover, the process of the openning and closing of the supramolecular boxes along with threading and escaping of the guests, respectively, was found to be reversible and pH-responsive. This study paves the way for the easy and modular preparation of different SHBs that may have myriad applications.

Labeling of smart PEG–dendron hybrids with fluorinated groups transformed their assemblies into enzyme-responsive micellar probes for 19F-magnetic resonance (MR). Two distinct labeling approaches were used to study the ability of these smart hybrids to be turned OFF at the assembled micellar state and to turn ON their 19F-MR signal upon enzymatic activation.

A cost-benefit analysis of onsite graywater recycling in single-family and multifamily homes was conducted to evaluate the merits of graywater recycling in arid urban regions using the City of Los Angeles as a case study. Onsite graywater recycling reduces potable water demand by 27% and 38% in single family and multifamily homes, respectively. At participation of 10%, the City will be able to reduce water supply and treatment related energy by 43,000 MWh/year, potable water demand by 2% and wastewater treatment load by 3%. Amending local building codes to require new constructions to include plumbing to divert graywater for reuse will be important for lowering the cost and encouraging adoption of graywater recycling. Given the economic benefits to the City, establishing a rebate program for residential graywater recycling could provide a needed incentive for developing an effective residential graywater recycling program. A third-party ownership model could be a viable model for residential graywater recycling program that reduces the upfront system and installation cost barrier as well as relieves residential property owners the responsibility for system operation and maintenance. A City-wide graywater reuse program could also be developed to satisfy regulatory requirements by monitoring system operation and maintenance by certified contractors.

Real-time membrane integrity monitoring is critically needed in order to ensure that reverse osmosis (RO) treatment and desalination processes provide a reliable barrier against the passage of pathogens for potable reuse applications. A pulsed marker membrane integrity monitoring (PM-MIM) method was developed for real-time assessment of RO membrane integrity. The sensitivity of the PM-MIM method was evaluated, using a fluorescent molecular marker, in a plate-and-frame RO (PFRO) membrane system with intact and compromised membranes (induced mechanically and via chemical oxidation). Analysis of the marker permeate concentration–time profiles, in response to a controlled marker feed pulse, allowed unambiguous detection of marker enhanced passage, which was indicative of membrane integrity loss. The PM-MIM approach, which is capable of demonstrating log removal value (LRV) above 4 for a fluorescent molecular marker (smaller in size than pathogens) should be suitable for providing a conservative estimate of pathogens LRV. However, regulatory acceptability of the present real-time PM-MIM approach will undoubtedly require long-term field evaluation in RO plants in order to establish the level of confidence to satisfy regulatory requirements for RO use in potable water reuse applications.

Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as Quantitative Structure-Activity Relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling. Importantly, it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas beyond traditional QSAR fields. These fields include nanotechnology, materials science, biomaterials, clinical informatics, and others. As modern research methods generate rapidly increasing amounts of data, knowledge of robust data-driven modelling methods is becoming essential for scientists in many disciplines both within and outside of chemical research. We hope that this contribution will serve to address this challenge.

A compartmental multimedia model was developed to enable evaluation of the dynamic environmental multimedia mass distribution and concentrations of engineered nanomaterials (ENMs). The approach considers the environment as a collection of compartments, linked via fundamental environmental intermedia transport processes. Model simulations for various environmental scenarios indicated that ENM accumulation in the sediment increased significantly with increased ENMs attachment to suspended solids in water. Atmospheric dry and wet depositions can be important pathways for ENMs input to the terrestrial environment in the absence of direct and distributed ENM release to soil. Increased ENM concentration in water due to atmospheric deposition (wet and dry) is expected as direct ENM release to water diminishes. However, for soluble ENMs dissolution can be the dominant pathway for suspended ENM removal from water even compared to advection. Mass accumulation in the multimedia environment for the evaluated ENMs (metal, metal oxides, carbon nanotubes (CNT), nanoclays) was mostly in the soil and sediment. The present modeling approach, as illustrated via different test cases, is suited for "what if" first tier analyses to assess the multimedia mass distribution of ENMs and associated potential exposure concentrations.

