Fundamental studies of methyl iodide adsorption in DABCO impregnated activated carbons.

Methyl iodide capture from a water vapor stream using 1,4-diazabicyclo[2.2.2]octane (DABCO)-impregnated activated carbons is, for the first time, fundamentally described here on the atomic level by means of both molecular dynamics and grand canonical Monte Carlo simulations. A molecular dynamics annealing strategy was adopted to mimic the DABCO experimental impregnation procedure in a selected slitlike carbon pore. Predictions, restricted to the micropore region, are made about the adsorption isotherms of methyl iodide, water, and nitrogen on both impregnated and bare activated carbon models. Experimental and simulated nitrogen adsorption isotherms are compared for the validation of the impregnation strategy. Selectivity analyses of the preferential adsorption toward methyl iodide over water are also reported. These simulated adsorption isotherms sum up to previous experimental studies to provide an enhanced picture for this adsorption system of widespread use at nuclear plant HVAC facilities for the capture of radioactive iodine compounds.

Predicting neopentane isosteric enthalpy of adsorption at zero coverage in MCM-41.

The isosteric enthalpy of adsorption for neopentane at relative pressures down to 3 × 10(-8) in MCM-41 was predicted for the temperature range from -15 to 0 °C. At such low pressures and temperatures, experimental measurements become problematic for this system. We used an atomistic model for MCM-41 obtained by means of a kinetic Monte Carlo method mimicking the synthesis of the material. The model was parametrized to represent experimental nitrogen adsorption isotherms at 77 K using grand canonical Monte Carlo simulations. The simulated isosteric enthalpy of adsorption shows very good agreement with available experimental data, demonstrating that GCMC simulations can predict heats of adsorption for conditions that are challenging for experimental measurements. Additional insights into the adsorption mechanisms, derived from energetic analysis at the molecular level, are also presented.

Volatile organic compound adsorption on a nonporous silica surface: how do different probe molecules sense the same surface?

In this work, we compare experimental results to molecular simulation results of volatile organic compound (VOC) adsorption on nonporous silica. We adopted an effective model for the rough solid surface, obtained by a temperature annealing scheme, plus an experimental/simulation nitrogen adsorption tuning process over the silica energetic oxygen parameter. The measurement/prediction of selected VOCs, specifically, n-pentane and methylcyclohexane, is presented in terms of adsorption isotherms, with an emphasis on the angle distribution analysis of the three studied probe molecules with respect to the same modeled surface.

Molecular recognition effects in atomistic models of imprinted polymers.

In this article we present a model for molecularly imprinted polymers, which considers both complexation processes in the pre-polymerization mixture and adsorption in the imprinted structures within a single consistent framework. As a case study we investigate MAA/EGDMA polymers imprinted with pyrazine and pyrimidine. A polymer imprinted with pyrazine shows substantial selectivity towards pyrazine over pyrimidine, thus exhibiting molecular recognition, whereas the pyrimidine imprinted structure shows no preferential adsorption of the template. Binding sites responsible for the molecular recognition of pyrazine involve one MAA molecule and one EGDMA molecule, forming associations with the two functional groups of the pyrazine molecule. Presence of these specific sites in the pyrazine imprinted system and lack of the analogous sites in the pyrimidine imprinted system is directly linked to the complexation processes in the pre-polymerization solution. These processes are quite different for pyrazine and pyrimidine as a result of both enthalpic and entropic effects.

Optimization of Cortisol-Selective Molecularly Imprinted Polymers Enabled by Molecular Dynamics Simulations.

Today, we heavily rely on technology and increasingly utilize it to monitor our own health. The identification of sensitive, accurate biosensors that are capable of real-time cortisol analysis is one important potential feature for these technologies to aid us in the maintenance of our physical and mental wellbeing. Detection and quantification of cortisol, a well-known stress biomarker present in sweat, offers a noninvasive and potentially real-time method for monitoring anxiety. Molecularly imprinted polymers are attractive candidates for cortisol recognition elements in such devices as they can selectively rebind a targeted template molecule. However, mechanisms of imprinting and subsequent rebinding depend on the choice and composition of the prepolymerization mixture where the molecular interactions between the template, functional monomer, cross-linker, and solvent molecules are not fully understood. Here, we report the synthesis and evaluation of a molecularly imprinted polymer selective for cortisol detection. Molecular dynamics simulations were used to investigate the interactions between all components in the prepolymerization mixture of the as-synthesized molecularly imprinted polymer. Varying the component ratio of the prepolymerization mixture indicates that the number of cross-linker molecules relative to the template impacts the quality of imprinting. It was determined that a component ratio of 1:6:30 of cortisol, methacrylic acid, and ethylene glycol dimethacrylate, respectively, yields the optimal theoretical complexation of cortisol for the polymeric systems investigated. Experimental synthesis and rebinding results demonstrate an imprinting factor of up to 6.45. The trends in cortisol affinity predicted by molecular dynamics simulations of the prepolymerization mixture were also corroborated through experimental analysis of those modeled molecularly imprinted compositions, demonstrating the predictive capabilities of these simulations.

