Efficient atomistic approaches to thermodynamic quantities for solid-liquid equilibria in alloys

Two important thermodynamic quantities are bulk solid and liquid free-energy as a function of composition G(x) and the solid-liquid interfacial free-energy γsl. For both, an accurate determination is required for modelling crystallisation and melting processes. In this thesis, I combine statistical mechanics and atomistic simulations to develop new approaches to calculate G(x) and γsl. In the case of G(x), a method based on a Free Energy Perturbation (FEP) technique is proposed, which allows to achieve ab initio accuracy at a fraction of the cost of previously proposed techniques. A proof-of-principle of this approach is given using simple many-body potentials. The case of the melting point calculation for a pure element and that of the free-energy for a binary Ni-Al alloy are discussed. Based on simplified theoretical models, the reasons for the success of this approach and its limitations are explained and guidelines for future, full ab initio calculations are given. For the case of γsl, it is proposed to use the Metadynamics (MTD) technique to reconstruct the Free Energy Surface (FES) for the solidification/ melting process, from which γsl can be extracted. This approach is first presented and discussed using a model Lennard-Jones potential. The robustness of this method is demonstrated and its advantages over other techniques are discussed, together with its limitations and possible ways to extend its use to more complex energy descriptions. The method is then applied to the case of Pb as described with a more realistic Embedded Atom Model (EAM) potential, and the results are used to assess experimental data. Given the promising results shown by these novel techniques, their use to build the foundations of a multi-scale approach to solidification and their application with more realistic calculations and complex problems can be envisaged in the future

Dynamic density functional theory of protein adsorption on polymer-coated nanoparticles

We present a theoretical model for the description of the adsorption kinetics of globular proteins onto charged core-shell microgel particles based on Dynamic Density Functional Theory (DDFT). This model builds on a previous description of protein adsorption thermodynamics [Yigit \textit{et al}, Langmuir 28 (2012)], shown to well interpret the available calorimetric experimental data of binding isotherms. In practice, a spatially-dependent free-energy functional including the same physical interactions is built, and used to study the kinetics via a generalised diffusion equation. To test this model, we apply it to the case study of Lysozyme adsorption on PNIPAM coated nanoparticles, and show that the dynamics obtained within DDFT is consistent with that extrapolated from experiments. We also perform a systematic study of the effect of various parameters in our model, and investigate the loading dynamics as a function of proteins' valence and hydrophobic adsorption energy, as well as their concentration and that of the nanoparticles. Although we concentrated here on the case of adsorption for a single protein type, the model's generality allows to study multi-component system, providing a reliable instrument for future studies of competitive and cooperative adsorption effects often encountered in protein adsorption experiments.Comment: Submitted to Soft Matte

Simple approach for calculating the binding free energy of a multivalent particle

We present a simple yet accurate numerical approach to compute the free energy of binding of multivalent objects on a receptor-coated surface. The method correctly accounts for the fact that one ligand can bind to at most one receptor. The numerical approach is based on a saddle-point approximation to the computation of a complex residue. We compare our theory with the powerful Valence-Limited Interaction Theory (VLIT) (J. Chem. Phys. 137, 094108(2012), J. Chem. Phys. 138, 021102(2013)) and find excellent agreement in the regime where that theory is expected to work. However, the present approach even works for low receptor/ligand densities, where VLIT breaks down.Comment: 5 pages, 2 figure

Theory of Solvation-Controlled Reactions in Stimuli-Responsive Nanoreactors

Metallic nanoparticles embedded in stimuli-responsive polymers can be regarded as nanoreactors since their catalytic activity can be changed within wide limits: the physicochemical properties of the polymer network can be tuned and switched by external parameters, e.g. temperature or pH, and thus allows a selective control of reactant mobility and concentration close to the reaction site. Based on a combination of Debye's model of diffusion through an energy landscape and a two-state model for the polymer, here we develop an analytical expression for the observed reaction rate constant $k_{\rm obs}$. Our formula shows an exponential dependence of this rate on the solvation free enthalpy change $\Delta \bar{G}_{\rm sol}$, a quantity which describes the partitioning of the reactant in the network versus bulk. Thus, changes in $\Delta \bar{G}_{\rm sol}$, and not in the diffusion coefficient, will be the decisive factor affecting the reaction rate in most cases. A comparison with recent experimental data on switchable, thermosensitive nanoreactors demonstrates the general validity of the concept

Theory and simulation of DNA-coated colloids: a guide for rational design.