Sensor fault detection and isolation (SFDI) approaches, based on support vector regression (SVR) plant sensor models and self-organizing-map (SOM) analysis, were investigated for application to reverse osmosis (RO) desalination plant operation. SFDI-SVR and SFDI-SOM were assessed using operational data from a small spiral-wound RO pilot plant and synthetic faulty data generated as perturbations relative to normal plant operational data. SFDI-SVR was achieved without false negative (FN) detections for sensor deviations of ≳|10%| and FN detections of, at the most, ≲|5%|, and for sensor deviations of ≳|4%| at sensor fault detection (FD) thresholds of up to ∼|4%|. False positive (FP) detections were almost invariant, with respect to sensor FD, being ≲|5%| for sensor deviations of ≳|5%|. Corrections of faulty sensor readings were within SVR model accuracy (AARE < 1%) for SFDI-SVR and ≲|5%| for SFDI-SOM. Although SFDI-SOM has lower detection accuracy, it requires a single overall plant model (or SOM), while providing pictorial representation of plant operation and depiction of faulty operational trajectories.

An experimental investigation was carried out to assess the removal efficiency of metal oxide nanoparticles from aqueous suspensions via sedimentation and the added benefit of membrane filtration. The study was conducted with aqueous suspensions of TiO2, ZnO, and CeO2 nanoparticles (NPs) of primary size of 10 nm–21 nm. The removal of NPs by gravitational settling was carried out with suspensions that were pretreated via pH adjustment and coagulant addition in order to increase the agglomerate size. Removal efficiencies were as high as 72.3–98.6% for the studied NPs with subsequent ultrafiltration of the remaining suspensions (post sedimentation) enabling essentially complete NP removal.

A novel model-based control system for the operation of a spiral-wound RO membrane desalination system was developed with a focus on maintaining energy-optimal operation. The control scheme utilized an operational model for spiral-wound RO desalting with a supervisory controller providing real-time updates of membrane permeability and the appropriate feed pressure set-points for maintaining the target permeate productivity at the lowest feasible specific energy consumption. System RO feed pressure and flow rates were controlled by a lower-level RO controller through adjustment of the RO high pressure feed pump, variable frequency drive, and RO concentrate valve. Seawater desalination tests with an RO plant, capable of permeate productivity up to 18 000 gallons/day, demonstrated effective self-adaptive energy-optimal operation, subject to feed salinity fluctuations, constraints imposed by the system’s physical limitations (i.e., minimum and maximum feasible operational pressures and flow rates), and the th...

The feasibility of utilizing chemically-enhanced seeded precipitation (CESP) for primary reverse osmosis (PRO) concentrate demineralization was evaluated, via both experimental field tests and process analysis, to assess its potential use in enabling recovery enhancement via secondary RO (SRO) desalting. Field evaluations of batch CESP along with process simulations for desalting of agricultural drainage (AD) water (6700–14,400 mg/L TDS, SIg = ~ 0.9) have suggested that a PRO-CESP-SRO desalting approach is both technically and economically feasible to enable overall desalting recovery of about 83% and, with partial concentrate recycling, of up to 93%. In the CESP process, initial partial lime treatment provides adsorptive removal of residual antiscalant from the PRO concentrate. This enables subsequent concentrate desupersaturation (with respect to the major scaling salt calcium sulfate) to occur via seeded gypsum precipitation, unimpeded by residual antiscalant. The desupersaturated PRO concentrate (~ 34% reduction in SIg from ~ 1.7 to ~ 1.1) can then be further desalted in an SRO step up to the limit that is feasible with antiscalant dosing for scale control. When considering the cost of residual brine disposal, the cost of AD water desalination by PRO-CESP-SRO on the basis of desalted water volume is lower than RO by up to 39%.

The development of data-driven RO plant performance models was demonstrated using the support vector regression model building approach. Models of both steady state and unsteady state plant operation were developed based on a wide range of operational data obtained from a fully automated small spiral-wound RO pilot. Single output variable steady state plant models for flow rates and conductivities of the permeate and retentate streams were of high accuracy, with average absolute relative errors (AARE) of 0.70%–2.46%. Performance of a composite support vector regression (SVR) based model (for both streams) for flow rates and conductivities was of comparable accuracy to the single output variable models (AARE of 0.71%–2.54%). The temporal change in conductivity, as a result of transient system operation (induced by perturbation of either system pressure or flow rate), was described by SVR model, which utilizes a time forecasting approach, with performance level of less than 1% AARE for forecasting periods of 2 s to 3.5 min. The high level of performance obtained with the present modeling approach suggests that short-term performance forecasting models that are based on plant data, could be useful for advanced RO plant control algorithms, fault tolerant control and process optimization.

