The Experts below are selected from a list of 28581 Experts worldwide ranked by ideXlab platform
Markus Niederberger - One of the best experts on this subject based on the ideXlab platform.
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Metal Oxide Nanoparticles in organic solvents
2009Co-Authors: Markus Niederberger, Nicola PinnaAbstract:Metal Oxide Nanoparticles in organic solvent , Metal Oxide Nanoparticles in organic solvent , کتابخانه دیجیتال جندی شاپور اهواز
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Metal Oxide Nanoparticles in organic solvents synthesis formation assembly and application
2009Co-Authors: Markus Niederberger, Nicola PinnaAbstract:Metal Oxide Nanoparticles in organic solvent , Metal Oxide Nanoparticles in organic solvent , کتابخانه دیجیتال جندی شاپور اهواز
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one minute synthesis of crystalline binary and ternary Metal Oxide Nanoparticles
Chemical Communications, 2008Co-Authors: Idalia Bilecka, Igor Djerdj, Markus NiederbergerAbstract:Highly crystalline Metal Oxide Nanoparticles such as CoO, ZnO, Fe(3)O(4), MnO, Mn(3)O(4), and BaTiO(3) were synthesized in just a few minutes by reacting Metal alkOxides, acetates or acetylacetonates with benzyl alcohol under microwave heating.
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thermal transformation of Metal Oxide Nanoparticles into nanocrystalline Metal nitrides using cyanamide and urea as nitrogen source
Chemistry of Materials, 2007Co-Authors: Jelena Buha, Markus Antonietti, Igor Djerdj, Markus NiederbergerAbstract:Preformed Metal Oxide Nanoparticles with varying crystallinity and different particle sizes and shapes can thermally be transformed into nanocrystalline Metal nitrides in the presence of cyanamide or urea as nitrogen sources. In the case of anatase Nanoparticles with crystallite sizes of 5, 10, and 20 nm, respectively, only the 5 nm sized TiO2 transformed completely into TiN. According to powder X-ray diffraction (XRD) and transmission electron microscopy measurements (TEM), the TiN particles are rather uniform in size and shape with a crystallite size of 3−5 nm, depending on the nitrogen source. In contrast to titania, vanadium Oxide Nanoparticles of much larger sizes and with different shapes reacted to nanocrystalline VN. However, the morphological features of the precursor particles are not transcribed into the final Metal nitrides with an average crystallite size of 15 nm. Crystallinity plays a role too, as only amorphous tantalum Oxide could be converted into nanocrystalline TaN. Furthermore, alumin...
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Nonaqueous sol-gel routes to Metal Oxide Nanoparticles
Accounts of Chemical Research, 2007Co-Authors: Markus NiederbergerAbstract:Sol-gel routes to Metal Oxide Nanoparticles in organic solvents under exclusion of water have become a versatile alternative to aqueous methods. In comparison to the complex aqueous chemistry, nonaqueous processes offer the possibility of better understanding and controlling the reaction pathways on a molecular level, enabling the synthesis of nanomaterials with high crystallinity and well-defined and uniform particle morphologies. The organic components strongly influence the composition, size, shape, and surface properties of the inorganic product, underlining the demand to understand the role of the organic species at all stages of these processes for the development of a rational synthesis strategy for inorganic nanomaterials.
Jerzy Leszczynski - One of the best experts on this subject based on the ideXlab platform.
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zeta potential for Metal Oxide Nanoparticles a predictive model developed by a nano quantitative structure property relationship approach
Chemistry of Materials, 2015Co-Authors: Alicja Mikolajczyk, Jerzy Leszczynski, Bakhtiyor Rasulev, Agnieszka Gajewicz, Nicole M Schaeublin, Elisabeth Maurergardner, Saber M Hussain, Tomasz PuzynAbstract:Physico–chemical characterization of Nanoparticles in the context of their transport and fate in the environment is an important challenge for risk assessment of nanomaterials. One of the main characteristics that defines the behavior of Nanoparticles in solution is zeta potential (ζ). In this paper, we have demonstrated the relationship between zeta potential and a series of intrinsic physico–chemical features of 15 Metal Oxide Nanoparticles revealed by computational study. The here-developed quantitative structure–property relationship model (nano-QSPR) was able to predict the ζ of Metal Oxide Nanoparticles utilizing only two descriptors: (i) the spherical size of Nanoparticles, a parameter from numerical analysis of transmission electron microscopy (TEM) images, and (ii) the energy of the highest occupied molecular orbital per Metal atom, a theoretical descriptor calculated by quantum mechanics at semiempirical level of theory (PM6 method). The obtained consensus model is characterized by reasonably go...
