Experiments and modeling of mine soil inertization through mechano-chemical processing: from bench to pilot scale using attritor and impact mills.

Mechano-chemical treatment has been recognized to be a promising technology for the immobilization of heavy metals (HMs) in contaminated soils without the use of additional reagents. Despite this, very few studies aiming to investigate the applicability of this technology at full scale have been published so far. In this study, a quantitative approach was developed to provide process design information to scale-up from laboratory- into pilot-scale mechano-chemical reactors for immobilizing heavy metals in contaminated mining soil. In fact, after preliminary experiments with laboratory-scale ball mills, experiments have been carried out by taking advantage of milling devices suited for pilot-scale applications. The experimental data of this work, along with literature ones, have been quantitatively interpreted by means of a mathematical model allowing to describe the effect of milling dynamics on the HM immobilization kinetics for applications at different scales. The results suggest that the mechanical process can trigger specific physico-chemical phenomena leading to a significant reduction of HMs leached from mining soils. Specifically, after suitably prolonged processing time, HM concentration in the leachate is lowered below the corresponding threshold limits. The observed behavior is well captured by the proposed model for different HMs and operating conditions. Therefore, the model might be exploited to infer design parameters for the implementation of this technique at the pilot and full scale. Moreover, it represents a valuable tool for designing and controlling mechano-chemical reactors at productive scale.

Mechanochemical immobilization of heavy metals in contaminated soils: A novel mathematical modeling of experimental outcomes.

Mechanochemical processing to immobilize heavy metals in contaminated soils has been proposed few years ago. The corresponding experimental results have shown that, under specific operating conditions, the mechanical energy provided by suitable ball mills, can greatly reduce heavy metals mobility without the addition of any reactant. Such results, together with the extreme simplicity of the proposed technique, are still very promising in view of its industrial transposition. Along these lines, the use of suitable mathematical models might represent a valuable tool which would permit to design and control mechano-chemical reactors for field applications. In this work, a simple albeit exhaustive model is proposed for the first time to quantitatively describe the effects of the dynamics of milling process, such as impact frequency and energy, on the immobilization kinetics. Model results and experimental data obtained so far are successfully compared in terms of leached heavy metals and immobilization efficiency evolution with treatment time. Finally, the potential capability of the model to contribute to the industrial scale transposition of the proposed technique is addressed.

Autotrophic growth and lipid production of Chlorella sorokiniana in lab batch and BIOCOIL photobioreactors: Experiments and modeling.

A novel mathematical model for the quantitative assessment of the effect of dissolved nitrogen on the autotrophic batch-growth and lipid accumulation of Chlorella sorokiniana, is proposed in this work. Model results have been validated through comparison with suitable experimental data performed in lab photobioreactors. Further experiments have been then performed using the BIOCOIL photobioreactor operated in fed-batch mode. The experimental results, which show that a maximum growth rate of 0.52day(-1) and a lipid content equal to 25%wt can be achieved with the BIOICOIL, have been successfully predicted through the proposed model. Therefore, the model might represent a first step toward the development of a tool for the scale-up and optimization of the operating conditions of BIOCOIL photobioreactors. Finally, the fatty acid methyl esters obtained by trans-esterification of lipids extracted from C. sorokiniana, have been analyzed in view of the assessment of their usability for producing biodiesel.

A novel quantitative model of cell cycle progression based on cyclin-dependent kinases activity and population balances.

Cell cycle regulates proliferative cell capacity under normal or pathologic conditions, and in general it governs all in vivo/in vitro cell growth and proliferation processes. Mathematical simulation by means of reliable and predictive models represents an important tool to interpret experiment results, to facilitate the definition of the optimal operating conditions for in vitro cultivation, or to predict the effect of a specific drug in normal/pathologic mammalian cells. Along these lines, a novel model of cell cycle progression is proposed in this work. Specifically, it is based on a population balance (PB) approach that allows one to quantitatively describe cell cycle progression through the different phases experienced by each cell of the entire population during its own life. The transition between two consecutive cell cycle phases is simulated by taking advantage of the biochemical kinetic model developed by Gérard and Goldbeter (2009) which involves cyclin-dependent kinases (CDKs) whose regulation is achieved through a variety of mechanisms that include association with cyclins and protein inhibitors, phosphorylation-dephosphorylation, and cyclin synthesis or degradation. This biochemical model properly describes the entire cell cycle of mammalian cells by maintaining a sufficient level of detail useful to identify check point for transition and to estimate phase duration required by PB. Specific examples are discussed to illustrate the ability of the proposed model to simulate the effect of drugs for in vitro trials of interest in oncology, regenerative medicine and tissue engineering.

Comprehensive modeling and investigation of the effect of iron on the growth rate and lipid accumulation of Chlorella vulgaris cultured in batch photobioreactors.

