The roles of adsorption in hydrate precipitation

It has been well established that organic compounds with adjacent hydroxyl groups in Bayer process liquor can inhibit gibbsite precipitation by acting as seed poisons. The degree of inhibition is a function of the number and stereochemistry of the hydroxyl groups. Seed poisons generally adsorb strongly onto hydrate surfaces, implying that surface coverage is the mechanism for yield inhibition. There are examples however of organics that strongly adsorb but do not lead to yield inhibition. There is a possibility that this apparent contradiction may be an artifact of differences in conditions between the adsorption and precipitation experiments. The present work investigates the adsorption and inhibition effects of a range of compounds under strictly similar conditions to clarify the role of adsorption on yield inhibition.

Preparation, characterization of surfactants modified clay minerals and nitrate adsorption

Organic surfactants modified clay minerals are usually used as adsorbents for hydrophobic organic contaminants remediation; this work however has shown organoclays can also work as adsorbents for hydrophilic anionic contaminant immobilization. Organoclays were prepared based on halloysite, kaolinite and bentonite and used for nitrate adsorption, which are significant for providing mechanism for the adsorption of anionic contaminants from waste water. XRD was used to characterize unmodified and surfactants modified clay minerals. Thermogravimetric analysis (TG) was used to determine the thermal stability and actual loading of surfactant molecules. Ion chromatography (IC) was used to determine changes of nitrate concentration before and after adsorption by these organoclays. These organoclays showed different removal capacities for anionic ions from water and adsorption mechanism was investigated.

Adsorption of the herbicide 2,4-D on organo-palygorskite

Among the clay minerals, montmorillonite is the most extensively studied material using as adsorbents, but palygorskite and its organically modified products have been least explored for their potential use in contaminated water remediation. In this study, an Australian palygorskite was modified with cationic surfactants octadecyl trimethylammonium bromide and dioctadecyl dimethylammonium bromide at different doses. A full structural characterization of prepared organo-palygorskite by X-ray diffraction, infrared spectroscopy, surface analysis and thermogravimetric analysis was performed. The morphological changes of palygorskite before and after modification were recorded using scanning electron microscopy, which showed the surfactant molecules can attach on the surface of rod-like crystals and thus can weaken the interactions between palygorskite single crystals. Real surfactants loadings on organo-palygorskites were also calculated based on thermogravimetric analysis. 1 CEC, 2 CEC octadecyl trimethylammonium bromide modified palygorskites, 1 CEC and 2 CEC dioctadecyl dimethylammonium bromide modified palygorskites absorbed as much as 12 mg/g, 42 mg/g, 9 mg/g and 25 mg/g of 2,4- dichlorophenoxyacetic acid respectively. This study has shown a potential on organo-palygorskites for organic herbicide adsorption especially anionic ones from waste water. In addition, equilibration time effects and the Langmuir and Freundlich models fitting were also investigated in details.

Reduction and adsorption of Pb2+ in aqueous solution by nano zero-valent iron : a SEM, TEM and XPS study

This study reports the synthesis, characterization and application of nano zero-valent iron (nZVI). The nZVI was produced by a reduction method and compared with commercial available ZVI powder for Pb2+ removal from aqueous phase. Comparing with commercial ZVI, the laboratory made nZVI powder has a much higher specific surface area. XRD patterns have revealed zero valent iron phases in two ZVI materials. Different morphologies have been observed using SEM and TEM techniques. EDX spectrums revealed even distribution of Pb on surface after reaction. The XPS analysis has confirmed that immobilized lead was present in its zero-valent and bivalent forms. ‘Core-shell’ structure of prepared ZVI was revealed based on combination of XRD and XPS characterizations. In addition, comparing with Fluka ZVI, this lab made nZVI has much higher reactivity towards Pb2+ and within just 15 mins 99.9% removal can be reached. This synthesized nano ZVI material has shown great potential for heavy metal immobilization from waste water.

Hydrolysis of genotoxic methyl-substituted oxiranes : Experimental kinetic and semiempirical studies