By exploiting the exquisite selectivity of DNA hybridization, DNA-coated colloids (DNACCs) can be made to self-assemble in a wide variety of structures. The beauty of this system stems largely from its exceptional versatility and from the fact that a proper choice of the grafted DNA sequences yields fine control over the colloidal interactions. Theory and simulations have an important role to play in the optimal design of self assembling DNACCs. At present, the powerful model-based design tools are not widely used, because the theoretical literature is fragmented and the connection between different theories is often not evident. In this Perspective, we aim to discuss the similarities and differences between the different models that have been described in the literature, their underlying assumptions, their strengths and their weaknesses. Using the tools described in the present Review, it should be possible to move towards a more rational design of novel self-assembling structures of DNACCs and, more generally, of systems where ligand-receptor are used to control interactions.This is the final version of the article. It first appeared from the Royal Society of Chemistry via http://dx.doi.org/10.1039/C5CP06981

Catalyzed bimolecular reactions in responsive nanoreactors

We describe a general theory for surface-catalyzed bimolecular reactions in responsive nanoreactors, catalytically active nanoparticles coated by a stimuli-responsive 'gating' shell, whose permeability controls the activity of the process. We address two archetypal scenarios encountered in this system: The first, where two species diffusing from a bulk solution react at the catalyst's surface; the second where only one of the reactants diffuses from the bulk while the other one is produced at the nanoparticle surface, e.g., by light conversion. We find that in both scenarios the total catalytic rate has the same mathematical structure, once diffusion rates are properly redefined. Moreover, the diffusional fluxes of the different reactants are strongly coupled, providing a richer behavior than that arising in unimolecular reactions. We also show that in stark contrast to bulk reactions, the identification of a limiting reactant is not simply determined by the relative bulk concentrations but controlled by the nanoreactor shell permeability. Finally, we describe an application of our theory by analyzing experimental data on the reaction between hexacyanoferrate (III) and borohydride ions in responsive hydrogel-based core-shell nanoreactors.Comment: 9 pages, 4 figure

Reaction rate of a composite core-shell nanoreactor with multiple, spatially distributed embedded nano-catalysts

We present a detailed theory for the total reaction rate constant of a composite core-shell nanoreactor, consisting of a central solid core surrounded by a hydrogel layer of variable thickness, where a given number of small catalytic nanoparticles are embedded at prescribed positions and are endowed with a prescribed surface reaction rate constant. Besides the precise geometry of the assembly, our theory accounts explicitly for the diffusion coefficients of the reactants in the hydrogel and in the bulk as well as for their transfer free energy jump upon entering the hydrogel shell. Moreover, we work out an approximate analytical formula for the overall rate constant, which is valid in the physically relevant range of geometrical and chemical parameters. We discuss in depth how the diffusion-controlled part of the rate depends on the essential variables, including the size of the central core. In particular, we derive some simple rules for estimating the number of nanocatalysts per nanoreactor for an efficient catalytic performance in the case of small to intermediate core sizes. Our theoretical treatment promises to provide a very useful and flexible tool for the design of superior performing nanoreactor geometries and with optimized nanoparticle load.Comment: 12 pages, 3 figures, Physical Chemistry Chemical Physics, 201

Precise generation of selective surface-confined glycoprotein recognition sites

Since glycoproteins have become increasingly recognized as key players in a wide variety of disease processes, there is an increasing need for advanced affinity materials for highly selective glycoprotein binding. Herein, for the first time, a surface-initiated controlled radical polymerization is integrated with supramolecular templating and molecular imprinting to yield highly reproducible synthetic recognition sites on surfaces with dissociation constants (KDs) in the low micromolar range for target glycoproteins and minimal binding to non-target glycoproteins. Importantly, it is shown that the synthetic strategy has remarkable ability to distinguish the glycosylated and non-glycosylated forms of the same glycoprotein, with >5-fold difference in binding affinity. The precise control over the polymer film thickness and positioning of multiple carbohydrate receptors plays a crucial role in achieving enhanced affinity and selectivity. The generated functional materials of unprecedented glycoprotein recognition performance open up a wealth of opportunities in the biotechnological and biomedical fields