Towards EMIC rational design: setting the molecular simulation toolbox for enantiopure molecularly imprinted catalysts.

A critical appraisal of the current strategies for the synthesis of enantiopure drugs is presented, along with a systematic background for the computational design of stereoselective porous polymers. These materials aim to achieve the enantiomeric excess of any chiral drug, avoiding the racemic separation. Particular emphasis is given to link statistical mechanics methods to the description of each one of the experimental stages within the catalyst's synthesis, setting a framework for the fundamental study of the emerging field of molecularly imprinted catalysts.Graphical abstractThe envisaged modelling tools in the EMIC toolbox: quantum mechanics (QM), molecular dynamics and Monte Carlo (in the NPT and NVT ensembles), grand canonical Monte Carlo (GCMC) and kinetic Monte Carlo (kMC), for the synthesis of an enantiopure drug via our proposed EMIC catalyst.

Modelling the interfacial behaviour of dilute light-switching surfactant solutions.

The direct molecular modelling of an aqueous surfactant system at concentrations below the critical micelle concentration (pre-cmc) conditions is unviable in terms of the presently available computational power. Here, we present an alternative that combines experimental information with tractable simulations to interrogate the surface tension changes with composition and the structural behaviour of surfactants at the water-air interface. The methodology is based on the expression of the surface tension as a function of the surfactant surface excess, both in the experiments and in the simulations, allowing direct comparisons to be made. As a proof-of-concept a coarse-grained model of a light switching non-ionic surfactant bearing a photosensitive azobenzene group is considered at the air-water interface at 298 K. Coarse-grained molecular dynamic simulations are detailed based on the use of the SAFT force field with parameters tuned specifically for this purpose. An excellent agreement is obtained between the simulation predictions and experimental observations; furthermore, the molecular model allows the rationalization of the macroscopic behaviour in terms of the different conformations of the cis and trans surfactants at the surface.

Computer simulation of volatile organic compound adsorption in atomistic models of molecularly imprinted polymers.

Molecularly imprinted polymers (MIPs) offer a unique opportunity to significantly advance volatile organic compound (VOC) sensing technologies and a number of other applications. However, the development of these applications using MIPs has been hindered by poor understanding of the microstructure of MIPs, geometry of binding sites, and the details of molecular recognition processes in these materials. This is further complicated by the vast number of optimization parameters such as building components and processing conditions. Computer simulations and molecular modeling can help us understand adsorption and binding phenomena in MIPs on the molecular level and thus provide a route to more efficient MIP design strategies. So far, molecular models have been either oversimplified or severely limited in length scale, essentially focusing on a single binding site. Here, we propose a more general, atomistically detailed model that describes the microstructure of MIPs. We apply this model to investigate adsorption of pyridine, benzene, and toluene in MIPs and demonstrate that it is able to capture a number of essential experimental features. Therefore, this model can serve as a starting point in computational design and optimization of MIPs.

Selective adsorption of volatile organic compounds in micropore aluminum methylphosphonate-alpha: a combined molecular simulation-experimental approach.