The development of classification nano-structure-activity Relationships (nano-SARs) of nanoparticle (NP) bioactivity is presented with the aim of demonstrating the integration of multiparametric toxicity/bioactivity assays to arrive at statistically meaningful class definitions (i.e., bioactivity/inactivity endpoints), as well as the implications of nano-SAR applicability domains and decision boundaries. Nano-SARs are constructed based on a dataset of 44 iron oxide core nanoparticles (NPs), used in molecular imaging and nano-sensing, containing bioactivity profiles for four cell types and four different assays. Class definitions are developed on the basis of 'hit' (i.e., significant bioactivity) identification analysis and self-organizing map based consensus clustering; these class definitions enable construction of nano-SARs of a high classification accuracy (>78%) with different NP descriptor combinations that include primary size, spin-lattice and spin-spin relaxivities, and zeta potentials. Analysis of the nano-SAR performance for different class definitions suggests that H4 (i.e., class with at least four hits) is a reasonable endpoint (from a 'regulatory' viewpoint) for keeping the level of false negatives (i.e., incorrect labeling of bioactive NPs as inactive) low. The establishment of a quantitative nano-SAR applicability domain is demonstrated, making use of a probability density with the H4 class definition and naive Bayesian classifier (NBC) model (with spin-lattice relaxivity and zeta potential as descriptors). Decision boundaries are determined for the above H4/NBC nano-SAR for different acceptance levels of false negative to false positive predictions, illustrating a practical approach that may assist in regulatory decision making with a consideration of reducing the likelihood of identifying bioactive NPs as being inactive.

The technical feasibility of operating a spiral-wound RO plant in a cyclic mode of feed-flow reversal (FFR) was evaluated for brackish water desalting under conditions of high mineral scaling propensity. Scale-free and continuous permeate productivity was demonstrated, with calcium sulfate as the model scalant, in an automated spiral-wound RO pilot system in which FFR was triggered by scale detection in an external membrane monitor (MeMo). Real-time detection of mineral scaling in an external RO MeMo cell, receiving its feed from the concentrate of the RO plant tail element, enabled cyclic FFR operation in a self-adaptive mode accomplished by feed-back RO plant control in which permeate productivity was maintained. Membrane permeability was restored after each FFR cycle even with the initiation of membrane cleaning (i.e., via FFR) after a measurable level of scale formation in the MeMo and spiral-wound RO pilot. FFR cycle periods varied in length given the stochastic nature of crystal nucleation on the membranes in both the RO plant and in the MeMo RO cell. Scale-free FFR operation was demonstrated, without anticalant addition, with the RO plant operating (up to 81% recovery) such that the gypsum saturation index was up to 3.45 at the membrane surface of the tail element.

Biofilm formation, which frequently occurs in microbial infections and often reduces the efficacy of antibiotics, also perturbs many industrial and domestic processes. We found that a new class of water soluble pillar[5]arenes bearing phosphonium moieties (1, 2) and their respective ammonium analogues (3, 4) inhibit biofilm formation with IC50 values in the range of 0.67–1.66 μM. These compounds have no antimicrobial activity, do not damage red blood cell membranes, and do not affect mammalian cell viability in culture. Comparison of the antibiofilm activities of the phosphonium-decorated pillar[5]arene derivatives 1 and 2 with their respective ammonium counterparts 3 and 4 and their monomers 5 and 6, demonstrate that while positive charges, charge cooperativity and the pillararene platform are essential for the observed antibiofilm activity the nature of the charges is not.