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from basic physics to mechanisms of toxicity the liquid drop approach applied to develop predictive classification models for toxicity of Metal Oxide Nanoparticles
Nanoscale, 2014Co-Authors: Natalia Sizochenko, Bakhtiyor Rasulev, Agnieszka Gajewicz, V E Kuzmin, Tomasz Puzyn, Jerzy LeszczynskiAbstract:Many Metal Oxide Nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of Metal Oxide Nanoparticles’ toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of Nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were established. A new approach for representation of Nanoparticles’ structure is presented. For description of the supramolecular structure of Nanoparticles the “liquid drop” model was applied. It is expected that a novel, proposed approach could be of general use for predictions related to nanomaterials. In addition, in our study fragmental simplex descriptors and several ligand–Metal binding characteristics were calculated. The developed nano-QSAR models were validated and reliably predict the toxicity of all studied Metal Oxide Nanoparticles. Based on the comparative analysis of contributed properties in both models the LDM-based descriptors were revealed to have an almost similar level of contribution to toxicity in both cases, while other parameters (van der Waals interactions, electronegativity and Metal–ligand binding characteristics) have unequal contribution levels. In addition, the models developed here suggest different mechanisms of nanotoxicity for these two types of cells.
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periodic table based descriptors to encode cytotoxicity profile of Metal Oxide Nanoparticles a mechanistic qstr approach
Ecotoxicology and Environmental Safety, 2014Co-Authors: Tomasz Puzyn, Agnieszka Gajewicz, Supratik Kar, Kunal Roy, Jerzy LeszczynskiAbstract:Abstract Nanotechnology has evolved as a frontrunner in the development of modern science. Current studies have established toxicity of some Nanoparticles to human and environment. Lack of sufficient data and low adequacy of experimental protocols hinder comprehensive risk assessment of Nanoparticles (NPs). In the present work, Metal electronegativity ( χ ), the charge of the Metal cation corresponding to a given Oxide ( χ ox ), atomic number and valence electron number of the Metal have been used as simple molecular descriptors to build up quantitative structure–toxicity relationship (QSTR) models for prediction of cytotoxicity of Metal Oxide NPs to bacteria Escherichia coli . These descriptors can be easily obtained from molecular formula and information acquired from periodic table in no time. It has been shown that a simple molecular descriptor χ ox can efficiently encode cytotoxicity of Metal Oxides leading to models with high statistical quality as well as interpretability. Based on this model and previously published experimental results, we have hypothesized the most probable mechanism of the cytotoxicity of Metal Oxide Nanoparticles to E. coli . Moreover, the required information for descriptor calculation is independent of size range of NPs, nullifying a significant problem that various physical properties of NPs change for different size ranges.
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using nano qsar to predict the cytotoxicity of Metal Oxide Nanoparticles
Nature Nanotechnology, 2011Co-Authors: Tomasz Puzyn, Bakhtiyor Rasulev, Agnieszka Gajewicz, Hueymin Hwang, Thabitha P Dasari, A Michalkova, Andrey A Toropov, Danuta Leszczynska, Jerzy LeszczynskiAbstract:It is expected that the number and variety of engineered Nanoparticles will increase rapidly over the next few years, and there is a need for new methods to quickly test the potential toxicity of these materials. Because experimental evaluation of the safety of chemicals is expensive and time-consuming, computational methods have been found to be efficient alternatives for predicting the potential toxicity and environmental impact of new nanomaterials before mass production. Here, we show that the quantitative structure-activity relationship (QSAR) method commonly used to predict the physicochemical properties of chemical compounds can be applied to predict the toxicity of various Metal Oxides. Based on experimental testing, we have developed a model to describe the cytotoxicity of 17 different types of Metal Oxide Nanoparticles to bacteria Escherichia coli. The model reliably predicts the toxicity of all considered compounds, and the methodology is expected to provide guidance for the future design of safe nanomaterials.
Tomasz Puzyn - One of the best experts on this subject based on the ideXlab platform.