The kinetics of acid-catalyzed hydrolysis of seven methylated aliphatic epoxides - R1R2C(O)CR3R4 (A: R1=R2=R3=R4=H; B: R1=R2=R3=H, R4=Me; C: R1=R2=H, R3=R4=Me; D: R1=R3=H, R2=R4=Me(trans); E: R1=R3=H, R2=R4=Me(cis); F: R1=R3=R4=Me, R2=H; G: R1=R2=R3=R4=Me) - has been studied at 36 ± 1.5°C. Compounds with two methyl groups at the same carbon atom of the oxirane ring exhibit highest rate constants (k(eff) in reciprocal molar concentration per second: 11.0 ± 1.3 for C, 10.7 ± 2.1 for F, and 8.7 ± 0.7 for G as opposed to 0.124 ± 0.003 for B, 0.305 ± 0.003 for D, and 0.635 ± 0.036 for E). Ethylene oxide (A) displays the lowest rate of hydrolysis (0.027 M-1 s-1). The results are consistent with literature data available for compounds A, B, and C. To model the reactivities we have employed quantum chemical calculations (MNDO, AM1, PM3, and MINDO/3) of the main reaction species. There is a correlation of the logarithm k(eff) with the total energy of epoxide ring opening. The best correlation coefficients (r) were obtained using the AM1 and MNDO methods (0.966 and 0.957, respectively). However, unlike MNDO, AM1 predicts approximately zero energy barriers for the oxirane ring opening of compounds B, C, E and G, which is not consistent with published kinetic data. Thus, the MNDO method provides a preferential means of modeling the acidic hydrolysis of the series of methylated oxiranes. The general ranking of mutagenicity in vitro, A > B > C, is in line with the concept that this sequence also gradually leaves the expoxide reactivity optimal for genotoxicity toward reactivities leading to higher biological detoxifications.

Synthesis, characterization and activity of an immobilized photocatalyst : natural porous diatomite supported titania nanoparticles

Diatomite, a porous non-metal mineral, was used as support to prepare TiO2/diatomite composites by a modified sol–gel method. The as-prepared composites were calcined at temperatures ranging from 450 to 950 _C. The characterization tests included X-ray powder diffraction (XRD), scanning electron microscopy (SEM) with an energy-dispersive X-ray spectrometer (EDS), high-resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS), and nitrogen adsorption/desorption measurements. The XRD analysis indicated that the binary mixtures of anatase and rutile exist in the composites. The morphology analysis confirmed the TiO2 particles were uniformly immobilized on the surface of diatom with a strong interfacial anchoring strength, which leads to few drain of photocatalytic components during practical applications. In further XPS studies of hybrid catalyst, we found the evidence of the presence of Ti–O–Si bond and increased percentage of surface hydroxyl. In addition, the adsorption capacity and photocatalytic activity of synthesized TiO2/diatomite composites were evaluated by studying the degradation kinetics of aqueous Rhodamine B under UV-light irradiation. The photocatalytic degradation was found to follow pseudo-first order kinetics according to the Langmuir–Hinshelwood model. The preferable removal efficiency was observed in composites by 750 _C calcination, which is attributed to a relatively appropriate anatase/rutile mixing ratio of 90/10.

Adsorption and mobility of metals in build-up on road surfaces

The study investigated the adsorption and bioavailability characteristics of traffic generated metals common to urban land uses, in road deposited solids particles. To validate the outcomes derived from the analysis of field samples, adsorption and desorption experiments were undertaken. The analysis of field samples revealed that metals are selectively adsorbed to different charge sites on solids. Zinc, copper, lead and nickel are adsorbed preferentially to oxides of manganese, iron and aluminium. Lead is adsorbed to organic matter through chemisorption. Cadmium and chromium form weak bonding through cation exchange with most of the particle sizes. Adsorption and desorption experiments revealed that at high metal concentrations, chromium, copper and lead form relatively strong bonds with solids particles while zinc is adsorbed through cation exchange with high likelihood of being released back into solution. Outcomes from this study provide specific guidance for the removal of metals from stormwater based on solids removal.

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

LacO-LacI interaction in affinity adsorption of plasmid DNA

Current approaches for purifying plasmids from bacterial production systems exploit the physiochemical properties of nucleic acids in non-specific capture systems. In this study, an affinity system for plasmid DNA (pDNA) purification has been developed utilizing the interaction between the lac operon (lacO) sequence contained in the pDNA and a 64mer synthetic peptide representing the DNA-binding domain of the lac repressor protein, LacI. Two plasmids were evaluated, the native pUC19 and pUC19 with dual lacO3/lacOs operators (pUC19lacO3/lacOs), where the lacOs operator is perfectly symmetrical. The DNA-protein affinity interaction was evaluated by surface plasmon resonance using a Biacore system. The affinity capture of DNA in a chromatography system was evaluated using LacI peptide that had been immobilized to Streamline™ adsorbent. The KD-values for double stranded DNA (dsDNA) fragments containing lacO1 and lacO3 and lacOs and lacO3 were 5.7 ± 0.3 × 10 -11 M and 4.1 ± 0.2 × 10-11 M respectively, which compare favorably with literature reports of 5 × 10-10 - 1 × 10-9 M for native laCO1 and 1-1.2 × 10-10 M for lacO1 in a saline buffer. Densitometric analysis of the gel bands from the affinity chromatography run clearly showed a significant preference for capture of the supercoiled fraction from the feed pDNA sample. The results indicate the feasibility of the affinity approach for pDNA capture and purification using native protein-DNA interaction.