Because a variety of human-related activities, engineer-ed nanoparticles (ENMs) may be released to various environmental media and may cross environmental boundaries, and thus will be found in most media. Therefore, the potential environmental impacts of ENMs must be assessed from a multimedia perspective and with an integrated risk management approach that considers rapid developments and increasing use of new nanomaterials. Accordingly, this Account presents a rational process for the integration of in silico ENM toxicity and fate and transport analyses for environmental impact assessment. This approach requires knowledge of ENM toxicity and environmental exposure concentrations. Considering the large number of current different types of ENMs and that those numbers are likely to increase, there is an urgent need to accelerate the evaluation of their toxicity and the assessment of their potential distribution in the environment. Developments in high throughput screening (HTS) are now enabling the rapid generation of large data sets for ENM toxicity assessment. However, these analyses require the establishment of reliable toxicity metrics, especially when HTS includes data from multiple assays, cell lines, or organisms. Establishing toxicity metrics with HTS data requires advanced data processing techniques in order to clearly identify significant biological effects associated with exposure to ENMs. HTS data can form the basis for developing and validating in silico toxicity models (e.g., quantitative structure-activity relationships) and for generating data-driven hypotheses to aid in establishing and/or validating possible toxicity mechanisms. To correlate the toxicity of ENMs with their physicochemical properties, researchers will need to develop quantitative structure-activity relationships for nanomaterials (i.e., nano-SARs). However, as nano-SARs are applied in regulatory applications, researchers must consider their applicability and the acceptance level of false positive relative to false negative predictions and the reliability of toxicity data. To establish the environmental impact of ENMs identified as toxic, researchers will need to estimate the potential level of environmental exposure concentration of ENMs in the various media such as air, water, soil, and vegetation. When environmental monitoring data are not available, models of ENMs fate and transport (at various levels of complexity) serve as alternative approaches for estimating exposure concentrations. Risk management decisions regarding the manufacturing, use, and environmental regulations of ENMs would clearly benefit from both the assessment of potential ENMs exposure concentrations and suitable toxicity metrics. The decision process should consider the totality of available information: quantitative and qualitative data and the analysis of nanomaterials toxicity, and fate and transport behavior in the environment. Effective decision-making to address the potential impacts of nanomaterials will require considerations of the relevant environmental, ecological, technological, economic, and sociopolitical factors affecting the complete lifecycle of nanomaterials, while accounting for data and modeling uncertainties. Accordingly, researchers will need to establish standardized data management and analysis tools through nanoinformatics as a basis for the development of rational decision tools.

The feasibility of removing calcium scale precursor ions from reverse osmosis (RO) concentrate by accelerated seeded precipitation (ASP) was investigated with the goal of increasing product water recovery and minimizing the volume of concentrate disposal from inland municipal wastewater desalination plants. Three seed materials were tested in laboratory trials — calcium carbonate, calcium sulfate and calcium phosphate. Calcium carbonate and calcium sulfate seed were not effective. The addition of calcium phosphate seed particles at 20 g L− 1 or phosphate ion in stoichiometric excess of the calcium concentration (250 mg L− 1 Ca = 6.25 mM Ca2+, 650 mg L− 1 HPO42− = 6.7 mM) decreased the calcium content in the RO concentrate to 10 mg L− 1. Evaluation of the accelerated seeded precipitation process using in-situ generated calcium phosphate seed at the pilot scale was performed on a 25 kL day− 1 pilot plant consisting of dissolved air flotation, ultrafiltration and reverse osmosis. The treated concentrate was filtered by a ceramic filtration system. Preliminary cost analyses indicate that high recovery RO using calcium phosphate precipitation can only be justified in inland situations where restrictions on concentrate disposal drive smaller evaporation pond storage volumes to offset the higher chemical and energy running costs.

A constant-number direct simulation Monte Carlo (DSMC) model was developed for the analysis of nanoparticle (NP) agglomeration in aqueous suspensions. The modeling approach, based on the "particles in a box" simulation method, considered both particle agglomeration and gravitational settling. Particle-particle agglomeration probability was determined based on the classical Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and considerations of the collision frequency as impacted by Brownian motion. Model predictions were in reasonable agreement with respect to the particle size distribution and average agglomerate size when compared with dynamic light scattering (DLS) measurements for aqueous TiO(2), CeO(2), and C(60) nanoparticle suspensions over a wide range of pH (3-10) and ionic strength (0.01-156 mM). Simulations also demonstrated, in quantitative agreement with DLS measurements, that nanoparticle agglomerate size increased both with ionic strength and as the solution pH approached the isoelectric point (IEP). The present work suggests that the DSMC modeling approach, along with future use of an extended DLVO theory, has the potential for becoming a practical environmental analysis tool for predicting the agglomeration behavior of aqueous nanoparticle suspensions.

