Surface Functionalized Mesoporous Silica Nanoparticles for Enhanced Removal of Heavy Metals: A Review

Human health and environmental sustainability are strongly influenced by the contamination of water resources with hazardous heavy metal ions due to the accumulation in human body via food chains. Thereby, researchers’ attention has been paid on effective methods for heavy metal ion scavenging to prevent them releasing to environment. Notably, Mesoporous Silica Nanoparticles (MSNPs) with high surface area, massive surface area to volume ratio, large pore volume and uniform pore distribution play a crucial role in addressing this challenge. Additionally, researchers focus on novel surface functionalization methods of MSNPs with suitable organic and inorganic moieties to amplify the adsorption efficiency of heavy metals. MSNPs possess easily functionalizable surface which facilitates the modifications and enhanced removal of heavy metals. The review article summarizes the different moieties used for functionalization of MSNPs such as amino, thio, carboxyl, phenyl, cyano groups, different types of polymers, inorganic functional groups. Further, a comparison has been made between functional and unmodified MSNPs to elaborate how these modifications have enhanced the removal performance of heavy metals in water. Further, this review provides an overview on different synthesis routes and structure directing agent used in synthesis of MSNPs. Moreover, pH effect on adsorption andreusability of modified NPs, while illustrating the mechanism of adsorption on to modified MSNPs surface has also been elaborated. Maximum adsorption capacity of each functional moiety has been taken into consideration with the aim of supporting future advancements. Keywords: Adsorption, Mesoporous silica nanoparticles, Heavy metals, Functionalization, Maximum adsorption capacit

Application of Metal/Metal Oxide Doped Electrospun Nanofiber Membranes in Sustainable Catalysis

The unsustainability of the production of catalysts due to limited resources and higher energy demands makes it critical to explore and reengineer new catalytic materials for future applications. Woefully, the unrelenting demand for the metals/metal oxides increases both the financial and environmental cost, particularly in mining and synthesis, rendering consumption unsustainable in its current form. In this context, electrospinning offers a new template for designing sustainable ways of minimizing the higher loading of catalysts and recyclability. In this context, metals/metal oxide doped electrospun membranes have grasped a great scientific interest as sustainable catalysts due to their enhanced catalytic activity and synergistic structure-property relationship of the doped material and the matrix. More specifically, the selectivity arising from the electronic properties and quantum mechanical interactions at the nanoscale of metal/metal oxide nanoparticles coupled with interactions at the electrospun membrane interfaces lead to such enhanced properties. This review article summarizes the applications of metals/metal doped electrospun membranes in different aspects of catalysis, such as thermocatalysis, photocatalysis, organocatalysis and electrocatalysis, with a particular focus on their sustainability. Keywords: Sustainable catalysis, metal/metal oxide doped catalysts, electrospinning, organocatalysis, photocatalysi

Potential Applications of Electrospun Nanofibers in Agriculture

Some of the major challenges associated with current agricultural practices include inefficient delivery and utilization of agrochemicals; fertilizers, pesticides, and pheromones; to crops. This results in low nutrient utilization efficiency with respect to applied fertilizers which leads to a greater economic burden to farmers to maintain crop yields at optimum levels. In addition, plant diseases by various pathogens also pose a threat to agriculture. In an effort to address some of the aforementioned challenges, electrospun nanofibers have emerged as a potential class of one-dimensional nanomaterials for use in agricultural applications. Unique characteristics of electrospun nanofibers such as enhanced surface area: volume ratio, high porosity distribution, and increased specific surface area pave the potential for agricultural applications that will be elaborated in this review. These applications include slow-release of fertilizers, pheromones and insecticides, seed and fruit coatings, plant protection, and nanofiber fabricated sensors. In addition, this review also focuses briefly on other preparation methods of nanofibers, and most importantly on the parameters that govern the electrospinning process; solution parameters, processing parameters, and ambient parameters. Furthermore, many more unexplored applications in the field of agriculture employing nanofiber usage exist, and it is believed that a greater understanding of the current nanofiber research and practices of green electrospinning will enable the upliftment of current boundaries to enable agricultural applications of nanofibers on a commercial scale. Keywords: nanofiber - agriculture - electrospinning - slow-release – senso