Affinity adsorption of plasmid DNA

The development of a protein-mediated dual functional affinity adsorption of plasmid DNA is described in this work. The affinity ligand for the plasmid DNA comprises a fusion protein with glutathione-S-transferase (GST) as the fusion partner with a zinc finger protein. The protein ligand is first bound to the adsorbent by affinity interaction between the GST moeity and gluthathione that is covalently immobilized to the base matrix. The plasmid binding is then enabled via the zinc finger protein and a specific nucleotide sequence inserted into the DNA. At lower loadings, the binding of the DNA onto the Fractogel, Sepharose, and Streamline matrices was 0.0078 ± 0.0013, 0.0095 ± 0.0016, and 0.0080 ± 0.0006 mg, respectively, to 50 μL of adsorbent. At a higher DNA challenge, the corresponding amounts were 0.0179 ± 0.0043, 0.0219 ± 0.0035, and 0.0190 ± 0.0041 mg, respectively. The relatively constant amounts bound to the three adsorbents indicated that the large DNA molecule was unable to utilize the available zinc finger sites that were located in the internal pores and binding was largely a surface adsorption phenomenon. Utilization of the zinc finger binding sites was shown to be highest for the Fractogel adsorbent. The adsorbed material was eluted with reduced glutathione, and the eluted efficiency for the DNA was between 23% and 27%. The protein elution profile appeared to match the adsorption profiles with significantly higher recoveries of bound GST-zinc finger protein.

A novel population balance model for the dilute acid hydrolysis of hemicellulose

Acid hydrolysis is a popular pretreatment for removing hemicellulose from lignocelluloses in order to produce a digestible substrate for enzymatic saccharification. In this work, a novel model for the dilute acid hydrolysis of hemicellulose within sugarcane bagasse is presented and calibrated against experimental oligomer profiles. The efficacy of mathematical models as hydrolysis yield predictors and as vehicles for investigating the mechanisms of acid hydrolysis is also examined. Experimental xylose, oligomer (degree of polymerisation 2 to 6) and furfural yield profiles were obtained for bagasse under dilute acid hydrolysis conditions at temperatures ranging from 110C to 170C. Population balance kinetics, diffusion and porosity evolution were incorporated into a mathematical model of the acid hydrolysis of sugarcane bagasse. This model was able to produce a good fit to experimental xylose yield data with only three unknown kinetic parameters ka, kb and kd. However, fitting this same model to an expanded data set of oligomeric and furfural yield profiles did not successfully reproduce the experimental results. It was found that a ``hard-to-hydrolyse'' parameter, $\alpha$, was required in the model to ensure reproducibility of the experimental oligomer profiles at 110C, 125C and 140C. The parameters obtained through the fitting exercises at lower temperatures were able to be used to predict the oligomer profiles at 155C and 170C with promising results. The interpretation of kinetic parameters obtained by fitting a model to only a single set of data may be ambiguous. Although these parameters may correctly reproduce the data, they may not be indicative of the actual rate parameters, unless some care has been taken to ensure that the model describes the true mechanisms of acid hydrolysis. It is possible to challenge the robustness of the model by expanding the experimental data set and hence limiting the parameter space for the fitting parameters. The novel combination of ``hard-to-hydrolyse'' and population balance dynamics in the model presented here appears to stand up to such rigorous fitting constraints.

Limitations of a laboratory scale model in predicting optimal pilot scale conditions for dilute acid pretreatment of sugarcane bagasse

Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.

Mathematical modelling of gas production and compositional shift of a CSG (coal seam gas) field: Local model development

In this work we discuss the development of a mathematical model to predict the shift in gas composition observed over time from a producing CSG (coal seam gas) well, and investigate the effect that physical properties of the coal seam have on gas production. A detailed (local) one-dimensional, two-scale mathematical model of a coal seam has been developed. The model describes the competitive adsorption and desorption of three gas species (CH4, CO2 and N2) within a microscopic, porous coal matrix structure. The (diffusive) flux of these gases between the coal matrices (microscale) and a cleat network (macroscale) is accounted for in the model. The cleat network is modelled as a one-dimensional, volume averaged, porous domain that extends radially from a central well. Diffusive and advective transport of the gases occurs within the cleat network, which also contains liquid water that can be advectively transported. The water and gas phases are assumed to be immiscible. The driving force for the advection in the gas and liquid phases is taken to be a pressure gradient with capillarity also accounted for. In addition, the relative permeabilities of the water and gas phases are considered as functions of the degree of water saturation.