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zeta potential for Metal Oxide Nanoparticles a predictive model developed by a nano quantitative structure property relationship approach
Chemistry of Materials, 2015Co-Authors: Alicja Mikolajczyk, Jerzy Leszczynski, Bakhtiyor Rasulev, Agnieszka Gajewicz, Nicole M Schaeublin, Elisabeth Maurergardner, Saber M Hussain, Tomasz PuzynAbstract:Physico–chemical characterization of Nanoparticles in the context of their transport and fate in the environment is an important challenge for risk assessment of nanomaterials. One of the main characteristics that defines the behavior of Nanoparticles in solution is zeta potential (ζ). In this paper, we have demonstrated the relationship between zeta potential and a series of intrinsic physico–chemical features of 15 Metal Oxide Nanoparticles revealed by computational study. The here-developed quantitative structure–property relationship model (nano-QSPR) was able to predict the ζ of Metal Oxide Nanoparticles utilizing only two descriptors: (i) the spherical size of Nanoparticles, a parameter from numerical analysis of transmission electron microscopy (TEM) images, and (ii) the energy of the highest occupied molecular orbital per Metal atom, a theoretical descriptor calculated by quantum mechanics at semiempirical level of theory (PM6 method). The obtained consensus model is characterized by reasonably go...
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from basic physics to mechanisms of toxicity the liquid drop approach applied to develop predictive classification models for toxicity of Metal Oxide Nanoparticles
Nanoscale, 2014Co-Authors: Natalia Sizochenko, Bakhtiyor Rasulev, Agnieszka Gajewicz, V E Kuzmin, Tomasz Puzyn, Jerzy LeszczynskiAbstract:Many Metal Oxide Nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of Metal Oxide Nanoparticles’ toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of Nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were established. A new approach for representation of Nanoparticles’ structure is presented. For description of the supramolecular structure of Nanoparticles the “liquid drop” model was applied. It is expected that a novel, proposed approach could be of general use for predictions related to nanomaterials. In addition, in our study fragmental simplex descriptors and several ligand–Metal binding characteristics were calculated. The developed nano-QSAR models were validated and reliably predict the toxicity of all studied Metal Oxide Nanoparticles. Based on the comparative analysis of contributed properties in both models the LDM-based descriptors were revealed to have an almost similar level of contribution to toxicity in both cases, while other parameters (van der Waals interactions, electronegativity and Metal–ligand binding characteristics) have unequal contribution levels. In addition, the models developed here suggest different mechanisms of nanotoxicity for these two types of cells.
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periodic table based descriptors to encode cytotoxicity profile of Metal Oxide Nanoparticles a mechanistic qstr approach
Ecotoxicology and Environmental Safety, 2014Co-Authors: Tomasz Puzyn, Agnieszka Gajewicz, Supratik Kar, Kunal Roy, Jerzy LeszczynskiAbstract:Abstract Nanotechnology has evolved as a frontrunner in the development of modern science. Current studies have established toxicity of some Nanoparticles to human and environment. Lack of sufficient data and low adequacy of experimental protocols hinder comprehensive risk assessment of Nanoparticles (NPs). In the present work, Metal electronegativity ( χ ), the charge of the Metal cation corresponding to a given Oxide ( χ ox ), atomic number and valence electron number of the Metal have been used as simple molecular descriptors to build up quantitative structure–toxicity relationship (QSTR) models for prediction of cytotoxicity of Metal Oxide NPs to bacteria Escherichia coli . These descriptors can be easily obtained from molecular formula and information acquired from periodic table in no time. It has been shown that a simple molecular descriptor χ ox can efficiently encode cytotoxicity of Metal Oxides leading to models with high statistical quality as well as interpretability. Based on this model and previously published experimental results, we have hypothesized the most probable mechanism of the cytotoxicity of Metal Oxide Nanoparticles to E. coli . Moreover, the required information for descriptor calculation is independent of size range of NPs, nullifying a significant problem that various physical properties of NPs change for different size ranges.