An approach to real-time analysis of mineral scale formation on reverse osmosis (RO) membranes was developed using an ex-situ direct observation membrane monitor (MeMo). The purpose of such monitoring is to signal the onset of mineral scaling and provide quantitative information in order to appropriately initiate system cleaning/scale dissolution. The above is enabled by setting the MeMo operating conditions (cross flow velocity and transmembrane pressure) to closely match the conditions in the monitored membrane plant (e.g., in the tail RO element) in order to mimic the surface scaling processes taking place inside the monitored RO plant element. Mineral scale in the MeMo system is monitored by comparison of consecutive images of the membrane surface for the purpose of determining the evolution of the fractional coverage by mineral salt crystals and the corresponding crystal count in the monitored region. Through online image analysis, once crystal growth is determined to be above a prescribed threshold, one can then initiate any number of cleaning protocols. Through early detection of membrane scaling (i.e., before permeate flux decline is observed), enabled by the present monitoring approach, the system operator can prevent irreversible membrane damage and loss of system productivity.

This study evaluated intermediate chemical demineralization (ICD) as a technique for overcoming mineral salt solubility limits that constrain the water recovery of reverse osmosis (RO) desalting. An empirical approach was developed to determine theoretical cation removal set points for ICD based on predetermined process design and operation guidelines to facilitate increasing the overall water recovery of Colorado River water desalting from 85% (i.e., in the primary RO unit) to 95% via a secondary RO (SRO) unit. Additionally, the study evaluated whether microfiltration (MF) or dual-media filtration (DMF) could serve as the filtration step prior to the secondary reverse osmosis (SRO) unit. The model suggested ranges for ICD influent total-carbonate-to-calcium ratios and ICD effluent pH to simultaneously mitigate barium sulfate, calcium sulfate, and silica scaling. MF was preferred over DMF as the filtration step prior to SRO based on significantly lower filter effluent turbidity and silt density indices. The overall PRO-ICD-SRO system operated for over 550 h at 95% total RO water recovery without evidence of scaling of the terminal RO elements, validating the cation removal set points developed through the ICD model and demonstrating the utility of ICD.

The response of a murine macrophage cell line exposed to a library of seven metal and metal oxide nanoparticles was evaluated via High Throughput Screening (HTS) assay employing luciferase-reporters for ten independent toxicity-related signaling pathways. Similarities of toxicity response among the nanoparticles were identified via Self-Organizing Map (SOM) analysis. This analysis, applied to the HTS data, quantified the significance of the signaling pathway responses (SPRs) of the cell population exposed to nanomaterials relative to a population of untreated cells, using the Strictly Standardized Mean Difference (SSMD). Given the high dimensionality of the data and relatively small dataset the validity of the SOM clusters was established via a consensus clustering technique. Analysis of the SPR signatures revealed two cluster groups corresponding to (i) sub-lethal pro-inflammatory responses to Al2O3, Au, Ag, SiO2 nanoparticles possibly related to ROS generation, and (ii) lethal genotoxic responses due to exposure to ZnO and Pt nanoparticles at a concentration range of 25 μg/mL-100 μg/mL at 12 h exposure. In addition to identifying and visualizing clusters and quantifying similarity measures, the SOM approach can aid in developing predictive quantitative-structure relations; however, this would require significantly larger datasets generated from combinatorial libraries of engineered nanoparticles.

Basic research in the chemistry of hexameric resorcin[4]arenes and pyrogallol[4]arenes during the last decade is reviewed. Applications of NMR methods to determine solution structures, host guest properties and exchange dynamics are discussed. The scientific issue is the behavior of molecules in small spaces; the challenge is to translate this information to practical applications in, say, catalysis or transport.

A two-step chemically-enhanced seeded precipitation (CESP) process was demonstrated for accelerated desupersaturation of antiscalant-containing, gypsum-supersaturated model solutions, which mimicked reverse osmosis (RO) concentrate from RO desalting of agricultural drainage water of high mineral scaling propensity. In the CESP process, CaCO3 precipitation is first induced via lime dosing for antiscalant scavenging, followed by subsequent CaSO4 precipitation via gypsum seeding for concentrate desupersaturation. It was demonstrated that lime-precipitated CaCO3 particles were able to scavenge generic and commercial polycarboxylic-acid antiscalants, thereby facilitating subsequent CaSO4 precipitation to progress with minimal retardation. The study demonstrated via a series of batch CESP cycles that gypsum particle recycling can sustain CaSO4 precipitation, suggesting that a continuous CESP process could be feasible. Process analysis suggests that CESP can be significantly less chemical-intensive than conventional precipitation softening and, with its integration as an intermediate RO concentrate demineralization process, can enable desalination water recovery enhancement via secondary RO desalting. For the present case of gypsum-saturated RO feed water, enhancement of overall water recovery from 63% up to 87% or higher appears to be feasible. The study suggests that there is merit for developing a continuous CESP process for high recovery RO desalting of brackish water of high gypsum scaling propensity.