Urea-Hydroxyapatite Nanohybrids for Slow Release of Nitrogen

While slow release of chemicals has been widely applied for drug delivery, little work has been done on using this general nanotechnology-based principle for delivering nutrients to crops. In developing countries, the cost of fertilizers can be significant and is often the limiting factor for food supply. Thus, it is important to develop technologies that minimize the cost of fertilizers through efficient and targeted delivery. Urea is a rich source of nitrogen and therefore a commonly used fertilizer. We focus our work on the synthesis of environmentally benign nanoparticles carrying urea as the crop nutrient that can be released in a programmed manner for use as a nanofertilizer. In this study, the high solubility of urea molecules has been reduced by incorporating it into a matrix of hydroxyapatite nanoparticles. Hydroxyapatite nanoparticles have been selected due to their excellent biocompatibility while acting as a rich phosphorus source. In addition, the high surface area offered by nanoparticles allows binding of a large amount of urea molecules. The method reported here is simple and scalable, allowing the synthesis of a urea-modified hydroxyapatite nanohybrid as fertilizer having a ratio of urea to hydroxyapatite of 6:1 by weight. Specifically, a nanohybrid suspension was synthesized by $\textit{in situ}$ coating of hydroxyapatite with urea at the nanoscale. In addition to the stabilization imparted due to the high surface area to volume ratio of the nanoparticles, supplementary stabilization leading to high loading of urea was provided by flash drying the suspension to obtain a solid nanohybrid. This nanohybrid with a nitrogen weight of 40% provides a platform for its slow release. Its potential application in agriculture to maintain yield and reduce the amount of urea used is demonstrated.Authors thank Hayleys Agro Ltd., Sri Lanka for initiating this research programme at SLINTEC and Nagarjuna Fertilizer and Chemical Ltd (NFCL), India for providing further support. Authors acknowledge Mr Sunanda Gunesekara of SLINTEC for assistance with scaling up the production process to enable the field trials. ARK acknowledges the financial support received from ICTPELETTRA Users Program, Trieste, Italy to conduct photoemission experiments at Materials Science beam line (MSB) and ELETTRA SRS on HA and urea coated HA samples. ARK further acknowledges Dr. R.G. Acres of MSB beam line for his extensive support to conduct photoemission experiments. We acknowledge the Department of Agriculture and Rice Research and Development Institute of Sri Lanka, in particular Dr Priyantha Weerasinghe, Mr D Sirisena and Dr Amitha Benthota for the assistance in carrying out pot and farmers filed trials. NFCL and Central Salt & Marine Chemicals Research Institute, Gujarat, India for TEM and BET analysis

Model choice: An Operational Comparison of Stochastic Streamflow Models for Droughts

The rapid development of stochastic or operational hydrology over the past 10 years has led to the need for some comparative analyses of the currently available long-term persistence models. Five annual stochastic streamflow generation models (autoregressive, autoregressive-moving-average (ARMA), ARMA-Markov, fast fractional Gaussian noise, and broken line) are compared on their ability to preserve drought-related time series properties and annual statistics. Using Monte Carlo generation procedures and comparing the average generated statistics and drought or water supply properties, a basis is established to evalute model performance on four different Utah study streams. A seasonal disaggregation model is applied to each of the generated annual models for each of the four study streams at a monthly disaggregation level. A model choice strategy is presented for the water resources engineer to select an annual stochastic streamflow model based on values of the historic time series\u27 lag-one serial correlation and Hurst coefficient. Procedures are presented for annual and seasonal model parameter estimatino, calibration, and generation. Techniques are included such as normality, trend-analysis, and choice of model. User oriented model parameter estimation techniques that are easy and efficient to use are presented in a systematic manner. The ARMA-Markov and ARMA models are judged to be the best overall models in terms of preserving the short and long term persistence statistics for the four historic time series studied. The broken line model is judged to be the best model in terms of minimizing the evonomic regret as determined by an agricultural crop production function. Documentation and listings of the computer programs that were used for the stochastic models\u27 parameter estimation, generation, and camparison techniques are presented in a supplementary appendix

