Degradation kinetics of isoproturon and its subsequent products in contact with TiO2 functionalized silica nanofibers

Abstract

A challenge for the photodegradation of (organic) micro-pollutants in waste water treatment is the mechanistic and kinetic understanding beyond the degradation of the initial (parent) harmful product, e.g. the phenylurea herbicide isoproturon (IPU). By combining liquid chromatography mass spectrometry and kinetic Monte Carlo modeling, we demonstrate that upon optimizing the dip-coating conditions (0.34 mol L -1 TiO2 solution at a coating speed of 160 mm min -1 ) for the functionalization of a superhydrophilic electrospun silica nanofibrous membrane (i) hydroxylation is a dominant reaction pathway and (ii) once IPU reacts on the surface of the TiO2 nanoparticles, further hydroxylation occurs sufficiently fast, with complete IPU removal under the detection limit (5-10 mg Lsolution -1 ) as a result of UV irradiation within 8 hours. As hydroxylation is dominant, degradation intermediates with a higher water solubility are formed and therefore a decreased toxicity is obtained upon reintroducing the treated solution into the environment. This is confirmed by respirometry, with an increase in the oxygen uptake rate of an activated sludge from 5.9 mg O2 gactivated sludge -1 h -1 for an untreated 10 mg L -1 IPU solution to 8.2 mg O2 gactivated sludge -1 h -1 for a solution irradiated for 8 hours, in line with a blank solution.

Gillespie-Driven kinetic Monte Carlo Algorithms to Model Events for Bulk or Solution (Bio)Chemical Systems Containing Elemental and Distributed Species

“…16 For systems with elemental species, analytical or pseudoanalytical solutions (e.g., based on the quasi-steady-state approximation; QSSA) are often readily available. 17,18 However, to model the time evolution of processes involving distributed species, only in some cases, an exact analytical solution may exist. 19−23 In most cases, the likely occurrence of several competing phenomena complicates the feasibility of an analytical approach.…”

“…For systems with elemental species, analytical or pseudoanalytical solutions (e.g., based on the quasi-steady-state approximation; QSSA) are often readily available. , However, to model the time evolution of processes involving distributed species, only in some cases, an exact analytical solution may exist. − In most cases, the likely occurrence of several competing phenomena complicates the feasibility of an analytical approach. This is undoubtedly the situation in polymer reaction engineering (PRE) with polymerization reactions in parallel and series and the additional complexity introduced by (chain length-dependent) diffusional limitations on the microscale (scale to define concentrations) and mixing/temperature heterogeneities at the macroscale (scale of the reactor), prohibiting the availability of an exact analytical solution. , For a general process, one thus needs to resort to numerical frameworks based on deterministic or stochastic problem formulations but maintain fundamental principles such as the consideration of Arrhenius laws and the mass law of action. ,− …”

Tailoring the Surface Properties of Micro/Nanofibers Using 0D, 1D, 2D, and 3D Nanostructures: A Review on Post‐Modification Methods

“…[ 139–141 ] The surface modification can be tailored mainly through the concentration of the solution and the immersion time. [ 142 ] This method allows the functionalization of nano‐/microfibers with distinct nanostructures as Co 3 O 4, [ 143 ] AgNWs, [ 144 ] TiO 2 , [ 145,146 ] SiO 2 , [ 147 ] Al 2 O 3 , [ 148 ] ZnO, [ 132,149 ] AgPO 4, [ 150 ] AgNPs, [ 151,152 ] graphene oxide, [ 153 ] reduced graphene oxide (rGO), [ 154 ] CNW(cellulose nanowhiskers):Ag, [ 155 ] CNW:Au, [ 156 ] sugarcane bagasse fly ash (SBFA), [ 157 ] MWCNTs, [ 158 ] and AgNPs/rGO. [ 159 ]…”

Synergy of Advanced Experimental and Modeling Tools to Underpin the Synthesis of Static Step-Growth-Based Networks Involving Polymeric Precursor Building Blocks

“…In a first instance, the focus is on [Tz] 0 equal to 3.6 mmol L −1 . These experimental data can be described using first-order kinetics assuming the quasi-steady-state approximation (QSSA) 94 for the calculation of the diradical intermediate (A*) and the nitrile imine (B) concentration, as elaborated in Section S3b.2 of the Supporting Information. It follows that for [Tz] 0 equal to 3.6 mmol L −1 , the NITEC kinetics are independent of the maleimide functionality (mono vs tri), as the pyrazoline yield profiles in Figure 4b for the orange (mono) and blue (tri) closed symbols (experimental data) as well as the corresponding simulated full llines match.…”