Various mixing operations between the feed, retentate and permeate streams are studied in this work to determine their effectiveness in decreasing the specific energy consumption (SEC) of single-stage (single-pass), two-pass and two-stage reverse osmosis (RO) processes operated at the limit of the thermodynamic restriction. The results show that in a single-stage RO process, partial retentate recycling to the feed stream does not change the SEC, while partial permeate recycling to the feed stream increases the SEC if targeting the same overall water recovery. Energy optimization of two-pass membrane desalination, with second-pass retentate recycling to the first-pass feed stream and operated at the limit imposed by the thermodynamic restriction, revealed the existence of a critical water recovery. When desalting is accomplished at recoveries above the critical water recovery, two-pass desalination with recycling is always less efficient than single-pass desalination. When desalting is accomplished at recoveries below the critical water recovery, an operational sub-domain exists in which the SEC for a two-pass process with recycling can be lower than for a single-pass counterpart, when the latter is not operated at its globally optimal state. For the two-stage RO process, diverting part of the raw feed to the second stage, in order to dilute the feed to the second-stage RO, does not decrease the minimal achievable SEC of a two-stage RO process. The various mixing approaches, while may provide certain operational or system design advantages (e.g., with respect to achieving target salt rejection for certain solutes or flux balancing), do not provide an advantage from an energy usage perspective.

Hydrogen-bond molecular capsules of resorcin[4]arenes (1) and pyrogallol[4]arenes (2) attracted much interest in the last decade. It was found, for example, that resorcin[4]arenes form hexameric capsules in non-polar organic solvents that can accommodate both trialkylamines and tetraalkylammonium salts. In search for the bulkiest guest that can be accommodated in the cavity of such capsules we found, with the aid of diffusion NMR, that such guests can interact also with the external surface of the hexameric capsules. Interestingly, monitoring the effect of CD3OD titration on the diffusion coefficients of the different components in such host–guest systems indicates that the interaction of such guests with the external surface of the hexameric capsule is significant and can be found also in case where guest's encapsulation occurs as in the case of trioctylamine (3) and tetraoctylammonium bromide (6). These CD3OD titrations showed also that these interactions are disrupted before the hexamer is disrupted an...

Thin poly(4-vinylpyridine) films terminally anchored onto nonporous inorganic oxide substrates were synthesized by aqueous phase reverse atom transfer radical graft polymerization (ATRGP). Surface initiators were immobilized on the inorganic substrate surface by chemically attaching glycidoxytrimethoxy silane onto the substrates followed by conversion of the glycidoxy silane into azobis silane by a reaction with 4,4′-azobis(4-cyanovaleric acid). Reverse ATRGP of 4-vinylpyridine onto the active surface azo sites was carried out in a 1-methyl-2-pyrrolidone/water solvent mixture using CuCl2/2,2′-bipyridine as the catalyst-ligand complex with initial monomer concentration [M]0 = 2.32M at 90°C. Controlled radical polymerization was achieved at catalyst to initiator molar ratios of 2 : 1 and 3 : 1, with a catalyst to ligand molar ratio of 1 : 2. Controlled polymerization was indicated by a first-order rate of polymerization kinetics, with respect to monomer conversion at the surface and in solution, the linear increase of the P4VP graft yield with time, and a low polydispersity index (PDI < 1.40). The highest graft yield of 8 mg/m2 was achieved at a 3 : 1 catalyst to initiator molar ratio which corresponded to a number-average molecular weight of 11,500 g/mol, surface density of 0.69 μmol/m2, and a polydispersity index of 1.28. AFM surface analysis of the grafted polymer films, prepared by reverse ATRGP of 4VP, revealed a decrease in the RMS surface roughness (RRMS = 1.04 nm) and feature size (feature diameter = 20–45 nm), relative to uncontrolled free radical graft polymerization (RRMS = 1.42 nm; feature diameter = 60–145 nm), thereby providing an additional indication that a denser and controlled reaction was achieved via reverse ATRGP. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009