A User\u27s Manual for Computer Programs Used in: Model Choice: An Operational Comparison of Stochastic Streamflow Models for Droughts

The rapid development of stochastic or operational hydrology over the past 10 years has led to the need for some comparative analyses of the currently available long-term persistence models. Five annual stochastic streamflow generation models (autoregressive, autoregressive-moviing-average (ARMA), ARMA-Markov, fast fractional Gaussian noise, and broken line) are compared on their ability to preserved drought-related time series properties and annual statistics. Using Monto Carlo generation procedures and comparing the average generated statistics and drought or water supply properties, a basis is established to evaluated model performance on four different Utah study streams. A seasonal disaggregation model is applied to each of the generated annual models for each of the four study streams at a monthly disaggregation level. A model choice strategy is presented for the water resources engineer to select an annual stochastic streamflow model based on values of the historic time series; lag-one serial correlation and Hurst coefficient. Procedures are presented for annual and seasonal model parameter estimation, calibration, and generation. Techniques to ensure a consistent matrix for successful matric decomposition are included such as normality, trend-analysis, and choice of model. User oriented model parameter estimation techniques that are easy and efficient to use are presented in a systematic manner. The ARMA-Markov and ARMA models are judged to be the best overall models in terms of preserving the short and long term persistence statistics for the four historic time series studied. The broken line model is judged to be the best model in terms of minimizing the economic regret as determined by an agricultural crop production function. Documentation and listings of the computer programs that were used for the stochastic models\u27 parameter estimation, generation, and comparison techniques are presente in a supplementary appendix

Cramer-von Mises and Anderson-Darling goodness of fit tests for extreme value distributions with unknown parameters

The use of goodness of fit tests based on Cramer-von Mises and Anderson-Darling statistics is discussed, with reference to the composite hypothesis that a sample of observations comes from a distribution, FH, whose parameters are unspecified. When this is the case, the critical region of the test has to be redetermined for each hypothetical distribution FH. To avoid this difficulty, a transformation is proposed that produces a new test statistic which is independent of FH. This transformation involves three coefficients that are determined using the asymptotic theory of tests based on the empirical distribution function. A single table of coefficients is thus sufficient for carrying out the test with different hypothetical distributions; a set of probability models of common use in extreme value analysis is considered here, including the following: extreme value 1 and 2, normal and lognormal, generalized extreme value, three-parameter gamma, and log-Pearson type 3, in all cases with parameters estimated using maximum likelihood. Monte Carlo simulations are used to determine small sample corrections and to assess the power of the tests compared to alternative approaches

New borate ester based polymer electrolyte for battery application

Safety is an indispensable feature for a battery particularly in large scale applications. In this respect, gel electrolytes are more attractive due to less possibility of electrolyte leakage and safer if abused. Unfortunately, most present gel electrolyte systems are mainly based on polyethers which supposed to be flammable. In addition, PEO and PPO based systems exhibit a low cation transference number. Therefore, the seeking of novel thermally stable and safety polymer electrolytes with improved electrochemical behaviour is crucial. In the present contribution, we propose a series of Li-ion conducting polymer electrolytes based on the poly(ethyleneglycol) (PEG) borate ester (PE-350B) and PEG-methacrylates (PME-400 and PDE-600, respectively) plasticized by M550B100 PEG-borate ester, which can be characterized as a thermally stable solvent with high flash point [1]