Results concerning the adsorption capacity of aluminum methylphosphonate polymorph alpha (AlMePO-alpha) for pure ethyl chloride and vinyl chloride by measured individual adsorption isotherms of these pure compounds are presented and discussed here. The experimental data supports the idea of using these materials as selective adsorbents for separating these compounds in mixtures. To explore this possibility further, we have performed grand canonical Monte Carlo simulations using a recently proposed molecular simulation framework for gas adsorption on AlMePO, and the results are presented here. The molecular model of the material was used in a purely transferable manner from a previous work (Herdes, C.; Lin, Z.; Valente, A.; Coutinho, J. A. P.; Vega, L. F. Langmuir 2006, 22, 3097). Regarding the molecular model of the fluids, an existing model for ethyl chloride was improved to capture the experimental dipole value better; an equivalent force field for the vinyl chloride molecule was also developed for simulation purposes. Simulations of the pure compounds were found to be in excellent agreement with the measured experimental data at the three studied temperatures. Simulations were also carried out in a purely predictive manner as a tool to find the optimal conditions for the selective adsorption of these compounds prior experimental measurements are carried out. The influence of the temperature and the bulk composition on the adsorption selectivity was also investigated. Results support the use of AlMePO-alpha as an appropriate adsorbent for the purification process of vinyl chloride, upholding the selective adsorption of ethyl chloride.

Nitrogen and water adsorption in aluminum methylphosphonate alpha: a molecular simulation study.

We present here Monte Carlo simulation and experimental results on the adsorption of nitrogen and water in aluminum methylphosphonate polymorph alpha (AlMePO-alpha). We have assumed a detailed atomic model for the material, using experimental information to construct the simulation cell. Nitrogen was modeled with two different approaches: as a simple Lennard-Jones (LJ) sphere with no charges, and as a diatomic molecule with charges explicitly included. Water was represented by the TIP4P model. Experimental adsorption isotherms were used to tune the proposed molecular model for the adsorbent. Simulated adsorption capacities were in agreement with the experimental results obtained for the studied systems. The influence of the surface model on the adsorption behavior was taken into account by considering different values of the surface methyl group size parameter. Our results corroborate the strong sensitivity of the simulation results to this parameter, as previously observed by Schumacher and co-workers. It is also observed that charged models are essential to accurately describe the low-pressure region of the adsorption isotherm, where the solid-fluid interaction rules the system behavior. However, a simple uncharged molecular model for nitrogen is able to describe the three loci arrangement at maximum loading. Experimental and simulation results presented here also confirm the low water affinity of AlMePO-alpha. These results enforce the application of this methodology to achieve quantitative predictions on similar systems, with the appropriate transferability of the molecular parameters.

Pore size distribution analysis of selected hexagonal mesoporous silicas by grand canonical Monte Carlo simulations.

We combine here a regularization procedure with individual adsorption isotherms obtained from grand canonical Monte Carlo simulations in order to obtain reliable pore size distributions. The methodology is applied to two hexagonal high-ordered silica materials: SBA-15 and PHTS, synthesized in our laboratory. Feasible pore size distributions are calculated through an adaptable procedure of deconvolution over the adsorption integral equation, with two necessary inputs: the experimental adsorption data and individual adsorption isotherms, assuming the validity of the independent pore model. The application of the deconvolution procedure implies an adequate grid size evaluation (i.e., numbers of pores and relative pressures to be considered for the inversion, or kernel size), the fulfillment of the discret Picard condition, and the appropriate choice of the regularization parameter (L-curve criteria). Assuming cylindrical geometry for both porous materials, the same set of individual adsorption isotherms generated from molecular simulations can be used to construct the kernel to obtain the PSD of SBA-15 and PHTS. The PSD robustness is measured imposing random errors over the experimental data. Excellent agreement is found between the calculated and the experimental global adsorption isotherms for both materials. Molecular simulations provide new insights into the studied systems, pointing out the need of high-resolution isotherms to describe the presence of complementary microporosity in these materials.

Thermodynamic properties and aggregate formation of surfactant-like molecules from theory and simulation.

The goal of this work is twofold: to predict the phase equilibria behavior of simplified surfactant models and to predict the population of aggregates as a function of pressure. We compare Monte Carlo simulation results of these systems with predictions from a modified version of the statistical associating fluid theory (soft-SAFT). Surfactant-like molecules are modeled as Lennard-Jones chains of tangent segments with one or two association sites. We study the influence of the number and location of the association sites on the thermodynamic properties and fraction of nonbonded molecules in all cases. The influence of the chain length is also investigated for a particular location of the sites. Results are compared with NPT Monte Carlo simulations to test the accuracy of the theory, and to study the molecular configurations of the system. Soft-SAFT is able to quantitatively predict the MC PVT results, independently of the location of the association sites. The theory is also able to capture the qualitative trend of the population of aggregates with pressure. Quantitative agreement is only obtained for specific locations of the sites.