Recent works have shown that specific strains of microalgae are capable to simultaneously increase their growth rate and lipid content when cultured under suitable concentrations of iron. While these results are promising in view of the exploitation of microalgae for producing biofuels, to the best of our knowledge, no mathematical model capable to describe the effect of iron on lipid accumulation in microalgae, has been so far proposed. A comprehensive mathematical model describing the effect of iron on chlorophyll synthesis, nitrogen assimilation, growth rate and lipid accumulation in a freshwater strain of Chlorella vulgaris is then proposed in this work. Model results are successfully compared with experimental data which confirm the positive effect of growing iron concentrations on lipid productivity of C. vulgaris. Thus, the proposed model might represent a useful tool to optimize iron-based strategies to improve the lipid productivity of microalgal cultures.

A simulation model for stem cells differentiation into specialized cells of non-connective tissues.

A novel mathematical model to simulate stem cells differentiation into specialized cells of non-connective tissues is proposed. The model is based upon material balances for growth factors coupled with a mass-structured population balance describing cell growth, proliferation and differentiation. The proposed model is written in a general form and it may be used to simulate a generic cell differentiation pathway during in vitro cultivation when specific growth factors are used. Literature experimental data concerning the differentiation of central nervous stem cells into astrocytes are successfully compared with model results, thus demonstrating the validity of the proposed model as well as its predictive capability. Finally, sensitivity analysis of model parameters is also performed in order to clarify what mechanisms most strongly influence differentiation and cell types distribution.

A novel simulation model for stem cells differentiation.

A novel mathematical model to simulate mesenchymal stem cells differentiation into specialized cells is proposed. The model is based upon material balances for extracellular matrix compounds, growth factors and nutrients coupled with a mass-structured population balance describing cell growth, proliferation and differentiation. The proposed model is written in a general form and it may be used to simulate a generic cell differentiation pathway occurring in vivo or during in vitro cultivation when specific growth factors are used. Literature experimental data concerning the differentiation of mesenchymal stem cells into chondrocytes in terms of total DNA and glycosaminoglycan content are successfully compared with model results, thus demonstrating the validity of the proposed model as well as its predictive capability. A further test of the model capability is performed for the case of in vivo fracture healing during which mesenchymal stem cells differentiate into chondrocytes and osteoblasts. Considerations about the extension of the proposed model to different pathologies beside fracture healing are reported. Finally, sensitivity analysis of model parameters is also performed in order to clarify what mechanisms most strongly influence differentiation and the distribution of cell types.

Remediation of heavy metals contaminated soils by ball milling.

In the present work, the use of ball milling reactors for the remediation of lead contaminated soils was investigated. Lead immobilization was achieved without the use of additional reactants but only through the exploitation of weak transformations induced on the treated soil by mechanical loads taking place during collisions among milling media. The degree of metal immobilization was evaluated by analyzing the leachable fraction of Pb(II) obtained through the "synthetic precipitation leaching procedure". The reduction of leachable Pb(II) from certain synthetic soils, i.e., bentonitic, sandy and kaolinitc ones, was obtained under specific milling regimes. For example, for the case of bentonitic soils characterized by a Pb(II) concentration in the solid phase equal to 954.4 mg kg(-1), leachable Pb(II) was reduced, after 7 h of mechanical treatment, from 1.3 mg l(-1) to a concentration lower than the USEPA regulatory threshold (i.e., 0.015 mg l(-1) for drinkable water). Similar results were obtained for sandy and kaolinitic soils. X-ray diffraction, scanning electron microscopy, electron dispersive spectroscopy and granulometric analyses revealed no significant alterations of the intrinsic character of sandy and bentonitic soils after milling except for a relatively small increase of particles size and a partial amorphization of the treated soil. On the other hand, the mechanical treatment caused the total amorphization of kaolinitic soil. The increase of immobilization efficiency can be probably ascribed to specific phenomena induced by mechanical treatment such as entrapment of Pb(II) into aggregates due to aggregation, solid diffusion of Pb(II) into crystalline reticulum of soil particles as well as the formation of new fresh surfaces (through particle breakage) onto which Pb(II) may be irreversibly adsorbed.

A novel simulation model for engineered cartilage growth in static systems.

A novel mathematical model to simulate the growth of engineered cartilage in static systems is proposed. This model is based on material balances for the involved species (glycosaminoglycan and collagen, both pertaining to extracellular matrix), as well as mass-structured population balance for simulating cell growth and its proliferation within the scaffold. This model may simulate tissue growth on static culture taking place in Petri dishes, static flasks, and well plates for different types of scaffolds (i.e., poly(glycolic acid) [PGA], PGA/poly(l-lactic acid), and collagen sponge). This work aimed to demonstrate that the model approach proposed in previous works, regarding engineered cartilage growth on PGA scaffolds performed in rotating bioreactors, may also be applied to different scaffolds and system configurations. In particular, the balance equation for simulating collagen production is introduced, as well as the use of spatial averaging over the spatial region to compare experimental data with the model. Experimental data from the literature in terms of cells, glycosaminoglycans, and collagen content have been successfully compared with model results, thus demonstrating the validity of the proposed model, as well as its predictive capability.