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using nano qsar to predict the cytotoxicity of Metal Oxide Nanoparticles
Nature Nanotechnology, 2011Co-Authors: Tomasz Puzyn, Bakhtiyor Rasulev, Agnieszka Gajewicz, Hueymin Hwang, Thabitha P Dasari, A Michalkova, Andrey A Toropov, Danuta Leszczynska, Jerzy LeszczynskiAbstract:It is expected that the number and variety of engineered Nanoparticles will increase rapidly over the next few years, and there is a need for new methods to quickly test the potential toxicity of these materials. Because experimental evaluation of the safety of chemicals is expensive and time-consuming, computational methods have been found to be efficient alternatives for predicting the potential toxicity and environmental impact of new nanomaterials before mass production. Here, we show that the quantitative structure-activity relationship (QSAR) method commonly used to predict the physicochemical properties of chemical compounds can be applied to predict the toxicity of various Metal Oxides. Based on experimental testing, we have developed a model to describe the cytotoxicity of 17 different types of Metal Oxide Nanoparticles to bacteria Escherichia coli. The model reliably predicts the toxicity of all considered compounds, and the methodology is expected to provide guidance for the future design of safe nanomaterials.
Brij B Maini - One of the best experts on this subject based on the ideXlab platform.
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effect of hydrophobic and hydrophilic Metal Oxide Nanoparticles on the performance of xanthan gum solutions for heavy oil recovery
Nanomaterials, 2019Co-Authors: Laura M Corredor, Maen M Husein, Brij B MainiAbstract:Recent studies revealed higher polymer flooding performance upon adding Metal Oxide Nanoparticles (NPs) to acrylamide-based polymers during heavy oil recovery. The current study considers the effect of TiO2, Al2O3, in-situ prepared Fe(OH)3 and surface-modified SiO2 NPs on the performance of xanthan gum (XG) solutions to enhance heavy oil recovery. Surface modification of the SiO2 NPs was achieved by chemical grafting with 3-(methacryloyloxy)propyl]trimethoxysilane (MPS) and octyltriethoxysilane (OTES). The nanopolymer sols were characterized by their rheological properties and ζ-potential measurements. The efficiency of the nanopolymer sols in displacing oil was assessed using a linear sand-pack at 25 °C and two salinities (0.3 wt % and 1.0 wt % NaCl). The ζ-potential measurements showed that the NP dispersions in deionized (DI) water are unstable, but their colloidal stability improved in presence of XG. The addition of unmodified and modified SiO2 NPs increased the viscosity of the XG solution at all salinities. However, the high XG adsorption onto the surface of Fe(OH)3, Al2O3, and TiO2 NPs reduced the viscosity of the XG solution. Also, the NPs increased the cumulative oil recovery between 3% and 9%, and between 1% and 5% at 0 wt % and 0.3 wt % NaCl, respectively. At 1.0 wt % NaCl, the NPs reduced oil recovery by XG solution between 5% and 12%, except for Fe(OH)3 and TiO2 NPs. These NPs increased the oil recovery between 2% and 3% by virtue of reduced polymer adsorption caused by the alkalinity of the Fe(OH)3 and TiO2 nanopolymer sols.
A. K. Sengupta - One of the best experts on this subject based on the ideXlab platform.
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Polymer-supported Metals and Metal Oxide Nanoparticles: synthesis, characterization, and applications
Journal of Nanoparticle Research, 2012Co-Authors: Sudipta Sarkar, Françoise Quignard, Eric Guibal, A. K. SenguptaAbstract:Metal and Metal Oxide Nanoparticles exhibit unique properties in regard to sorption behaviors, magnetic activity, chemical reduction, ligand sequestration among others. To this end, attempts are being continuously made to take advantage of them in multitude of applications including separation, catalysis, environmental remediation, sensing, biomedical applications and others. However, Metal and Metal Oxide Nanoparticles lack chemical stability and mechanical strength. They exhibit extremely high pressure drop or head loss in fixed-bed column operation and are not suitable for any flow-through systems. Also, Nanoparticles tend to aggregate; this phenomenon reduces their high surface area to volume ratio and subsequently reduces effectiveness. By appropriately dispersing Metal and Metal Oxide Nanoparticles into synthetic and naturally occurring polymers, many of the shortcomings can be overcome without compromising the parent properties of the Nanoparticles. Furthermore, the appropriate choice of the polymer host with specific functional groups may even lead to the enhancement of the properties of Nanoparticles. The synthesis of hybrid materials involves two broad pathways: dispersing the Nanoparticles (i) within pre-formed or commercially available polymers; and (ii) during the polymerization process. This review presents a broad coverage of Nanoparticles and polymeric/biopolymeric host materials and the resulting properties of the hybrid composites. In addition, the review discusses the role of the Donnan membrane effect exerted by the host functionalized polymer in harnessing the desirable properties of Metal and Metal Oxide Nanoparticles for intended applications.